Tootfinder

Pattern matching in #csharp is probably the most impactful addition to the language since LINQ. #dotnet

Anthropic details the "Assistant Axis", a pattern of neural activity in language models that governs their default identity and helpful behavior (Anthropic)
https://www.anthropic.com/research/assistant-axis

The assistant axis: situating and stabilizing the character of large language models
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

LLMs are masters of the "Understood"—the vast library of human output. But they lack "Understanding"—the creative spark that generates those concepts in the first place.
https://www.ocrampal.com/the-understood-understanding-gap-why-llms-hit-…

The Understood-Understanding Gap: Why LLMs Hit a Wall
Large Language Models have become ubiquitous in knowledge work, yet a curious pattern has emerged. Talk to consultants at McKinsey, BCG, Bain, and you'll hear the same refrain: "I don't really know how I can leverage AI to boost my productivity beyond research and brainstorming." The same applies to programmers,