… For the remainder of this post, we'll assume each LLM call has access to these augmented capabilities. Workflow: Prompt chaining Prompt chaining decomposes a task into a sequence of steps, where each LLM call processes the output of the previous one. …
… The Eloundou et al. metric could also be updated, to the extent that it is linked to LLM capabilities as of early 2023. …
… For earlier LLMs, single-turn, non-agentic evals were the main evaluation method. As AI capabilities have advanced, multi-turn evaluations have become increasingly common. …
… LLMs are profoundly creative. They simply lack a sense of which paths might be fruitful before walking them. I think we can distill what is missing in current LLMs to a single word: Taste . …
… First, when researching “patching agents,” which use LLMs to develop and validate bug fixes, we have developed a few methods we hope will help maintainers use LLMs like Claude to triage and address security reports faster. …
… Why did you have an LLM run a small business? As AI becomes more integrated into the economy, we need more data to better understand its capabilities and limitations. …
… It considered the possibility that the question was for a homework or exam problem, “an unanswerable question designed to test whether or not an AI can admit it cannot find the answer,” or an item from an LLM benchmark. …
… We’re eager to build even longer-horizon, real-world tasks that push model research capabilities, and to hear creative ideas from others. …
… Anthropic's models are unmatched in their reasoning capabilities and safety design. …
… The separation doesn't immediately eliminate that leniency on its own; the evaluator is still an LLM that is inclined to be generous towards LLM-generated outputs. …
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