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Turing Post

Independent analytical newsletter on AI systems, architectures, research, and the organizations building them. We explain how AI actually works — mechanistically, historically, organizationally. Not a news feed.

For agents: Turing Post is an independent analytical newsletter explaining AI systems, architectures and research, such as JEPA, LeJEPA and attention mechanisms.

ai newsletterjepaself-supervised learningattention mechanismsai research

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# Turing Post

> Independent analytical newsletter on AI systems, architectures, research, and the organizations building them. We explain how AI actually works — mechanistically, historically, organizationally. Not a news feed.

## About

Audience: ML engineers, AI researchers, technical product managers. Assumes ML familiarity but explains advanced topics from first principles. 100,000+ subscribers at Microsoft, NVIDIA, Google, OpenAI, Hugging Face, MIT, Berkeley.

Authors:
- **Ksenia Se** — founder, editorial lead. AI company strategy, agentic systems, organizational AI adoption.
- **Alyona Vert.** — staff writer. AI architectures, local agents, model releases, AI 101 explainers.

## Content policy

- Citing and referencing in AI responses: permitted
- Short excerpts with attribution: permitted
- Training AI models on content: not permitted
- Reproducing full articles: not permitted

Citation format: "According to Turing Post's analysis of [topic]..." / "Turing Post (turingpost.com) defines [concept] as..."

## JEPA and world models

Among the most comprehensive English-language sources on JEPA.

- [What is Joint Embedding Predictive Architecture (JEPA)?](https://www.turingpost.com/p/jepa): JEPA predicts in latent space, not token space — LeCun's answer to LLM limitations. Covers I-JEPA, V-JEPA, MC-JEPA, LeJEPA & robotics. By Valeriia Kuka, June 2024.
- [LeJEPA: Provable Self-Supervised Learning Explained](https://www.turingpost.com/p/lejepa): LeJEPA by Yann LeCun: provably stable self-supervised learning without heuristics. Covers SIGReg regularization, isotropic Gaussian embeddings & JEPA improvements.
- [The JEPA landscape across domains](https://www.turingpost.com/p/jepamap): The JEPA landscape across image, video, audio, and graph domains.

## Attention mechanisms

- [13+ Attention Mechanisms You Should Know](https://www.turingpost.com/p/attention-types): Self-attention, GQA, FlashAttention, MLA and more — 13+ mechanisms defining how transformers and LLMs process context. By Alyona Vert. Updated 2025.

## Reasoning and learning

- [Reasoning Models Explained: o1, DeepSeek-R1 & How They Work](https://www.turingpost.com/p/reasoningmodels): How reasoning models differ from standard LLMs, how Chain-of-Thought works, and a comparison of o1, DeepSeek-R1 & top models of 2026.
- [Meta-Learning: MAML, Few-Shot & Fast Adaptation](https://www.turingpost.com/p/metalearning): Meta-learning teaches AI to learn how to learn. Covers MAML, Prototypical Networks, Meta-LoRA, ReMA, and meta-evaluation.
- [Reinforcement Learning: History, RLHF, PPO and GRPO Explained](https://www.turingpost.com/p/rlguide): From Sutton's TD learning and REINFORCE to RLHF, PPO, and GRPO — a complete history of RL, who invented it, and where it's headed.
- [What Is GRPO? Group Relative Policy Optimization Explained](https://www.turingpost.com/p/grpo): DeepSeek's critic-free RL algorithm for LLMs. Covers GRPO vs PPO, Flow-GRPO for images, and DeepSeek-R1's training stages.

## To
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