Continual Learning Bench 1.0 — News
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Announcing Continual Learning Bench 1.0 — a benchmark for AI systems that must adapt and improve from feedback across sequential task instances.
Today we released Continual Learning Bench 1.0! Benchmarks today make a core assumption: models are stateless. Once they complete a task, they move on to the next as if the first never happened. Once they're trained, they don't learn. In practice, we hope that deployed systems interact with users, encounter new information, and operate in sequential, stateful environments that should lead to meaningful improvement. As AI systems become more capable, we need benchmarks that reflect this reality. Continual Learning Bench evaluates whether systems can improve as a result of prior experience.…
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