21 related articles

Analysis of DeepSeek founder Liang Wenfeng's rare investor dialogue, exploring the company's vision-driven culture, strategic restraint toward AGI, and open-source philosophy in the US-China AI race.

An open-source GitHub repo curates 30+ legally free AI/ML classic books covering deep learning, RL, NLP, computer vision & more, with automated link checking.

Awesome Free AI Books is an open-source repo with 30+ legally free AI & ML classic textbooks covering deep learning, reinforcement learning, NLP, LLMs, and more — all linking to official sources with weekly automated link checks.

How can users in China use Claude? This article deeply compares four solutions: official subscription, proxy subscription (WildCard), relay platforms (2233/0011.ai), and API aggregation (OpenRouter).

Ornith 1.0 by Deep Reinforce reinforces Qwen 3.5 for code agents. We test Ornith 9B & 35B MoE on Chinese writing, logic, and invoice OCR, with full llama.cpp deployment guide.

nuReasoning is an autonomous driving dataset by Motional & UCLA with ~20K long-tail clips annotated for spatial, decision, and counterfactual reasoning, explorable via FiftyOne.
Can LLMs Really Understand Computer Ar…
Can LLMs truly understand computer architecture papers? This article analyzes core challenges—from surface pattern matching to deep reasoning—and defines their capability limits for researchers.

OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.

From SHRDLU to modern neuro-symbolic AI: explore procedural semantics, CCG grammars, semantic parsing, and interactive fiction engines in today's NLP landscape.

A four-stage AI Agent development roadmap: from core theory and ReAct paradigm to multi-agent collaboration and production deployment. Covers DeepSeek, Coze, Dify, and more.

A deep dive into Chain of Thought (CoT) prompting: from prompt construction to reasoning chain generation, revealing the three mechanisms behind AI's improved reasoning. Covers math, medical, and financial use cases.
Causal Theory Cracks Open the LLM Blac…
How can we solve the LLM black box problem? This article explores how causal theory powers mechanistic interpretability research — from causal intervention and activation patching to circuit discovery — and its implications for AI safety and alignment.
Latent Reasoning: The Next-Generation …
Is CoT really AI 'thinking'? This deep dive covers latent reasoning's rise — Coconut, HRM, BDH — and the core trade-offs between interpretability, efficiency, and governance in high-stakes AI.

Chess and Go have been conquered by AI, but imperfect information games with hidden data are the true frontier. This article dives deep into Tactico: how imitation learning + self-play RL train AI toward Nash equilibrium.

A Reddit user ran EQ tests on ChatGPT 5.5 and 5.6, covering meeting emotion ranking, chess-behavior judgment, and facial attractiveness. Version 5.6 shows clear gains in multimodal emotional understanding, but social common sense remains a core weakness.

Are large language models truly intelligent? This article analyzes core AI limitations — pattern matching, hallucinations, reasoning deficits — and explores next-gen directions like inference-time compute, neuro-symbolic AI, and embodied intelligence.

Explore how AI image generation makes sci-fi aesthetics concrete—from futuristic architecture to alien landscapes, AI is bringing dream-crafting within reach. Analyzing the tech evolution, cultural resonance, and democratization of concept design behind Reddit's trending works.

A fine-tuning experiment making an LLM believe 'Japan's capital is Paris' reveals the fragility of AI knowledge storage, boundaries of knowledge editing, and deep implications for model poisoning and AI safety.

A PKU-Stanford trainer breaks down how Python surpasses Stata and R, how AI-driven Skills and Paper Workflow automate empirical research from data to LaTeX paper drafts.

Generative AI is reshaping software development, shrinking demand for junior developer roles. This article analyzes why entry-level positions are most at risk, the talent pipeline implications, and how junior developers can leverage AI tools to stay competitive.