Why did editing 0.016% of AI weights increase math performance by 6x? The mechanics and configuration secrets of the MIT study

Conclusion: The 0.016% weight edit fixed "premature termination due to thinking loops," and even unedited models can reach an ...

What is this "PHP" everyone is talking about?

The "PHP turmoil" making headlines. What is happening right now, explained in 5 minutes even if you are IT-illiterateIn ...
techflowpost

$40 Billion Valuation, US Company Finally Creates a Competitor to China's Open-Source Models

Thinking Machines Lab, founded by the former OpenAI CTO, released its second-generation model Inkling 2 Small and openly ...
Digital Production

FLAPI: Baselight Beyond the Grading Suite

FilmLight's Jason Peterson, Mustapha Laatita and Steve Chapman explain why FLAPI exists, how it scales, what it costs and ...
INCRYPTED

Qwen by Alibaba on a Home PC: Instructions, Requirements, and Unexpected Test Results

Alibaba’s 27-billion-parameter Qwen3.8-27B scores 61.7% on SWE-bench Pro in the developer leaderboard. In its 4-bit version, ...