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Discover curated categories that organize my posts by themes.
How AI learned to model its surroundings — from early control and reinforcement learning through the JEPA lineage to world foundation models for physical AI
Embodied AI, VLA models, world models, and physical AI robotics — where AI acts in the physical world. Covers VLA+, Cosmos, DreamerV3, PAN, and JEPA
The economics of intelligence — from the cost of a token to the future of work: pricing, compute as currency, growth, labor, and what abundance does to value.
The systems AI runs on: compute, chips, inference, RAG and retrieval — and the economics of serving intelligence at scale. Curated by Turing Post.
How LLMs are trained and improved: RL methods like GRPO and DPO, distillation, fine-tuning, quantization, and retrieval — explained for practitioners.
Tokens, embeddings, attention, scaling, inference — the foundational AI concepts explained from the ground up for engineers and researchers.
The structural blueprints behind the models – transformers, mixture-of-experts, state-space models, diffusion, JEPA – and how each design choice shapes what a system can learn
In-depth analysis of AI model architectures: LLMs, reasoning models, world models, VLMs, and small models. Curated by Turing Post for AI practitioners.
What changes when AI becomes an operational resource? Covers AI ROI, workflow redesign, AI-native startups, enterprise maturity, and AI flywheels.
How to think about open models when money, risk, and strategy are on the line
how we talk to our children about AI will shape how they talk back to it
How AI agents work, think, and act autonomously. Turing Post covers multi-agent systems, agentic memory, and the evolving AI software stack — for practitioners.
Machine learning fundamentals explained: LLMs, agents, RAG, transformers, inference & RL. Turing Post's AI 101 series — updated weekly.
How computer vision evolved: from perceptrons (1950s) and early models to AlexNet, ImageNet, and spatial intelligence — a research-backed series.—
In-depth analysis of AI infrastructure companies powering compute at scale: CoreWeave, Nscale, GPU clouds & more. Turing Post AI Infra Unicorns series
Foundation model operations in practice: RAG, fine-tuning, deployment, monitoring & vector databases. Turing Post FMOps series for AI engineers.
Froth on the Daydream — Turing Post's weekly AI digest. Curated analysis of the most important AI research, models, and industry developments from the past week.
Guest posts, expert guides, and practitioner insights from the ML and AI community — curated by Turing Post for engineers and researchers.
The history of LLMs: mechanical translation, AI winters, RNNs, Transformers, BERT, and ChatGPT — a complete series with deep-dives by Turing Post.
Conversations on AI agents, inference, open models, and the future of software — with researchers and founders from NVIDIA, OpenAI, Mozilla & more. By Turing Post.
Global perspective, featuring China, Russia, India, Israel, Europe, and beyond
AI concepts visualized: model architectures, RL approaches, JEPA, and agentic memory — explained through infographics and visual guides. Curated by Turing Post.
Inside the fastest-growing generative AI companies: OpenAI, Anthropic, Mistral, Perplexity, Character AI and more. In-depth analysis by Turing Post.
Origins traces who coined the terms that shaped AI, how they spread, and why their meanings changed over time.