In 2024, practically 90% of the world’s most notable AI fashions got here out of business. Only a yr prior, that determine was 60%. As the size, value, and compute required to construct frontier AI techniques proceed to rise, the hole between tutorial and company growth has grown tougher to disregard.
The most recent AI Index Report from Stanford’s Institute for Human-Centered Synthetic Intelligence (HAI) gives a snapshot of this accelerating shift. Academia stays a significant driver of foundational analysis, nonetheless producing a major share of extremely cited papers. However it’s more and more outpaced in terms of constructing the biggest and quickest fashions. Coaching compute necessities now double each 5 months, and datasets double each eight, whereas power use rises yearly. On the fringe of frontier AI innovation, the bar for entry is climbing quick.
This pattern has triggered alarm in scientific communities that rely upon entry to superior AI techniques to do their work. As the prices and infrastructure wants of mannequin growth scale past the attain of educational labs, there are rising considerations about reproducibility, transparency, and scientific independence.
However the story isn’t totally bleak. In response to the report, open-weight fashions are starting to shut the efficiency hole with their closed-source business counterparts. On some key benchmarks, the distinction between open and closed fashions shrank from 8% to only 1.7% within the span of a yr. That speedy progress gives hope to researchers, educators, and public-sector establishments who depend on open instruments to construct domain-specific purposes or consider new strategies.
Determine 2.1.34 illustrates the efficiency traits of the highest closed-weight and open-weight LLMs on the Chatbot Area Leaderboard, a public platform for benchmarking LLM efficiency. (Supply: Stanford HAI AI Index Report)
Additionally working in favor of accessibility is a dramatic drop in inference prices. Between November 2022 and October 2024, the associated fee to run a system performing on the degree of GPT-3.5 fell by greater than 280-fold. {Hardware} prices have declined by 30% yearly, and power effectivity is enhancing at a price of 40% per yr. These traits are serving to to decrease the barrier to entry for AI builders and customers outdoors of hyperscale AI, even when the barrier to coaching frontier fashions stays excessive.
Nonetheless, the focus of frontier innovation raises broader questions. Trade now controls the vast majority of influential fashions, and competitors on the prime is tightening. In response to Stanford, the efficiency hole between the first- and tenth-ranked fashions dropped from 11.9% to five.4% in only one yr. The frontier shouldn’t be solely quickly advancing however can also be turning into more and more crowded. For establishments with out entry to proprietary instruments, information, or compute, the window to take part meaningfully could also be shrinking.
The distinction between the highest- and Tenth-ranked fashions on the Chatbot Area Leaderboard dropped from 11.9% in 2024 to only 5.4% by early 2025, reflecting tighter competitors on the frontier. (Supply: Stanford HAI AI Index Report)
The stakes are particularly excessive for science. From local weather modeling to biomedical analysis, entry to the newest and biggest AI techniques can instantly affect the pace and scope of discovery. That makes the well being of the open supply AI ecosystem not only a technical challenge, however a scientific one. As open fashions develop extra succesful, and as efforts to construct collaborative, clear instruments achieve momentum, the hope is that researchers will retain no less than some room to experiment and innovate on the edge, without having a company companion or a billion-dollar funds.
Amid rising considerations over entry and management in AI growth, Stanford HAI's report additionally emphasised that the know-how’s influence extends far past the lab: “AI is a civilization-changing know-how — not confined to anyone sector, however reworking each business it touches,” mentioned Russell Wald, govt director at Stanford HAI and member of the AI Index Steering Committee, in a launch. “Final yr we noticed AI adoption speed up at an unprecedented tempo, and its attain and influence will solely proceed to develop. The AI Index equips policymakers, researchers, and the general public with the info they should make knowledgeable choices — and to make sure AI is developed with human-centered values at its core.”
Within the race to outline the way forward for AI, who will get to construct on the frontier and who will get left behind could also be simply as necessary as how highly effective the fashions turn into.
Entry the complete Stanford HAI 2025 AI Index Report at this hyperlink.
