Learn how to evaluate LLM quality and limitations using a range of testing techniques, from unit and regression testing to ...

This is the 2nd part of my analysis on Anthropic Claude and its system-wide prompt, focusing on the mental health directives.

Moving forward requires coordinated technical, policy, and educational responses. An outright ban on AI in peer review, as is ...

The model learns that hedging is a signal of lower-quality output. This creates a systematic bias toward sounding certain.

The AI was smarter than the person setting it up ...

I finally stopped babying my MacBook.

Anthropic Claude provides open access to their system-wide prompt. I analyze the portions dealing with AI mental health guidance. An AI Insider analysis and scoop.

The days of simply hoping to rank through passive optimization for opaque algorithms have officially come to an end and the ...

Look to these key metrics and benchmarks to evaluate the performance, capability, reliability, and safety of your AI models ...

Pilots that looked promising do not always survive the transition, and the failure pattern is consistent enough that data leaders can plan around it. This article describes three failure modes that ...

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...