Benchmarks are a key driver of progress in AI. But they also have many shortcomings. The new GPT-Fathom benchmark suite aims to reduce some of these pitfalls.
Benchmarks allow AI developers to measure the performance of their models on a variety of tasks. In the case of language models, for example, answering knowledge questions or solving logic tasks. Depending on its performance, the model receives a score that can then be compared with the results of other models.
These benchmarking results form the basis for further research decisions and, ultimately, investments. They also provide information about the strengths and weaknesses of individual methods.
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