Great conversation with @craigss at @EyeOn_AI about how the industry spends too much time talking about compute and data-centers, when we should be talking about more creative, more efficient ways to scale AI. We cover: - The hidden cost-multiplier within every model in production today. - How the scaling laws of transformer-based models have become the biggest bottleneck in AI. - How our team at Subquadratic solved the problem with a new model architecture that is 128x more efficient than frontier models at 2M tokens without compromising on performance. Thanks to Craig and the Eye on AI team for the thoughtful conversation. Check out the full episode below.

we gave our AI an eye for detail. 👀 Meet WeVisOne-VL, an open-source 2B/4B model from our Weixin Vision team. It finds and counts objects, reads text, and makes precise masks and cutouts—no separate SAM needed. Not in the image? "None."

Billionaire @mcuban says AI is “not smart,” arguing it predicts patterns but doesn't understand consequences or have inherent ethics. He says he'd trust a seeing-eye dog over AI to guide him across a busy street. (Via @jaynitx, Original source: @StevenBartlett)

The MacBook notch finally does something useful. a dev built Coucou: Mochi, a tiny character that lives in your notch and keeps an eye on your AI coding agents while you do something else. what Mochi does: • watches → Claude Code, Cursor, Codex and Gemini CLI sessions • shows → live file changes and diffs • approves → Claude Code permission prompts from the notch • answers → agent questions without opening the terminal the extras: → chat with Claude, GPT, Gemini or local models → drop files on the notch for context → no telemetry, open source You keep working. Mochi babysits the agents. the repo:

AI inference is entering a new phase. On this episode of Eye on A.I., d-Matrix CEO @sidsheth joins @craigss to unpack the “premium token economy,” why purpose-built infrastructure matters, and how organizational AI could change the way companies operate. Listen here: