Chinese outfit Zhipu AI claims it trained a new model entirely using Huawei hardware, and that it’s the first company to build an advanced model entirely on Chinese hardware.

Zhipu, which styles itself Z.ai and runs a chatbot at that address, offers several models named General Language Model (GLM). On Wednesday the company announced GLM-Image, that it says employs “an independently developed ‘autoregressive + diffusion decoder’ hybrid architecture, which enables the joint generation of image and language models.” represents an important advance on the Nano Banana Pro image-generating AI. — Read More

Starting 2026, most people are aware that a handful of Chinese companies are making strong, open AI models that are applying increasing pressure on the American AI economy.

While many Chinese labs are making models, the adoption metrics are dominated by Qwen (with a little help from DeepSeek). Adoption of the new entrants in the open model scene in 2025, from Z.ai, MiniMax, Kimi Moonshot, and others is actually quite limited. This sets up the position where dethroning Qwen in adoption in 2026 looks impossible overall, but there are areas for opportunity. In fact, the strength of GPT-OSS shows that the U.S. could very well have the smartest open models again in 2026, even if they’re used far less across the ecosystem. — Read More

Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream width and diversifying connectivity patterns. While yielding substantial performance gains, this diversification fundamentally compromises the identity mapping property intrinsic to the residual connection, which causes severe training instability and restricted scalability, and additionally incurs notable memory access overhead. To address these challenges, we propose Manifold-Constrained Hyper-Connections (mHC), a general framework that projects the residual connection space of HC onto a specific manifold to restore the identity mapping property, while incorporating rigorous infrastructure optimization to ensure efficiency. Empirical experiments demonstrate that mHC is effective for training at scale, offering tangible performance improvements and superior scalability. We anticipate that mHC, as a flexible and practical extension of HC, will contribute to a deeper understanding of topological architecture design and suggest promising directions for the evolution of foundational models. — Read More

#china-ai

Or: The West banned the machines. China hired the machinists. Sometimes plans just do not go how you planned them. Ironically, I had been writing this article for a month now, and all research pointed at China being way too far behind. Well…

December 2025. Reuters reveals that China completed an operational EUV lithography prototype in a high-security Shenzhen facility. Not through reverse engineering captured ASML machines. Not through some breakthrough in domestic optics manufacturing. Through something far simpler.

They recruited the humans who knew how to build them. — Read More

In this wave of artificial intelligence, it’s easy to be swept up in grand narratives: computing power, models, the scale of parameters, disruption, and replacement. But the changes truly worth documenting often happen out of sight: how AI is used, how it enters daily life, and how it changes the way people work.

Last week, The Intellectual and Doubao jointly launched: “A Story Collection | How Were You ‘Amazed’ by AI This Year?”, not asking “how powerful is AI,” but a more specific question: When AI enters your work and life, what exactly does it change?

…Perhaps what is truly worth documenting is not what AI can do, but how researchers, after its intervention, re-understand their work, judgments, and responsibilities—what tasks can be automated, and what problems must still be decided by humans.

These scattered and specific experiences constitute the first batch of “field notes” of AI entering the scientific field. They may not be complete, but they are sufficiently honest. — Read More

… China’s extensive AI-powered visual surveillance systems are already well documented. This report reveals new ways that the Chinese Communist Party (CCP) is using large language models (LLMs) and other AI systems to automate censorship, enhance surveillance and pre-emptively suppress dissent.

… AI-powered technology is widening the power differential between China’s state-supported companies operating abroad and foreign populations—further enabling some Chinese companies to systematically violate the economic rights of vulnerable groups outside China, despite Beijing’s claims that China respects the development rights and sovereignty of other countries.

The risks to other countries are clear. China is already the world’s largest exporter of AI-powered surveillance technology; new surveillance technologies and platforms developed in China are also not likely to simply stay there. — Read More

Chinese artificial intelligence startup DeepSeek released two powerful new AI models on Sunday that the company claims match or exceed the capabilities of OpenAI’s GPT-5 and Google’s Gemini-3.0-Pro — a development that could reshape the competitive landscape between American tech giants and their Chinese challengers.

The Hangzhou-based company launched DeepSeek-V3.2, designed as an everyday reasoning assistant, alongside DeepSeek-V3.2-Speciale, a high-powered variant that achieved gold-medal performance in four elite international competitions: the 2025 International Mathematical Olympiad, the International Olympiad in Informatics, the ICPC World Finals, and the China Mathematical Olympiad. — Read More

Large language models have made significant progress in mathematical reasoning, which serves as an important testbed for AI and could impact scientific research if further advanced. By scaling reasoning with reinforcement learning that rewards correct final answers, LLMs have improved from poor performance to saturating quantitative reasoning competitions like AIME and HMMT in one year. However, this approach faces fundamental limitations.

Pursuing higher final answer accuracy doesn’t address a key issue: correct answers don’t guarantee correct reasoning. Moreover, many mathematical tasks like theorem proving require rigorous step-by-step derivation rather than numerical answers, making final answer rewards inapplicable.

To push the limits of deep reasoning, we believe it is necessary to verify the comprehensiveness and rigor of mathematical reasoning. Self-verification is particularly important for scaling test-time compute, especially for open problems without known solutions. Towards self-verifiable mathematical reasoning, we investigate how to train an accurate and faithful LLM-based verifier for theorem proving. We then train a proof generator using the verifier as the reward model, and incentivize the generator to identify and resolve as many issues as possible in their own proofs before finalizing them. — Read More

A Chinese vibe coding tool went viral so fast that its signature feature crashed just days after it launched.

LingGuang, an AI app for vibe coding and building apps using plain-language prompts, launched last Tuesday and reached over 1 million downloads in four days. By Monday, the app had crossed 2 million downloads, said Chinese tech group Ant Group, which built the AI coding assistant tool.

On Monday, LingGuang ranked first on Apple’s mainland China App Store for free utilities apps and sixth overall for free apps. — Read More

Today’s children are true “AI natives.” They are born and raised in the AI ​​era; interacting with the digital world is an innate instinct. The AI ​​entities that provide them with education must also be immersive, interactive, personalized, and warm.

The birth of AI English teacher Jessica heralds the future of education: no longer one-way knowledge transmission, but rather the natural acquisition of a communication ability to face the world through symbiosis and dialogue with AI. She possesses a vast amount of knowledge, boundless patience, a memory capable of remembering every child’s situation, and a warm heart—a true “super-teacher.” — Read More