Secta

IN 2014 A DEVELOPER TOLD A ROOM OF FOUNDERS THAT A TWO-DOZEN-PERSON LAB ONCE INVENTED THE PERSONAL COMPUTER, THE GUI, OBJECT-ORIENTED CODE AND ETHERNET IN ABOUT FIVE YEARS. THEN HE ASKED WHY, WITH A THOUSAND TIMES THE MONEY, WE HAVEN'T DONE ANYTHING THAT BIG SINCE. 41 minutes from Alan Kay -- Xerox PARC veteran, the man who coined "object-oriented" and sketched the laptop before it existed. -> His split: invention vs innovation. Invention is a real leap into the unknown. Innovation is just polishing and repackaging what already exists and almost everyone, including tech, only does the second one. PARC could leap because it was funded to invent, not to ship. That kind of funding mostly died, so we got 40 years of incremental. His sharpest line: the interesting future isn't about data, it's about meaning -- a system that actually knows something, not the way Siri pretends to. That is exactly the bet on AI right now. The question isn't a faster autocomplete, it's whether the machine understands what you mean -- the leap Kay said we stopped even attempting. You thought progress was steady and forward. This is the talk that shows most of it was just polish on a 40 year old idea. Save this. Watch it before your next "new" idea ↓

man negotiates his own release after Argentina finally survives Vozinha's reflexes 👀 Ransom arrangement is now super easy. Predict the FIFA WC, and enjoy faster execution and instant withdrawals on DG3.

This guy built a home AI supercomputer out of Mac Studios. Five machines, wired together, running as one local inference cluster through Exo. The point is not that it looks insane on a desk. The point is what it replaces. Most people rent intelligence one message at a time. ChatGPT Pro. Claude Code Max. Cursor. Transcription tools. Research tools. API credits. The stack quietly turns into a $400/month bill just to use compute sitting in someone else’s datacenter. This setup flips the model. Macs use unified memory, so the GPU can use the same memory pool as the system. Exo then splits large open-source models across multiple machines, letting the cluster run models a single computer could not handle alone. DeepSeek. GLM. Kimi. Qwen. The kind of models people usually access through cloud APIs can now sit on a desk, running privately, overnight, with no rate limits and no token anxiety. The old flex was paying for every frontier model. The new flex is owning the box that keeps thinking after you close the tab. Bookmark this and read the full setup below.

A guy makes ~$10,000/month testing security systems for major grocery chains. He walks into a supermarket with the director’s approval and blends in like any other customer. Except he is not looking at the shelves. He is looking for the small failures everyone assumes are already handled. Emergency communication. Alert workflows. Response chains. Tiny broken processes customers never see. One report. One payment. A few weeks later, the problems are gone. I built the software version of that mindset with Claude Fable 5. Not “ask one question, get one answer.” I mean giving Claude a full goal, a workspace, files, tests, and a definition of done — then letting it inspect, fix, verify, and keep going until the job is actually finished. That is the real shift. The new skill is not prompting. It is delegation: clear brief, clear finish line, enough context, and a hard stop condition. Read the full guide below.