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#Industry news

All collected and published items, ordered by time. Picks are a selected subset.
Opinion

Viewpoints, commentary, analysis, interviews, and discussion of trends.

10/16Fri
  1. 量子位28

    How Antai MBA Is Training Future Business Leaders for the AI Era

    Shanghai Jiao Tong University Antai College of Economics and Management is reshaping its MBA education to prepare business leaders who can combine technical understanding with business judgment and responsibility. Its “Five Links” talent framework connects AI, science and technology innovation, industry, global perspectives, and Shanghai Jiao Tong University resources. The college also plans to co-create 1,000 AI projects with companies over the next decade and has announced curriculum and training changes for the 2027 cohort.

10/11Sun
  1. The Decoder36

    Nadella Adopts Trump's "Super Intelligence" Term, Attacks OpenAI and Anthropic

    Microsoft CEO Satya Nadella used "Super Intelligence" instead of "Artificial Intelligence" in a new blog post, echoing President Trump's preferred terminology. Nadella argued AI models should be treated like insider security threats, calling for model diversity, complete logging, independent auditing and human shutdown ability, while criticizing Anthropic and OpenAI. The Decoder reports the rebranding breaks with decades of scientific meaning and that Nadella's arguments serve Microsoft's business strategy.

10/10Sat
  1. 雷锋网30

    NIO's Li Bin Says AI Is Driving Up Car Costs as NIO's Average Selling Price Tops BBA

    NIO founder and CEO Li Bin told Leiphone that AI data centers are competing with automakers for memory, PCB, copper, aluminum and battery resources, creating "diseconomies of scale" where higher volumes can raise costs. NIO's Q2 per-vehicle cost rose 14,000 yuan from the end of last year, adding about 1.5 billion yuan in quarterly costs. NIO's Q2 average transaction price reached 406,000 yuan, about 180,000 yuan above Audi.

10/9Fri
10/8Thu
  1. 雷锋网22

    Li Yuan of Benewake: making eyes for machines, and eleven years of choosing the hard path

    Benewake founder Li Yuan has spent eleven years building lidar for drones, trains, cars, and robots. In the first half of this year, Benewake delivered 250,000 lidar units for robots; robotics accounted for more than half of company revenue, and 2025 robotics revenue doubled from 2024. Li believes measurements such as distance and position from lidar should become learning material that helps machines understand the physical world.

  2. 雷锋网34

    What I know about Zhang Lei: an MSRA algorithm race and half the Chinese AI scene

    In 2002, Microsoft Research Asia held an internal competition for face-detection algorithms. Zhang Lei, less than two years out of his PhD, led interns Xiao Rong, Zhu Long, Chen Longbin, and others in reducing the false-positive rate from 'one false alarm for every positive' to 1% in three months, beating the team of face-recognition expert Li Ziqing. Their approach was eventually integrated into Windows. During 20 years at Microsoft, Zhang also built a celebrity-recognition system that could identify 200,000 people with 99% accuracy and released the MS Celeb dataset. OpenAI later drew on its image-text matching approach when training the 400-million-example CLIP model.

10/4Sun
  1. 量子位36

    The hottest AI job is FDE: monthly pay of ¥50,000, with Anthropic, OpenAI, and AWS competing for talent

    The Forward Deployed Engineer (FDE) has become the hottest AI role. Public salary data overseas show a median of about $200,000, while major Chinese companies are offering monthly salaries of ¥30,000–¥50,000. Anthropic announced a $100 million investment to train 10,000 FDEs by the end of 2027. OpenAI formed a deployment company with $4 billion in investment, and AWS set aside $1 billion to build an FDE division. Practitioners say communicating requirements takes more than 70% of the job, with development accounting for only 30%.

10/3Sat
6/1Mon
  1. Import AI26

    Import AI 459: why AI regulation is hard, scaling laws for protein-folding models, and pricing extinction risk from AI systems

    Import AI 459 discusses the difficulty of AI regulation, scaling laws for protein-folding models, and how to price extinction risks from AI systems. Economists at the University of Virginia, Anthropic, and the Bank of Canada estimate that nominal U.S. AI GDP was about $250 billion in 2025, with quality-adjusted real annual growth of about 2,600%. U.S. AI compute spending rose from $37 billion in 2023 to $219 billion in 2025, while compute capacity grew by more than 200% annually.