Devarshi lalani

@Surendar__05 Regardless of one's proficiency with AI tools, problem-solving skills remain paramount for success in leading companies and startups.

Be honest guys,Are you still grinding DSA in the AI era?

@sama Anything worse than this?? @sama

I am happy everyone is switching to Codex, but Tibo if you start rate limiting me or making me use worse models...

What the hell @sama @OpenAI @ChatGPTapp Please bring something good in gpt 5.5

Please try to improve @ChatGPTapp @OpenAI @sama

@abhijitwt Assembly

guess the language he codes in?

@Amank1412 Agree 💯💯 Son of anton

You may have Claude, Cursor, Codex, and Gemini but you still can't match his intelligence.

@AnthropicAI This practice is entirely legal and ethical, akin to companies such as Deepseek utilizing the Claude API. They leverage Claude's reasoning and answers to train their smaller parameter models.??

We’ve identified industrial-scale distillation attacks on our models by DeepSeek, Moonshot AI, and MiniMax. These labs created over 24,000 fraudulent accounts and generated over 16 million exchanges with Claude, extracting its capabilities to train and improve their own models.

@DesiCodqs Rustttttt always

Which programming language gives you this physique ?

@chrishayduk It's truly exciting to witness the remarkable work that has gone into building AlphaFold 2 from scratch. .

I'm rebuilding AlphaFold2 from scratch in pure PyTorch. No frameworks on top of PyTorch. No copy-paste from DeepMind's repo. Just nn.Linear, einsum, and the 60-page supplementary paper. The project is called minAlphaFold2, inspired by Karpathy's minGPT. The idea is simple: AlphaFold2 is one of the most important neural networks ever built, and there should be a version of it that a single person can sit down and read end-to-end in an afternoon. Where it stands today: - ~3,500 lines across 9 modules - Full forward pass works: input embedding → Evoformer → Structure Module → all-atom 3D coordinates - Every loss function from the paper (FAPE, torsion angles, pLDDT, distogram, structural violations) - Recycling, templates, extra MSA stack, ensemble averaging — all implemented - 50 tests passing - Every module maps 1-to-1 to a numbered algorithm in the AF2 supplement The Structure Module was the most satisfying part to build. Invariant Point Attention is genuinely beautiful — it does attention in 3D space using local reference frames so the whole thing is SE(3)-equivariant, and the math fits in about 150 lines of PyTorch. What's next: - Build the data pipeline (PDB structures + MSA features) - Write the training loop - Train on a small set of proteins and see what happens The repo is public. If you've ever wanted to understand how AlphaFold2 actually works at the level of individual tensor operations, this is meant for you. Repo: github.com/ChrisHayduk/mi…

github.com/codeMaestro78/… MLcli is kow completely ready.... I appreciate your contributions and thoughts.

I've successfully finished building my transformer architecture.

These days, my bots are all coming together! 🤖 Clawdbot, Moltbot, and OpenClaw are a triple threat. Which one is your favorite? 🤔 #BotLife #AI

How was the Silicon Valley so ahead of its time? @steipete is a gilfoyle ?

@rasmalai Haskell

@rasmalai Rust

@elonmusk I think @Grokipedia should improve its LaTeX rendering. While going through the Brownian motion content, I noticed that the mathematical equations would be much clearer with better LaTeX formatting.

Try Grokipedia.com

GitHub:- github.com/codeMaestro78/… AutoML is on the way.....

@aditiitwt Black life/newlife.py

Write something which only programmers can understand

@zackvoell That's why they were able to give accurate prediction 😅😅🥲🥲

How did they make this without Claude Code?

MLCLI version `v0.3.0` has been released. Go checkout Github :- github.com/codeMaestro78/… Website (docs) :- mlcli.vercel.app Python package (PyPi):- piwheels.org/project/mlcli-… pypi.org/manage/project…