We are finally beginning to understand how LLMs work: No, they don't simply predict word after word

Large language models have formed their own, universal language and unique ways of solving mathematical problems, researchers' breakthroughs reveal.

We are finally beginning to understand how LLMs work: No, they don't simply predict word after word

Circuit tracing is a relatively new technique that lets researchers track how an AI model builds its answers step by step – like following the wiring in a brain. It works by chaining together different components of a model. Anthropic used it to spy on Claude's inner workings. This revealed...Read Entire Article

Why do large IA language models invent information? Anthropical attempts an approach, to analyze the context in which Claude "hallucinates" Large Language Models (LLMs) such as GPT-4 and GPT-3 have revolutionized the treatment of natural language, offering impressive capabilities in text generation, translation and understanding. However, despite their power, these models can sometimes produce incorrect or invented information, a phenomenon...

GitHub for Beginners: How to get LLMs to do what you want

Welcome back to season two of GitHub for Beginners, a series designed to help you navigate GitHub more confidently! So far, we’ve explored how to use GitHub Copilot and some of its essential features. Today, we will be learning all about large language models (LLMs) and the basics of prompt engineering. LLMs are powerful, and the way we interact with them via prompts matters. For example, have you ever tried asking an LLM a question, but it…

How do AI language models work internally? Anthropic has developed an analytical technique that provides bizarre insights and shows that much is different than thought.

Anthropic has announced a tool it calls an “AI microscope” that allows us to partially examine the inner workings of the Claude 3.5 Haiku language model. The analysis shows that the system generates abstract, cross-linguistic representations of information, indicating a deeper level of data processing than simple statistical word matching. Key findings include Claude’s use of a so-called “universal language of thought”: internal concepts that ar…