world models

AI

2026-08-16 07:28:10

Researchers Say Emotion Signals Can Improve How AI Agents Choose Actions

Researchers from the University of Science and Technology of China and Oxford, as cited in the source article, tested whether AI agents perform better when they use internal emotion-like representations to choose skills instead of relying only on text and external feedback. The report says the models showed consistent pairings between states such as curiosity, confusion, tension, optimism, disappointment, and the actions they took during tasks. In a shopping experiment, those pairings mapped to behaviors including product search, query reformulation, purchase confirmation, and price comparison. To check whether the pattern was more than coincidence, the researchers sampled 200 skill-selection events and found a 76.5% semantic consistency rate. The article also says emotion-driven skill selection, named EMOTION2SKILL, lifted success rates in difficult household tasks that often require recovery after mistakes. In the experiments described, success in "heating objects" rose from 9.6% to 56.9%, while "picking up two objects" increased from 4.4% to 31.3%. Separately, a Tianjin University team embedded emotion into a world model called Large Emotional World Model, or LEWM, and reported accuracy gains of as much as 45.72% on its self-built dataset. The piece links both studies to Anthropic’s April experiment on Claude Sonnet 4.5, which reportedly identified fine-grained emotion directions aligned with the Go Emotions taxonomy.

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Anthropic

2026-08-13 02:15:18

Anthropic Reportedly in Talks to Buy Israeli AI Startup Decart for $6 Billion

Anthropic is in talks to acquire Israeli AI startup Decart for $6 billion, according to Bloomberg, in what would be the company’s largest acquisition to date if completed. The deal has not been finalized. Decart, founded in September 2023 by Dean Leitersdorf and Moshe Shalev, focuses on world models and cross-chip inference optimization. The company has about 100 employees, has raised roughly $450 million, and was last valued at about $4 billion after a $300 million round backed by investors including NVIDIA and Amazon. Decart said its optimization platform can deliver agentic inference speeds of up to 1,600 tokens per second, while its world-model system can generate video at 100 frames per second, though those figures have not been independently verified. In October 2024, the startup launched Oasis, which it described as the world’s first real-time interactive generative AI video model, and said the product passed 1 million users within three days. Israeli outlet Calcalist had earlier reported that NVIDIA was initially the leading buyer, before another international company entered the process. Possible buyers mentioned at the time included SpaceX, Amazon, and cloud provider Nebius, with a reported price range of $6 billion to $7 billion.

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ScaleForce

2026-08-12 02:37:08

ScaleForce reveals two funding rounds in 40 days as embodied AI data demand rises

ScaleForce, a data infrastructure startup focused on embodied AI, has disclosed its first financing update, saying it completed two funding rounds within 40 days. The investors named in the announcement include leading domestic embodied AI industry backers, Hengxu Capital, and Kailian Capital. Though the company has been operating for less than three months, it said a multi-million-yuan data order from TaShi Zhihang has already been fully launched, and that it has formed partnerships with multiple world model companies, leading embodied AI hardware makers, and industry solution providers. The company is positioning itself around a problem now drawing more attention across embodied intelligence: a shortage of high-quality real-world interaction data. In its account, the gap between the data needed to train general autonomous embodied models and the amount of usable physical interaction data currently available remains extremely wide. ScaleForce says its MatrixOS platform is designed to cover collection, processing, cleaning, generalization, management, and delivery of physical AI data. It also disclosed product metrics tied to its ADA and GDP engines, overseas expansion efforts, and the backgrounds of its founding and technical leadership team, including founder Guo Jiangliang, whose prior experience includes Baidu AI Cloud and Innovation Qizhi.

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Fei-Fei Li

2026-08-06 08:13:13

Fei-Fei Li says World Labs wants to build scalable digital worlds for robotics after SceniX acquisition

World Labs’ acquisition of SceniX is being framed by CEO Fei-Fei Li and SceniX co-founder Yunzhu Li as a move to solve one of robotics’ hardest bottlenecks: the shortage of training and evaluation data. In an a16z interview, the two said robots are the first major proving ground for “spatial intelligence,” a category World Labs sees as the next frontier for AI. Their joint plan centers on a real-to-sim-to-real stack that maps physical environments into aligned digital worlds, where robots can be trained and tested more safely, more quickly and at larger scale. Li said World Labs’ Marble model can already turn images and text into geometrically consistent worlds, while SceniX brings robotics, simulation and evaluation expertise. Yunzhu Li argued that the company is not trying to bet on a single robot body or a single model architecture. Instead, it is building infrastructure that can support different hardware types, multimodal policy models and simulation workflows. Both executives said simulation is not a substitute for real-world data, but a necessary partner to it, particularly for counterfactual reasoning, reliability testing and iteration speed. They also said near-term deployment is more likely in semi-structured settings such as warehouses, restaurants and hotels than in fully unstructured home environments.

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AI startups

2026-08-06 02:28:30

China AI Startups Shift to World Models and Robotics; H1 Funding Tops 2025 Total

Chinese AI startups are shifting their investment focus from text-generation models to world models and robotics, according to a report by CryptoBriefing cited by Techub News. In the first half of 2026, Chinese robotics startups raised roughly $5.6 billion, already surpassing the full-year total for 2025. Shengshu, Manifold AI and Striding AI were among names that completed large financing rounds. AI² Robotics and X Square Robot have both reached valuations above $2.9 billion. The deals are structured mainly as traditional equity, with sovereign or quasi-sovereign capital involved in most cases. No major company in this space has issued a token or integrated blockchain infrastructure so far. The report's analysis attributes part of the shift to US chip export controls, which hit pure text-generation models harder. World models and robotics have different compute requirements, and China's existing chip ecosystem may satisfy some of those application scenarios.

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AI

2026-07-24 05:35:17

Serenity Says World Models Are Becoming AI’s Biggest Investment Consensus in China

Analyst Serenity says China’s primary AI funding is moving away from early base-model startups and into embodied AI, physical AI, and world models.

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WAIC 2026

2026-07-17 08:59:20

WAIC 2026 panel says embodied AI must clear narrow use cases first as competition shifts to data and closed-loop validation

Speakers at a WAIC 2026 roundtable said general-purpose embodied intelligence remains a distant goal, with near-term progress more likely to come from specialized deployments. Fudan University Vice President Jiang Yugang, AgiBot partner Yao Maoqing, Tashi Zhihang CEO Chen Yilun and Liangyuan Xinchuang CEO Jiang Xu discussed world models, arguing that their core task is to understand how the physical world works and predict the next state or action rather than simply render images. The panel identified data as the main bottleneck. Chen said existing video datasets lack key modalities such as force and touch, while ideal training data would need complete modalities, high-frequency interaction and real-world origins. Yao estimated that building common-sense physical prediction could require more than 100 million hours of real-world data. On commercialization, the speakers pointed to manufacturing as the clearest large-scale application over the next three years, though Jiang Xu said capability jumps may first appear in everyday settings such as homes and offices. The shared conclusion: the field’s next battleground is shifting from model architecture to access to high-quality data and the ability to validate systems through closed-loop scenarios.

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Tian Keyu

2026-07-15 01:44:00

Tian Keyu returns to AI with a world-model startup reportedly valued at $200 million after ByteDance lawsuit

Tian Keyu, the former ByteDance intern who was dismissed and later sued for 8 million yuan over an alleged attack on the company’s large-model training project, has resurfaced in the AI sector with a new startup, according to media reports citing people familiar with the matter. The venture is focused on world models, a field tied to AI systems that aim to understand space, motion and causal relationships in the physical world. The project was reportedly incubated and led by FiveY Capital partner Meng Xing, has raised tens of millions of U.S. dollars, and is valued at about $200 million. Tian’s profile has remained unusually polarizing. He is a PhD student at Peking University and a graduate of Beihang University’s School of Software. In 2024, he helped produce the VAR image-generation paper that won the NeurIPS best paper award, with the related GitHub project attracting more than 4,400 stars. But his public notoriety came from a dispute at ByteDance. The company said in November 2024 that a former intern had maliciously interfered with model training tasks by writing and modifying code, causing heavy resource losses. Tian later denied carrying out the attack, said another intern was responsible, and said he had reported the matter to police after being defamed.

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