
ℏεsam
@Hesamation • 83,430 subscribers
apes made fire, then GPUs, then ASI
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bro created an AI job search system for Claude Code that scored 700+ job applications and actually got him a job. AND IT'S NOW OPEN-SOURCE. It scans multiple company career pages, rewrites your CV per job, and even fills application forms. The repo has: > 14 skill modes (evaluate, scan, PDF, ...) > Go terminal dashboard > ATS-optimized PDF generation via Playwright > 45+ companies pre-configured (Anthropic, OpenAI, ElevenLabs, Stripe...) GitHub:
ℏεsam5,788,835 просмотров • 3 месяцев назад

someone trained an AI for +2,000 hours using RL to see if it can beat human world record in Trackmania. the interesting part was that he still had to take inspiration from the top player techniques, then FORCE the AI to learn them. finally, AI was able to beat the top player by 0.01 seconds.
ℏεsam1,852,768 просмотров • 1 месяц назад
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Dario told the Senate in 2023 that “the scaling of open-source models” was going down “a very dangerous path.” in other words: open weight models are fine until they get good enough to threaten the closed-model business, then they become a matter of national security.
ℏεsam519,186 просмотров • 22 дней назад

these guys are making Claude, Hermes, and DeepSeek argue with each other instead of just agreeing with you. this is the practical future of agent teams. with Bloome you just pick a task template, and it spins up a full agent team in a group chat to collaborate and get the job done. research, review, writing, market analysis, or anything you want. they brainstorm, review, and plan together. meanwhile, you or other human teammates can steer them or jump in, and stay in the same conversation so nothing gets lost across tools. since this is actual work, Bloome works across web, mobile, and desktop. try the desktop app first if you're using it seriously. same flexibility on the agent side too, you can connect any agents you want: ChatGPT, OpenClaw, Gemini… check them out →
ℏεsam61,952 просмотров • 10 дней назад

WAIT WAIT WAIT. is anyone gonna talk about the fact how Thinking Machines demo looks insanely similar to GPT 4o demo from 2 YEARS AGO?
ℏεsam423,048 просмотров • 2 месяцев назад

this professor explains Game Theory so well it makes you want to learn it now.
ℏεsam899,780 просмотров • 7 месяцев назад

this game on steam teaches math and coding better than 99% of the uni courses out there.
ℏεsam719,415 просмотров • 6 месяцев назад

Andrej Karpathy beautifully explains the fundamental difference of learning between a human and an LLM. > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” many of the best minds in this field think LLMs are not really learning anything, and therefore are incapable of surpassing human-level intelligence.
ℏεsam895,122 просмотров • 9 месяцев назад

"I use AI in a separate window. I don't enjoy Cursor or Windsurf, I can literally feel competence draining out of my fingers." DHH, the legendary programmer and creator of Ruby on Rails has the most beautiful and philosophical idea about what AI takes away from programmers.
ℏεsam1,164,849 просмотров • 1 год назад

3Blue1Brown’s new video explains why every LLM is actually a compression machine. everyone describes pre-training as “next token prediction” but that’s just the surface-level objective. in reality it is a means to making the most efficient text compressor. prediction and compression are two sides of the same coin. when you train the model to predict the next token you’re not just teaching it to guess the next word but how to best encode the human knowledge it sees. better compression means better abstraction means better reasoning at some point, compression stops looking like storage or a database (as some like to call it on X) and looks like an approximation of understanding.
ℏεsam119,751 просмотров • 1 месяц назад