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OpenAI thinks AI benchmarks are broken . Now the society is set up a program to fix how AI models are nock .
The unexampled OpenAI Pioneers Program will focus on creating evaluations for AI models that “ set the barroom for what good see like , ” as OpenAI phrased it in ablog post .
“ As the pace of AI adoption accelerates across industries , there is a motivation to understand and improve its impingement in the world , ” the company continued in its post . “ make sphere - specific evals are one way to better reflect real - world use cases , help teams assess model performance in practical , high - wager environments . ”
As therecentcontroversywith the crowdsourced bench mark LM Arena and Meta ’s Maverick model illustrate , it ’s tough to know , these days , precisely what differentiates one mannequin from another . Many wide used AI benchmarks measure public presentation on esoteric tasks , like puzzle out doctorate - level math problems . Others can be gamed , or do n’t ordinate well with most hoi polloi ’s predilection .
Through the Pioneers Program , OpenAI hopes to create benchmarks for specific domains like sound , finance , policy , healthcare , and account . The lab tell that , in the hail month , it ’ll work with “ multiple companies ” to plan tailor benchmarks and finally share those benchmarks publicly , along with “ industry - specific ” evaluations .
“ The first cohort will focus on startup who will help lie the foundations of the OpenAI Pioneers Program , ” OpenAI wrote in the blog post . “ We ’re selecting a handful of startup for this initial age bracket , each working on high - economic value , applied purpose cases where AI can get real - world impact . ”
company in the program will also have the opportunity to work with OpenAI ’s team to make poser improvements via reinforcement fine tuning , a proficiency that optimizes models for a minute set of tasks , OpenAI say .
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The big question is whether the AI community will embrace benchmarks whose creation was funded by OpenAI . OpenAI has supported benchmarking travail financially before , and designed its own evaluation . But partnering with client to liberate AI tests may be seen as an honourable bridge deck too far .
