Welcome to Tech Beat, your daily read on the stories shaping our digital world.
A twenty-six thousand word blog post from AI startup Goodfire is sending ripples through the research community. Researcher Nick Cammarata argues that large language models may be far more interpretable than anyone assumed — meaning we could actually understand what's happening inside them. If the claim holds up, it would fundamentally change how we think about AI safety and control.
From artificial intelligence to institutional finance, JPMorgan has brought its JPM Coin to the public Ethereum blockchain, allowing corporate clients to settle dollar-backed transactions in seconds, around the clock, any day of the year. It's a cautious but meaningful step — one of the world's largest banks putting real money on infrastructure it doesn't fully control.
And in the world of AI performance, Inception Labs has unveiled Mercury three, a diffusion-based language model capable of generating one thousand tokens per second. That's a striking departure from how most models work today, and early numbers suggest the speed isn't coming at a steep cost to quality — though independent benchmarks will tell the fuller story.
Keep surfing. Tech Beat out.
