arXiv -> alphaXiv Students at Stanford have built alphaXiv, an open discussion forum for arXiv papers. alphaXiv You can post questions and comments directly on top of any arXiv paper by changing arXiv to alphaXiv in any URL!

Announcing "Super Study Guide: Transformers & Large Language Models", a 250-page book with ~600 colored illustrations covering the concepts of the Stanford workshop that Shervine and I are teaching at this summer.

Topics include: - Transformers (how they work, detailed examples) - LLMs (pretraining, prompt engineering, finetuning, preference tuning, optimizations such as quantization) - Applications (RAG, translation, etc.) Book: amazon.com/dp/B0DC4NYLTN/

The Future of #ElectricVehicles via Franco Ronconi 🇮🇹 #Innovation #Technology #Tech #Automation #Mobility #Automotive #Transport #EVs cc: Dr Maggie Lieu Balakrishna Rao Chris Anderson

Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion via Wevolver #AI #MachineLearning #ArtificialIntelligence #Robotics #RPA #ML #MI cc: Yann LeCun @bernardmarr Marcus Borba

This machine can automatically iron and dry your clothes at once by GiGadgets #Tech #Technology #Innovation #EmergingTech cc: @pbalakrishnarao Rich Tehrani Pascal Bornet

It’s happening.

I drew these strawberries with mathematical equations.

🛠️ DeepSeek-R1: Technical Highlights 📈 Large-scale RL in post-training 🏆 Significant performance boost with minimal labeled data 🔢 Math, code, and reasoning tasks on par with OpenAI-o1 📄 More details: github.com/deepseek-ai/De… 🐋 4/n

🤖🔬Today we are debuting Zochi, the world’s first Artificial Scientist with state-of-the-art contributions accepted in ICLR 2025 workshops. Unlike existing systems, Zochi autonomously tackles some of the most challenging problems in AI, producing novel contributions in

Here are the top AI Papers of the Week (April 14 - 20): - GUI-R1 - AgentA/B - DocAgent - SocioVerse - A Survey of Frontiers in LLM Reasoning - Scaling Reasoning in Diffusion LLMs via RL Read on for more:

🚨This week's top AI/ML research papers: - Test-Time RL - PHYBench - Process Reward Models That Think - Tiny Reasoning Models via LoRA - Learning to Reason under Off-Policy Guidance - SplitReason - Learning Adaptive Parallel Reasoning with LMs - Token-Shuffle - Describe Anything

Grok 4 (Thinking) achieves new SOTA on ARC-AGI-2 with 15.9% This nearly doubles the previous commercial SOTA and tops the current Kaggle competition SOTA

Thank you to the xAI team for working with us to validate Grok 4's score and inviting us to the watch the live stream

Less than 500 days since releasing their first model in March 2024, xAI has released the leading AI model

🇮🇳 India at #ICML2025! From Lossfunk 📄 ACCEPTED PAPERS: 42 💡 SPOTLIGHTS: 6 (3 oral, 3 spotlight) 👥 AUTHORS: 96 🏆 GLOBAL RANK: #18 Thread with all papers & Indian authors below 👇

From GPT to MoE: I reviewed & compared the main LLMs of 2025 in terms of their architectural design from DeepSeek-V3 to Kimi 2. Multi-head Latent Attention, sliding window attention, new Post- & Pre-Norm placements, NoPE, shared-expert MoEs, and more... magazine.sebastianraschka.com/p/the-big-llm-…

The real reason people from top universities succeed isn't just IQ. When you get into IIT or Harvard or MIT, you've already proven you can delay gratification for years. You studied when your friends partied. You chose hard classes when easy ones were available. You optimized for

I study the history of software because most people think code innovation happens in a vacuum. They see React and think Facebook just invented components. They miss the decades of work on MVC patterns, the failed attempts at web components, the slow evolution from server-side

One of the most important papers in AI: a tiny brain-inspired 27M param model trained on 1000 samples outperforms o3-mini-high on reasoning tasks! Still can't believe this tiny lab of Tsinghua grads gets 40% on ARC-AGI, solves hard sudoku and mazes. We're still so early.