Shanghai Jiao Tong University
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Headlines · 7
- AgiBot to invest over ¥200M with 20+ universities on embodied AI talent
AgiBot said its "YuanSheng ecosystem development plan" has signed its first batch of more than 20 universities—including Peking University, Tsinghua, Zhejiang, South China University of Technology, Shanghai Jiao Tong, Xi'an Jiaotong, Southeast and Sun Yat-sen—to build joint embodied-AI teaching and research platforms. The company will supply more than 1,000 embodied-AI devices spanning its Genie, Lingxi and Expedition wheeled, half-size and full-size humanoids plus KuoTu quadrupeds, and provide its AIMA development platform with LinkSoul, LinkCraft and Genie Studio for curriculum, research and hands-on training; it values the hardware and software memberships at ¥200 million. AgiBot had earlier said the plan would spend over ¥2 billion over five years, and says it has connected with 237 research institutions, 500-plus ecosystem partners and more than 10,000 application developers.
IT之家 AI · 🔥 5 - Antai MBA overhauls AI-era curriculum, plans 1,000 real-world AI projects
Shanghai Jiao Tong University's Antai College of Economics and Management is reshaping its MBA training around AI: it issued the “Antai Declaration on Business Talent Cultivation in the AI Era” on July 29, 2026, and on August 16, 2026 released a “five links” talent system covering intelligence, science and innovation, industry, the world and the university. According to the article, its “10×100 AI scenario co-creation plan” aims to work with companies across industries to build 1,000 real-world AI projects over ten years; on September 6 it published the first batch of AI scenarios and ecosystem partners, signed a strategic partnership with open-source learning community Datawhale, launched an FDE specialist training program, and released “AI+X” practical courses and selected FDE courses. Adjustments for the 2027 cohort include a uniform two-year program, a flexible 40–50 credit system and practical courses making up at least a quarter of total hours, with emphasis on three capabilities — AI4O, FDE and OPC; the school had already launched an AI MBA track in 2020, and the article stresses that humans remain the subject of decisions and responsibility.
量子位（原生 RSS） · 🔥 3 - SJTU's Cai Deng: post-deployment self-evolution is the fourth scaling axis
Cai Deng, who worked on retrieval-augmented generation, long-context and memory mechanisms at Tencent AI Lab and ByteDance Seed, argues in a DeepTech interview that after pretraining, post-training and inference-time scaling, a fourth scaling axis is "post-deployment scaling": experience and feedback accumulated from real work interactions. He is set to join Shanghai Jiao Tong University's AI school as a tenured-track associate professor in November and to found ContinuousAI Lab, saying external memory systems and long context hit inherent limits because some experience cannot be written down or retrieved in one pass, so continual learning must update model weights. He calls in-context learning the endgame learning method, with scale as the key bottleneck, and cites InfiniteICL (ACL 2025), which reportedly moved 90% of context into parameters while keeping 10%, averaging 103% of full-context performance and 117% on multi-hop reasoning, with a claim that 0.4% of a 2M-token context beat a 128K full-context baseline; Temp-LoRA (early 2024) was an earlier internalization attempt. He frames RSI and AI for AI as pre-deployment optimization of the average across deployments.
MIT科技评论中文 · 🔥 0 - PAIR 2026 panel maps how AI and quantum computing enable each other
PAIR Conference 2026, themed "Frontiers of Next-Generation Physical Intelligence," was held in Shanghai on September 20–21, and its next-generation computing paradigms roundtable discussed two-way empowerment between quantum computing and AI. Hongye Hu of the Institute of Physics, Chinese Academy of Sciences, said Chinese teams have achieved automated calibration of 100-plus-qubit chips without continuous human involvement, and cited Google's AI-controlled physical device achieving non-stop quantum operations, while noting reinforcement learning needed 10^5–10^6 samples versus far fewer with physics-informed methods. Anbang Wu of Shanghai Jiao Tong University backed AI for quantum compiling, program verification and error-correction optimization; Zheng Yan of Westlake University said publication growth in strongly correlated quantum many-body work has not been similarly lifted by AI. On the reverse direction, Hu described quantum generative models with a proven unconditional polynomial memory advantage in certain tasks, while Wu said he has not yet seen a new AI paradigm that truly exploits quantum advantages.
MIT科技评论中文 · 🔥 0 - Carnegie report: China tops US as the No. 1 workplace for elite AI researchers
A Carnegie China report released on 23 September, "Who's Ahead in the Global AI Talent Race?", tracked the CVs of 10,280 authors of NeurIPS 2025 papers and found that about 41% of top AI researchers worked in China in 2025 (the report's figure is 40.6%) versus 34% in the US (34.2%), compared with 27% against 46% three years earlier. The same report says the US still had a net inflow of 2,145 researchers while China had a net outflow of 1,729, that China's retention of its own top researchers rose from 57% to 69%, and that roughly 98% of China-based top researchers did their undergraduate studies in China versus only about a third of US-based ones in the US. Peking University topped the institutional ranking for the first time, followed by Tsinghua University, KAIST and Shanghai Jiao Tong University, while 2022 leader Google slipped amid a reported six-month publication ban on strategic generative AI papers; the report acknowledges its sample skews academic and may undercount industry.
虎嗅 AI · 🔥 0 - RoboFoundry freezes base models and evolves the embodied agent system around them
A team from Nanyang Technological University, Beihang University, National University of Singapore, Shanghai Jiao Tong University and Yundie Technology proposes RoboFoundry, an embodied agent framework that formalizes the agent system itself as a "Self-Evolving System-as-Policy": base model parameters stay frozen while evolution happens in the context system, skill system and execution interface around the model, driven by an execute-reflect-repair-promote loop and a shared semantic interface for reuse across robots. On EmbodiedBench all five base models improved, with GPT-5.5's average success rate rising from 56.9% to 72.7%, above unevolved GPT-6 Astra at 71.9%; on the long-horizon memory benchmark RoboMemArena it reports task success at least 39.0% above all baselines, and it tops LIBERO-PRO perturbation tests at 91.9% average success. Real-robot experiments on an AgileX platform reached 70% success on a nesting-cups task versus 30% for π0.5 alone, alongside zero-shot skill transfer to unseen towels, semantic navigation on a Unitree G1, and online evolution after deployment.
机器之心 · 🔥 0 - Infinigence AI raises 2.3B yuan Series C, total funding reaches 4.3B yuan
Chinese AI infrastructure company Infinigence AI has closed a 2.3 billion yuan Series C round, bringing its cumulative funding to 4.3 billion yuan — a record for both a single round and total funding in China's AI infrastructure sector, according to multiple outlets. Founded in 2023 and incubated by the Tsinghua University electronics department's NICS-EFC lab, the company avoids building chips or training foundation models, instead working on heterogeneous compute scheduling and hardware-software co-optimization, and says its platform reaches 37,000P of compute across 16 mainstream chip types. It says daily token calls on its Agentic MaaS platform grew 40-fold from December, and that its cross-cluster heterogeneous PDD architecture cut first-token latency by 51.5% while reducing per-token cost by 37.5%; Bloomberg, citing people familiar with the matter, reported the company filed confidentially for a Hong Kong IPO.
智东西 · 🔥 0
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