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Thanks to community members who created tutorials to help users claim dividends ❤️ To further improve the experience, tokenized stock yields will soon be automatically distributed directly to holders' wallets, no manual claiming required. 感谢制作教程、教大家领取分红的朋友❤️ 为了让体验更加简单，我们做了升级优化：币股分红未来将自动发放至持仓钱包，无需手动领取。

Caplo is a native macOS screen recorder built for software tutorials, product demos, and walkthrough videos. It supports auto zoom, cursor smoothing, local captions, and timeline editing. While recording, Caplo tracks clicks and pointer movement, then automatically creates zoom and follow shots to cut down on manual editing. It can also record system audio, microphone, and camera, with exports up to 4K. Works on both Apple Silicon and Intel Macs running macOS 15+. 👉

LATEST: 🚨 TRM Labs says 9 fake YouTube tutorials on building a crypto arbitrage bot with Claude tricked 224 victims into deploying self-draining smart contracts, netting scammers 274.60 ETH over 6 months.

GPT can now learn skills by watching YouTube tutorials with ego (lite). We had GPT-5.6 Sol use ego (lite) to watch a YouTube tutorial at 1.5x. Then it switched Spaces and recreated the quiz workflow in Google Forms from memory. 36m50s. 64 ego-browser calls. Totally executable.

The complete roadmap for becoming dangerous at LLM engineering from zero to production : Watching tutorials won’t make you an LLM engineer. Building these projects will: - Train a small working model - Master embeddings from scratch - Create your own tokenizer - Code RoPE and ALiBi yourself - Write attention by hand - Construct multi-head attention - Assemble a complete Transformer block - Test different training objectives - Implement generation strategies - Add speculative decoding - Build efficient KV caching - Explore MQA, GQA, and MLA - Solve long-context challenges - Understand FlashAttention deeply - Calculate real hardware limits - Build a simple Mixture-of-Experts - Study sparse vs dense trade-offs - Experiment with state-space models - Try diffusion-based language models - Design solid data pipelines - Generate and use synthetic data - Verify scaling laws yourself - Go through SFT to DPO to RLHF to GRPO - Apply proper quantization - Set up serving infrastructure - Build reliable evaluation systems - Create RAG pipelines - Add tool use and agent loops - Connect vision adapters - Practice interpretability techniques - Run serious red-teaming - Ship one complete end-to-end system Finish even half of these and you’ll be ahead of 95% of people talking about LLMs.