The University of Hong Kong’s diffusion model team raises nearly 500 million yuan, backed by Huawei and Shunwei Capital.
Beating AI News Flash: Shenzhen-based diffusion language model firm DiffuSpace has closed two consecutive financing rounds totaling nearly 500 million yuan. The rounds were jointly led by Matrix Partners China, Shunwei Capital, and Legend Capital, with follow-on investments from Huawei Harbin Investment, Horizon Robotics, and others. Multiple media outlets note this is the largest financing round in the global diffusion language model space. DiffuSpace was founded in May this year by The University of Hong Kong professor Kong Lingpeng and his PhD students Gong Shansan and Ye Jiacheng. The team previously co-developed Dream 7B with Huawei Noah’s Ark Lab and has open-sourced the model’s weights. It uses diffusion large language model (dLLM) technology. Unlike mainstream models like GPT and Claude that generate text sequentially, diffusion models can process content across multiple positions simultaneously before gradually completing and refining it. DiffuSpace is currently training a new 30-billion-parameter model, with plans to release and open-source it soon. The company will focus on advancing code agents and local deployment on devices including smartphones, automobiles, and robots.
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New World Model Odyssey-3 scores 66.1 in physics benchmark test, outperforms FLUX 3, now open for free trial.
Beating AI Express: World model company Odyssey has officially launched Odyssey-3, with its Flash version now available for free trial. The model can generate explorable worlds in real time from text, with visuals updating dynamically as users move or rotate the camera. The team also showcased experiments applying the same model to robotic arms, humanoid robots, vehicles, and game characters.
Odyssey-3 first learns object movement and action outcomes from internet videos, game play recordings, and physical simulations. When deployed for robots or vehicles, the main pre-trained model parameters remain unchanged; the team only needs to train additional small control modules to translate the model’s learned knowledge into operational instructions. While different machines still require separate adaptation, full retraining of the entire model is unnecessary.
Odyssey trained a dedicated control module using just 20 hours of simulated driving data, enabling a car to operate on real roads in India. In tests, the simulated data training scheme delivered approximately 77% of the driving distance between two safety officer takeovers compared to the real driving video training scheme. For the humanoid robot developed in partnership with Flexion, after training on tens of hours of remote control demonstration data, it can complete tasks even under varying lighting conditions.
In game experiments, the control module learned from roughly 2 hours of Grand Theft Auto V (GTA V) gameplay footage, and without additional training, it enabled characters to ride horses and move in Red Dead Redemption 2. In the Physics-IQ Verified physical video prediction test, Odyssey-3 Pro scored 66.1 points, surpassing FLUX 3 [large]’s 64.35 points, with both results being the best from 8 trials. Odyssey also released WorldMark evaluation results, where the model secured first place in three out of four interaction scenarios.
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Ethereum rebounded to break through $2,500, with its 24-hour decline narrowing to 2.4%.
According to HTX market data, Ethereum has rebounded to break through the $2,500 mark, with its 24-hour decline narrowing to 2.4%.
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US after-hours trading rebounds for semiconductor, optical communication, and storage-related concepts; LITE's CEO states that all optical device production capacity will have been fully sold out by early 2029.
According to market data from BIT (bit.com), semiconductor, optical communications and storage concepts rebounded in U.S. after-hours trading. Applied Optoelectronics (AAOI) rose nearly 5%, while Lumentum (LITE) gained 3%. Michael Hurlston, CEO of leading optical communications firm Lumentum, said today that as tech companies race to build faster AI data centers, the company’s optical component production capacity has been fully booked through early 2029. For some products, about 70% of demand will still go unmet next year, and for others, 30% of demand will remain unsatisfied through 2028. Back in April this year, Hurlston had stated that he expected full-year 2028 production capacity would be fully booked within two quarters.
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A high-win-rate trader goes long on 12,000 Ethereum, valued at $29.88 million.
According to Lookonchain monitoring, trader 0x2371 — who boasts a 100% win rate across four previous long positions, generating total profits of $9.26 million — has opened a new position: a 20x leveraged long on 12,000 Ethereum (ETH) worth $29.88 million, with an unrealized profit of $626,000 so far.
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Smart trader 0x2371 opens 20x long on 12,000 $ETH ($29.88M), unrealized profit hits $626K
Smart trader 0x2371, with a 100% win rate and $9.26M in total profit, is trading again!
After the market dropped, he opened a 20x long on 12,000 $ETH ($29.88M) and is now sitting on an unrealized profit of $626K.
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