What's Missing From LLM Chatbots: A Sense of Purpose

AimostAll news brief curated from The Gradient.

Source details

Original source
The Gradient
Published
2024-09-09
Primary topic
Foundation Models

Why it matters

Model launches, benchmark jumps, API upgrades, context window changes, and frontier LLM competition. Use the original source for the full report, then use the directory shortcuts below to compare the products and workflows the story points toward.

What happened

LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as these measures get more and more saturated, is user experience increasing in proportion to these scores? If we envision a future

What to do next

Compare the hosted model pages first, then check the related tools and buyer guides before changing workflow standards.

LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as these measures get more and more saturated, is user experience increasing in proportion to these scores? If we envision a future

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