Realtime AI News
AQuA：让量化研究 Agent 持续进化，也让回测结果经得起检验
AQuA：让量化研究 Agent 持续进化，也让回测结果经得起检验. 自主研究系统的上限，不只取决于模型有多聪明，也取决于系统能否分辨什么是新证据，什么只是一次偶然的高分。
According to qbitai.com, AQuA：让量化研究 Agent 持续进化，也让回测结果经得起检验.
自主研究系统的上限，不只取决于模型有多聪明，也取决于系统能否分辨什么是新证据，什么只是一次偶然的高分。
The signal matters because AI capabilities are moving into more specific product, infrastructure, or business workflows.
The next things to watch are availability, pricing or access limits, and whether the update creates a measurable workflow change for builders or enterprise users.
Why it matters
This update reflects the continued movement of AI capabilities into concrete product, platform, and industry contexts.
Nearby Updates
All08/31, 10:59
China's AI Model Call Volume Leads for 18 Consecutive Weeks; Zhipu's NiuLai Tops Chart, DeepSeek-V4-Pro Falls Off
Sina reports that Zhipu's NiuLai model has jumped to the top of China's latest weekly AI large-model API call-volume ranking, while DeepSeek-V4-Pro fell off the list. The report says China's AI large-model call volume has led the field for 18 consecutive weeks, a sign that momentum among the country's top model providers is shifting.
08/31, 11:04
OpenAI buys thousands of Mac minis to train AI agents, turning Apple's Macs into training infrastructure
OpenAI has bought tens of thousands of Mac mini and Mac Studio systems for reinforcement learning and computer-use agent training, and is still trying to secure more units, according to a report from The Information. Anthropic is renting Mac minis through AWS for similar work, as Apple's desktop hardware unexpectedly becomes AI training infrastructure.
08/31, 10:51
New Entrant StartLux-27B Local Model Reportedly Beats DeepSeek V4 Flash
Sina Finance reports that a new player, the locally deployable StartLux-27B model, has outperformed DeepSeek V4 Flash in a head-to-head comparison. The claim, if verified, would highlight how local deployment models are increasingly competing with cloud APIs on capability and cost.
08/31, 11:11
Three-month-old startup Lingxi Zhiyong takes national third in industrial humanoid contest with ROSS Harness
At the industrial assembly and loading station of the 2nd World Humanoid Robot Games, Lingxi Zhiyong — founded just three months ago — reached the national top three with a score of 160 using a robot built from a demo-grade chassis, the only robotics company besides industry leaders to win in the industrial scenario category. The breakout came from its self-developed ROSS Harness Agent, which lets models, skills and memory co-evolve in real tasks.