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All news · Today8 items

#Expert views

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

  2. 雷锋网28

    IROS 2026 keynote: more data does not mean better robot decisions

    At IROS 2026, University of Queensland researcher Jen Jen Chung argued in a keynote that data volume is not the same as information, and that blindly piling up data can degrade robot policies. Drawing on drone soaring, multi-robot communication and contact-rich assembly work, she said data value is unevenly distributed and that sharing or collecting only decision-changing information beats full broadcasts or uniform sampling.

  4. Nathan Lambert · X28

    I’m more bought into AI becoming far more efficient, which is a massive lever on diffusion, than I am on AI models making massive breakthroughs that result in eliminating all the known weaknesses of LLMs. Happily spending a few hours reflecting on RSI after a great SF week.

    I’m more bought into AI becoming far more efficient, which is a massive lever on diffusion, than I am on AI models making massive breakthroughs that result in eliminating all the known weaknesses of LLMs. Happily spending a few hours reflecting on RSI after a great SF week.

  5. François Chollet · X43

    François Chollet Says Science Offers a Reference Point for AI RSI

    François Chollet argues that science is a recursively self-improving system and a useful reference point for understanding AI RSI. He says scientific inputs—including headcount, R&D spending, and compute—have grown exponentially, while scientific impact has remained roughly linear because research tackles the easiest, highest-impact problems first. Chollet believes AI RSI is already happening and will accelerate, but says it will not lead to an “intelligence explosion.”

  6. TechCrunch · AI40

    a16z Partner Olivia Moore Discusses the State of Consumer AI: ChatGPT Still Far Ahead, Six Major Categories Still Blank

    a16z partner Olivia Moore has released a Top 100 consumer AI apps report. ChatGPT remains the biggest player, while smaller players like Suno and ElevenLabs show lasting vitality. The report notes that categories such as social, dating, marketplaces, retail, travel, finance, and health have no products on the Top 100 list. Moore believes consumer AI is still in its early days, and the opportunity lies in moving beyond subscriptions and API charges to explore more monetization methods such as advertising.

10/9Fri
  1. Simon Willison22

    Matthew Green: Public-key cryptography may face a crisis of confidence under the impact of AI

    Cryptographer Matthew Green says there is a 1% chance we live in a Minicrypt world where public-key cryptography is impossible, and a 15% chance we will substantially lose confidence in existing public-key cryptographic algorithms. He points out that the speed at which AI creates surprises and the speed at which humans update standards differ by several orders of magnitude, and only by preparing in advance can we recover from such shocks.

  5. OpenAI Developers · X11

    OpenAI Developer Finds Dishwashing Details “a Little Concerning”

    @jomatech introduces “ChatGPT for Dishwashing” and says GPT-6 achieves state-of-the-art results on dishwashing benchmarks for long-running jobs and difficult stains. The post also describes the Navier–Stokes Millennium Prize Problem as a $1 million challenge about whether the equations describing fluid motion can break. OpenAI Developers says, “The attention to detail is a little concerning.” https://t.co/UOfOtusB9q

  8. Kevin Weil · X24

    "The invention of the boat reduced the importance of swimming, but enabled the discovery of new lands." Beautiful analogy from @ylecun about the opportunities and changes with AI, in mathematics and in science more broadly.

    "The invention of the boat reduced the importance of swimming, but enabled the discovery of new lands." Beautiful analogy from @ylecun about the opportunities and changes with AI, in mathematics and in science more broadly.

  11. Latent Space36

    Periodic Labs' Liam Fedus and Ekin Dogus Cubuk on "synthesis superintelligence": from semiconductors to superconductors

    In an interview, Periodic Labs' Liam Fedus and Ekin Dogus Cubuk proposed a "synthesis superintelligence" approach: reinforcement learning in physical experiments, AI-driven materials characterization, density functional theory (DFT), and high-throughput labs. The aim is for models to learn the full process of doing science, rather than only studying published results.

10/8Thu
  2. Satya Nadella · X47

    Satya Nadella Envisions Copilot as an “Infinite SaaS Factory”

    Satya Nadella says Microsoft aims to make Copilot a new operating system for work, connecting agents with business context, workflows, and systems of record. Microsoft announced 30+ new Copilot skills across Dynamics 365 Sales, Service, and Customer Insights, and introduced Copilot Managed Runtime for code hosted in a company’s environment under IT governance. Nadella describes a future where people can use Copilot’s Code experience to customize or build software connected to their existing business systems.

  3. Clément Delangue · X34

    We urgently need more public traces of AI agents attacking and defending systems. Defenders can’t learn from what they can’t see. If you have traces and are being pressured to keep them private, my DMs are open. Let’s level the playing field and fight the asymmetry and lack of transparency in AI!

    We urgently need more public traces of AI agents attacking and defending systems. Defenders can’t learn from what they can’t see. If you have traces and are being pressured to keep them private, my DMs are open. Let’s level the playing field and fight the asymmetry and lack of transparency in AI!

  4. 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.

  5. 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.

  6. 雷锋网32

    Dialogue with ONTIME Mobility COO Han Feng: The stronger the world model, the more real data becomes the true moat

    ONTIME Mobility COO Han Feng believes that as world model capabilities grow stronger, the importance of real data will not diminish: synthetic data is responsible for expanding known long-tail scenarios, while real data is responsible for discovering unknown problems and providing calibration and validation. ONTIME Mobility does not train large models; instead, it collects real data through routine mobility services, Robotaxi, and offline operations and maintenance networks, and delivers training materials to autonomous driving, world model, and embodied intelligence companies through a data closed loop.

  8. Simon Willison12

    Ben Affleck discusses machine learning and visual-effects workflows

    Ben Affleck said he became more interested in technology after moving from film to digital and can write 'pretty terrible Python scripts', since visual-effects workflows have included machine learning for years. He described convolutional neural networks as predecessors to transformers that process tensors and perform edge detection and feature extraction, making it easier to isolate green-screen footage and replace the background.

  10. Noam Brown · X62

    Noam Brown says LLMs surpass top human experts on some research problems

    Noam Brown argues that LLMs have crossed an important threshold by surpassing top human experts on some research problems, with the gap between slightly below and slightly above expert performance helping explain the seemingly sudden surge in math results. He emphasizes that capabilities remain jagged and models are still worse than humans in many ways, but expects continued improvements to bring breakthroughs in other domains and a new era of scientific discovery.

10/7Wed
  2. Jim Fan · X27

    It is increasingly clear that humanity will solve the Riemann hypothesis before we pass the Physical Turing Test - you come back to a clean home after a wild Sunday party, and you can't tell whether a human or a robot did the job. We are not Moravec's paradox-pilled enough.

    It is increasingly clear that humanity will solve the Riemann hypothesis before we pass the Physical Turing Test - you come back to a clean home after a wild Sunday party, and you can't tell whether a human or a robot did the job. We are not Moravec's paradox-pilled enough.

  4. Kevin Weil · X50

    Kevin Weil praises OpenAI’s mathematics release and anticipates progress in physical sciences

    Kevin Weil celebrates OpenAI’s mathematics release today, saying much work remains to get models of the same caliber in the physical sciences. He urges imagining the possibilities and expresses confidence that models will get there. In the quoted post, @willdepue says he asked GPT 6 Pro and Fable 5.1 to rank discoveries from the last three years by human or AI origin, reporting that 81% were released today.

  5. The Decoder38

    Microsoft publishes Nobel economist Daron Acemoglu's bearish AI forecast: just 1.5% GDP growth over a decade

    Microsoft published Nobel Prize-winning economist Daron Acemoglu's pessimistic forecast: AI will add only about 1.5% to GDP over a decade and replace at most 5% of jobs, far below some AI labs' expectations. He says the bottleneck is human behavior: companies need to reallocate tasks, upskill employees, and reorganize processes, a transition that may take longer than electrification and cannot be solved by larger models. What is missing, he argues, is AI that is easy to deploy and changes how production works.

  6. Microsoft Research22

    Microsoft Research: why AI evaluations can fail unexpectedly outside traditional benchmarks

    Jennifer Neville of Microsoft says models can fail unexpectedly when tested beyond traditional benchmarks. Evaluation is essential to pushing the performance boundaries of current AI systems and aligning them with user needs. She recommends paying close attention to data when using AI systems, since the data itself is often the first thing to examine when results differ from expectations.

10/6Tue
  1. Mustafa Suleyman · X51

    Daron Acemoglu predicts AI will replace only about 5% of human work in 10 years

    Mustafa Suleyman summarizes Daron Acemoglu’s essay in the first issue of The Humanist Review, MAI’s new magazine, predicting AI will replace only about 5% of what humans do over 10 years. Acemoglu expects roughly 1.5% added to GDP over that period and advocates AI tools that improve workers’ capabilities, citing organizational barriers to adoption and the difficulty of full automation even at 99% accuracy. Read his full essay: https://humanistreview.ai/issue-1/acemoglu-ai-replace-workers/

  3. The Verge · AI48

    Sam Altman says AI is worth the price of 'some bad things'

    OpenAI CEO Sam Altman said on Politico's Decoded podcast that AI's benefits will be so great that 'the world should accept some bad things happening', including hacking and scams, because people can use AI to do 'orders of magnitude more good things'. He described this tradeoff as a key difference between OpenAI and Anthropic, positioning OpenAI as the 'pragmatic middle' between them, while acknowledging extreme risks such as humans losing control of AI systems.

10/5Mon
  1. The Verge · AI28

    Senator Adam Schiff on AI regulation, free speech, and impeaching Trump again

    California Democratic Senator Adam Schiff criticized the Trump administration for gathering AI CEOs to sign nonbinding AI safety commitments, saying they do not address real national-security threats. He supports creating a new AI regulator and noted that Anthropic faced government pressure after refusing to use AI for domestic mass surveillance and fully autonomous weapons.