AI/ML/NLP
REAP Explained: How Cerebras Prunes MoE Experts
REAP is Cerebras's one-shot method for pruning redundant Mixture-of-Experts. Learn the saliency math and how it shrinks GLM-4.6 and Qwen3-Coder by up to 40%.
AI/ML/NLP
How modern AI actually works, from attention to alignment.
AI/ML/NLP
Constitutional AI: Making Claude Safe Without Human Labels
Constitutional AI (CAI) is Anthropic's method for training safe AI without massive human labeling: RLAIF, self-critique, and how it compares to RLHF.
AI/ML/NLP
Efficient Attention: FlashAttention to Long Context
Process 100K+ token contexts efficiently. Learn FlashAttention, linear attention, GLA, and how modern LLMs handle long documents without running out of memory.
AI/ML/NLP
Instruction Tuning: Fine-Tune LLMs to Follow Directions
Instruction tuning (SFT) turns base LLMs into assistants like ChatGPT. Covers dataset creation, Alpaca, FLAN, and the quality vs quantity tradeoff.
AI/ML/NLP
AI Code Generation: How Copilot, Cursor and Claude Work
Understand how GitHub Copilot, Cursor, and Claude generate code. Learn pass@k evaluation, HumanEval benchmarks, and best practices for AI-assisted programming.
AI/ML/NLP
AI in Astronomy: How Machine Learning Finds Exoplanets
How NASA and astronomers use AI to classify galaxies, detect exoplanets, and find gravitational waves, from JWST image processing to autonomous discovery.
AI/ML/NLP
LLM Quantization Guide: Run 70B Models on Consumer GPUs
Run 70B parameter models on a single GPU. Learn LLM quantization from 8-bit to 2-bit precision: GPTQ, AWQ, GGUF, QuIP#, and when to use each method.
AI/ML/NLP
RLHF Explained: How ChatGPT and Claude Learn from Humans
Understand RLHF, the technique behind ChatGPT and Claude. Learn reward modeling, PPO optimization, DPO, and how AI assistants become helpful and safe.
AI/ML/NLP
Vision-Language Models Explained: GPT-4V, LLaVA and Claude
Understand how GPT-4V, LLaVA, and Claude see images. Learn VLM architecture: vision encoders, multimodal fusion, and how to reduce hallucination in production.
AI/ML/NLP
RAG Tutorial: Retrieval-Augmented Generation Explained
Learn RAG from scratch: chunking strategies, embeddings, vector databases, and fusion mechanisms. Build AI that grounds its answers in its sources.
AI/ML/NLP
Mixture of Experts Explained: Mixtral, DeepSeek and Grok
Understand MoE, the architecture behind Mixtral 8x7B, DeepSeek, and Grok. Learn expert routing, load balancing, and why sparse models beat dense ones.
AI/ML/NLP
Chain-of-Thought Prompting: How LLMs Reason Step by Step
Chain-of-thought prompting helps models like GPT-4 and Claude solve hard problems. Covers zero-shot CoT, self-consistency, and implementation examples.