AI Research Topics

Discover curated categories that organize my posts by themes.

The History of World Models

A chronological series on how machines learned to predict their surroundings — from control theory and model-based RL to world foundation models.

Embodied AI & Robotics: VLA Models & World Models

Where AI acts in the physical world: VLA models, robot policies, simulation, and planning. Covers VLA+, Cosmos, DreamerV3, PAN, and physical AI.

Economics

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.

AI Infrastructure: Inference, Chips & RAG Systems

The systems AI runs on: compute, chips, inference, retrieval and RAG pipelines — and what it costs to serve intelligence at scale.

LLM Post-Training: GRPO, DPO, RLHF & Fine-Tuning

How LLMs are trained and improved: RL methods like GRPO and DPO, distillation, fine-tuning, quantization, and retrieval — explained for practitioners.

AI Concepts & Techniques

Tokens, embeddings, attention, scaling, inference — the foundational AI concepts explained from the ground up for engineers and researchers.

Architectures

The structural blueprints behind AI models: transformers, mixture-of-experts, state-space models, diffusion, and JEPA — and what each design makes possible.

AI Models: In-Depth Analysis

Deep dives into individual AI models: LLMs, reasoning models, VLMs, and small models — capabilities, benchmarks, and how they compare.

The Org Age of AI

What changes when AI becomes an operational resource? Covers AI ROI, workflow redesign, AI-native startups, enterprise maturity, and AI flywheels.

Open Source AI in 2026

How to think about open models when money, risk, and strategy are on the line

AI Literacy

how we talk to our children about AI will shape how they talk back to it

AI Agents

How AI agents work, think, and act autonomously. Turing Post covers multi-agent systems, agentic memory, and the evolving AI software stack — for practitioners.

AI 101

Turing Post's weekly explainer series: one AI concept at a time, from first principles, for engineers who want the mechanism, not the metaphor.

The History of Computer Vision

How computer vision evolved: from perceptrons (1950s) and early models to AlexNet, ImageNet, and spatial intelligence — a research-backed series.—

AI Infra Unicorns: Company Deep Dives

In-depth analysis of AI infrastructure companies powering compute at scale: CoreWeave, Nscale, GPU clouds & more. Turing Post AI Infra Unicorns series

FMOps: Foundation Model Operations for AI Engineers

A practitioner series on running foundation models in production: fine-tuning, deployment, monitoring, evaluation, and cost control.

"Froth on the Daydream"

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.

Community Twist: Guest Posts & Practitioner Insights

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

The history of LLMs: mechanical translation, AI winters, RNNs, Transformers, BERT, and ChatGPT — a complete series with deep-dives by Turing Post.

Interviews with Innovators

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 AI Affairs

Global perspective, featuring China, Russia, India, Israel, Europe, and beyond

Twitter Library

AI concepts visualized: model architectures, RL approaches, JEPA, and agentic memory — explained through infographics and visual guides. Curated by Turing Post.

GenAI Unicorns: Company Deep Dives

Inside the fastest-growing generative AI companies: OpenAI, Anthropic, Mistral, Perplexity, Character AI and more. In-depth analysis by Turing Post.

Origins

Origins traces who coined the terms that shaped AI, how they spread, and why their meanings changed over time.