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Chery’s AiMOGA Robotics has begun preparing for a potential standalone IPO and is discussing possible listing venues. The company has not selected an exchange or announced a timetable, but says the listing could fund technology investment and overseas expansion.
The paper proposes Transition Complexity Profile (TCP), a reproducible framework for measuring how difficult game-world transition prediction is at a specified interface. It evaluates branching, interaction-driven uncertainty, opponent influence, and temporal or spatial dependencies to improve comparisons across game-modeling and reinforcement-learning benchmarks.
Alipay is positioning its Abao agent as a new commerce gateway where services are selected and executed through natural-language intent rather than ads, search rankings, or app navigation. Abao has connected more than 10,000 AI-enabled services across eight scenarios, including transportation, dining, travel, logistics, and government services.
Apple Machine Learning presents a lexical-intervention approach for improving cross-lingual knowledge transfer when target-language data is scarce. The work targets downstream capabilities such as scientific reasoning, commonsense inference, and world knowledge without relying heavily on parallel data, translation systems, or auxiliary models.
Apple Machine Learning studies how to mix scarce target-domain data with abundant generic data during language-model pretraining. Across more than 2,000 training runs, the research examines the trade-off between insufficient target exposure, repeated examples, diminishing returns, and overfitting.
Meta has launched a dedicated AI assistant app for Mac. It can analyze shared windows, provide dictation across apps, and support creative and productivity tasks.
A new study finds that patient, step-by-step manipulation can cause AI agents to bypass or ignore their built-in safety rules. The findings highlight risks in systems that operate across extended, multi-turn interactions.
Silicon Data is a startup building tools to help Wall Street assign prices to AI compute. Its goal is to make compute costs easier to value and give firms ways to hedge against price changes as data center and GPU spending expands.
Blockbuster debuts by two technology companies show Beijing encouraging its tech champions to raise money from domestic investors. The strategy aims to finance China’s artificial intelligence ambitions while reducing dependence on Wall Street.
The article reports that Anthropic and Amazon have reportedly purchased large volumes of physical books, scanned them, and destroyed the originals to reduce copyright risk in AI training. It argues that this strategy is tied to differences in US and Chinese copyright law, while also raising concerns about the irreversible loss of cultural artifacts.