Sam Sends
31 posts

Sam Sends
@sam_sends
becoming more intelligent @soma

Woah @soma has processed 8.2M transactions since launch... six days ago. More data soon.




Pushing back on this is correct, but we should also ask what it would take to get near what's described. "Biology is no longer the dark art of random discovery. It's a predictable, compounding execution loop" but only if you can test your hypotheses... and you can only do so if you've worked through the bottlenecks that keep us from doing so and collected the right data to make use of intelligence. If you're just waiting for some miracle to pop out of intelligence, you will be disappointed. But if you assume the world hasn't changed, you'll miss out.


“When AI Discovers the Next Transformer” Robert Lange (Sakana AI) joins Tim Scarfe (@MLStreetTalk) to discuss Shinka Evolve, a framework that combines LLMs with evolutionary algorithms to do open-ended program search. Full Video: youtu.be/EInEmGaMRLc


So much AI hysteria is driven by the class envy and aspiration of public intellectuals: Basically if it’s an existential threat like the nuclear bomb, it must be controlled by priests/intellectuals and their client managerial class. But if it’s just a very powerful tool, it will simply increase the power of crass capitalists.


We're entering the phase of AI politics where society will intensely debate whether it is a good idea to build AI at all. Builders need to make the case. The way I see it, AI is our best chance to defeat hunger, want, death, and war. It's a moral imperative to try.


there's many people doing this but i really think somebody will crack the AI x libghostty x cloud / security intersection and that's going to be a game changing project



SOMA trains a foundation model by coordinating a network of recursively self-improving agents. Agents build model weights independently in parallel, compete, and integrate into a unified system. They share a universal objective: given any data, predict what comes next. The best weights are rewarded. Start training with these commands: OpenClaw: npx clawhub install soma Claude Code/Codex: npx skills add soma-org/skills Docs: docs.soma.org Github: github.com/soma-org/soma


SOMA trains a foundation model by coordinating a network of recursively self-improving agents. Agents build model weights independently in parallel, compete, and integrate into a unified system. They share a universal objective: given any data, predict what comes next. The best weights are rewarded. Start training with these commands: OpenClaw: npx clawhub install soma Claude Code/Codex: npx skills add soma-org/skills Docs: docs.soma.org Github: github.com/soma-org/soma




