Localized reading
جعلت مكعب روبيك يحل نفسه باستخدام Jev من @typesafeai، وهو يحله كما يفعل الإنسان: في 94 حركة، لا في الحل الأمثل المؤلف من 22 حركة. Jev ليس نموذجًا لغويًا كبيرًا؛ إنه يجيب عن سؤال واحد خلال نحو 250 مللي ثانية باحتمال...
Original post / EN
I got a rubik's cube to solve itself with @typesafeai 's Jev and it solves it like a person does, 94 moves, not the 22 move optimal solution. Jev isn't an LLM, it just answers one question in ~250ms with a probability. so I put the beginner method in code (the one you'd learn on youtube: white cross, corners, middle layer, yellow layer) and at every step Jev just looks at the cube and picks which case it's in. code checks every pick. ~4 seconds of model time total. video is slowed down so you can read it!
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Quoted post
Diogo Almeida @CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x https://t.co/JSybNG2BKJ
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