Open-Source AI Models Gain Momentum, Challenging Industry Giants

Openness in AI is necessary to promote fair and competitive markets, said FTC's Lina Khan

This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Log in. Foundation models, like OpenAI's GPT4, are capital-intensive, requiring expensive talent, costly computer infrastructure, and volumes of data. "These conditions have allowed, in some instances, the biggest technology companies to get a layup in the AI space," Khan said. Incumbents can limit access to critical AI resources, like compute, Khan said. Earlier this year, the FTC launched an investigation into major cloud providers' multibillion-dollar investments in generative AI startups due to growing concerns about competition. This includes Microsoft's $13 billion investment in OpenAI, as well as Google and Amazon's multibillion-dollar investments in Anthropic. To fully realize AI's potential, Khan underscores the importance of openness in the field. There needs to be a "real commitment to a philosophy of openness across the industry, which means open markets, but also open architecture, open ecosystems, and open-source software." Open-source software has historically fostered competition as it allows researchers and engineers to accumulate innovation. In particular, Khan calls for AI models' weights to be publicly available. These "open-weight models" lower costs and decrease barriers to entry, enabling innovation at the application layer. However, she warns against the "open to closed playbook," in which technology may be open-source to start but could reverse course and become proprietary over time. Khan also notes that the FTC has worked to increase openness in the labor market. "Some of the best engineers in America have been bound by restrictive non-compete clauses," Khan said. "We've heard from startups that secure funding entered the market only to find that they can't grow because the talent pool has been locked up by dominant players." Earlier this year, the FTC banned non-compete clauses, allowing "developers, designers, and researchers across the country to move freely from company to company with their innovative ideas and unique expertise." Data privacy is another priority for the FTC, Khan noted. In the past, dominant players have engaged in anti-competitive practices by changing their terms of service or privacy policies and thereby reneging on their user privacy commitments. For instance, the FTC hit Meta with a $5 billion fine in 2019 for misleading users about their data protections. In the age of AI, Khan said both consumers and enterprises are uncertain of their data's protections when using foundation models. There is "just a general uncertainty about...whether [firms'] competitively sensitive information and proprietary information is or is not being fed back in." "It's especially important to try to prevent this stuff on the frontend rather than playing catch-up and clean up on the backend when you've already lost so much innovation and opportunity," Khan said. The FTC has worked closely with the antitrust division of the Department of Justice. "I'm a law enforcer, not a regulator," said Jonathan Kanter, the assistant attorney general for antitrust, at the YC event. "My job isn't to regulate a market. It is to enforce the law only when companies violate it to make sure competition can thrive." In March, the DOJ filed a lawsuit against Apple for maintaining a monopoly over the smartphone market. It also filed a lawsuit against Google, accusing the company of illegally using its dominance to manipulate the search and search advertising markets. Tech investors have been frustrated by the top regulators' blockings of mergers and acquisitions. "We can't sell our companies," a New York VC recently told Business Insider. One YC founder expressed in the YC forum that many startups hope to exit via acquisitions, but he said he was concerned about the "chilling effect on acquisitions" due to the DOJ and FTC's investigations. However, Kanter highlights that for the vast majority of acquisitions, the DOJ doesn't do anything. "We focus on the instances where there are bottlenecks to competition," which is in the single digits, he said. "We only focus on deals that have problems...it's a narrow set of deals that satisfy a narrow set of criteria." To avoid government review, Big Tech has begun exploring new pathways from traditional M&A. In March, Microsoft paid $650 million in a licensing deal to Inflection AI, an emerging OpenAI rival, to use its AI models and hire most of its employees. Inflection's ex-CEO now heads Microsoft's AI products and research division. Amazon followed suit, licensing tech and hiring execs away from AI agent startup Adept in June.

Open Source AI Has Founders -- and the FTC -- Buzzing

Y Combinator is famed for its Demo Days, where portfolio companies pitch their apps and wares in hopes of growing from a fledgling company into the next AirBnB. But on Thursday, the startup incubator hosted a mélange of founders, venture capitalists, and US policy makers in its airy industrial space in San Francisco to tackle a defining topic for so many startups today: AI as the latest frontier in the battle between Big Tech and the little guys. For many early-stage tech entrepreneurs, questions around AI can carry existential weight. Ever since ChatGPT was unleashed in late 2022, OpenAI's technology, along with fast follows from Google's and Microsoft's AI teams, has dominated the conversation around this new era of artificial intelligence. But the increasing availability -- and potency -- of open source AI models has the potential to upend those dynamics. On Thursday, the enthusiasm for open source extended beyond just YC-backed founders who stand to benefit from a less expensive way to harness generative AI's power. Lina Khan, the chairperson of the Federal Trade Commission, was one of the most prominent advocates for open-source AI at the event. Speaking to a crowd of approximately 200 entrepreneurs, Khan said it's not an exaggeration to suggest that nearly all of Y Combinator's most successful companies wouldn't exist without open source software and the community behind it. The FTC has been focused on defining and exploring open weights AI models, which are slightly less "open" than fully open-source AI models. With open weights models available to them, "smaller players can bring their ideas to market," Khan suggested. Khan also clearly articulated the stakes for this particular crowd. "Conditions have allowed the biggest technology companies to get a leg up in the AI race," she said. "If you control the raw materials, you can control the market and shut out smaller companies who don't have the infrastructure to compete." Khan's statements were made as part of a broader argument for fair and open competition in the tech industry, and in defense of the regulatory actions the FTC and the US Justice Department have taken against Big Tech companies over the past four years. US Assistant Attorney General Jonathan Kanter spoke Thursday at YC, too, emphasizing that the agencies are looking out for a "little tech" -- a phrase that would resonate with the YC crowd. The appearance of two regulatory heavyweights before a community of this "move fast and break things" crowd might have seemed unlikely as recently as a year ago. Founded in 2005 by the entrepreneurs Paul Graham and Jessica Livingston, among others, YC is more famously known for the intense mentorship and bootcamp-like atmosphere it provides fledgling companies than for its ties to the DC establishment. The shift is intentional. Last October, Y Combinator CEO Garry Tan brought on policy expert Luther Lowe to help facilitate conversations between YC and DC. The arrival of Lowe, who spent more than 15 years in public policy at Yelp and was one of Google's most prominent critics, has clearly brought a certain polish and high-profile policy talk to YC events. Thursday marked the second time that FTC chairperson Khan has spoken to YC founders since Lowe joined.

FTC's Khan Backs Open AI Models in Bid to Avoid Monopolies

Open artificial intelligence models that allow developers to customize them with few restrictions are more likely to promote competition, Federal Trade Commission Chair Lina Khan said, weighing in on a key debate within the industry. "There's tremendous potential for open-weight models to promote competition," Khan said Thursday in San Francisco at startup incubator Y Combinator. "Open-weight models can liberate startups from the arbitrary whims of closed developers and cloud gatekeepers."

Silicon Valley shaken as open-source AI models Llama 3.1 and Mistral Large 2 match industry leaders

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Open-source artificial intelligence has reached a watershed moment, challenging the long-held dominance of proprietary systems and promising to reshape the AI landscape. This week, two significant developments have propelled open-source AI models to the forefront of technological capability, potentially democratizing access to cutting-edge AI tools. Just a day later, Mistral, an emerging French AI lab, released Mistral Large 2, a model that reportedly matches or surpasses existing top-tier systems, particularly in multilingual applications. These back-to-back releases mark a pivotal shift in the AI world. For years, tech giants have jealously guarded their most powerful AI models, citing concerns over safety, potential misuse, and competitive advantage. This week's developments have shattered that paradigm, igniting debates about equity, innovation, and the ethical implications of democratizing such transformative technology. Industry experts are hailing this week's developments as a potential turning point in AI history, comparable to pivotal moments that have sparked technological revolutions in the past. The sudden availability of frontier-level open-source models is expected to dramatically accelerate AI development globally, potentially reshaping entire industries and altering the balance of power in the tech world. This rapid democratization of cutting-edge AI capabilities could usher in a new era of innovation and competition, with far-reaching consequences for businesses, researchers, and society at large. Open-source challengers shake up the AI status quo The implications of this week's announcements are far-reaching. Smaller companies and individual developers can now access sophisticated AI capabilities without the hefty price tags or vendor lock-in associated with proprietary systems. This democratization could fuel an unprecedented wave of innovation, as diverse minds from around the globe contribute to and build upon these powerful tools. However, the widespread availability of advanced AI also raises new challenges. Organizations must now grapple with how to differentiate themselves in a world where cutting-edge AI capabilities are becoming commoditized. The onus falls on business leaders and technical decision-makers to rapidly develop strategies that leverage these open technologies while adding unique value. The geopolitical ramifications of this shift are equally significant. As AI becomes increasingly central to national competitiveness, the proliferation of open-source models could alter the global balance of power in technology. Countries and regions that effectively harness these openly available resources may gain significant advantages in AI development and application. A double-edged sword: The thrilling and terrifying dawn of AI for all Despite the excitement, skeptics urge caution in accepting claims of parity with top proprietary models at face value. The AI field is known for its rapid advancements and shifting benchmarks, making "frontier-level" a moving target. Moreover, raw model capability is just one factor in AI system effectiveness; data quality, fine-tuning, and application-specific optimizations play crucial roles in real-world performance. The abrupt open-sourcing of frontier-level AI also intensifies ongoing debates about AI safety and ethics. While transparency can aid in identifying and addressing biases or vulnerabilities, it may also lower barriers for malicious actors seeking to exploit these powerful tools. The AI community now faces the urgent challenge of striking a delicate balance between openness and responsible development. For policymakers, this week's developments underscore the critical need for adaptive regulatory frameworks that can keep pace with technological advancements while ensuring public safety and ethical use of AI. The tech industry may need to rapidly reevaluate business models and competitive strategies in a landscape where cutting-edge AI capabilities have suddenly become widely accessible. Navigating the new frontier: Collaboration, ethics, and the future of AI As the dust settles on this landmark week, the true impact of these milestones will be determined by how effectively the global community harnesses the potential of open-source AI while mitigating its risks. The sudden democratization of frontier-level AI has the potential to accelerate innovation, reshape industries, and fundamentally alter our relationship with artificial intelligence. In this new era, collaboration and ethical considerations will be paramount. The open-source AI revolution promises to unlock unprecedented possibilities, but it also demands a heightened sense of responsibility from developers, businesses, and society as a whole. As we navigate this transformative period, one thing is clear: the future of AI is becoming more open, more accessible, and more participatory than ever before, and the pace of change is accelerating rapidly.