Amazon Challenges Nvidia's AI Chip Dominance with Trainium and Project Rainier

Amazon Halts Inferentia AI Chip Development To Take On Nvidia: How Trainium Is Shaping Up To Be The New Weapon In AI Chip Wars - Apple (NASDAQ:AAPL), Amazon.com (NASDAQ:AMZN)

Amazon.com Inc. AMZN has decided to halt the development of its Inferentia AI chip, shifting its focus to the Trainium chip. What Happened: This decision is part of Amazon's broader strategy to enhance cost performance in AI model training, reported Nikkei on Thursday. Since it entered the AI chip market in 2018, Amazon Web Services has been offering both Inferentia and Trainium chips to AI companies. See Also: Trump's AI Czar Plans, Alibaba's New Model, Cathie Wood On Tesla AI, And Musk's Combat Transformation: This Week In Artificial Intelligence However, Rahul Kulkarni, AWS's director of compute, announced that the product lines will merge, with a focus on Trainium for both inference and training tasks. Trainium is designed with a larger memory capacity and supports diverse data formats, enabling rapid computations across multiple servers. "We can get to the same level of optimization and cost performance benefits by doubling down on Trainium as a single, unified product," Kulkarni stated. Subscribe to the Benzinga Tech Trends newsletter to get all the latest tech developments delivered to your inbox. Why It Matters: During a tech event in Las Vegas, Amazon unveiled the Trainium2 chip and announced plans for the Trainium3 chip, expected in 2025. The Trainium3 will use a 3-nanometer chipmaking process, doubling Trainium2's computing performance. With this, Amazon aims to challenge Nvidia Corporation NVDA, which holds a 90% share in the AI chip market. Apple Inc. AAPL and AI startup Anthropic are among those adopting Trainium2 for AI development. In October, Amazon reported third-quarter net sales of $158.9 billion, marking an 11% increase compared to the previous year. This performance surpassed the Street's consensus forecast of $157.2 billion, as per data from Benzinga Pro. Price Action: Amazon's stock rose by 1.1% on Thursday, finishing at $220.55. In the after-hours session, it saw a dip of 0.1%, reaching $220.32. So far this year, Amazon shares have surged by 47.1%, significantly outperforming the Nasdaq 100 index, which gained 29.5% over the same period. Amazon has a consensus price target of $238.16 from 38 analysts, with JMP Securities setting the highest target at $285 on Nov. 1. Latest ratings from Needham, BMO Capital, and MoffettNathanson indicate an average target of $244.67, implying an upside potential of 11.05%. Image via Shutterstock Check out more of Benzinga's Consumer Tech coverage by following this link. Read Next: Apple's Foldable iPhone Could Spark Smartphone Market Revival In 2026, Says Expert Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs

Amazon Takes On Nvidia With Cheaper AI Supercomputers, Servers - Amazon.com (NASDAQ:AMZN)

Amazon is building AI supercomputers in collaboration with OpenAI rival Anthropic. On Tuesday, Amazon.com Inc's AMZN cloud unit showcased fresh data center servers embedded with its artificial intelligence (AI) chips at the company's Re:Invent event. The new servers, dubbed Trn2 UltraServers, will target Nvidia Corp's NVDA flagship server, packed with 72 of its latest Blackwell chips, Reuters reports. Nvidia commands the AI chips market with over 70% market share. Also Read: Marvell Unveils New Platform, Targets Growing AI Bandwidth Demands Amazon Web Services disclosed Apple Inc AAPL as a customer for the AI chips during the event. Amazon is building artificial intelligence supercomputers in collaboration with OpenAI rival Anthropic, which will feature hundreds of thousands of Amazon's latest AI training chip, Trainium 2. Apple executive Benoit Dupin told Reuters that Apple is already using Trainium2 chips, and AWS chief Matt Garman told Reuters that Trainium3 will debut in 2025. Gadi Hut, the business development lead for AI chips at AWS, said that AWS can connect more chips than Nvidia and that some AI models can be trained at a 40% lower cost than Nvidia chips. Amazon also announced expanded collaboration with Marvell Technology, Inc MRVL on AI and data connectivity products, which Bank Of America Securities analyst Justin Post deems mutually beneficial for the companies and will help alleviate some AWS dependence on supply-constrained Nvidia chips. Prior reports indicated Blackwell chips' production challenges at Nvidia impacted AWS' data center plans. Amazon also announced an expanded partnership with Oracle Database, Orbital Materials, and AWS' overhaul of the cloud contact center solution with new Generative AI solutions. Price Action: AMZN stock is up 1.9% at $217.60 at last check Wednesday. Also Read: Intel's New CEO Change Unlikely To Help Gain Traction Versus Taiwan Semi And Nvidia: Analysts Photo: Shutterstock AMZNAmazon.com Inc$217.001.67%Overview Rating:Good62.5%Technicals Analysis1000100Financials Analysis400100WatchlistOverviewAAPLApple Inc$242.820.07%MRVLMarvell Technology Inc$114.0018.9%NVDANVIDIA Corp$141.630.98%Market News and Data brought to you by Benzinga APIs

Jeff Bezos' Amazon Unveils Powerful AI Chip Clusters To Supercharge Anthropic's Models, Challenging Nvidia And OpenAI's Dominance - NVIDIA (NASDAQ:NVDA), Amazon.com (NASDAQ:AMZN)

On Tuesday, Jeff Bezos' Amazon.com, Inc. AMZN unveiled advanced AI chip clusters designed to enhance the performance of its partner, Anthropic. This development aims to challenge the current market leaders, Nvidia Corporation NVDA and ChatGPT-maker OpenAI. What Happened: During Amazon's biggest re:Invent conference of the year, the tech giant deployed hundreds of thousands of its Trainium2 semiconductors into clusters, significantly boosting Anthropic's processing power. The new chip cluster, named Project Rainier, is expected to be the world's largest dedicated AI hardware set, containing over 100,000 chips. Amazon intends to provide an alternative to Nvidia's GPUs, which are often expensive and scarce. The company said it will provide customers with computing power supported by Nvidia's new Blackwell chip beginning early next year, reported Bloomberg. See Also: Apple's Foldable iPhone Could Spark Smartphone Market Revival In 2026, Says Expert Amazon Web Services announced that it began providing customers with its latest chips starting Tuesday. Amazon's CEO, Andy Jassy, introduced the Nova models, which can generate text, images, and video. These models are Amazon's latest attempt to rival OpenAI's advanced GPT models. Why It Matters: This latest development in AI chip clusters is part of Amazon's ongoing partnership with Anthropic. The e-commerce giant has boosted this collaboration with a $4 billion investment in the AI startup, bringing the total to $8 billion. This partnership also positions AWS as Anthropic's primary cloud provider and training partner, leveraging AWS Trainium and Inferentia chips for future models. Earlier in September, Amazon also received some positive news when the U.K.'s Competition and Markets Authority approved this partnership, allowing Amazon to proceed without regulatory hurdles. Subscribe to the Benzinga Tech Trends newsletter to get all the latest tech developments delivered to your inbox. Last month, Amazon reported third-quarter sales of $158.9 billion, reflecting an 11% increase compared to the last year. This figure surpassed the Wall Street consensus estimate of $157.2 billion, according to data from Benzinga Pro. Price Action: Amazon's stock rose by 1.30% on Tuesday, finishing at $213.44. In pre-market trading, it saw a further increase of 0.35%, reaching $214.18. So far this year, Amazon shares have surged by 43.76%, significantly outperforming the Nasdaq 100 index, which gained 28.32% over the same period. Amazon holds a consensus price target of $238.16 from 38 analysts, with the highest target of $285 set by JMP Securities on Nov. 1. The latest ratings from BMO Capital, MoffettNathanson, and Redburn Atlantic point to an average target of $239.67, suggesting an 11.92% upside. Check out more of Benzinga's Consumer Tech coverage by following this link. Read Next: Benzinga Bulls And Bears: Amazon, Tesla, Rivian, Palantir And How Dogecoin Helped Low-Income Families Achieve Homeownership Image via Shutterstock Market News and Data brought to you by Benzinga APIs

AWS takes on Nvidia and Amazon shares are loving it

Amazon Web Services (AWS) announced the launch of a new AI supercomputer, Project Rainier, constructed from its proprietary Trainium chips, aiming to rival Nvidia's dominance in the AI chip market. This supercomputer, which will be finalized by 2025, is poised to be one of the largest ever used for training AI models. Following this revelation, Amazon's stock price increased by over 1%, reaching nearly $213. AWS's Project Rainier will feature an "Ultracluster" built from the company's Trainium chips, which are tailored for AI applications. The collaboration with AI startup Anthropic, valued at approximately $18 billion, includes their commitment to utilize this supercomputer for AI training. This partnership has seen AWS invest a cumulative $8 billion into Anthropic as they work together to enhance the performance of Trainium chip technology. In addition to Project Rainier, AWS is also developing Project Ceiba, a partnership with Nvidia that will utilize more than 20,000 Nvidia Blackwell GPUs for AI applications. The announcement of these projects coincides with the impending release of AWS's Ultraserver, designed to leverage its advanced Trainium chips. AWS's ongoing investment in AI infrastructure is underscored by its commitment to allocate over $100 billion over the next decade to AI capabilities. This investment comes as demand for AI technologies surges, with AWS positioning itself as a strong competitor against market giants such as OpenAI. Recently, Apple has also indicated plans to implement Trainium chips for its own AI initiatives. Matt Garman, CEO of AWS, stated, "Today, there's really only one choice on the GPU side, and it's just Nvidia. We think that customers would appreciate having multiple choices." This assertion reflects AWS's ambitions to provide alternatives within the AI chip market, seeking to capitalize on the demand for more efficient and cost-effective processing solutions. Forecasts suggest that Trainium chips could deliver between 30% and 40% better price performance compared to current GPU-powered instances, further enticing companies to explore AWS's offerings for their AI needs. Key clients already employing Trainium technology include Apple, Adobe, and Databricks, indicating strong industry interest. Amazon's stock rose over 1% after unveiling updates at its re:Invent conference, highlighting Trainium2 AI chips, a custom "Ultraserver," and plans for an AI supercomputer featuring Anthropic as its first customer. AWS CEO Matt Garman emphasized Trainium2's 30-40% cost advantage over GPUs like Nvidia's, positioning Amazon as a competitor in the AI chip market while maintaining its reliance on Nvidia hardware. The company also announced a Trainium3 chip for 2025 and plans to invest $100 billion in AI data centers. Amazon's stock, up 40% year-to-date, reflects optimism around its expanding AI capabilities and competitive edge in cloud computing. As these developments unfold, Amazon's proactive strategy is designed to bolster its market position within the AI sphere, challenging Nvidia's current supremacy. The latest advancements reported at the ongoing AWS re:Invent conference, coupled with Amazon's substantial investment plans and strategic partnerships, reveal an aggressive push into AI infrastructure to meet growing corporate demands.

Amazon Announces Supercomputer, New Server in Push To Take on Nvidia

The "Ultracluster" announced by the tech giant's Amazon Web Services (AWS) cloud computing arm was designed by Amazon's chip lab in Austin, Texas, The Wall Street Journal reported. Amazon last month invested an additional $4 billion in Anthropic, whose Claude chatbot is a rival to OpenAI's ChatGPT. "Together with Anthropic, AWS is building an EC2 UltraCluster of Trn2 UltraServers -- named Project Rainier -- containing hundreds of thousands of Trainium2 chips and more than 5x the number of exaflops used to train their current generation of leading AI models," Amazon said. An exaflop is a measure of a supercomputer's performance. According to the Journal, the new chips and servers highlight AWS's commitment to the homegrown Trainium it is positioning as a "viable alternative" to the graphics processing units (GPUs) sold by Magnificent Seven rival Nvidia (NVDA). Amazon shares, which are 0.7% higher in premarket trading, have gained 40% year-to-date through Tuesday.

Amazon ramps up AI offerings with powerful chip arrays, large language model

Amazon.com is ramping up its artificial intelligence offerings, rolling out powerful new chip arrays and a large language model it says can compete with leading rivals. The Seattle-based company is stringing together hundreds of thousands of its Trainium2 semiconductors into clusters that will make it easier for partner Anthropic to train the large language models required for generative AI and other machine learning tasks. The new arrays will quintuple the startup's current processing power, Amazon said. Amazon Web Services, the cloud services division, began offering its latest chips to customers on Tuesday, the company said at its annual re:Invent conference. Andy Jassy, marking his first appearance at the trade show since becoming Amazon's chief executive officer in 2021, introduced the new models -- called Nova. Capable of generating text, images and video, they represent Amazon's latest effort to compete with OpenAI and other builders of the large language models that power chatbots and other generative AI tools. AWS, the largest seller of rented computing power, runs many of the servers that other companies rent to train artificial intelligence applications. AWS also makes models built by other companies, including Anthropic's Claude and Meta Platforms's Llama, available to AWS customers. But the company has yet to produce a large language model widely seen as competitive with OpenAI's most advanced GPT models. Prior Amazon-built models released in the last two years, called Titan, were generally smaller in scope. The Nova models, some available now and others next year, include a "multimodal to multimodal" version that can take text, speech, images and video as inputs and generate responses in each mode. Amazon, Jassy said, would continue to both develop its own models and offer those built by others. "We are going to give you the broadest and best functionality you can find anywhere," he said. Amazon last month said it was investing an additional $4 billion in Anthropic. As part of the deal, Anthropic said it would use Amazon's cloud and its chips to develop its most advanced models. The new chip cluster, called Project Rainier, will contain "significantly more" than 100,000 chips, Gadi Hutt, who works with customers at Amazon's Annapurna Labs chipmaking unit, said in an interview. Amazon says it expects the cluster to be the world's largest set of dedicated AI hardware. Amazon hopes the chips, the company's third generation of AI semiconductors, will prove competitive with Nvidia Corp.'s products, offering AWS customers an alternative when developing generative AI products. For most companies, Nvidia's graphics processing units, which are costly and often in short supply, are the default hardware for such tasks today. Amazon says it will offer customers computing power backed by Nvidia's new Blackwell chip starting early next year.

Amazon Is Building a Mega AI Supercomputer With Anthropic

At its Re:Invent conference, Amazon also announced new tools to help customers build generative AI programs, including one that checks whether a chatbot's outputs are accurate or not. Amazon is building one of the world's most powerful artificial intelligence supercomputers in collaboration with Anthropic, an OpenAI rival that is working to push the frontier of what is possible with artificial intelligence. When completed, it will be five times larger than the cluster used to build Anthropic's current most powerful model. Amazon says it expects the supercomputer, which will feature hundreds of thousands of Amazon's latest AI training chip, Trainium 2, to be the largest reported AI machine in the world when finished. Matt Garman, the CEO of Amazon Web Services, revealed the supercomputer plans, dubbed project Rainer, at the company's Re:Invent conference in Las Vegas today, along with a host of other announcements cementing Amazon's rising dark-horse status in the world of generative AI. Garman also announced that Tranium 2 will be made generally available in so-called Trn2 UltraServer clusters specialized for training frontier AI. Many companies already use Amazon's cloud to build and train custom AI models, often in tandem with GPUs from Nvidia. But Garman said that the new AWS clusters are 30 to 40 percent cheaper than those that feature Nvidia's GPUs. Amazon is the world's biggest cloud computing provider, but until recently, it might have been considered a laggard in generative AI compared to rivals like Microsoft and Google. This year, however, the company has poured $8 billion into Anthropic, and it has quietly pushed out a range of tools through an AWS platform called Bedrock to help companies harness and wrangle generative AI. At Re:Invent, Amazon also showcased its next-generation training chip, Trainium 3, which it says will offer four times the performance of its current chip. It will be available to customers in late 2025. "The numbers are pretty astounding" for the next-generation chip, says Patrick Moorhead, CEO and chief analyst at Moore Insight & Strategy. Moorhead says that Trainium 3 appears to have received a significant performance boost from an improvement in the so-called interconnect between chips. Interconnects are critical in developing very large AI models, as they enable the rapid transfer of data between chips, a factor AWS seems to have optimized for in its latest designs. Nvidia may remain the dominant player in AI training for a while, Moorehead says, but it will face increasing competition in the next few years. Amazon's innovation "shows that Nvidia is not the only game in town for training," he says.

AWS details Project Rainier AI compute cluster with hundreds of thousands of chips - SiliconANGLE

AWS details Project Rainier AI compute cluster with hundreds of thousands of chips Amazon Web Services Inc. today detailed Project Rainer, a compute cluster powered by hundreds of thousands of its custom AWS Trainium2 chips. The company is using the system to support the artificial intelligence development efforts of Anthropic PBC. AWS parent Amazon.com Inc. has invested $8 billion in the OpenAI rival since last September. A few weeks ago, Anthropic detailed that it will help the cloud giant enhance the Trainium chip line. The Trainium2 is powered by eight so-called NeuronCores, which in turn each comprise four compute modules. One of the modules is a so-called GPSIMD engine optimized to run custom AI operators. Those are highly specialized, low-level code snippets that machine learning teams use to boost the performance of their neural networks. The eight NeuronCores are supported by 96 gibibytes of HBM memory, which is considerably faster than other RAM varieties. The Trainium2 moves data between its HBM pool and NeuronCores at a speed of up to 2.8 terabits per second. The faster information can reach the part of the chip where it will be processed, the sooner calculations can begin. The hundreds of thousands of Trainium2 chips in Project Rainier are organized into so-called Trn2 UltraServers. Those are internally-developed servers that AWS detailed today alongside the compute cluster. Each machine includes 64 Trainium2 chips that can provide 332 petaflops of aggregate performance when running sparse FP8 operations, a type of calculation that AI models use to crunch data. AWS didn't deploy the servers that make up Project Rainer in a single data center as is the usual practice. Instead, the cloud giant decided to spread out the machines across multiple locations. That approach simplifies logistical tasks such as sourcing enough electricity to power the cluster. The benefits of spreading out hardware across multiple facilities historically came at a cost: increased latency. The greater the distance between the servers in a cluster, the more time it takes data to travel between them. Because AI clusters regularly shuffle information among their servers, this latency increase can significantly slow down processing. AWS addressed that limitation with an internally-developed technology called the Elastic Fabric Adapter. It's a network device that speeds up the flow of data between the company's AI chips. Moving information between two disparate servers involves numerous computing operations. Some of those operations are carried by the servers' operating system. AWS' Elastic Fabric Adapter bypasses the operating system, which allows network traffic to reach its destination faster. Under the hood, the device processes traffic with the help of an open-source networking framework called libfabric. The software lends itself to powering not only AI models but also other demanding applications such as scientific simulations. AWS expects to complete the construction of Project Rainier next year. When it comes online, the system will be one of the world's largest compute clusters for training AI models. AWS said that it will provide more than five times the performance of the system that Anthropic has been using until now to develop its language models. The announcement of Project Rainier today comes about a year after AWS disclosed plans to build another large-scale AI cluster. Project Ceiba, as the other system is called, runs on Nvidia Corp. silicon rather than Trainium2 processors. The original plan was to equip the supercomputer with 16,384 of the chipmaker's GH200 graphics cards. Last March, AWS switched to a configuration with 20,736 Blackwell B20 chips that is expected to provide six times as much performance. Project Ceiba will support Nvidia's internal engineering efforts. The chipmaker plans to use the system for projects spanning areas such as language model research, biology and autonomous driving.

AWS and Anthropic to Build 5x Larger Supercomputer | PYMNTS.com

Amazon Web Services (AWS) and Anthropic are building a supercomputer that will be five times the size and have five times the performance of the one Anthropic used to train its current generation of artificial intelligence (AI) models. Dubbed "Project Rainier," the EC2 UltraCluster of Trn2 UltraServers will use hundreds of thousands of Trainium2 chips for model training -- five times the size of its previous cluster -- AWS said in a Tuesday (Dec. 3) press release. The Trn2 UltraServers, which were introduced Tuesday and are available in preview, are designed to provide performance and cost efficiency for customers who are training and deploying AI models and future large language models and foundation models, according to the release. "With models approaching trillions of parameters, we understand customers also need a novel approach to train and run these massive workloads," David Brown, vice president of compute and networking at AWS, said in the release. "New Trn2 UltraServers offer the fastest training and inference performance on AWS and help organizations of all sizes to train and deploy the world's largest models faster and at a lower cost." Project Rainier will deliver more than five times the number of exaflops -- a measure of performance for a supercomputer -- used by Anthropic for its current AI models, according to the release. "When completed, it is expected to be the world's largest AI compute cluster reported to date available for Anthropic to build and deploy their future models on," the release said. This news came about two weeks after Amazon and Anthropic announced an expanded partnership that includes Amazon investing another $4 billion in the AI company -- bringing its total investment in Anthropic to $8 billion -- and Anthropic making AWS its primary training partner. The expanded partnership builds on one announced in September 2023 that included Amazon making its initial investment of $4 billion in Anthropic and Anthropic making AWS its primary cloud partner. "By combining Anthropic's expertise in frontier AI systems with AWS's world-class infrastructure, we're building a secure, enterprise-ready platform that gives organizations of all sizes access to the forefront of AI technology," Anthropic said in a Nov. 22 press release announcing the expanded partnership.

Amazon to Provide Anthropic Chip Clusters With Five Times Power

Amazon.com Inc. will provide artificial intelligence partner Anthropic with a massive cluster of homegrown chips it says will quintuple the startup's current processing power. The company is stringing together hundreds of thousands of its Trainium2 semiconductors into arrays that will make it easier for Anthropic to train the large language models required for generative AI and other machine learning tasks.

Amazon Unveils New AI Model, Chips, Supercomputer for Anthropic

Amazon on Tuesday unveiled half a dozen artificial intelligence models the company plans to sell to cloud customers and which it said were comparable to models sold by Google, Anthropic, OpenAI and others. It also showed a new version of its AI data center chip, which it is using to build a server cluster for Anthropic. Some of the Amazon models are multimodal, meaning they can generate images