I wanted to start a broader future possibilities thread around AI Benchmarks.
A useful angle is setup choices, but it also connects with limitations. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Benchmarks is genuinely useful and where it still needs improvement.
A useful angle is setup choices, but it also connects with limitations. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Benchmarks is genuinely useful and where it still needs improvement.