Daily Digest: How LLMs think

PLUS: Copilot Agents and monster raises.

May 22, 2024

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Hello folks, here’s what we have today;

PICKS

  1. New tutorial: Generate website analysis reports from URLs using AI.

  2. Mapping the mind of a LLM. You know how AI models are often seen as a black box? Well, Anthropic does this crazy thing of looking inside them to understand what makes them tick. They've extracted millions of features from Claude 3.0 Sonnet, like gender bias, bridges and code errors. 🍿Our Summary (also below)

  3. Microsoft is expanding Copilot to teams and agents. Copilot can soon act as a team member in meetings and chats. It can also manage projects and track deadlines. Microsoft also gave a sneak peek into what agents that do tasks autonomously will look like in their ecosystem.

  4. It was a funding frenzy yesterday with huge rounds getting announced. Some of the larger ones:

  5. ChatGPT’s Connected Apps feature has started to roll out to more users. Same with Google’s “Gemini in Workspace” features. Check if you’ve got them.

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NEWS
QUICK BITES

You know how AI models are often seen as a black box? Well, Anthropic, the folks behind Claude, have made some pretty cool progress in understanding the inner workings of these models.

What's going on here?

They've basically created a conceptual map of Claude's "brain," identifying how it represents millions of different concepts, from the Golden Gate Bridge to gender bias.

What does this mean? 

It's like they've peeked under the hood of a car and figured out how the engine works. This isn't just about knowing how Claude identifies "San Francisco" or "immunology," it's about understanding how it connects more abstract ideas like "bugs in code" or "keeping secrets."

It's wild. Anthropic found features for everything from "Golden Gate Bridge" to "gender bias" to "keeping secrets". They can even manipulate these concepts to see how they change Claude's behaviour. Likeamplifying the Golden Gate Bridge feature, they can make the model believe its physical form is the bridge.

Why should you care? 

For starters, this is a HUGE step in AI safety. By understanding how AI models think, we can potentially make them less biased, less likely to be tricked into harmful behaviour, and more aligned with human values.

It's not just about safety though. This discovery also sheds light on how AI models understand and use language, which could lead to even more powerful and sophisticated AI systems in the future.

Who knows what we'll be able to do once we fully understand how these models tick?

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