'As the pace of AI adoption accelerates across industries, there is a need to understand and improve its impact in the world,' the company continued in its post. 'Creating domain-specific evals are one way to better reflect real-world use cases, helping teams assess model performance in practical, high-stakes environments.' As the recent controversy with the crowdsourced benchmark LM Arena and Meta's Maverick model illustrate, it's tough to know, these days, precisely what differentiates one model from another. Many widely-used AI benchmarks measure performance on esoteric tasks, like solving doctorate-level math problems. Others can be gamed, or don't align well with most people's preferences. Through the Pioneers Program, OpenAI hopes to create benchmarks for specific domains like legal, finance, insurance, healthcare, and accounting. The lab says that, in the coming months, it'll work with 'multiple companies' to design tailored benchmarks and eventually share those benchmarks...
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