10 results on this page
Alibaba’s net profit fell 75% to $1.54 billion in the June quarter as capital spending reached $9.98 billion. The spending reflects a major investment in AI infrastructure and cloud capabilities rather than a deterioration in core business performance.
Meitu Imaging & Vision Research Institute (MT Lab) proposes a new scene text editing approach for languages ranging from Chinese to low-resource languages. The research is presented as an ICML 2026 contribution and focuses on making text changes appear seamless within images.
Ant Group’s quarterly profit barely grew after the company increased spending on artificial intelligence. The investments target healthcare, large language models, and payment services, while expansion costs also pressured results.
Claude is expanding into protein design, adding a scientific research capability to its existing AI portfolio. The update suggests potential use in computational biology and biotech workflows, though the article excerpt does not provide implementation or benchmark details.
Zhongbo Juli is increasing its investment in Moonshot AI once again. The move underscores the continuing competition around AGI, computing limits, and engineering execution.
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.
Stecon Group Pcl plans to bid for three data-center construction projects valued at a combined 49.8 billion baht, or about $1.5 billion. The company expects Thailand’s accelerating technology investment to drive further growth.
Unitree has launched the R1, a bionic seven-axis robotic arm priced from 9,900 yuan. It combines 0.1 mm repeatability, force feedback, collision detection, and a lightweight desktop design for research, education, industrial, and service-robot applications.
This systematic review examines how large language models support mental-health applications, including social-media analysis, clinical conversational agents, therapy support, and psychoeducation. It also covers multimodal diagnosis, prompt engineering, interpretability, and the ethical and regulatory safeguards needed for responsible deployment.
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.