惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

D
DataBreaches.Net
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Google DeepMind News
Google DeepMind News
博客园 - 聂微东
Microsoft Azure Blog
Microsoft Azure Blog
V
Visual Studio Blog
IT之家
IT之家
博客园 - 【当耐特】
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
B
Blog
爱范儿
爱范儿
阮一峰的网络日志
阮一峰的网络日志
云风的 BLOG
云风的 BLOG
Vercel News
Vercel News
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
H
Hackread – Cybersecurity News, Data Breaches, AI and More
H
Help Net Security
J
Java Code Geeks
aimingoo的专栏
aimingoo的专栏
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
B
Blog RSS Feed
Blog — PlanetScale
Blog — PlanetScale
S
SegmentFault 最新的问题
Apple Machine Learning Research
Apple Machine Learning Research

Tech - South China Morning Post

Multinational pharmaceutical companies to benefit from new China guidelines: analysts Hong Kong lawmaker swipes at US lack of ‘clarity’ as city eyes crypto lead China’s Hesai adds colour to lidar to help EVs level up in self-driving ‘State-of-the-art’ models can struggle with basic office work, says AI executive Opinion | As AI evolves, school syllabuses must evolve with it Winner of second Beijing robot half-marathon smashes human world record by 6 minutes Asia’s supply chains could give it edge over US in AI race: Granite Asia’s Foo Chinese software firms defy ‘SaaSpocalypse’ with strategic AI partnerships Huawei retains lead in China smartphones, Apple shipments surge in first quarter China’s drug makers are speeding up – will AI be their secret weapon? Hong Kong seen leading Asia in push to scale stablecoins, HSBC says ByteDance, Tencent step up AI talent battle amid reports of DeepSeek loss White House and Anthropic CEO discuss working together amid Mythos AI fears Chinese LED chipmaker’s purchase of Dutch firm collapses after US opposition How Amazon uses closer China supply ties to counter tariffs, Shein and Temu ‘Horrible’ for US if DeepSeek AI models run on Huawei chips: Nvidia CEO Chinese platforms fined 3.6b yuan over ‘ghost’ takeaways amid cutthroat rivalry Manycore, one of Hangzhou’s ‘Six Little Dragons’, surges on Hong Kong IPO debut How the rise of AI agents could finally make China’s open-source models pay ‘Buy what they can, steal what they can’t’: US lawmakers slam China’s AI tactics China’s lithium giant Ganfeng sees profit jump as EV, ESS battery demand soars Chinese tech giants, AI ‘godmother’ Li Fei-Fei race into world models Black market workarounds scale up for Claude as Anthropic tightens ID checks TSMC targets over 30% revenue surge in 2026, ramps up capex amid AI boom BrainCo’s brain-computer interface wows at HSBC summit with mind-controlled hand Chinese investors cheer Tesla’s AI chip progress, boosting shares of suppliers ASML boosts 2026 sales forecast despite shrinking China sales China’s EV battery giant CATL to set up mining arm to secure supply chain From ‘probing minds’ to verified account: how Musk’s stance on TikTok shifted Amazon bets on Shenzhen smart warehouse to cut merchant storage costs by 45%
How a Chinese physical AI start-up’s new paradigm bypasse...
Coco Feng · 2026-06-25 · via Tech - South China Morning Post

A Chinese physical AI start-up has launched a new world model designed to simulate reality by embedding the laws of physics directly into its code – a departure from the data-driven approaches favoured by American tech giants like OpenAI and Meta Platforms.

Shanghai-based Fysics AI announced the launch of the Fysiverse, which it described as a “new-generation physics-based world model that adheres to real-world physical laws”, in a post on its WeChat social media account on Wednesday.

The start-up, founded by former Nvidia senior manager Zhang Lihua, said the model “represents a new paradigm” that could effectively address issues commonly faced by currently available world models, such as “physical illusions, reasoning failures, and breakdowns in non-standard scenarios”.

The world model sector, used to create content and train robots or self-driving technology, is currently dominated by three major paradigms.

The first is video-based generation that duplicates movements by learning from massive video clips. OpenAI’s Sora is a typical example, with the firm describing scaling video generation models as “a promising path towards building general purpose simulators of the physical world”.

The second way is to let the model, without knowledge of physics, construct its own rules of the world in a black box. Meta’s V-JEPA series, short for video joint embedding predictive architecture, is one such system that takes a “self-supervised learning approach”, according to Meta’s website.