DeepSeek's AI Breakthrough: Implications for Nvidia and the AI Industry

Nvidia Calls China's DeepSeek an "Excellent AI Advancement": Should Investors Press the Buy Button? | The Motley Fool

One might think that artificial intelligence (AI) chip king Nvidia (NVDA -2.84%) might not be so pleased with the Chinese company DeepSeek, considering that news of DeepSeek's achievement in the AI space led to an intense single-day sell-off that erased roughly $600 billion of Nvidia's market cap on Jan. 27. However, Nvidia -- along with analysts and investors -- has taken a more constructive view, arguing that DeepSeek's ability to design an AI chatbot comparable to OpenAi's ChatGPT should be lauded, and that its may represent an opportunity for the entire AI market. With that in mind, should investors buy the dip on Nvidia? When DeepSeek surged into the public consciousness, the market initially responded by selling off Nvidia because the Chinese start-up claimed to have created a chatbot similar to ChatGPT at a fraction of the cost. Th Chinese company says it spent only $5.6 million to train its large language model, and used less powerful graphics processing units (GPUs) that are compliant with U.S. export restrictions. The U.S. has banned companies like Nvidia from selling some of their most advanced chips to China due to concerns about how that country might use their capabilities. Part of the investment thesis for Nvidia lately has been that it has an enormous competitive moat, thanks to its cutting-edge GPUs and its CUDA platform. Its high gross profit margins -- in the 74% to 79% range last year -- support this premise, showing that it has near-complete control of the AI chip market and its own pricing power. But all this could be threatened if a company with fewer than 200 employees spent less than $10 million and used old Nvidia chips to replicate the current state of the art in AI software. Many doubt that the cost of DeepSeek's chatbot was only $5.6 million, and have questioned what inputs actually went into its design. That's why it was interesting to see Nvidia's commentary about DeepSeek. An Nvidia spokesperson praised it as "an excellent AI advancement" that illustrates how new models can be created "leveraging widely available models and compute that is fully export control compliant." The company also said that DeepSeek shows that Nvidia's chips are useful in China, a material revenue driver for the company, and that this market will need more of its chips to meet demand. Analysts largely refuted the idea that DeepSeek's rise could mean the end of Nvidia. Most actually see it as an opportunity for the broader AI trend. Daniel Newman, chief strategist at global tech researcher The Futurum Group, called the sell-off an overreaction: "If we can use compute more efficiently ... the companies that we're saying aren't driving enough revenue will be able to build their models cheaper. They'll be able to create solutions with less overhead expense, and they're going to drive more [earnings per share]." Although companies like Meta Platforms have pledged to spend tens of billions on AI infrastructure, they could also likely benefit if it turns out that some of this spending is not necessary, although that would open the door for competitors as well. Do I think Nvidia is done for? Absolutely not. Companies like Nvidia with tons of resources tend to find ways to not only survive but also get ahead of competitors. If DeepSeek does make AI software more widespread, that could drive more uses and boost demand for Nvidia's chips. Following the big sell-off on Jan. 27 and a mild rebound on Jan. 28, the company's forward price-to-earnings ratio (P/E) stood slightly above its five-year average. My issue with Nvidia and its "Magnificent Seven" cohort is that they are still trading at high multiples in a bull market that has lasted for more than two years. There is still a lot we don't know about AI and how widespread it will actually become. If anything, the arrival of DeepSeek demonstrates how early we still are in the AI game. Similar events also happened in the dot-com bubble. That was followed by a steep pullback among internet stocks that had run too high too quickly -- but eventually, the internet ultimately changed everything. If you plan to hold the stock for 10 to 20 years, then you can definitely buy Nvidia now. However, I think it could be a bumpy ride in the near term.

Is Nvidia Stock a Buy? | The Motley Fool

Perhaps no stock exemplified the past year's artificial intelligence (AI) frenzy more than Nvidia (NVDA -2.84%). The semiconductor chipmaker's business benefited as tech companies spent billions of dollars to buy its AI offerings. Shares of Nvidia were up nearly 90% over the past 12 months through the end of January. But when Chinese start-up DeepSeek announced on Jan. 27 it produced a large language model (LLM) for less than $6 million, a fraction of the money spent by U.S. companies, Nvidia shares plunged 17%. The stock since recovered, but it's still below the 52-week high of $153.13 reached on Jan. 7. Does this create a buying opportunity? Or is DeepSeek threatening to upend Nvidia's future earnings? Read on to learn if Nvidia remains a worthwhile long-term investment in AI. DeepSeek's AI price tag was shockingly low, prompting concerns that Nvidia will lose business. If one company were able to produce the AI technology inexpensively, others could do so without Nvidia's pricey products. But the Chinese start-up's success is unlikely to impact Nvidia in a substantial way for several reasons. For starters, it's possible DeepSeek used restricted advanced AI chips. The U.S. Commerce Department is investigating that possibility. In addition, ChatGPT creator OpenAI accused DeepSeek of stealing OpenAI's data to make its software. AI requires mountains of data to perform tasks, so if DeepSeek inappropriately used OpenAI's content, that's another reason others may not be able to replicate LLMs on the cheap. Moreover, the U.S. is in a battle with China for digital supremacy. This led to export restrictions on the sale of AI chips to China. After DeepSeek's arrival, more restrictions may be coming, which would make it challenging for other Chinese companies to develop low-cost LLMs. The U.S.-China rivalry may also result in DeepSeek being banned. The DeepSeek AI technology is already barred by federal agencies such as the U.S. Navy and NASA. The U.S. passed a law banning another Chinese company, TikTok, over privacy and security concerns. President Donald Trump paused the ban's implementation, but eventually it will happen unless Congress reverses it or TikTok is sold to a U.S. business. Given how much AI relies on data to function, banning DeepSeek and other Chinese AI companies makes more sense than banning TikTok. A U.S. ban is not the only possibility. Italy banned DeepSeek at the time of this writing. Such actions by other nations would curb AI competition from China. These factors indicate Trump's recently announced Stargate project, which calls for up to half a trillion dollars in AI infrastructure investment, will proceed as planned. Nvidia is one of the companies working on the project. Nvidia CEO Jensen Huang met with Trump on Jan. 31 to discuss AI policy. That level of access and input into U.S. AI strategy means Nvidia is positioned to benefit as policies evolve. After all, Nvidia is already seen as the preeminent AI chip provider. Its reputation helped it achieve record revenue of $35.1 billion in its fiscal third quarter, ended Oct. 27, 2024. This represents an impressive 94% increase from a year ago. On top of its revenue growth, the company's other financials are outstanding, illustrating its strong underlying business. Its Q3 net income of $19.3 billion was a 109% increase from the prior year. Its Q3 balance sheet contained $96 billion in total assets, including $38.5 billion in cash, cash equivalents, and investments. Nvidia's cash hoard alone is greater than its Q3 total liabilities of $30 billion. Adding to this, the chipmaker's latest computing architecture, Blackwell, is selling well. CFO Colette Kress said on the earnings call, "We are on track to exceed our previous Blackwell revenue estimate of several billion dollars." The company is also more than an AI company. Its chips are used in other industries, such as in robotics, PCs, gaming consoles, and the automotive sector as cars increasingly add more digital capabilities. Nvidia's strong financials and revenue growth, the popularity of its products, and the diverse range of applications for its chips put the company in a position to prosper for years to come, making its stock an excellent long-term AI investment. And now is a good time to buy shares. That's because of Nvidia's stock valuation. Here's a look at its price-to-earnings (P/E) ratio, which tells you how much investors are willing to pay for a dollar's worth of earnings. Nvidia's P/E multiple is on the low end of where it's been over the past year at the time of this writing. This indicates the company's shares are reasonably priced compared to the past. Its stock valuation adds to its strong business, making now a good time to scoop up shares of this leading AI chipmaker ahead of its fiscal Q4 earnings report on Feb. 26.

Is Nvidia in Deep Trouble Due to DeepSeek? | The Motley Fool

DeepSeek, a Chinese artificial intelligence (AI) company that develops large language models (LLMs), turned the world of AI on its head recently when it claimed that it spent just $5.6 million (note this is million, not billion) on computing power to develop its base AI model. That would be a fraction of what U.S. companies have been spending on computing power to build their AI models. And demand for infrastructure to power AI software is expected to be immense. For example, Microsoft plans to spend $80 billion building out AI-capable data centers this year. Historically, about half of the spending on data centers goes toward servers. Meta Platforms, meanwhile, announced it would spend $65 billion this year on AI development, while the recently announced Stargate project backed by Oracle, OpenAI, and Softbank has plans to spend $500 billion on AI infrastructure over the next several years. The claim that DeepSeek could build an LLM so cheaply sent shock waves through the markets last week, and Nvidia (NVDA -3.09%) was the biggest loser. Nvidia's graphics processing units (GPUs) are central to the tech world's AI infrastructure buildout as they are the primary source of the specific type of rapid computing power that AI systems require. The market's logic was simple: If DeepSeek can create an LLM chatbot on par with (or better than) ChatGPT or Meta's Llama using far less processing power, that does not bode well for GPU demand. In the U.S., tech companies have been using steadily more GPUs to develop each new iteration of their AI models. For example, Meta is deploying 160,000 GPUs to train Llama 4 -- 10 times as many as it used to train Llama 3. Elon Musk's xAI, meanwhile, used 20,000 GPUs to train its Grok 2 model, while for Grok 3, it used 100,000 GPUs for phase 1 of its training, then boosted it to 200,000 for phase 2. If effective models can be built using much less computing power, that could potentially be bad news for Nvidia. While DeepSeek's chatbot is widely viewed as being very good, there is no verification about how much it actually spent on computing power, how many GPUs it used, or which particular models they were. The company claims it used a little more than 2,000 GPUs to train its model and that it had access to 10,000 older Nvidia A100 GPUs. Some experts do not believe it. Alexandr Wang, CEO of Scale AI, has said in interviews that it was his understanding that DeepSeek had access to about 50,000 more advanced Nvidia H100 chips, but that it can't say so publicly because U.S. regulations forbid their export to China. There is a belief that China is getting high-end Nvidia chips through Singapore. Nvidia's H100 chips cost $25,000 each, so 50,000 chips would have cost $1.25 billion. That's far higher than the asserted development price tag of $5.6 million. SemiAnalysis analyst Dylan Patel has estimated that DeepSeek and its parent company, Chinese hedge fund High-Flyer, have access to tens of thousands of Nvidia GPUs and have spent well north of $500 million on GPUs. Meanwhile, OpenAI has recently said that it has proof that DeepSeek was trained in part by extracting data from ChatGPT's model. Microsoft, an OpenAI investor, has found examples of data exfiltration through OpenAI developer accounts linked to DeepSeek. By extracting data from an established model, a company would be able to train a new model at a much lower cost through a process called distillation. Top White House AI advisor David Sacks has said that intellectual property theft may have indeed occurred, saying there was substantial evidence of it. While there is a lot of doubt surrounding DeepSeek's cost claims, and it appears that it could have gotten a leg up in its model's development by distilling data from OpenAI, there is also an argument to be made that even if DeepSeek was able to develop an AI model at a much cheaper price, that wouldn't necessarily hurt Nvidia. Jevons paradox is an economic theory that posits that when a resource becomes more efficient and costs are lowered, those lower costs lead to more consumption of the resource, and thus, the higher efficiency doesn't negatively impact overall demand. With AI, the belief is that lower computing costs will increase the technology's adoption. Upon initially hearing of DeepSeek's cost claims, Microsoft CEO Satya Nadella tweeted: "Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can't get enough of!" A number of Wall Street analyst firms, meanwhile, have said that this could be a good thing for Nvidia. That group includes Cantor Fitzgerald, which said that this will lead to the AI industry wanting more computing power, not less. At this point, I think investors should be skeptical of DeepSeek's claims. There is a lot of doubt about the costs used to build its model, and apparent evidence that it piggybacked off of OpenAI's model. In that light, the sell-off in Nvidia stock looks like a great buying opportunity. There is still a lot of AI infrastructure spending planned, and I don't think DeepSeek's claims are going to slow it down. Trading at a forward price-to-earnings (P/E) ratio of 27 based on analysts' 2025 estimates and a forward price/earnings-to-growth ratio (PEG) of under 0.85, the stock looks like a bargain. Stocks with positive PEG ratios below 1 are typically viewed as undervalued, and growth stocks often have PEGs much higher than that. For investors who have been waiting for a dip to buy Nvidia, this is their chance.

Here's What I'm Doing With My Nvidia Shares After DeepSeek's Groundbreaking Innovation

Nvidia (NVDA -2.99%) stock took a haircut recently after China-based startup DeepSeek announced the success of its R1 model at building open-source large language models for a fraction of the currently expected cost. Compared to the billions of dollars U.S. companies are investing to win the artificial intelligence (AI) race, DeepSeek reportedly did it for just $5.6 million. This caused Nvidia's stock to plummet by nearly 20%, However, I think that's an overreaction. Although there are some valid concerns, I think this decline represents a buying opportunity for investors. After all, DeepSeek's model was still trained on Nvidia GPUs. Nvidia GPUs were used to train DeepSeek's R1 model While the news headlines were filled with claims that DeepSeek trained its AI model for just $5.6 million, that's not a fair assessment. That figure doesn't include any hardware costs, or any of the pre-training costs that it took to arrive at that point. This is a key caveat that many investors are forgetting. Still, DeepSeek had a real efficiency breakthrough that the domestic AI hyperscalers haven't discovered yet. As for the hardware, DeepSeek used Nvidia H800 GPUs, which are modified from typically used H100 GPUs to abide by U.S. export restrictions. With a large number of consumers trying out DeepSeek's AI model, it undoubtedly had to purchase more GPUs to run all of the workloads, which is another catalyst for Nvidia's stock. Domestically, AI companies aren't going to cancel their Nvidia orders just because a competitor exceeded their performance. Instead, they'll continue increasing their computing power alongside making the models more efficient, which will increase the pace of innovation overall. Furthermore, DeepSeek's model likely only has consumer implications. There are questions about the security of the AI model and what information it collects from users. As a result, it's unlikely that any business will build its AI model on DeepSeek's platform. In my opinion, DeepSeek's efficiency breakthrough shouldn't be seen as a threat to Nvidia's business. Instead, it should be seen as a catalyst, as AI models are getting closer to becoming more mainstream and widely used. With that in mind, I'm looking to increase my stake in Nvidia stock, as there are just too many growth tailwinds to ignore. Nvidia's stock is on sale after the DeepSeek scare For its fiscal 2026 (ending January 2026), Wall Street analysts expect Nvidia's revenue to rise by 52%. That number may or may not change depending on how Nvidia's management comments on GPU demand during its next earnings call (likely at the end of February). But, for the reasons I laid out above, Nvidia likely won't see its growth trajectory affected. NVDA PE Ratio data by YCharts. As a result of the drop, Nvidia's stock is also on sale. At the time of writing, the stock trades for 44 times forward earnings, which isn't the cheapest valuation in the world. However, it still represents pretty good value for a company that's expected to grow at a strong pace over the next few years. While some may be scared to take a position in Nvidia's stock (an understandable view), I think it's time to take advantage. There's nothing wrong with waiting on the sidelines for more news, but the stock may recover by then. It's a guessing game of risk management, and I think the risk-reward profile for Nvidia is promising here.

Does DeepSeek's Breakthrough Help or Hurt Nvidia Stock? 3 Views You Should Know. | The Motley Fool

Perhaps no stock was more profoundly affected by the news from DeepSeek than Nvidia (NVDA -3.67%). In a sense, DeepSeek validated its dominance by announcing its H800 accelerators trained its model for less than $6 million. That cost is a tiny fraction of the hundreds of millions of dollars OpenAI has spent on ChatGPT's development cost. However, the news calls into question the demand for Nvidia accelerators. Lower-cost AI will likely increase demand for the technology, which may help Nvidia. Still, if entities can build AI models on less expensive technologies, they will presumably have less need to pay premium prices for its top-of-the-line AI chips. Knowing that, investors may wonder how best to invest in Nvidia stock going forward. In this article, three Motley Fool contributors will share their opinions on Nvidia and what investors should do next. Jake Lerch: When it comes to my opinion on Nvidia, I'm unmoved by the recent DeepSeek AI announcement. First of all, I'm taking the news with a healthy spoonful of skepticism. Granted, some AI experts have praised the open-source code that has been released, noting it is an impressive and significant breakthrough. However, questions remain about which -- and how many -- Nvidia GPUs were used to train this new model. But bear in mind that the U.S. government has placed export restrictions on Nvidia GPUs, specifically to prevent Chinese interests from gaining access to them. In other words, don't hold your breath waiting for full transparency on how DeepSeek was built -- and for what purpose. In any event, Nvidia's position as the leading horse in the race to design the best AI chips remains intact. Moreover, the next step in the AI revolution isn't about who will build the next great large language model (LLM). Instead, investors should remain focused on the bigger picture: AI-powered tools and applications are poised to deliver real-world productivity gains across the economy. Logistics, healthcare, finance, and every other sector will likely generate more sales and more profits as the AI revolution rolls on. Moreover, this breakthrough, such as it is, will not alleviate the need for better and faster chips. After all, if the technological revolution of the last four decades has taught us anything, it's that no one wants to be stuck with outdated technology. People, companies, and governments are always eager to pay up for newer and faster computational power. Remember: The world wasn't satisfied with dial-up internet, and we won't be satisfied with Nvidia A100s, either. The company will continue to innovate with improved chips like its latest, the Blackwell. And it is my belief that those chips will deliver innovations that will outshine DeepSeek. Justin Pope: It's been quite a stressful week for Nvidia shareholders. The stock plunged by double digits after DeepSeek, a Chinese AI company, recently sent Wall Street scrambling. DeepSeek claims its AI models deliver similar performance to OpenAI's while being open-source (freely available to developers) and costing significantly less to train and operate. More specifically, DeepSeek claims it trained its V3 (chat) AI model using a cluster of 2,048 Nvidia H800 GPUs, which cost approximately $5.5 million. This would be a remarkable achievement considering the tens of millions of dollars AI companies, like OpenAI and Google (owned by Alphabet), have spent on Nvidia's superior H100 chips. The company credits software engineering for the accomplishment, leaning toward efficiency rather than hardware to deliver the performance it needs. The fear is that Nvidia's GPU sales could cool off as other companies replicate DeepSeek's techniques. Nvidia depends on a small handful of AI hyperscalers for a considerable chunk of its revenue. Multiple industry experts are highly skeptical of the $5.5 million training costs. While Nvidia has claimed that DeepSeek operated within the parameters of chip export restrictions, some question whether the figure excludes additional costs or whether the model was genuinely developed from scratch. That said, DeepSeek's breakthroughs in efficiency seem more plausible. Because its model is open-source, anyone can see how the company did it, and can also run tests. Plus, DeepSeek is severely undercutting OpenAI's pricing. Its R1 (reasoning) model's API outputs cost just $2.19 per 1 million tokens versus $60 for ChatGPT's o1. The bottom line for Nvidia is that it's probably too early to react. Technology companies like Microsoft still can't support their AI demand, so it's unlikely that these massive AI investments will drop off overnight. Business should remain strong for Nvidia. However, over time, a push for cost efficiency could dent GPU demand if efficiency through software engineering can help lengthen the lifespan of existing AI chips. That arguably makes Nvidia a riskier stock moving forward than a few weeks ago. It's still one of the best AI stocks one can buy, but to minimize risk, consider dollar-cost averaging and diversifying your portfolio. Will Healy: The challenge to investing in Nvidia after the DeepSeek news comes down to one attribute: competitive advantage. Nvidia's financials and stock have been on fire since the spring of 2023 when OpenAI revealed that Nvidia AI accelerators powered GPT-4. None of Nvidia's competitors had offered an alternative at that time. Nvidia's accelerators and corresponding CUDA software remain far ahead of competitive offerings. Indeed, demand for the most advanced accelerators is unlikely to disappear, and it is possible Nvidia's competitive advantage will remain intact once analysts dig into the details of DeepSeek's breakthrough. Additionally, DeepSeek did not leave the Nvidia universe to train its models, which bodes well for the company. However, high demand has taken the prices of its state-of-the-art H200 accelerators above $30,000. Should demand at the top end fall, it could force Nvidia to cut the price of this technology. This is concerning since the data center segment, which designs the accelerators, was 87% of company revenue in the first nine months of fiscal 2025 (ended Oct. 27, 2024). Also, the $91 billion in revenue during that time frame rose 135% year over year. Nonetheless, if this latest development reduces its pricing power, that could mean significantly lower revenue per unit, which would presumably slow or possibly reverse Nvidia's revenue growth. Moreover, valuations show Nvidia stock may have a long way to fall. Many investors may overlook this issue since a 47 P/E ratio is arguably low for a fast-growing stock. Unfortunately, the price-to-book ratio of 46 is far above AMD's book value multiple of 3. Investors would likely question that book value multiple in an environment of slowing revenue growth. Furthermore, Nvidia has fallen by more than 50% twice since 2018, a reminder that Nvidia's momentum can turn quickly to the negative. It is premature to assume DeepSeek's breakthrough will bring another such decline in the stock price, and even if it does, Nvidia is unlikely to lose its overall competitive advantage. Still, with considerable downside possible, now may not be a good time to hold a disproportionately large position in Nvidia stock.

Nvidia Stock Investors Just Got Bad News From DeepSeek, but Certain Wall Street Analysts See a Silver Lining | The Motley Fool

Nvidia (NVDA 8.93%) made stock market history on Monday, Jan. 27, but not the good kind. The chipmaker saw its share price decline 17%, due to concerns about an artificial intelligence (AI) model from Chinese start-up DeepSeek. That nosedive erased $589 billion of its market value, the largest single-day loss for any company on record. What triggered the meltdown? Despite regulations from the U.S. government that prohibit Nvidia from exporting its most advanced AI chips to China, DeepSeek reportedly created a large language model that rivals the performance of the more sophisticated models created in the U.S. The company also claims it trained the model while spending much less money and without the most advanced Nvidia chips. That news has been disastrous for Nvidia shareholders, given how sharply the stock crashed. But many Wall Street analysts see the sell-off as an overreaction that creates a long-awaited buying opportunity for investors. DeepSeek published a research paper last week claiming its R1 reasoning model rivals the performance of OpenAI's o1 problem-solving model on certain benchmarks. The Chinese start-up also claims it spent less than $6 million training the large language model and says it completed the training with only 2,048 Nvidia H800 graphics processing units (GPUs). Importantly, the H800 GPU was designed specifically to comply with export restrictions. Comparatively, OpenAI spent more than $100 million training its GPT-4 model and used the more powerful Nvidia H100 GPUs. The company hasn't disclosed the precise number, but analysts estimate OpenAI used over 10,000 processors to train GPT-4. That estimate is plausible, given that Meta Platforms used 16,000 Nvidia H100 GPUs to train its Llama 3 model, spending an estimated $60 million. The implications are alarming for Nvidia. If DeepSeek trained R1 using fewer, less-powerful chips, then U.S. companies could theoretically reduce spending by mimicking the training techniques employed by the Chinese AI start-up. In turn, hyperscale companies like Amazon, Alphabet, Meta Platforms, and Microsoft could spend less than previously anticipated on Nvidia GPUs in the coming years. While DeepSeek trained its R1 model with impressive efficiency, many analysts view that as a positive development. They think it will accelerate the pace at which artificial intelligence is adopted, driving greater demand for Nvidia GPUs. Also, some industry experts question the validity of DeepSeek's claims concerning costs and infrastructure. Investors should remember that the DeepSeek situation is evolving rapidly and analysts may change their opinions. Meta Platforms and Microsoft are scheduled to report financial results on Jan. 29, followed by Alphabet and Amazon on Feb. 4. The market may get more clarity when the management teams at those companies host their quarterly earnings calls. However, several analysts currently believe DeepSeek's breakthrough will have little impact on long-term demand for Nvidia GPUs. In that sense, while the news has been disastrous for Nvidia shareholders, it has a silver lining: Nvidia stock is much cheaper today than it was last week, which creates a compelling buying opportunity for prospective investors. Indeed, among the 39 analysts who follow the company -- eight of whom updated their forecast in the last two days -- Nvidia has an average target price of $177 per share. That implies 50% upside from its current share price of $118.

Nvidia's Stock Just Did Something It Hasn't Done in a Year. Here's What History Says Happens Next. | The Motley Fool

Nvidia stock is tanking, and history suggests a clear direction of what way it could go in 2025. Over the last few days, the financial world has gone into a tizzy over a new start-up in the artificial intelligence (AI) realm. Chinese company DeepSeek sent shockwaves around the world after releasing a model akin to ChatGPT. The primary reason investors are panicking is because DeepSeek claims to have trained its model on older, less sophisticated chipware from Nvidia (NVDA -3.67%). These claims have left investors scratching their heads, questioning if Nvidia's newer architecture is worth the hefty price tag. As a result, shares of Nvidia have gone into a days-long downward spiral. Is this a buying opportunity, or could Nvidia stock be headed much lower? Below, I'm going to analyze some interesting trends in Nvidia's stock and make the case for what direction I think shares could be headed. The graph below illustrates multiple sell-offs seen in Nvidia stock in the days following DeepSeek's arrival. Though you'd think declines of this magnitude say it all, there's actually something pretty interesting going on in the background. When a stock price moves, so does the value of the company. In the case of Nvidia, the company's cratering share price has resulted in as much as $600 billion of lost market capitalization. On the surface, this looks horrific. However, as it often is the case with investments driven by overwhelming emotions, there's more than meets the eye. Since Nvidia's market cap has dropped, so, too, have its valuation multiples. As of this writing (Jan. 29), Nvidia's forward price to earnings (P/E) multiple is 30.1. Below, I'm going to dive into why this contraction in valuation multiples is important and what history suggests could happen next. In the table below, I've summarized Nvidia's forward P/E as of quarter end for the last year. Data source: Yahoo! Finance. The last time Nvidia's forward P/E hovered around 30 was last January. This is important to note because back in January 2024, Nvidia's market cap was $1.5 trillion -- approximately half of what it is today. Given the parity between the company's forward P/E between now and a year ago, you might be inclined to think Nvidia stock will soar higher -- as was the case throughout 2024. While such dynamics are what history suggests could happen, there is some important nuance to consider this time around. Since Nvidia's current forward P/E multiple is in line with where it was a year ago despite the company's market value doubling, this implies that Wall Street analysts are also expecting Nvidia's earnings to double. Looked at a different way, if Nvidia's market cap had doubled, but the company's earnings didn't accelerate at a commensurate pace, then Nvidia's forward P/E would have widened. This is a concept known as valuation expansion. But as I pointed out in the intro, the DeepSeek storyline is calling into question what demand trends are going to look like for AI infrastructure -- especially graphics processing units (GPU), which are Nvidia's bread and butter. Candidly, I would not be surprised to see some analysts begin haircutting their revenue and earnings projections for Nvidia. While this does not mean Nvidia should be seen as overvalued, I think investors need to let industry experts digest the DeepSeek news and refine their models accordingly. In other words, Nvidia's current forward P/E being nearly identical to where it was ago could be seen as a bit of coincidence, as earnings estimates are almost certainly going to change -- thereby calling into question how relevant the forward P/E ratio is right now. At a broader level, though, I'm confident Nvidia will remain a leader in the AI race as its GPUs should continue playing an important role in the technology's development going forward. Just how much? That's the billion-dollar question. So while history may suggest Nvidia's value could double this year, I'd think twice about that. In the long-run, I do think there's still a lot of value to be recognized investing in Nvidia stock. I just don't think shares are going to double again in 2025.

Should You Buy Nvidia Before Feb. 26? The Evidence Is Piling Up, and Here's What It Says. | The Motley Fool

Nvidia (NVDA -2.84%) stock soared 171% last year for the best performance in the Dow Jones Industrial Average, which it recently joined. The year was fantastic for the artificial intelligence (AI) chip giant. It entered this famous benchmark, reported record revenue, and readied the release of its new game-changing Blackwell architecture. In recent days, though, Nvidia's momentum has screeched to a halt as the stock lost about 15% over the past five trading sessions. The reason for the drop? Chinese start-up DeepSeek announced it had trained its AI model for a fraction of the amount big U.S. tech companies have been investing. The idea is that maybe these Nvidia customers have been spending too much, and following the DeepSeek news, they may adjust their strategies and cut their investments. Meanwhile, Nvidia is heading for its next big catalyst on Feb. 26, so you may be wondering if you should buy the stock before that date and potentially benefit from near-term and long-term gains. The evidence is piling up and here's what it shows. First, let's take a quick look at Nvidia's meteoric rise to fame in the AI market. The company historically was a top seller of graphics processing units (GPUs) to the video gaming industry, but as it became clear that the GPU could excel in other businesses, it created the CUDA parallel computing platform to help make that a reality. Today, though Nvidia continues to serve the video game market, the company's biggest business is AI. It's data center unit makes up 87% of today's revenue, and revenue has reached records -- growing in the double-digits or triple-digits -- quarter after quarter. This is not only due to the GPUs that power the crucial steps of training and inferencing of models, but also to the company's entire ecosystem of AI products and services, from networking options to software. All of this has helped supercharge Nvidia's stock performance as investors sought to get in on this high-growth player that's been leading in a high-growth market. Now let's consider the catalyst that's right around the corner: Nvidia is set to report fiscal fourth-quarter and full-year 2025 earnings on Feb. 26. Earnings reports generally trigger some stock movement, based on whether the company reports good or bad news. In some cases, the company can deliver a positive report, but investors still may sell some shares to lock in their profits. So it's impossible to predict with 100% certainty what a stock will do following an earnings report. Evidence before us right now offers some clues about direction in the weeks and months to come and could help investors make a smart decision. The DeepSeek news may have initially seemed negative for Nvidia, but it's unlikely to change anything for the tech powerhouse. The company's latest chip has proven it's the fastest and most efficient -- and its top customers want the best for their projects. As a result, I'd be very surprised if they did an about-face and cut spending on premium chips. In recent days, experts have cast doubts on the validity of DeepSeek's cost estimate. Analyst firm SemiAnalysis wrote that the GPU investment may have totaled more than $500 million -- a far cry from the less than $6 million DeepSeek announced. So I don't see the DeepSeek news as a long-term headwind. On top of this, Nvidia has reached a big moment right now. The company is launching its new Blackwell architecture, and in this quarterly report on Feb. 26 will announce the first Blackwell revenue figures. Last quarter, it predicted this would be several billion dollars, suggesting this new platform will be a major revenue driver for the company in the months to come. It's also important to keep in mind that the general environment for AI is positive right now. The U.S. government and OpenAI recently announced a $500 billion project to build out infrastructure in the country and named Nvidia as a key partner. This is against the backdrop of an already growing market. Analysts forecast today's $200 billion AI market may reach more than $1 trillion by the end of the decade. All of this shows us Nvidia's revenue growth opportunity is far from over. So, should you buy Nvidia stock before the upcoming earnings report? The evidence I've talked about so far and one more element offer an answer. Today, after the recent declines, Nvidia stock is trading at 27x forward earnings estimates, its lowest level in a year, and it looks dirt cheap, considering all of the positive points I've mentioned above. The answer, therefore, is yes. Right now, before Feb. 26, is a great time to get in on this top AI stock that could soar in the near term, but more importantly, over the long run.

What Is the Jevons Paradox and How Does It Make Nvidia Stock a Buy After DeepSeek's Revolutionary Breakthrough? | The Motley Fool

After DeepSeek's R1 model was released, it ignited a panic among stocks associated with artificial intelligence (AI). The Chinese startup reportedly trained its model for only $5.6 million, making many question why U.S. companies are pouring billions of dollars into computing power. This caused Nvidia's (NVDA -3.67%) stock to fall by nearly 20%. Nvidia is the primary beneficiary of AI spending in the U.S., as most AI models are trained on its hardware. In fact, DeepSeek's R1 model was trained on Nvidia's H800 chips (the more powerful H100 chips aren't available in China due to export bans). I see this drop as a buying opportunity, not a time to sell. There's a specific behavior that occurs after a breakthrough in efficiency known as the Jevons paradox, and I think all investors should familiarize themselves with it. The Jevons paradox was developed in 1865 by William Jevons, an economist from England. He observed that as a resource becomes more efficient thanks to technological advancements, the consumption of the resource doesn't drop. Instead, use rises because the cost has fallen enough to make it more accessible. This paradox was originally observed in coal usage during the Industrial Revolution but can also be seen in other areas, like fuel consumption in vehicles. If your car could instantly get 10 times better gas mileage, would you use it the same amount, or would you take it on more road trips because it's now cheaper to do so? This same mindset is currently being applied to the AI arms race, as DeepSeek's innovative breakthrough to train models more efficiently could increase the computing power needed. As models become more efficient, they will become more cost-effective for consumers and businesses alike. This will drive further demand for the product as the price falls, requiring more AI computing power. This is a counterargument to the knee-jerk sell-off that occurred after DeepSeek's R1 model gained popularity. I think it's a valid point and can be used to scoop up Nvidia shares for a much cheaper price tag. Despite the sell-off, Nvidia's stock still doesn't trade for bargain bin prices. As of the time of writing, Nvidia trades for 51 times trailing earnings and 44 times forward earnings. Those aren't historically cheap prices for most stocks, but most stocks aren't growing at the same pace Nvidia is. During the third quarter of Nvidia's fiscal 2025 (ended Oct. 27, 2024), its revenue rose 94%, which helps justify its price tag. Management expects fourth-quarter revenue to be around $37.5 billion, indicating 70% revenue growth. Nvidia's quarter just ended this week, so the effect (if any) of DeepSeek's R1 model won't be known until Q1 of fiscal 2026. We'll likely get a Q4 earnings announcement for Nvidia in late February when management will undoubtedly field questions about the strength of its business looking forward. Currently, Wall Street analysts still have strong growth in mind, with revenue expected to rise 52% in fiscal 2026. I think this is still a fair assumption, as I don't think the overall AI investing landscape will be affected by DeepSeek's breakthrough. Despite some market scares from DeepSeek's new AI model, I still believe that Nvidia has a strong investment thesis, as its GPUs are training models worldwide. Nvidia has a dominant market position, and its strength should allow it to continue its success well past 2025.

What Does Chinese AI Start-Up DeepSeek Mean for Nvidia Stock?

DeepSeek, a Chinese artificial intelligence (AI) start-up, is sending shock waves through the U.S. tech sector by demonstrating its latest AI assistant, which achieves performance comparable to or even surpassing some of the world's best chatbots. The kicker here is that DeepSeek reportedly accomplished this using significantly less computational power, relying on fewer and less advanced AI chips -- particularly Nvidia's (NVDA -3.67%) cutting-edge GPUs, which are typically considered essential for such tasks. This development suggests a potentially disruptive method for developing large language models (LLMs), offering a more efficient alternative to current strategies. It raises questions about future infrastructure investments and the demand for AI chips. The market's reaction has been swift: As of this wriging, Nvidia's stock has plunged more than 22% from its recent peak, with similar declines in other leading AI tech stocks. Let's explore what DeepSeek's emergence could mean for Nvidia and how it might affect investors' portfolios. The innovation behind DeepSeek's success Artificial intelligence is not only a major theme in technology but also a national security issue, given its pivotal role in areas like data analysis, intelligence, and military applications. This has led the United States to impose bans or severe restrictions on exporting high-end technologies, such as specialized AI semiconductors, to China since 2023, aiming to slow the country's technological progress and safeguard crucial supply chains. Despite these constraints, DeepSeek managed to develop AI models like DeepSeek-V3 and DeepSeek-R1 with cutting-edge capabilities on a reported training budget of around $6 million. Its white paper outlines an innovative approach that combines software ingenuity with new training techniques to maximize the potential of older Nvidia GPUs, surpassing their initial capabilities. DeepSeek's models have shown impressive results next to market-leading alternatives from OpenAI, Alphabet, and Meta Platforms in benchmarks for problem-solving, mathematical reasoning, coding, and general knowledge. The DeepSeek AI Assistant rapidly ascended to become the most-downloaded free application on the Apple App Store in the United States, demonstrating significant market traction and consumer acceptance. DeepSeek's disruptive influence is further underscored by its open-source platform, which makes the code publicly accessible, allowing businesses and developers to customize AI models without incurring the high costs of proprietary systems. For those seeking to integrate DeepSeek's most advanced models into existing tech infrastructure via an application programming interface (api), the company reportedly offers commercial pricing that is significantly lower than that of its competitors. Implications for Nvidia DeepSeek's emergence has multiple implications for the broader tech sector. Given the initial sell-off, the market has interpreted this development as decisively negative, likely based on a concern that novel AI development methods could reduce the demand for cutting-edge, expensive hardware and cut into the competitive moat of established leaders. That being said, the impact on Nvidia may be more nuanced as it looks like the next-generation AI chips, including Nvidia's Blackwell GPU architecture, are essential for pushing the boundaries of high-performance computing. If DeepSeek managed to break AI performance benchmarks with legacy hardware, its methods toward computational efficiency implemented by other tech players could make Nvidia's high-end products incrementally even more powerful. This scenario could help expand the AI market by opening up new uses that may become cost-effective while accelerating the timetable toward future breakthroughs like artificial general intelligence (AGI) applications as a demand driver for Nvidia. On the other hand, it is also clear that DeepSeek has introduced a new layer of complexity regarding Nvidia's growth runway. According to Wall Street analysts monitored by Yahoo! Finance, the chipmaker is expected to reach $197 billion in revenue in fiscal 2026, which ends in January 2026, driving a 51% increase in earnings per share (EPS) to $4.45. Any sign that customers are pivoting away from large orders, even at the margin, would undermine this earnings outlook and further pressure the stock. The company's upcoming fiscal 2025 fourth-quarter and full-year earnings report, set to be released on Feb. 26, will provide Nvidia CEO Jensen Huang and hist eam a chance to address whether DeepSeek is affecting the business and reassure shareholders. Data source: Yahoo! Finance. FY = fiscal year. YOY = year over year. The big picture for investors DeepSeek appears to have signaled a new shift toward efficiency in AI software, highlighting the rapidly changing landscape. Recognizing near-term uncertainties with an expectation for volatility to continue, I believe investors should stay the course with Nvidia as an AI leader with a technological edge in hardware. Unless there is evidence that its financials are under pressure, a positive long-term outlook should support the stock, which remains well positioned to rebound.

DeepSeek Shocked the AI Market Last Week. Here's Why Nvidia's Latest Move Should Crush the Panic. | The Motley Fool

Nvidia (NVDA -3.67%) is known for its dominance in artificial intelligence (AI) chips, holding about 80% of the market. The company sells the world's most expensive AI chips -- or graphics processing units (GPUs) -- but customers are willing to pay the price thanks to these products' top performance. Nvidia chief Jensen Huang has even said that, over time, Nvidia's chips are the best deal as they save on total cost of ownership. For Nvidia to keep on winning, customers must continue to flock to the company for their AI needs -- and get in on the company's latest and highest-priced chips. The tech giant, promising AI customers updated chips on an annual basis, has used innovation to keep this momentum going. But late last month, something happened that called into question Nvidia's ability to keep revenue growth soaring over the long term. Chinese startup DeepSeek announced that it had trained its R1 model in two months for less than $6 million. That compares with the billions of dollars top U.S. tech companies have spent on Nvidia AI chips. As a result, Nvidia stock sank 17% in one trading session, losing nearly $600 billion in market value. DeepSeek's news clearly shocked the market -- but Nvidia just did something that should crush the panic. Before we get to that, though, let's take a closer look at the DeepSeek news. As mentioned, the startup trained a model for much less than American tech companies have been spending on their programs. And DeepSeek says its R1 model rivals OpenAI's model o1, suggesting companies could slash their current AI budgets and still obtain pretty decent results. Nvidia even called DeepSeek's accomplishment "an excellent AI advancement." Investors, concerned that companies actually would reduce spending on Nvidia's most powerful GPUs, rushed to sell Nvidia stock. The idea was revenue could decline significantly if customers decide they don't need the tech giant's latest innovations and instead could opt for less expensive GPUs from Nvidia or rivals. But it's important to keep in mind that when things look too good to be true, they often are. First, we can't be certain the R1 training cost less than $6 million. Experts have said that, considering all of the steps involved in bringing a model to the launch stage, the figure looks much too low. For example, a report by consulting firm Semianalysis estimates DeepSeek spent more than $500 million on the project. Another important point: DeepSeek has said it used Nvidia chips designed for the Chinese market. These are meant to be less powerful than Nvidia's main line of chips to comply with the U.S. government's export controls. But some experts have questioned whether DeepSeek also relied on other Nvidia chips potentially purchased before the export controls kicked in. We don't have answers to these questions, of course, but what this shows us is the picture isn't detailed enough to prove that cheaper chips can do the job. Now, let's consider Nvidia's latest move. The company announced that the DeepSeek R1 model now is available for preview as an Nvidia NIM microservice -- and soon will be fully available as part of the Nvidia Enterprise software platform. Nvidia NIM allows developers to access AI models and build their own applications. This may lead to greater sales of Nvidia's latest GPUs as they can maximize inferencing performance. The company's new Blackwell architecture will give test-time scaling -- a technique that allows a model to think over a problem -- on models like DeepSeek R1 "a giant boost," Nvidia says. Nvidia, following the DeepSeek announcement, also noted the importance of high-powered tools for AI inferencing, saying, "Inference requires significant numbers of Nvidia GPUs and high-performance networking." So the latest move by Nvidia shows that, regardless of the performance that's achieved using lower-powered chips, its premium GPUs still are going to deliver the best results. And it's very likely that Nvidia's biggest customers -- tech-oriented powerhouses such as Meta Platforms and Tesla -- will opt for excellence, meaning they'll keep flocking to Nvidia for its latest GPUs. This should crush the panic that shook Nvidia stock following the DeepSeek announcement. And it should reassure investors that, over the long term, DeepSeek's accomplishment isn't likely to upset Nvidia's AI leadership, revenue growth -- or the potential for this top stock to rocket higher.

2024's Best-Performing Dow Jones Stock Is 2025's Worst Performer. Is the Sell-Off a Buying Opportunity? | The Motley Fool

In November, Nvidia (NVDA -5.12%) replaced Intel in the Dow Jones Industrial Average. The swap gave the value-focused index more exposure to technology and artificial intelligence (AI). Nvidia was by far the best-performing Dow component in 2024. But at the time of this writing, it is down 11% year to date, making it the worst-performing Dow stock in 2025. Here's why a big move in the growth stock wouldn't necessarily drag down the Dow, why Nvidia is under pressure, and whether the stock is worth buying now. Nvidia is the third-largest company by market capitalization behind Microsoft and Apple -- which are also Dow components. But a further sell-off in Nvidia is unlikely to move the index by much. In fact, the Dow gained 0.7% on the day of Nvidia's plunge. Unlike the S&P 500 and Nasdaq Composite, which are cap-weighted, the Dow is price-weighted. Meaning that companies with lower stock prices have lower weights in the index even if they are more valuable. Due to its lower stock price, Nvidia only makes up 1.7% of the Dow. The Dow has become much more tech-focused in recent years due to the additions of Salesforce, Amazon, and Nvidia. Still, these companies, plus Microsoft, Apple, IBM, and Cisco Systems, comprise only 23% of the index. In sum, Nvidia is large enough to affect the S&P 500 and Nasdaq Composite, but it could fall by 50% and not even move the Dow by 1%. Between fiscal 2020 and 2024, revenue for Nvidia's compute and networking segment went from $3.28 billion to $47.41 billion. The investment thesis shifted from a company whose chips were mainly used for gaming, PCs, visualization, and software for internal applications, to data center sales. Sales and operating income have grown exponentially as customers build large language models (LLMs) using Nvidia graphics processing units (GPUs). The company has continued to innovate, pouring money into research and development to build even more powerful chips. Announced in March 2024, its Blackwell GPU delivers 4 times faster AI training and 30 times faster AI inferencing compared to Nvidia's Hopper GPU architecture, which was announced in March 2022. The company's lead over the competition, its continued product development, and deep pockets from customers like Microsoft, Alphabet, Amazon, Meta Platforms, and Tesla have helped pole-vault Nvidia to one of the three most valuable companies in the world. And unlike some growth-driven rallies, Nvidia's results back up the stock's ascent. There are 33 U.S. companies with over $100 billion in trailing 12-month sales. But only one company, Nvidia, has a profit margin of over 55%. The next closest are Microsoft and Meta Platforms, which both have 36% profit margins. So Nvidia is truly in a league of its own in terms of combining sales and profitability. Because the company is growing so quickly, Nvidia's price-to-earnings ratio of 46.7 doesn't look all that expensive. But if growth slows, the stock could look overvalued. The biggest risks to Nvidia are competition and demand. And one of those risks just got put on full display. Nvidia shares fell 17% on Jan. 27 due to fears of lower demand for its chips. Chinese start-up DeepSeek reportedly built its own LLM powered by older Nvidia hardware for far lower cost than OpenAI's ChatGPT. If advanced AI systems can run at lower cost, it could erode Nvidia's pricing power and reduce the market for its cutting-edge chips. However, if AI becomes cheaper and more accessible, it could increase computing demand, which could be a net positive for Nvidia even if its margins come down. Higher demand for GPUs sent the stock price soaring to new heights. So if investors believe demand will fall, it stands to reason the stock could also take a hit. At times like this, it can be best to zoom out and focus on the big picture. For Nvidia, the million-dollar question is whether new AI models will continue requiring more computing power to operate or if its customers can make do with less. And if costs do come down, can the market expand enough so that Nvidia's growth story remains intact? Nvidia's differentiating factor is that its data center GPUs are vastly superior to those made by competitors like Advanced Micro Devices. So it can charge top dollar. But if data center GPUs become more commoditized, then the company may lose some of its edge. Given all the unknowns, the simplest way to approach Nvidia would be to include it in a basket of other AI stocks -- including other chipmakers, hyperscalers, software companies, and more. One way is to invest in an exchange-traded fund (ETF) with exposure to top AI names, like the iShares Semiconductor ETF or the Vanguard Information Technology ETF. Then your portfolio can benefit as AI evolves without being solely dependent on Nvidia to maintain its dominance. Alternatively, you could take a wait-and-see approach to Nvidia. The company will report fourth-quarter and full-year fiscal 2025 results on Feb. 26, during which analysts will assuredly get management's thoughts on DeepSeek and cheaper AI. Perhaps most important of all, it's worth remembering that the greatest advantage of being an individual investor is that you don't have to get caught up in market noise and can view sell-offs within the context of your own interests, financial goals, and risk tolerance. If you've had Nvidia on your watch list for a while, the good news is that the stock just got cheaper. But if you are still unsure about Nvidia, that's OK, too.

Why This Nvidia Shareholder Isn't Losing Sleep Over DeepSeek AI | The Motley Fool

No one thought the path to artificial general intelligence (AGI) would be smooth for investors, but the emergence of DeepSeek has clearly thrown a plot twist into the AI narrative. Nvidia (NVDA -3.67%) and other AI stocks plunged on Monday, Jan. 27, as investors responded to the threat from DeepSeek, the Chinese AI chatbot that rivals top models like ChatGPT for a fraction of the cost. Nvidia lost 17% in one session, wiping out $600 billion in market value, the biggest one-day loss for a single stock in market history. Since then, Nvidia has recouped some of those losses, a sign investors may believe the sell-off may have been an overreaction. Nonetheless, AI stocks remain significantly lower, and Nvidia itself tipped its hat to the Chinese start-up, with a spokesperson calling it "an excellent AI advancement." DeepSeek also seems to be gaining credibility, as Microsoft, which is believed to be OpenAI's biggest investor, has already added the model to its Azure cloud infrastructure service. So how big of a threat is DeepSeek to the AI ecosystem? To answer that question, let's outline a few facts about DeepSeek first. DeepSeek is a Chinese AI start-up founded by hedge fund chief Liang Wenfeng in May 2023. Unlike OpenAI's ChatGPT or Alphabet's Gemini, DeepSeek uses an open-source large language model, meaning developers can update it and adapt it to their own needs. DeepSeek is significant because its R1 model rivals OpenAI's o1 in categories like math, code, and reasoning tasks, and it purportedly does that with less advanced chips and at a much lower cost. According to one estimate, it costs OpenAI's o1 model $60 to generate a million tokens of output, while DeepSeek's R1 can deliver the same quantity for just $2.19. DeepSeek has impressed industry insiders with a 22-page research paper explaining how its model works, but the company has also been accused by OpenAI of using a method called distillation to build its models, a cost-efficient way of training an AI model using larger, more adept ones. Doing so constitutes a violation of OpenAI's terms of service. Distillation is commonly used in AI, but if that accusation is true, it would seem to undermine a lot of DeepSeek's credibility, making it seem like the Chinese start-up plagiarized at least part of its model. There's also a debate over how much DeepSeek actually paid for its infrastructure, as it said it cost just $5.6 million to train its V3 model. The V3 was built on Nvidia H800s, which were made to get around U.S. export rules and perform similarly to H100s, Nvidia's GPUs that have been widely used to build AI infrastructure and models in the U.S. Analysts have cast doubt on the $5.6 million figure, and that doesn't seem to include essential costs like research, architecture, or data, making it difficult to do a direct comparison with U.S-based AI models that have required billions of dollars in investments. It's too early to know what the implications of DeepSeek are for Nvidia and the broader AI sector, and there's still a lot of uncertainty around what exactly DeepSeek has achieved. The company appears to have made genuine gains in efficiency, but those seem less impressive if its model was built in part by borrowing from OpenAI. The true cost of the model also isn't fully clear. The DeepSeek-R1 launch was called a "Sputnik moment" by Silicon Valley honcho Marc Andreessen and others, and the geopolitical implications of the new chatbot could be just as meaningful as the technological ones. The U.S. could respond by intensifying the tech cold war with China, tightening export rules further and taking other measures. Additionally, allowing DeepSeek on U.S. smartphones while banning TikTok seems incongruous, and U.S. corporations and governments are likely to be skeptical of handing their data over to a Chinese start-up. For Nvidia investors, it's also worth remembering that this is just one episode in a years-long technology evolution, and is probably not as meaningful as a $600 billion one-day sell-off makes it seem. Even if DeepSeek shifts the entire industry to a more efficient open-source architecture, that could be a positive for Nvidia over the long run. According to Jevons paradox, lowering the price to run AI models could increase demand, leading to an increase in total consumption, which would drive more purchases of AI chips from Nvidia, though likely at a lower cost. It's also meaningful that DeepSeek was built on Nvidia chips. No one's challenging its supremacy there. Investors shouldn't miss the forest for the trees here. You should remember that a competent AI chatbot isn't the goal here. The ultimate goal is artificial general intelligence, including applications like autonomous vehicles and robotics, and it's unclear if DeepSeek dramatically changes the calculus around that. Those technologies are powerful and valuable enough that the race toward AGI will continue, and the tech giants competing in it will continue to pour billions into the infrastructure necessary to build it. Efficiency is important, but technological leadership is the real prize here. Nvidia stock was already dealt a setback by DeepSeek, and that could be true of Nvidia's business as well, but the company has proven itself to be nimble before. It's evolved its technology to go from primarily serving video games to cryptocurrency mining, AI, autonomous vehicles, 3D rendering, and more. CEO Jensen Huang is rightly regarded as a visionary in the industry, and it continues to rapidly innovate with its new Rubin platform in development. The AI frontier will continue to evolve, and Nvidia will adapt to market conditions as needed. Whatever the impact of DeepSeek, the race to AGI isn't going away, and neither is Nvidia.

Nvidia Stock Investors Just Got Good News From Meta Platforms and Microsoft | The Motley Fool

China's DeepSeek recently published a research paper that shocked Wall Street. The startup company claims it spent less than $6 million to train an artificial intelligence (AI) model whose performance matches or nearly matches that of leading U.S. models. Comparatively, OpenAI spent more than $100 million on its GPT-4 model. Nvidia (NVDA -3.67%) stock declined sharply on the news. Its market value fell nearly $600 billion in a single day, the largest daily loss by any listed company in history. The logic behind the crash is straightforward: If DeepSeek built a good AI model for less money, U.S. companies can use the same training methods to achieve similar efficiencies. Consequently, investors are worried U.S. companies would spend less than anticipated on Nvidia GPUs, which are usually the most expensive line item in AI infrastructure budgets. But the market may have overreacted. Nvidia shareholders just got good news from Meta Platforms (META 0.32%) and Microsoft (MSFT 0.02%), two of its largest customers. Read on to learn more. Meta Platforms CFO Susa Li told analysts on the fourth-quarter earnings call that capital expenditures would increase as much as 66% to $65 billion in 2025 to support its generative AI efforts and core business. That represents a material acceleration from the 39% increase in capital expenditures last year. CEO Mark Zuckerberg also provided context, telling analysts Meta's ability to spend heavily on AI is going to be a "strategic advantage" over time. He also said more efficient training methods do not necessarily reduce the need for AI chips. Instead, he sees recent breakthroughs as an opportunity to apply more computing power to inference workloads to "generate a higher level of intelligence and a higher quality of service." Not to be outdone by DeepSeek, Microsoft CEO Satya Nadella said on the latest earnings call: "We ourselves have been seeing significant efficiency gains in both training and inference for years now. On inference, we have typically seen more than 2x price-performance gain for every hardware generation and more than 10x for every model generation due to software optimizations." However, Nadella thinks the consequences will be favorable for Nvidia. "As AI becomes more efficient and accessible, we will see exponentially more demand," he told analysts on the call. Nadella also posted on X: "Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket." In the 1860s, economist William Stanley Jevons argued that the technological advancements that made coal a more efficient energy source paradoxically created more demand for coal. Put differently, Jevons believed the cost reductions arising from the greater price performance of coal were more than offset by the resultant increase in spending. When applied to Nvidia, the Jevons paradox means more efficient AI training methods will ultimately drive more demand for AI software and services. In turn, the cost savings arising from improved price performance of GPUs may be more than offset by the resultant increase in demand for those AI processors. Indeed, since DeepSeek published its report, Morgan Stanley analysts have upwardly revised their capital expenditure estimates, such that AI infrastructure spending among the four biggest hyperscalers -- Amazon, Alphabet, Meta, and Microsoft -- is projected to increase 32% to $317 billion in 2025, up from 28%. And that figure could increase further after Amazon and Alphabet report financial results this week. Importantly, other Wall Street analysts seem to be thinking along similar lines. Despite the DeepSeek news, Nvidia still has a median target price of $175 per share among the 67 analysts who follow the company. That implies 45% upside from its current share price of $120.

Nvidia Could Be a No-Brainer Buy in February | The Motley Fool

Nvidia (NVDA -3.67%) soared 171% last year and has established itself as a leader in one of today's highest-growth areas: artificial intelligence (AI). The tech giant not only dominates the AI chip market, but it's also built an empire of AI products and services that make it the go-to place for any company aiming to develop an AI platform. As a result, Nvidia's earnings have taken off, driven by its data center business -- the unit that serves AI customers. In the most recent quarter, revenue reached a record of more than $35 billion. That's more than the company generated annually just a couple of years ago. All this success has been great for Nvidia and its shareholders. Now, though, investors wonder if the momentum will continue. For example, news last month from Chinese AI company DeepSeek prompted concerns about demand for Nvidia's most expensive AI chips. But in spite of this and any other concerns, two points in particular could make Nvidia a no-brainer buy in February. So first, let's consider the Nvidia story so far. The company designs and sells the world's most powerful graphics processing units (GPUs), or chips used for crucial AI tasks like the training and inferencing of models. Big tech companies from Meta Platforms to Amazon are customers, and demand for Nvidia's latest chip architecture -- Blackwell -- has been "staggering." Blackwell is launching now, and Nvidia expects several billions of dollars in Blackwell revenue in the fourth quarter that ended at the close of January. So, the product is expected to be a smashing success right out of the gate. The recent news that caused Nvidia stock to stumble suggested U.S. tech companies are spending too much on AI -- and could be doing the same job with a smaller investment. Startup DeepSeek said it trained its model in just two months and for less than $6 million. This compares to the billions of dollars U.S. companies have invested -- and a lot of that has gone toward Nvidia's top chips and related products. But I think the market was too quick to jump to conclusions. Whether DeepSeek really completed training for that amount or not, Nvidia's highest-performance GPUs still have proven they are more efficient than the company's older GPUs -- and even other rival chips on the market today. And since speed and efficiency is the name of the game, it's unlikely Nvidia's customers will change their strategies and abandon the latest innovations. Now, let's consider the two reasons why Nvidia is a no-brainer buy in the month of February. The first is that Nvidia is set to report fiscal fourth-quarter earnings later this month -- on Feb. 26 -- and at that point we'll learn more about the Blackwell launch and initial revenue from the platform. Nvidia's earlier comments about high demand offer us reason to be optimistic, and positive news could send the shares soaring from today's level. The second reason to buy Nvidia now is the company not only will continue to benefit from the ongoing AI infrastructure build-out -- a good example is the newly announced $500 billion infrastructure project in the U.S. -- but it also should benefit from a new wave of AI growth just ahead. This is as companies start to apply AI to their businesses -- an example of this is the creation of AI agents, or software that can consider a problem, develop a solution, and apply it. Nvidia and its partners have created blueprints that integrate with Nvidia Enterprise software -- and these blueprints allow customers to develop their own AI agents. So Nvidia is setting itself up to win as this new era of AI growth unfolds. All this means that buying Nvidia stock at the start of February could boost your portfolio in the weeks to come, but even more importantly, over the long term. And that's why this stock is a no-brainer AI buy right now.

Here's the Worst-Case Scenario for Nvidia Stock | The Motley Fool

The AI industry was rocked in recent days with the release of an open source AI model from Chinese start-up DeepSeek that can compete with the best AI models from U.S. companies despite purportedly costing just $6 million to train. While it's possible the claims about costs are exaggerated or flat-out untrue, the DeepSeek model appears to be the real deal. While cheap, powerful AI models are a great thing for companies looking to deploy AI, it's potentially terrible news for Nvidia (NVDA 8.93%). The bull thesis for Nvidia, which dominates the market for powerful AI accelerators that are necessary to train the most advanced AI models, relies on the assumption that each successive generation of AI models will require more and more computational horsepower to train and run. DeepSeek's breakthrough raises some serious questions. This uncertainty led to an epic plunge for Nvidia stock on Monday that wiped out hundreds of billions of dollars in market value. A cheap AI model capable of trading blows with the best models from Open AI and Anthropic isn't enough on its own to scuttle Nvidia's growth story. Cheap and efficient AI models could spur more demand and ultimately drive sales of AI accelerators higher in the years ahead. Former Intel CEO Pat Gelsinger stated in a post on X that "Computing obeys the gas law. Making it dramatically cheaper will expand the market for it." Cheap AI models that don't require massive clusters of high-powered graphics processing units (GPUs) to train and run may not be a negative for Nvidia if it greatly expands the use of AI. However, there's another problem lurking. Nvidia's multitrillion-dollar valuation rests on one more important assumption: AI models will continue to become more capable as more computing resources are thrown at them. This was certainly true in the early days of AI, but it may not be true for much longer. AI companies have largely exhausted the data used to train AI models, and new AI models aren't leaping ahead in terms of performance anymore. The founders of Andreessen Horowitz noted late last year that improvements are slowing down, and AI models may be hitting a ceiling. It's important to remember how large language models (LLMs) work. Ultimately, these models predict the next token in a stream of tokens. That's it. There's no reasoning going on, just the illusion of reasoning. While new techniques could unlock improved performance, it makes sense that there would be a limit to the capabilities of this class of AI model. It's the combination of cheap AI models and this potential ceiling in capabilities that would be the death knell for Nvidia stock. If AI models stop improving meaningfully no matter how much computing power is thrown at them, and a top-tier model can be trained cheaply on second-rate hardware, that's the ballgame. Demand for Nvidia's expensive AI accelerators would likely fall off a cliff as the AI bubble bursts. Even under this scenario, AI will still be a useful and potentially game-changing technology for companies that find good use cases. However, the GPU gravy train for Nvidia would come to an end, and tech giants pouring tens of billions of dollars into AI data centers would likely never recoup those investments. Nvidia is still valued at more than $3 trillion. The company is selling a lot of pricey data center GPUs and churning out incredible profits, but this valuation depends on two assumptions that are starting to look like they may not be true. First, that AI models will require ever-growing amounts of computing power to train and run, and second, that there is no ceiling in their capabilities. DeepSeek's cheap AI model represents a big crack in Nvidia's growth story. It's not enough on its own to derail the AI king. However, when cheap AI models are combined with the very real prospect that AI models just aren't going to get much more capable from here, the basis for Nvidia's stratospheric market value falls apart. I can't predict the future, and neither can you, but the uncertainty surrounding the future of the AI industry makes Nvidia an incredible risky stock.

Nvidia vs. Alphabet: Which Artificial Intelligence (AI) Stock Should You Buy After the Emergence of China's DeepSeek? | The Motley Fool

The dip in some of the market's hottest stocks could be a buying opportunity. The emergence of a small Chinese artificial intelligence (AI) company called DeepSeek initially put a giant hole in the U.S. stock market. Tech stocks -- particularly those connected to the AI trend -- got crushed, and GPU king Nvidia (NVDA -3.35%) lost roughly $600 billion of its market cap in a single day as investors grew concerned about the company's moat, and whether AI software could be trained and powered at lower costs with less powerful chips. Now the big question that analysts and investors are grappling with is how serious a threat DeepSeek actually is to the AI sector's status quo. Some think that the company may have invested more money and used higher-quality chips to develop the DeepSeek R1 large language model than it's letting on, while others think its claims are legitimate. Some also think DeepSeek's innovations could prove a net positive for other AI companies long term. After the recent sell-off, would investors be better served to buy the dip on Nvidia or Alphabet (GOOGL -0.82%) (GOOG -0.76%)? The big reason that Nvidia got hit so hard by DeepSeek is that the Chinese company allegedly managed to create a chatbot with capabilities rivaling ChatGPT, but at a fraction of the cost. DeepSeek says it trained its model for just $5.6 million and used older Nvidia chips to do it. Meanwhile, OpenAI has spent more than $100 million to train certain ChatGPT models. Nvidia issued a statement on Jan. 27 that seemingly praised DeepSeek and said that the chips used to build its model were "fully export control compliant." The chipmaker also said DeepSeek shows why its chips are needed and that they will be needed in the future. One group of analysts seemed to concur. Cantor analyst C.J. Muse called the sell-off a complete overreaction: We think this view is farthest from the truth and that the announcement is actually very bullish with AGI (artificial general intelligence) seemingly closer to reality and Jevons Paradox (what happens when improved efficiency actually boosts demand, causing resources to be used up more quickly overall) almost certainly leading to the AI industry wanting more compute, not less. Muse also noted that there are some doubts about what chips DeepSeek actually used, but he ultimately believes the innovation is bringing the world closer to an artificial general intelligence and will ultimately lead to more widespread use of AI. However, there is also a camp that is concerned DeepSeek is starting to shrink Nvidia's incredible moat, which has supported its 75% operating profit margins. Analysts at BMO said while there are still a lot of questions, the current information available suggests that DeepSeek likely used servers with 50% to 75% less power intensity than servers that use Nvidia's most recent GPUs. No analysts have outright said they were putting a sell rating on Nvidia stock yet, but the backdrop remains uncertain. Alphabet faces a similar threat from DeepSeek. However, its stock didn't sell off as hard, largely because it's in a different place than Nvidia. For one thing, its stock didn't perform nearly as well in 2024. Alphabet has been dealing with its own issues, notably including a Department of Justice lawsuit that accused the company of using monopolistic practices to dominate the digital ad space and employing pricing methods that essentially made it the only shop in town. A federal judge agreed with Justice. The department then submitted a filing that some view as asking the judge to force Alphabet to break itself up and sell its Chrome browser. While many suspect a breakup plan won't actually come to fruition, it would adversely impact the company if it did. Additionally, while investors have priced more and more potential into Nvidia's stock, Alphabet's stock price may not fully reflect its AI strengths and opportunities. The company actually builds AI data center chips of its own, for example, and its DeepMind unit is similar to OpenAI. Yet according to D.A. Davidson analyst Gil Luria, these divisions -- potentially worth multiple hundreds of billions of dollars -- are not adequately priced into the stock. Luria still has a hold rating on Alphabet, but would become more optimistic about it if management makes more of an effort to unlock value. As things stand, I don't foresee impending doom for Nvidia. I think the magnitude of the DeepSeek-driven sell-off also had to do with the fact that Nvidia had been trading at an elevated valuation, making it more vulnerable to a correction. Even after the sell-off, the stock still trades at about 41 times forward earnings, which may end up looking like a discount someday. For now, though, I'd recommend buying Alphabet over the AI chip king. Alphabet is still dealing with the overhang of the Justice Department lawsuit, but I don't expect it to have to sell its Chrome browser. Furthermore, the stock only trades at about 22 times forward earnings, and that price may not be giving the company any credit for its AI businesses.

Nvidia's worst week in years: Another 6% drop -- should you panic too?

Nvidia shares tumbled nearly 6% in intraday trading on Wednesday, continuing a turbulent week characterized by concerns over the competitiveness of American AI firms and their spending on the emerging technology. This decline followed a significant drop of over 17% on Monday, which resulted in a loss of nearly $600 billion off Nvidia's market cap. The decline was fueled by the rapid rise of lower-cost AI models from Chinese companies, such as DeepSeek, which claims its AI model can operate on par with American counterparts at a much lower cost. This new competition prompted analysts at Bank of America to describe the situation as "AI's Sputnik moment," indicating that it could compel U.S. firms to increase their spending on AI technologies, potentially benefiting Nvidia, Broadcom, and other AI chipmakers. During the sell-off, Nvidia led losses in the Dow Jones Industrial Average and was among the top decliners on the S&P 500 and Nasdaq. Other AI-focused stocks, including Broadcom and Palantir, also experienced declines. The market faced additional pressure as Chinese tech giant Alibaba introduced a new AI model that it claims outperforms offerings from DeepSeek, OpenAI, and Meta Platforms. Facing this competitive landscape, the earnings reports of Meta and Microsoft are anticipated, as investors are keen to see how these companies justify their AI investments. Analysts from Morgan Stanley noted that advancements by DeepSeek could positively influence Microsoft and Meta, hinting that Meta might adopt these developments and that Microsoft's Azure platform might benefit from increased proliferation of AI models. Microsoft shares drop 4.5% while Meta gains 2.5% in Germany Bank of America reiterated a "buy" rating and a $190 price target for Nvidia, suggesting that the recent sell-off represents an enhanced buying opportunity. Despite the bleak market conditions, retail investors demonstrated optimism in Nvidia; data from VandaTrack indicated that over $562 million was invested in the stock on Monday, marking the largest single-day inflow in its records. On Tuesday, as Nvidia's shares rebounded approximately 9%, retail investors contributed nearly $360 million more. In total, retail investors injected over $920 million into Nvidia shares across the tumultuous two days. Strategists on Wall Street largely agreed with this bullish sentiment. Fundstrat's head of Research, Tom Lee, referred to the situation as a "buy the dip" moment for Nvidia, while Bank of America Analyst Vivek Arya supported this view, stating the recent downturn presented a sound buying opportunity for Nvidia and similar companies. DeepSeek's claim that its AI model uses cheaper chips and less data has raised concerns regarding future AI chip sales for industry leaders like Nvidia and questioned the long-term dominance of U.S. hyperscalers. Bernstein analyst Stacy Rasgon characterized the sector's sell-off driven by DeepSeek's emergence as "overblown," stating it does not indicate "doomsday for AI infrastructure." Disclaimer: The content of this article is for informational purposes only and should not be construed as investment advice. We do not endorse any specific investment strategies or make recommendations regarding the purchase or sale of any securities.

Why Did Apple and Meta Platforms Rise While Nvidia Fell 17% in 1 Day? | The Motley Fool

Jan. 27 was a wild day in the stock market as investors reacted to Chinese start-up DeepSeek's R1 "reasoning" model that competes with OpenAI's o1 model. Here's a look at how markets are reacting to DeepSeek's impact on AI and why Meta Platforms stands out as a top AI stock to buy now. Reports indicate that DeepSeek was able to build its model at a far lower cost than OpenAI's solution, which led to fears of slowing demand for AI infrastructure like Nvidia graphics processing units (GPUs) or Broadcom's application-specific integrated circuits. The news marks a potential step change in the way AI investments are viewed. The Donald Trump-backed $500 billion Stargate AI project is tasked with building out data centers to support AI workflows. Microsoft is on track to spend around $80 billion on AI in fiscal 2025. If highly sophisticated AI tools can be built fairly inexpensively, more scrutiny may be warranted on AI spending. And investors won't applaud a company just because it is throwing money at AI. However, a subsequent 9% rebound in Nvidia the following day on Jan. 28 came as some investors and analysts viewed efficiency improvements as a net positive, arguing that overall compute demand could increase if AI became more affordable for smaller companies. A similar comparison would be the price of an iPhone over time. When the iPhone first came out in 2007, it cost $499 for the 4 GB version and $599 for the 8 GB model. Inflation-adjusted, that cost is closer to $780 for the 4 GB and $930 for the 8 GB. But the new iPhone 16 starts at just $799, so the cost of an iPhone has stayed about the same since its release despite product innovation and exponential storage increases. Rather, Apple has grown by several folds since then, both in terms of earnings and the stock price, because the iPhone became a consumer staple and Apple expanded its ecosystem across accessories and services. The same could occur with Nvidia. If the market for its products grows, Nvidia won't need to rely so much on pricing power, which could benefit the company long-term. As of market close on Jan. 24, Apple was the worst-performing component of the Dow Jones Industrial Average year to date. So a rebound in Apple, which may be viewed as less of a pure AI play than companies like Nvidia, makes some sense. But what may come as a surprise is Meta, which blasted to a new all-time high on Tuesday. In October, I predicted that Meta would be worth more than Alphabet and Amazon by 2026, which I still think will happen. Meta is one of the clearest examples of AI fueling rapid growth and margin expansion. AI is instrumental in Meta's algorithms for delivering engaging content to users so they stay on the platform longer and, therefore, see more ads. Meta AI is also helpful for creators to customize content, engage with their audiences, and more. So although Meta is spending a substantial amount of money on research and development (R&D), it is still growing its revenue and operating income at a breakneck pace. Meta has operating margins around 40%, even considering around 27 cents for every dollar in revenue goes toward R&D. The results are even more impressive once factoring in steep (and growing) losses from Meta's Reality Labs division, which makes hardware and metaverse software, and invests in AI. Meta has a price-to-earnings (P/E) ratio of just 31.8 and a forward P/E of 26.5, which is a reasonable valuation for a high-octane growth stock. But again, the valuation is even more attractive once considering Reality Labs' impact on earnings. In the first three quarters of 2024, Meta lost $12.76 billion on Reality Labs and reported net income of $41.52 billion. So if you take out Reality Labs, the amount that investors are paying for the rest of Meta (the advertising business) is actually dirt cheap. The sell-off in Nvidia is a painful reminder of the importance of knowing what you own and why you own it, and aligning your investments with your risk tolerance. Nvidia is a phenomenal, highly innovative company. But its value is also based on continued rapid earnings growth. Meta isn't expected to grow earnings as quickly as Nvidia and is a better value. Still, Nvidia could be worth owning if you have a high risk tolerance and believe in the long-term investment thesis. But the stock could continue to be highly volatile while investors re-evaluate Nvidia's role in the future of AI.

1 Wall Street Analyst Thinks Nvidia Stock Is Going to $175. Is It a Buy? | The Motley Fool

Shares of Nvidia (NVDA -3.67%) suffered a sharp drop earlier this week. News that low-cost artificial intelligence (AI) model from DeepSeek, a Chinese AI start-up, could compete with the most advanced offerings from companies like OpenAI sent a shockwave through the tech sector. If you can build it for millions, why spend billions on Nvidia's data center chips? This is the core concern that sent Nvidia tumbling. But some Wall Street analysts believe DeepSeek's accomplishment will benefit the chip giant. Citigroup analyst Atif Malik maintained a "buy" rating on the stock with a $175 price target, implying upside of 40% over Nvidia's current share price of about $125. However, there are mixed opinions about how DeepSeek will ultimately impact Nvidia's data center business. If DeepSeek can build a state-of-the-art AI model at low cost, it could push big tech companies to adopt similar AI training techniques to do more with less, slowing Nvidia's recent momentum. The company's data center segment hauled in $30.8 billion of revenue in its fiscal 2025 third quarter, more than doubling year over year. However, an Nvidia spokesperson told CNBC on Monday that DeepSeek's accomplishment is an "excellent AI advancement." And there is a possibility that instead of pushing tech companies to pull back on data center spending, the efficiency of DeepSeek's model will only increase the overall demand for AI and Nvidia's hardware to further accelerate innovation in the space. Is the stock heading to $175, and should you buy it now? There are a lot of unknowns at present, and some experts are skeptical of DeepSeek's claim that it trained its advanced model for under $6 million. Still, with Nvidia stock already trading at a premium valuation, it may struggle to hit new highs in the near term as investors sort out what DeepSeek means for the industry. The safest course is to wait until after Nvidia's earnings report on Feb. 26 when management updates investors on demand trends. That will offer insight into how these recent developments are impacting the business.

Where Will Nvidia Stock Be in 3 Years? | The Motley Fool

If you held on to Nvidia (NVDA -3.67%) stock for the last three years, you are probably laughing all the way to the bank. A $10,000 bet made in early 2022 would be worth almost $55,000 today -- an impressive return of 450%. That said, past performance doesn't guarantee future results. And the dynamics that helped Nvidia achieve such remarkable performance could change significantly. The new Chinese large language model (LLM) DeepSeek is the elephant in the room. It purportedly demonstrated that advanced AI models can be built without outrageous costs, in stark contrast to the strategies used by its American rivals, such as OpenAI, Alphabet, and Meta Platforms. Let's explore how this story could develop over the next three years and beyond. While it's easy to blame DeepSeek for all the AI industry's challenges, that might miss the big picture. The core problem is that training LLMs is too expensive relative to their profit potential. While the emergence of a dramatically cheaper Chinese rival brought this problem into the mainstream, industry observers have been discussing it for months. In June 2024, Goldman Sachs published a report titled "Gen AI: Too Much Spend, Too Little Benefit." The paper suggested that the $1 trillion in capital expenditures tech giants are expected to pour into generative AI hardware and development is unlikely to pay off because of the technology's inherent limitations. It argued that LLMs might not be ideal at solving complex problems that can justify their development costs. For Nvidia, this problem is distant because it focuses on the pick-and-shovel side of the opportunity -- making the graphics processing units (GPUs) that cloud computing companies use to build their AI computing power (which is then rented to consumer-facing start-ups). However, as these start-ups continue to fail or burn through money (OpenAI lost $5 billion in 2024), it may be a matter of time before chip demand starts to slow. While AI bulls were content to ignore the warning signs of unsustainable industry spending, DeepSeek made the problem too obvious to ignore. With its launch in January, the company's open-source generative AI chatbot quickly became the most downloaded free app in the U.S. on Apple's App Store -- beating out its American rival ChatGPT. More importantly, DeepSeek's R1 model has similar performance to ChatGPTs o1 despite being developed for $6 million using less advanced Nvidia H800 chips, according to its developers. OpenAI claims DeepSeek may have used its proprietary models to train R1 in a process called "distillation," and the White House's AI and crypto czar David Sacks believes "it is possible" that IP theft occurred during its development. Over the coming years, it is possible that the U.S. government could intervene on behalf of American AI companies by further restricting chip exports to China (a move that could hurt Nvidia's sales in that country) or try to undermine DeepSeek based on intellectual property enforcement or national security concerns, as was done to TikTok. But ultimately, it seems like the cat is out of the bag, and even if the U.S. manages to stamp out DeepSeek, other cheaper LLMs could rise to take its place. The already questionable economics behind big tech's AI chip spending has become even harder to justify. Over the coming years, investors should expect Nvidia's growth and margins to decline as industry participants realize they don't need its latest (and most expensive) hardware to develop LLMs and other generative AI applications. But while the stock's exponential growth trajectory will likely end, investors shouldn't expect a crash.

Nvidia Stock Drops Wednesday as AI Chipmaker's Roller-Coaster Week Continues

Bank of America analysts told clients in a note Wednesday they see this as "AI's Sputnik moment," suggesting the competition could push U.S. firms to spend even more on AI, to the benefit of Nvidia, Broadcom, and other AI chipmakers. Nvidia (NVDA) shares tumbled nearly 6% in intraday trading Wednesday, dashing hopes for a quick recovery from losses earlier in the week amid concerns about competitiveness of American AI firms and their spending on the emerging technology. The AI chipmaker's stock led losses in the Dow Jones Industrial Average, and was among the top decliners on the S&P 500 and Nasdaq Wednesday. Shares of Broadcom (AVGO), Palantir (PLTR), and several other AI darlings over the past year also were lower. The surging popularity of an app from Chinese startup DeepSeek, which runs on an AI model it claimed can perform on par with American rivals at a fraction of the cost, had sent Nvidia and a slew of other U.S. tech stocks into a tailspin Monday. Despite a brief rebound in Tuesday's session, the tech sector fell back into the red Wednesday as Chinese tech giant Alibaba (BABA) rolled out a new AI model it says can outperform models from DeepSeek, OpenAI, and Meta Platforms (META). The rapid rise of lower-cost models from Chinese companies that can compete with those from leading American firms has spurred a reckoning on Wall Street, with earnings from Meta and Microsoft (MSFT) likely to be in the spotlight later tonight as both firms face pressure to prove their AI investments can yield results that justify the costs. Analysts have so far remained mostly bullish on their prospects, with Morgan Stanley analysts telling clients that advances by DeekSeek could prove "positive" for Microsoft and Meta, suggesting Meta could implement them and that Microsoft's Azure platform would benefit from a proliferation of AI models and consumer applications. Bank of America analysts told clients in a note Wednesday they see this as "AI's Sputnik moment," suggesting competition could push U.S. hyperscalers like Microsoft, Amazon (AMZN), and Alphabet (GOOGL) to spend even more on AI, to the benefit of Nvidia, Broadcom, and other AI chipmakers. They reiterated a "buy" rating and $190 price target for Nvidia's stock, adding they "view the recent selloff as an enhanced buy opportunity."

Can Nvidia Stock Still Hit $200 in 2025? | The Motley Fool

Nvidia (NVDA -3.67%) stock was crushed on Jan. 27, dropping 17% in a single session after a fresh wave of doubts came to the forefront following the cost-effective artificial intelligence (AI) model unveiled by Chinese start-up DeepSeek. DeepSeek's claim that it trained its R1 model for just $6 million and made it competitive enough to perform as well as the more expensive o1 reasoning model from OpenAI rattled investors. Shares of Nvidia have delivered stellar gains over the past couple of years, as its revenue and earnings have grown remarkably thanks to the booming demand for its expensive graphics cards that are used for training and deploying AI models. So, DeepSeek's claim of doing more with less has raised fresh concerns about the potential demand for Nvidia's chips in the future. However, this is not the only factor that has been weighing on Nvidia stock of late. The potential restriction on Nvidia's chip exports to international destinations and the relative slowdown in spending on AI infrastructure are also issues (which have now been exacerbated by DeepSeek's breakthrough). However, pressing the panic button and selling Nvidia on this piece of news may not be a smart move. After all, there are enough tailwinds suggesting that it may be able to regain its mojo once again and even hit the $200 mark. Concerns about a slowdown in AI infrastructure spending seem to have been put to rest based on recent announcements made by the major stakeholders in this space. First, Microsoft announced that it is set to raise its capital expenditure (capex) by 43% in the current fiscal year to $80 billion as it looks to build more AI data centers. Now, Meta Platforms has also announced that it will increase its 2025 capex by roughly 50% from last year's estimated outlay. The announcements by these tech giants have also been accompanied by a major development at the White House. SoftBank, OpenAI, Oracle, and Abu Dhabi-based AI investment firm MGX have announced that they will "begin deploying $100 billion immediately" for building AI infrastructure in the U.S. as a part of the Stargate Project. Of course, you may be wondering if the low cost of training DeepSeek's model will lead Nvidia customers to reduce their spending on its chips. It's too early to jump to a conclusion, but there is a possibility that the demand for Nvidia's data center graphics cards won't be dented. That's because the efficiency displayed by DeepSeek could encourage more companies to build cost-efficient AI models, which means that compute demand is likely to remain solid. So, there is a possibility that AI-focused spending by U.S. tech titans in 2025 could head higher once again. This would pave the way for Nvidia to sustain the outstanding revenue and earnings growth that the company has been clocking over the past couple of years. A big reason why Nvidia will be the most likely beneficiary of the AI splurge in 2025 is because it continues to dominate the market for data center graphics processing units (GPUs). The company controls an estimated 70% to 95% of the AI data center GPU market per various estimates, though there's a good chance that its share is at the higher end of that range. That's because rivals such as AMD and Intel have barely managed to make a dent in the AI chip market. AMD is Nvidia's closest competitor in the AI data center GPU market, and its estimated 2024 revenue from sales of these chips is a fraction of Nvidia's potential revenue from this space. Things are even worse at Intel, as the company is expected to fall short of its $500 million AI chip revenue target for 2024. So, Nvidia is on track to corner most of the incremental spending on AI chips this year. Even better, the doubling of advanced chip packaging capacity by Nvidia's foundry partner Taiwan Semiconductor Manufacturing should ideally allow the former to cater to the terrific demand from the tech giants. As a result, there's a good chance that Nvidia's earnings growth in fiscal 2026 (which will begin shortly and coincide with 11 months of 2025) could be higher than what analysts are expecting. That could be the reason why this semiconductor stock could jump to $200 this year. Nvidia stock needs to jump 55% from current levels to hit $200. Consensus estimates are projecting a 50% increase in Nvidia's earnings in fiscal 2026 to $4.45 per share. The Street-high estimate points toward a 101% jump in its bottom line. However, Nvidia can beat the average earnings growth estimate for the new fiscal year on the back of incremental spending on AI infrastructure and the capacity improvements by TSMC. Assuming it achieves a 75% jump in its bottom line, Nvidia could report earnings of $5.16 per share in fiscal 2026. Applying a forward earnings multiple of 40 (in line with the company's five-year average forward earnings multiple) to the projected earnings for the fiscal year would be enough to help Nvidia stock hit $200. What's more, the forward earnings multiple of 40 assumed above is lower than the stock's trailing earnings multiple. So, this AI stock could deliver healthy gains even if it trades at a discount going forward.

Why Nvidia Stock Plummeted This Week | The Motley Fool

Nvidia (NVDA -3.67%) stock saw a big valuation pullback in this week's trading. The graphics processing unit (GPU) leader's share price fell 15.8% from its level at the previous week's market close, according to data from S&P Global Market Intelligence. Nvidia was hit with sell-offs this week as information surrounding the new R1 artificial intelligence (AI) model from DeepSeek signaled a potential paradigm shift in AI training and inference. In addition to the possibility that new approaches to AI software could mean lower demand for Nvidia's GPUs, the company's stock also saw pullbacks in conjunction with geopolitical and macroeconomic pressures. Nvidia stock saw a massive pullback in Monday's trading, closing out the daily session down 17%. The sell-off worked out to a roughly $600 billion pullback in the GPU leader's market capitalization and marked the biggest-ever valuation pullback for a company on a pure-dollar basis. The Monday sell-off for the stock was spurred by the market's reaction to a new AI model from DeepSeek -- a Chinese company. According to information from DeepSeek and other reports, its R1 model was matching or beating the performance of OpenAI's latest GPT model. At the same time, it reportedly took under $6 million to train -- far below the $100 million training figure for OpenAI's model. Strikingly, DeepSeek's model was said to be able to perform reasoning and inference applications with far lower processing and cooling requirements. Nvidia's incredible valuation rise has been powered by the central role that its advanced GPUs play in training and running high-performance AI applications. If more efficient artificial intelligence models are able to deliver high levels of performance with lower processing needs, it could hurt demand for Nvidia's hardware. In addition to the immediate business-specific implications of DeepSeek's technology, Nvidia stock also lost ground in conjunction with broader geopolitical dynamics related to artificial intelligence. The R1 model highlighted the possibility that the U.S. is losing its lead over China in AI and the rising tensions between the two countries. Even if R1 winds up having a relatively minimal impact on Nvidia's business, the trajectory of relations between the U.S. and China could have a big impact on the company's valuation over the next five years. Adding more bearish catalysts, Nvidia stock was pushed lower by macroeconomic catalysts on two fronts. For starters, the Federal Reserve said at its meeting this week that it would be keeping the benchmark interest rate at its current level. The central banking authority also gave some cautious commentary about the outlook for rate cuts this year and indicated that it was waiting to see the impacts of new economic policies before making any moves. Investors then got another bearish development late in the week's trading when the Trump administration announced that it would be rolling out new tariffs on China, Mexico, and Canada. Nvidia continues to have a strong lead in the GPU market, but it looks like the stock could continue to be volatile in the near term. The company is scheduled to release its fourth-quarter results on Feb. 26, and the report is poised to be an important performance catalyst for the AI leader's valuation and the stock market at large.

Is Nvidia a 'buy' after crashing 15pc? Here's what top fundies say

Gift 5 articles to anyone you choose each month when you subscribe. The sudden emergence of DeepSeek, a low-cost Chinese artificial intelligence disruptor, onto the world stage this week has sent shockwaves though the fast-growing AI investment landscape, triggering a trillion-dollar sell-off in former sector darling Nvidia in the process. Despite the huge market reaction, however, Australia's top fund managers remain divided on whether the advent of DeepSeek's latest open-source platform - named R1 - will prove a turning point in the global race to develop AI, or simply a buying opportunity given the oversized market reaction.

ANALYSIS: Deepseek's AI Innovations Should Help Nvidia, Not Hurt It - Advanced Micro Devices (NASDAQ:AMD), ARM Holdings (NASDAQ:ARM)

Experts say Deepseek's AI costs are much higher than $5.6 million, contrary to mainstream news coverage. The U.S. markets have been in a frenzy over the past few days thanks to a new AI model from Chinese company Deepseek. The market reaction has been challenging for chipmakers and semiconductors companies like Nvidia Corp NVDA , Advanced Micro Devices Inc AMD, Arm Holdings ARM, and others. Nvidia experienced a historic drop in its stock price, plummeting nearly 17% and erasing over $589 billion in market capitalization -- the largest single-day market cap loss for any company in U.S. history. Broadcom also saw a significant decline, with shares falling approximately 17%, while AMD's stock price dropped by 4.89%. ARM faced a decline of about 8% on Monday, contributing to a broader selloff across the semiconductor industry. Despite the buzz around DeepSeek's latest model, R1, the news is largely positive for chipmakers like Nvidia. The market sell-off appears unwarranted and presents a potential long-term buying opportunity for investors. Deepseek is a secretive AI company based in China, backed by a parent quant fund called High-Flyer. The company's whole thesis is to build Artificial General Intelligence (AGI) and open-source it for general use. While they've been building models and AI technology for a few years, they only recently captured the interest of the American press. The company made headlines for a few reasons: 1) the press misreported that Deepseek trained a reasoning AI model for roughly $5.6 million, 2) investors felt like the fact that Deepseek was able to build a competitive AI model for so cheap implied that the demand for semiconductor chips used for AI, like the ones Nvidia sells, would be lower in the long run. In fact, most of the news from Deepseek shows that semiconductors and chips will only get more valuable over time. Chinese companies are already having difficulty keeping up with chip demand after US sanctions prevented advanced chips for AI from being sold to China. Deepseek founder Liang Wenfeng said that the biggest limitation for his company is the availability of high-end AI chips. "Money has never been the problem for us; bans on shipments of advanced chips are the problem," he said, according to ChinaTalk. Also Read: DeepSeek Selloff Is A Correction, Not Start Of 'Sustained Bear Market': Goldman Sachs AI chips were traditionally used to train large language models and to give them knowledge of all the info on the Internet. But that was a while ago. Today, AI companies mainly use chips for inference -- the computing required to generate answers or outputs for users in real-time. For instance, when you use tools like ChatGPT or Claude, the responses you receive are powered by inference compute. If the answers are slow, it's often because the system is handling a high volume of requests, and there's limited compute available for your specific query. Even if the demand for chips for training models goes away, the more AI use there is, the more demand there will be for inference compute. And while most of the media says that Deepseek was able to build a competitive AI model for only $5.5 million, that appears to be incorrect based on expert opinions and Deepseek itself, according to Ray Wang, a Washington-based Analyst specializing in U.S.-China economic and technology Competition. "I think DeepSeek is actually quite explicit when it comes to the cost of training their model, as laid out in their Technical Paper of V3 and R1. The claim of 5.6 million for DeepSeek for their model is wrong as it was written like this in their technician paper," Wang told Benzinga. The deeply technical paper explained that Deepseek's costs for training their model took only 2.788 million GPU hours. At $2 per GPU Hour for Nvidia's H800 chip (widely used for AI training), the cost is around $5.6 million. It doesn't account for various associated costs -- from R&D and talent to long-term operational costs, failed experiments, and general infrastructure costs like electricity. This is all to say that the fear that Deepseek's innovations will crush the demand for chips in the upcoming AI revolution is vastly overstated. Deepseek proves you can get much more juice out of high-end AI chips than previously thought, making them more efficient and valuable. If anything, the demand for AI chips from companies like Nvidia, Broadcom, and ARM are only going to increase as AI companies figure out new and innovative uses for them. Read Next: Dan Ives Says Chinese Startup DeepSeek's $6 Million AI Development Assertion Is 'Likely A Fictional Story' Image created using artificial intelligence via Midjourney. AMDAdvanced Micro Devices Inc$116.862.36%Overview Rating:Speculative37.5%Technicals Analysis660100Financials Analysis200100WatchlistOverviewARMARM Holdings PLC$146.04-2.29%AVGOBroadcom Inc$204.22-1.51%NVDANVIDIA Corp$121.00-6.19%Market News and Data brought to you by Benzinga APIs

Not just DeepSeek: Here's why Nvidia stock hasn't recovered

The stock market is unpredictable. Sometimes, bad news boosts a stock, while good earnings send it tumbling. That's just how the market works. There is a strong demand online for Nvidia's new RTX 50 series graphics cards, but that doesn't necessarily translate to big sales. That's because Nvidia cannot keep store shelves stocked. Many online retailers sold out of their supply within minutes. Scalpers are now selling Nvidia's graphic cards for a premium on the aftermarkets. Some retailers are informing customers to expect months of delays and backorders of the RTX 5090 and 5080. While the demand is there, it's clear that's not the sole reason why Nvidia's RTX 50 series is impossible to find in stores. Many retailers received fairly low stock quantities, as Nvidia reportedly experienced manufacturing issues. Overall, these issues may not be a reason for a stock to fall. But they do point to why Nvidia couldn't depend on the RTX 50 series release to help too much in its recovery. U.S.-based AI companies like OpenAI and Nvidia are still reeling from the China-based startup's release of the DeepSeek-R1 AI model. DeepSeek reportedly created an AI model that's at least on par with OpenAI's latest model. In addition, they say they did it with fewer resources in processing power and funding. It reportedly cost DeepSeek less than $6 million to create a model that OpenAI spent hundreds of millions on. Few companies have benefitted from the AI boom in the U.S. than Nvidia, which supplies U.S. tech companies with processing power to build their AI models. Although DeepSeek has done its damage, the looming threat is far from over. DeepSeek has released additional AI models for AI-generated images and is developing even more advanced models. In addition, other China-based companies, such as Alibaba, have announced their own advanced AI models that are supposedly even more powerful than those already available. DeepSeek wasn't the only thing that hit Nvidia this week. In a speech earlier this week, President Donald Trump announced a plan intended to move computer chip manufacturing from Taiwan to the U.S. What's the plan? Tariffs. "In the very near future, we're going to be placing tariffs on foreign production of computer chips, semiconductors, and pharmaceuticals to return production of these essential goods to the United States," Trump said in a speech. "They left us and went to Taiwan," Trump said, referring to companies like Apple, Qualcomm, and Nvidia, which manufacture their chips in Taiwan. Trump said the tariff could be as high as 100 percent. Trump's proposed tariffs could cause the price of these products to skyrocket for U.S. customers. In turn, companies like Nvidia would likely sell fewer products or make a smaller profit to compensate for the increased cost passed on to consumers.

DeepSeek's AI Model Sparks National Security Concerns and Market Turmoil | Investing.com UK

The artificial intelligence (AI) revolution is moving at lightning speed, and one of the biggest stories from last week underscores just how critical the technology has become -- not just for Silicon Valley, but for America's national security and global competitiveness. Enter DeepSeek, a Chinese AI startup that's sent shockwaves through the market with the release of a new, highly cost-efficient AI model. While DeepSeek may not yet be a household name, its impact has been swift. NVIDIA Corporation (NASDAQ:NVDA) -- the dominant player in AI chip design and, as of this morning, the world's third-largest company by market cap -- saw its stock price tumble after DeepSeek's latest model demonstrated a level of efficiency that many on Wall Street fear could challenge America's AI supremacy. To understand why DeepSeek is making headlines, let's look at NVIDIA's market swings. Last Monday, the tech giant lost an astonishing $590 billion in market value. Tuesday saw a rebound of $260 billion, only to drop again by $130 billion on Wednesday. The company plunged 15.8% for the week, its worst weekly showing since September 2022. Why the volatility? DeepSeek's AI model, built at a fraction of the cost of leading U.S. models, signals the potential for a new price war in AI. Unlike OpenAI's ChatGPT and Meta's Llama models -- trained on expensive high-end semiconductors -- DeepSeek has developed an alternative that is allegedly 45 times more efficient than its competitors. Its final training run cost only $5.6 million, compared to the vastly higher sums required for U.S.-made models. For many investors, this raises big questions: Will AI's profit margins shrink as efficiency increases? Are NVIDIA's high-priced AI chips at risk of being undercut? Most importantly, what are the implications for aerospace and defense, where AI is becoming an essential tool in modern warfare and national security? DeepSeek's breakthrough isn't just a financial story -- it's a national security issue. President Donald Trump wasted no time responding, saying DeepSeek should be a "wake-up call" for Silicon Valley. Supporting AI development, including the data centers that power it, is no longer just about business -- it's a matter of strategic importance. That may be partly why, in his second week back in office, Trump announced the launch of Stargate, a $500 billion joint AI venture led by SoftBank (TYO:9984) and OpenAI. Backed by Oracle (NYSE:ORCL) and MGX, Stargate intends to invest $100 billion immediately into AI infrastructure in the U.S. The goal? To cement America's leadership in AI and keep its edge in technological warfare and cybersecurity. But, as some analysts and investors are pointing out, if the Chinese can match American AI's performance at a fraction of the cost, is $500 billion too high? In any case, the Stargate development should catch the attention of investors looking at aerospace and defense. AI-driven military applications, from autonomous drones to advanced cyber defense, are not just science fiction anymore. They're already reshaping global conflict. The ability to train AI models more efficiently could shift the balance of power in how wars are fought, how intelligence is gathered and how cybersecurity threats are handled. Meanwhile, American tech giants are doubling down on AI investments. Mark Zuckerberg posted on Facebook (NASDAQ:META) that 2025 will be a "defining year for AI," with Meta planning to invest $60-$65 billion in AI infrastructure alone. The company expects to double its GPU (graphics processing unit) capacity to 1.3 million chips by the end of next year, significantly ramp up AI hiring and bring 1 gigawatt (GW) of computing power online. The AI boom is already creating massive economic ripples. According to Sensor Tower, revenues for AI chatbot and AI art generators have skyrocketed from $30 million in 2022 -- the year ChatGPT was launched -- to nearly $1.3 billion in 2024, representing an incredible 4,100% increase. Sensor Tower reports that the U.S. leads the world in AI monetization, accounting for 45% of global revenue, while China lags at just 2%. While DeepSeek has proven technically impressive, it's also raised serious red flags. For one, Microsoft and OpenAI are investigating whether DeepSeek acquired data from ChatGPT in an unauthorized manner. And two, cyber intelligence firm KELA has already exposed major security vulnerabilities in DeepSeek's R1 model, showing that it can be easily manipulated to generate malicious content, including ransomware instructions, fake news fabrication and even details on explosives and toxins. For this reason, U.S. military service members have been warned not to use DeepSeek AI tools due to potential security risks. Despite legitimate concerns, I agree with UBS that DeepSeek's emergence does not derail the overall AI growth story. As its editorial team notes, AI is not a zero-sum game. A more cost-efficient model could actually accelerate adoption across industries, further fueling productivity gains and market expansion. For investors, this means keeping an eye on how AI is reshaping aerospace and defense. The biggest beneficiaries may not be the AI application companies themselves, but rather the firms building the infrastructure: semiconductor manufacturers, data centers, cloud computing providers, cybersecurity firms and defense contractors integrating AI into next-generation applications. With the U.S. making AI a national priority, we're seeing an unprecedented wave of investment into the sector. Whether it's OpenAI's partnership with Stargate, Meta's multi-billion-dollar AI expansion or defense firms using AI for military innovation, the message is clear: AI isn't just the future of tech -- it's the future of national security. *** Holdings may change daily. Holdings are reported as of the most recent quarter-end. The following securities mentioned in the article were held by one or more accounts managed by U.S. Global Investors as of (12/31/2024): NVIDIA Corp (NASDAQ:NVDA), Microsoft Corp (NASDAQ:MSFT).

Nvidia's $600 Billion Stock Crash: AI Competition Sparks Market Turmoil

Nvidia's stock experienced a substantial 17% decrease that sent shares to close at $118.58 On Monday, Nvidia suffered the largest single-day market cap loss in U.S. history, shedding $600 billion in value as its stock plunged 17% to close at $118.58. The sharp decline was fueled by investor concerns over rising AI competition, particularly from China's DeepSeek, which has introduced a cost-effective alternative to Nvidia's high-end GPUs. The sell-off also triggered a broader market downturn, with the Nasdaq falling 3.1% and other AI-related tech stocks, including Broadcom and Oracle, experiencing significant losses. The creation of has created market uncertainties regarding future AI chip market trends. It operates as a Chinese AI research lab. DeepSeek released its open-source large language model through an implementation of the Nvidia H800 chips. The speed and cost-effectiveness of its development raised concerns that alternative AI models could reduce the reliance on Nvidia's high-end GPUs. has dominated the AI data center chip market for a long time, supplying industry giants such as Alphabet, Meta and Amazon. However, analysts at Cantor expressed confidence that AI advancements will ultimately drive more demand for computing power rather than reduce it. Despite this reassurance, Nvidia's dramatic stock gains in recent years have left investors wary of potential downturns. In 2023, the stock surged 239%, followed by a 171% rise in 2024. The sell-off also impacted other tech companies tied to AI and data centers.another major AI chip manufacturer saw its stock drop by 17% erasing $200 billion in market value. Companies like Dell, Hewlett Packard Enterprise and Super Micro Computer, which rely on Nvidia's GPUs, suffered losses of at least 5.8%. Oracle, a key player in AI infrastructure, fell 14%. exceeded previous record declines, including its own $279 billion drop in September and Meta's $232 billion loss in 2022. The decline even surpassed the market cap of major corporations like Coca-Cola and Chevron. CEO Jensen Huang's net worth also took a hit, dropping by $21 billion. DeepSeek's rising popularity was further highlighted as its AI app surpassed OpenAI's ChatGPT in Apple's U.S. App Store rankings. The rapid development of alternative AI models has sparked discussions about global AI competition and U.S. policies on technology exports. Market investors and industry leaders watch AI chip dominance closely because Nvidia stands as the third most valuable publicly traded company after Microsoft and Apple.

These 3 Stocks are at Most Risk From China's AI Innovation

Here are three stocks that will continue to suffer in this new DeepSeek era. January 27 stands as one of the most eye-opening days in recent Wall Street history. That's when the markets realized Western technology consumers had been lining up to download a low-cost yet advanced AI assistant app called DeepSeek-V3. See, DeepSeek isn't just another ChatGPT-like AI assistant -- it performs just as well as but the Chinese developers behind DeepSeek claim they spent just $5.6 million in semiconductor chips, about one-tenth of the astronomical development costs companies like OpenAI and Meta Platforms have spent on chips for their AI apps. As markets realized the same AI performance can be achieved with fewer, and slower, chips, the companies supplying the expensive chips, and the companies that have spent billions on AI already, took a beating. But that's just the beginning. Here are three other stocks that will struggle in this new DeepSeek era. See, DeepSeek engineers leveraged Nvidia's (NVDA) reduced-capacity H800 graphics processing units (GPUs) to train its AI model, which achieved more robust performance outputs with lower development costs. That's a departure from usual AI model construction, as many US companies used significantly more powerful - and way more expensive - Nvidia H100 GPUs to get, as DeepSeek claims, more or less the same performance results. On Wall Street, the market carnage rolled in fast and furious. On January 27, Nvidia shares plummeted 17%, while competitors like Broadcom (AVGO) fell 17.4% and Marvel Technology (MRVL) face-planted by 19.1%. Chip stocks and the companies using those chips for AI technology development rebounded modestly in the days following the DeepSeek news. By January 30, NVDA was only down 15% for the previous five days, while Broadcom (-10.25%) and Marvel (-12.50%) followed suit. Still, the damage hasn't been contained, at least while the notion of a cheaper and equally effective way of building AI models lingers. "DeepSeek AI's entry into the market offers a disruptive combination of high-level capabilities at a fraction of the cost of industry giants like OpenAI," said Mel Morris, CEO at Corpora.ai, a London-based research engine technology firm. "This affordability opens the door for smaller companies and startups to leverage advanced AI technology that was previously inaccessible. Additionally, the open-source model empowers developers to fine-tune and experiment with the system, fostering greater flexibility and innovation." Morris said that the emergence of DeepSeek AI could challenge the current competitive landscape and push major players like OpenAI to adapt quickly. "The idea that competition drives innovation is particularly relevant here, as DeepSeek's presence is likely to spur faster advancements in AI technology, leading to more efficient and accessible solutions to meet the growing demand," he notes. Even so, DeepSeek and similar companies in the AI development pipeline may not be the tech sector wrecking ball investors think. "Many people felt the rising tech giants' capital expenditures would likely lead to a bubble, but instead, DeepSeek's breakthrough will likely extend the rally for AI over time," said James Wo, founder and CEO of Digital Finance Group (DFG), a global blockchain and digital asset investment firm with more than $1 billion in assets under management. Wo says the DeepSeek long-term model sustainability is no guarantee as the company (and others like it) must also keep up with market shifts. "Relying on a single breakthrough of training efficiency without consistent innovation will cause it to plateau and lose its competitive edge over time," he noted. "Overall, DeepSeek's breakthrough may not completely replace high-performant AI systems entirely but rather coexist in a hybrid ecosystem where different tools are optimized for specific use cases." Three Stocks That May Have a Problem With the Ascent of AI It's early in the game, and pinpointing stocks that will suffer at the hands of the DeepSeek saga is a tall task, as the technology and financial facts linked to the story are still being sorted out. Based on the idea that DeepSeek represents a more efficient way of building AI models, however, the following stocks would be at risk. Nvidia. Perhaps the biggest DeepSeek-related concern is for manufacturing companies that depend heavily on high-end AI hardware sales. "Nvidia is the obvious choice here, but others, like AMD and certain semiconductor manufacturers, could also face headwinds if AI-reliant companies shift toward more cost-effective solutions," says Drew Cohen, marketing lead at the cryptocurrency company GME Ethereum Oracle. Technology billionaires took a big financial hit from the DeepSeek dip, with Oracle's Larry Ellison, who saw his net worth fall by $27.6 billion early last week. (Nvidia CEO Jensen Huang wasn't far behind, with his net worth down by $20.8 billion.) Oracle's stock value fell by $70 billion in the DeepSeek melee, although ORCL recouped half of those losses by the week's end. The longer-term problem is that Oracles has been investing heavily in data center development to match up with AI heavyweights like Amazon and Microsoft. A cheaper way to develop AI models threatens that model, mainly by curbing the need for pricey data center operations. Broadcom. Broadcom has emerged as a powerful force in the AI network technology realm. If DeepSeek's impact on AI development sticks, it will hurt chip companies developing AI semiconductors and crimp their share performance. This week, Morgan Stanley cut its target price on AVGO from $265 to $246, citing "deflationary" AI evolutionary innovations and reduced AI spending enthusiasm. The Takeaway on DeepSeek and Impacted AI and Chip Stocks Even if DeepSeek doesn't see widespread adoption by enterprises in the US, it represents a tipping point. "The technology industry is waking up to the fact they don't need to rely on the walled gardens and expensive fees of hyperscalers to access highly-advanced and innovative AI capabilities," said Marc Suidan, chief financial officer at Backblaze (BLZE), a data storage cloud company in San Mateo, Cal. Up until a few days ago, it was conventional wisdom for most that AI innovation required a massive amount of capital and infrastructure that only multi-trillion dollar tech giants could provide. But that was an illusion, Suidan said. "Using concepts and practices of the past that would eventually get chips to be way more productive, or disruptive innovation using open source solutions, DeepSeek mastered the second one, and proved that with limited resources, they can develop a powerful AI solution," he noted. What if you could pinpoint stocks with massive profit potential like Matador Resources, which soared 2,100% in just two years? Or Photronics, a semiconductor stock that doubled in under a year? That's the power of our new 'Benzinga Trade Alerts'. Photo Courtesy: Mamun_Sheikh On Shutterstock.com Market News and Data brought to you by Benzinga APIs

Amid Nvidia And Chinese AI Anxieties, Top Analyst Predicts Higher AI Infrastructure Demand Despite Market Jitters: 'The Market Is Overreacting To DeepSeek's Success' - Microsoft (NASDAQ:MSFT), Meta Platforms (NASDAQ:META)

Nvidia Corporation NVDA on Monday experienced significant investor anxiety following the emergence of DeepSeek, a Chinese AI firm. Despite the market's reaction, a top analyst suggests that the demand for AI infrastructure will continue to rise. What Happened: Deepwater Asset Management's managing partner, Gene Munster took to X, formerly Twitter, and said, "I believe the market is overreacting to DeepSeek's success." He suggested that DeepSeek's achievement likely reflects progress in chip architecture but noted its impact remains uncertain. "It's unclear if it's a 5% or 500% improvement," Munster said. Munster also pointed out an overlooked angle in the conversation: "What's being missed today is if there is a more efficient way to train models, it could increase the level of investment to build AI infrastructure given the prospects of reaching artificial general intelligence are more achievable." See Also: Jensen Huang's Biggest Fear Isn't AI Competition -- It's Pre-Show Butterflies: How Silicon Valley's Coolest Leaders Like Mark Zuckerberg And Elon Musk Are Gripped With Stage Fright The analyst said that the market will remain on edge until the earnings reports from major tech companies like Microsoft Corporation MSFT, Meta Platforms Inc. META, and Tesla Inc. TSLA. Nvidia's earnings are anticipated on Feb. 26, with a focus on model training costs. In a paper published last month, DeepSeek researchers revealed that training the DeepSeek-V3 model used Nvidia's H800 chips, with costs totaling under $6 million. Why It Matters: On Monday, Nvidia also acknowledged DeepSeek's model performance, underscoring the ongoing demand for its advanced chips. "DeepSeek's work illustrates how new models can be created using that technique, leveraging widely-available models and compute that is fully export control compliant," the company stated. DeepSeek's R1 model, described as a ChatGPT killer, has outperformed OpenAI with significantly lower costs. Nvidia's stock has sunk below its 200-day moving average for the first time in two years, marking a historic technical reset. The company lost about $600 billion in market capitalization, setting a record for the largest single-day loss in U.S. stock market history. Price Action: During the regular hours on Monday, Nvidia's shares plunged approximately 17% to $118.58. However, in the after-hours trading, the shares witnessed a 1.35% gain, according to data from Benzinga Pro. Image via Shutterstock Read Next: Apple's iPad Turns 15 Today: Here's A Throwback To When Steve Jobs Explained Called It The 'Third Category' After Phones And Notebooks Disclaimer: This content was partially produced with the help of Benzinga Neuro and was reviewed and published by Benzinga editors. METAMeta Platforms Inc$661.552.17%Overview Rating:Good62.5%Technicals Analysis1000100Financials Analysis400100WatchlistOverviewMSFTMicrosoft Corp$434.56-2.14%NVDANVIDIA Corp$120.18-15.7%TSLATesla Inc$396.41-2.50%Market News and Data brought to you by Benzinga APIs

Fundstrat's Tom Lee Sees Nvidia's 17% Plunge As An 'Opportunity,' Calls Nasdaq's Over 600 Points Plunge Drop A Market 'Overreaction' - Microsoft (NASDAQ:MSFT), Meta Platforms (NASDAQ:META)

Fundstrat Global Advisors' head of research Tom Lee believes Monday's massive tech sector sell-off, which saw Nvidia Corp. NVDA shares plunge 17%, represents a buying opportunity rather than a fundamental shift in the artificial intelligence landscape. What Happened: "To me, it's an overreaction," Lee told CNBC's "Closing Bell," comparing the drop to Nvidia's March 2020 decline that proved to be a significant entry point for investors. "I'd be looking at this as an opportunity," Lee said. Lee dismissed concerns that Nvidia could become "Betamax" - referencing the obsolete video format that lost to VHS - noting that such a scenario would be the only justification for Monday's severe selling pressure. The sell-off was triggered by Chinese AI startup DeepSeek's announcement of a free, open-source large language model developed for under $6 million using Nvidia's H800 chips. See Also: Bitcoin, Ethereum, Dogecoin Recover As DeepSeek Troubles Mount For US Tech Stocks: Analyst Suggests BTC Could Hit Fresh Highs Over Upcoming Two Weeks Why It Matters: The cost-efficient breakthrough sparked fears about the sustainability of massive AI infrastructure investments, leading to Nvidia's largest single-day market value loss of approximately $600 billion. The market reaction came despite Nvidia's statement that DeepSeek's development used export-control-compliant technology. "DeepSeek's inference requires significant numbers of Nvidia GPUs and high-performance networking," the company said. Major tech companies continue to demonstrate confidence in AI investments, with Microsoft Corp. MSFT planning $80 billion in AI infrastructure spending for 2025 and Meta Platforms Inc. META projecting $60-65 billion. Price Action: Nvidia's stock closed at $118.58 on Monday, down 16.86% for the day. In after-hours trading, the stock edged up 1.35%. Over the past year, Nvidia's stock surged 89.81%, according to data from Benzinga Pro. Read Next: Jensen Huang Says 'Everything That Moves Will Be Robotic Soon' As Nvidia CEO Envisions Star Wars-Inspired R2-D2 Personal Assistants And Humanoid Robots Image Via Shutterstock Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. METAMeta Platforms Inc$662.430.39%Overview Rating:Good62.5%Technicals Analysis1000100Financials Analysis400100WatchlistOverviewMSFTMicrosoft Corp$436.470.44%NVDANVIDIA Corp$123.854.59%Market News and Data brought to you by Benzinga APIs

Here Are the Stock Market Winners and Losers from the DeepSeek AI Upheaval

Software stocks advanced on expectations that their margins and demand for their AI products will improve as AI becomes less expensive to run. AI stocks were this past week when Wall Street took notice of a high-performance, shockingly efficient open-source AI model from Chinese start-up DeepSeek. The high-performance model, which DeepSeek said was trained in a matter of months for about $6 million, sparked concern that useful AI may not require the most powerful and most expensive hardware. It also threatened to undercut the investment thesis that has so far prevailed among U.S. tech companies: spend aggressively to build computing capacity and develop the most powerful models. A sell-off of semiconductor and computer networking stocks on Monday was followed by a modest rebound, but DeepSeek's damage was still evident when markets closed Friday. Below, we look at some of the winners and losers of the reckoning of the past week. Shares tumbled 17% on Monday, their biggest one-day drop since March 2020 when it became evident Covid-19 would upend daily life around the world. The chip giant's market cap, which stood at $3.6 trillion before last week, shrank by nearly $590 billion, the largest loss of market value for a single company on record. DeepSeek, some investors thought, could force U.S. tech giants to refocus their efforts on making more nimble, efficient AI models, and subsequently reduce their spending on Nvidia's most sophisticated chips. Analysts were generally skeptical of that narrative. Bank of America analysts argued DeepSeek could be "AI's Sputnik moment" that fuels even more AI investment beneficial to Nvidia. But some saw reason to be wary. Morgan Stanley analysts wrote that "the stock market reaction is probably more important than the cause," and warned DeepSeek's success could temper AI spending enthusiasm and compel the Trump administration to ratchet up semiconductor export controls. Nvidia stock, despite recovering some of Monday's losses, finished the week 16% lower. The stock was bolstered by DeepSeek on Monday when it dodged the AI sell-off and rose about 2%. Investors felt vindicated by the success of DeepSeek's model, which -- like Meta's large language model, Llama -- is open-source. CEO Mark Zuckerberg, speaking during the company's earnings call on Wednesday, said DeepSeek had "only strengthened our conviction this is the right thing for us to be focused on," referring to open-source AI, as opposed to proprietary models. Meta's stock also got a boost from a strong quarterly earnings report. Meta easily surpassed Wall Street's expectations on both the top and bottom lines, and executives in their comments to analysts possibly allayed some jitters about the DeepSeek threat. ServiceNow Shares of enterprise software company ServiceNow (NOW) finished their rollercoaster ride of a week about 1% lower. The stock climbed 4% in the first two sessions of the week, boosted by optimism that DeepSeek's cost-efficient model could hasten the development of more affordable AI models. Analysts and investors were quick to note software companies would immediately benefit from lower computing costs. More efficient AI could not only widen their margins, it could also enable them to develop and run more models for a wider variety of uses, driving greater consumer and commercial demand. ServiceNow shares were trading near a record high when the company on Wednesday reported disappointing quarterly results, leading its stock to plummet 11%. CEO Bill McDermott's optimism about the company's AI prospects couldn't counter Wall Street's disappointment that subscription revenue grew slower than expected and was forecast to grow even slower in the current quarter.

Tom Lee says this is the worst market overreaction since 2020 pandemic outbreak

Fears around the future of the artificial intelligence trade pushed Nvidia shares down by nearly 17% on Monday and weighed on the stock market - but investors seem to be overreacting, according to Tom Lee, head of research at Fundstrat Global Advisors. Chinese AI startup DeepSeek spurred a sell-off on Monday. The company last month debuted a free, open-source large language model that it claims took less than $6 million to build. The development ignited fears that competitive AI models could be built on the cheap and with less-powerful chips . The tech sector sold off in earnest, sliding more than 5% on Monday as shares of Nvidia and Broadcom suffered. "To me, it's an overreaction," Lee told CNBC's "Closing Bell'" on Monday. "Nvidia's decline is the worst since March 2020, and we know that ended up being a huge opportunity for investors. It's not a fun day, but I'd be looking at this as an opportunity." NVDA 1D mountain Nvidia stock. Monday's market moves also reflected a broader sense of worry that the AI race between China and the U.S. is entering a new phase with Beijing possibly pulling ahead. Lee said he would be "personally surprised if Nvidia became Betamax in the past week," which he noted would be the only situation that would justify selling the chip giant's shares to the degree seen on Monday. To be sure, Lee also said time will tell if the sell-off will bear fruit and turn out to be a a longer-term trend for the chipmaker. For now, he stands by his view that Nvidia's slide is a buying opportunity. "We don't know if its overblown," he cautioned. Outside of tech, Lee said he likes financials moving forward, adding that the sector is his No.1 S & P 500 sector idea. "I think financials to me represent a pretty good fundamental case of change this year because we have a new administration, a Fed that is dovish, yields that aren't painful for banks - and a time when it could lead to upside for capital markets activity, and multiples are low," Lee said.

Chamath Palihapitiya Warns Of AI Shift: 'The Battle Is Now More About AI Inference Vs Training' As DeepSeek Sparks Nvidia Selloff - Microsoft (NASDAQ:MSFT), Meta Platforms (NASDAQ:META)

Billionaire investor Chamath Palihapitiya has issued a stark warning about the shifting AI landscape, following Chinese startup DeepSeek's demonstration of a cost-efficient AI model that triggered a $600 billion selloff in Nvidia Corp. NVDA shares. What Happened: In a detailed analysis shared on X, the former Facebook executive emphasized that the AI industry's focus is pivoting from training to inference capabilities. "The battle of usage is now more about AI inference vs Training," Palihapitiya noted, suggesting that while the U.S. should maintain export controls on AI training chips, inference chips should be treated differently. AI training is the process of teaching an AI model to recognize patterns in data, while AI inference is the process of using that trained model to make predictions. Drawing a parallel to nuclear technology, Palihapitiya argued that while the U.S. shouldn't export advanced AI training capabilities, it should promote its inference solutions globally. "We should never export our knowledge of enriching uranium... but we should export our ability to build nuclear energy if it can help advance American priorities," he explained. The venture capitalist, who disclosed his stake in AI chip company Groq, called for urgent collaboration with Middle Eastern allies to establish global inference infrastructure. He warned of potential market volatility affecting major tech stocks, particularly noting that Nvidia faces the highest risk while Tesla Inc. TSLA remains least exposed. See Also: Nvidia Says DeepSeek An 'Illustration' Of How New AI Models Can Be Created While Being Export-Control Compliant Amid $600 Billion Market Value Plunge Why It Matters: DeepSeek's achievement - developing a competitive AI model for just $5.57 million compared to traditional costs in the hundreds of millions - prompted Palihapitiya to criticize U.S. innovation strategy. "We've been running towards the big money/shiny object spending programs... vs thinking through the problem more cleverly," he stated. The commentary comes as Nvidia acknowledged DeepSeek's compliance with export controls, while major tech companies like Microsoft Corp. MSFT and Meta Platforms Inc. META maintain substantial AI infrastructure spending plans exceeding $60 billion each for 2025. Read Next: Cathie Wood Swoops In To Buy AMD Shares Amid DeepSeek Tech Upheaval, Dumps Tesla Stock Worth $8.1 Million Image Via Shutterstock Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. METAMeta Platforms Inc$661.552.17%Overview Rating:Good62.5%Technicals Analysis1000100Financials Analysis400100WatchlistOverviewMSFTMicrosoft Corp$434.56-2.14%NVDANVIDIA Corp$120.18-15.7%TSLATesla Inc$396.41-2.50%Market News and Data brought to you by Benzinga APIs