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Wednesday

  1. Story1 reports · 1 facts

    Google releases world model Genie 4

    On October 27, 2026, Google DeepMind released the world model Genie 4, focused on real-time interactive simulation and introducing native audio to the series for the first time. According to the official introduction, the model is built on capabilities from the Gemini family: Gemini Omni is responsible for making the simulation match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain the simulation's coherence; users can control scenes in real time using natural language, and each world also instantly generates ambient sound, music, and interactive dialogue. The next day, Google DeepMind further explained that Gemini 3.8 Flash breaks down goals in a loop and checks frames to maintain causal coherence across multi-step events, and that Gemini 4 Argon has also been used to jointly simulate tasks with Gemini Robotics; the company said it remains an early experimental model, that object permanence and complex physical interactions still drift during long runs, that all generated content carries a SynthID watermark, and that it is currently being previewed to trusted testers first. On October 28, Ethan Mollick posted that Genie 4 can run DOOM, and tested it generating a game-like environment as it goes, saying the experience is not perfect. On October 29, Peter Yang used Genie 4 to build 5 worlds in real time, arguing that world models are the next big direction for AI after LLMs.

    On October 27, 2026, Google DeepMind released the world model Genie 4, focused on real-time interactive simulation and introducing native audio to the series for the first time. According to the official introduction, the model is built on capabilities from the Gemini family: Gemini Omni is responsible for making the simulation match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain the simulation's coherence; users can cont

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Friday

  1. Story1 reports · 1 facts

    The Institute for Advanced Study in Mathematics of Zhejiang University and Zhijiang Laboratory launch the Future Mathematics Program

    On October 30, 2026, ScienceNet published an interview report mentioning that the Institute for Advanced Study in Mathematics of Zhejiang University and Zhijiang Laboratory jointly launched the Future Mathematics Program. The report stated that the program focuses on four areas: mathematical foundation models, formal verification, AI mathematical mechanisms, and interdisciplinary empowerment. Li Jianshu, an academician of the Chinese Academy of Sciences, said in the report that AI may change the paradigm of mathematical research, and pointed out that mathematics has done far from enough for AI; Wang Jian, an academician of the Chinese Academy of Engineering, believes that AI's reasoning ability currently comes mainly from code, and that learning deeper reasoning from mathematical data will bring greater gains. The report also mentioned that Google DeepMind's AI agent solved 9 previously unsolved Erdős problems and tackled 44 open mathematical conjectures in May this year, and that OpenAI recently published 722 mathematical manuscripts generated by its internal AI models on GitHub, while 25 Fields Medalists including Terence Tao and Deng Yu jointly issued an open letter warning of a serious misalignment between AI and mathematics. Currently, no further progress on the program has been disclosed.

    AI's reasoning ability currently comes mainly from code, and that learning deeper reasoning from mathematical data will bring greater gains. The report also mentioned that Google DeepMind's AI agent solved 9 previously unsolved Erdős problems and tackled 44 open mathematical conjectures in May this year, and that OpenAI recently published 722 mathematical manuscripts generated by its internal AI models on GitHub, while 25 Fields Medalists including Terence Tao and Deng Yu jointly issued an open

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  2. Latent Space

    Latent Space announces AIE CODE coding agent conference curation themes

    Latent Space host swyx introduces the curation approach for the annual flagship conference AIE CODE, which is single-track, invitation-only, and aimed at about 1,000 agent engineers. This year's three themes are Scaling without Slop, System One models, and Increasing Ambition, among which Jarred Sumner will share Bun's rewrite in Rust and a Bun AOT preview. The article also rounds up that day's AI news, including Mistral's open-weight release and OpenAI's frontier model monitoring.

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    #newsletter#Industry news#Agents#English text is being prepared.
  3. TMTPost · AGI

    ByteDance World Model Exposed: Zhang Yiming's Strategy and Its Divergence from Google Genie 4's Approach

    A TMTPost article states that ByteDance has listed world models as one of its four major AI priorities for 2026, with the goal of releasing at least one version by the end of the year, benchmarked against Google Genie 3, and that users can enter cloud-generated worlds via Pico headsets using voice and motion. The article also reviews Google Genie 4, released on October 28, which supports real-time changes to weather, camera movement, and the introduction of characters using natural language, and adds sound for the first time. The article also mentions that ByteDance's internal evaluations show its world model's overall performance is about 10% behind the then-current global SOTA, with generation metrics at about 20fps.

    A TMTPost article states that ByteDance has listed world models as one of its four major AI priorities for 2026, with the goal of releasing at least one version by the end of the year, benchmarked against Google Genie 3, and that users can enter cloud-generated worlds via Pico headsets using voice and motion. The article also reviews Google Genie 4, released on October 28, which supports real-time changes to weather, camera movement, and the introduction of characters using natural language, and

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    #hot-signal#Industry news#Multimodal#Video
  4. TMTPost · AGI

    Microsoft, Google, and Amazon Earnings Side by Side: The AI Infrastructure Race Reaches a Watershed

    The latest earnings reports from the three cloud providers Microsoft, Google, and Amazon show cloud businesses accelerating across the board: AWS third-quarter revenue was $45.98 billion, up 39.3% year over year; Azure posted $33.165 billion for the quarter, up 48%; Google Cloud revenue was $30.71 billion, more than doubling year over year; and their backlogs reached $578 billion, $677 billion, and $561 billion, respectively. Over the same period, all three posted negative free cash flow: Amazon had a net outflow of $42.36 billion over the past 12 months, Alphabet was negative $9.07 billion, and Meta had a net outflow of $2.12 billion, while only Microsoft remained positive at $18.6 billion. Market reactions diverged; Alphabet fell 12.64% in a single day on slowing advertising growth and its swing to negative cash flow, and the article argues that the competitive bottleneck is shifting from chips to power, land, and grid-connection approvals.

    The latest earnings reports from the three cloud providers Microsoft, Google, and Amazon show cloud businesses accelerating across the board: AWS third-quarter revenue was $45.98 billion, up 39.3% year over year; Azure posted $33.165 billion for the quarter, up 48%; Google Cloud revenue was $30.71 billion, more than doubling year over year; and their backlogs reached $578 billion, $677 billion, and $561 billion, respectively. Over the same period, all three posted negative free cash flow: Amazon

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    #hot-signal#Industry news#English text is being prepared.#English text is being prepared.

Wednesday

Friday

Sunday

  4. Story1 reports · 0 facts

    Google releases Gemini 3.5 Flash

    On May 19, 2026, Google DeepMind released the Gemini 3.5 series, debuting the Gemini 3.5 Flash model first. According to its introduction, the model scored 76.2% on Terminal-Bench 2.1, outputs at 4 times the speed of other frontier models, has been fully opened up, and has become the default model for the Gemini app and AI Mode in global Search; Gemini 3.5 Pro is planned for launch next month. On May 20, Google's Noam Shazeer said that Gemini 3.5's combination of performance and speed makes it suitable for long-horizon and agentic tasks. On the same day, separate reports said that Gemini Spark, a 24/7 personal AI agent powered by Gemini 3.5, can work across apps such as Docs, Calendar, and Slides, and keeps running after the computer is turned off, with rollout starting next week.

    On May 19, 2026, Google DeepMind released the Gemini 3.5 series, debuting the Gemini 3.5 Flash model first. According to its introduction, the model scored 76.2% on Terminal-Bench 2.1, outputs at 4 times the speed of other frontier models, has been fully opened up, and has become the default model for the Gemini app and AI Mode in global Search; Gemini 3.5 Pro is planned for launch next month. On May 20, Google's Noam Shazeer said that Gemini 3.5's combination of performance and speed makes it s

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Tuesday

Thursday

  1. The Verge AI

    SemiAnalysis Analyst Interprets Anthropic S-1: The Ledger Behind the Valuation and AGI Narrative

    The Verge's Decoder podcast invited SemiAnalysis analyst Joey Brookhart to break down the S-1 filed by Anthropic, discussing its potential Nasdaq listing at a valuation of $1.5 trillion to $2 trillion. Brookhart said Anthropic has achieved over $70 billion in ARR, with inference gross margins turning from negative 94% two years ago to positive 85%, and revenue per megawatt of inference at about $65 million, but revenue is highly concentrated in coding scenarios, and about 70% of compute is used for training and research. He also mentioned that Anthropic has $500 billion to $600 billion in compute commitments over the next 7 to 10 years, and compared OpenAI's more consumer-oriented business structure.

    The Verge's Decoder podcast invited SemiAnalysis analyst Joey Brookhart to break down the S-1 filed by Anthropic, discussing its potential Nasdaq listing at a valuation of $1.5 trillion to $2 trillion. Brookhart said Anthropic has achieved over $70 billion in ARR, with inference gross margins turning from negative 94% two years ago to positive 85%, and revenue per megawatt of inference at about $65 million, but revenue is highly concentrated in coding scenarios, and about 70% of compute is used

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    #tech-media#Industry news#Anthropic#OpenAI

Saturday

  1. Cailianshe

    AI-driven cyberattacks erupt intensively; industry insiders call October a "Black October" for cybersecurity

    Cailianshe reported that in recent weeks hackers have massively deployed AI agents and automated tools to launch attacks, and industry insiders describe this month as Black October in the cybersecurity world. A major vulnerability was exposed in PHP, and as many as 70% of websites worldwide may face the risk of being hacked. The U.S. National Security Agency and the FBI warned enterprises to shut down their websites if they cannot patch immediately, and some government websites in Canada, Belgium, France and the Netherlands have proactively gone offline. Shane Fry, chief technology officer of security firm RunSafe Security, said AI can weaponize a vulnerability into attack code within hours, whereas in the past this took weeks or even months.

    Cailianshe reported that in recent weeks hackers have massively deployed AI agents and automated tools to launch attacks, and industry insiders describe this month as Black October in the cybersecurity world. A major vulnerability was exposed in PHP, and as many as 70% of websites worldwide may face the risk of being hacked. The U.S. National Security Agency and the FBI warned enterprises to shut down their websites if they cannot patch immediately, and some government websites in Canada, Belgiu

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    #chinese#English text is being prepared.#Safety / alignment#Agents
  2. Shao Meng

    Claude engineering lead Felix on how to use Claude: fewer role-based Agents, use adversarial review to constrain output

    In an interview, Claude engineering lead Felix Rieseberg said he barely writes code anymore; his core approach is to hand crash data, business tools, and a computer to the model and let it decide what to fix itself, rather than having a human act as a relay repeating things item by item. He suggests opening multiple threads on the same output dedicated to proving it wrong, then opening another as a judge to filter which criticisms hold up; rather than giving each Agent a tiny slice of data, it is better to give a panoramic business view and well-documented tools. He also mentioned that the half-life of Skills is extremely short, that both official guidance and his own advice are to use them cautiously, and that self-evaluation within the same session remains unreliable, so external signals should be sought as much as possible.

    In an interview, Claude engineering lead Felix Rieseberg said he barely writes code anymore; his core approach is to hand crash data, business tools, and a computer to the model and let it decide what to fix itself, rather than having a human act as a relay repeating things item by item. He suggests opening multiple threads on the same output dedicated to proving it wrong, then opening another as a judge to filter which criticisms hold up; rather than giving each Agent a tiny slice of data, it i

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    #hot-signal#English text is being prepared.#Agents#English text is being prepared.

Friday

  1. TMTPost · AGI

    Pichai Reviews Gemini 4 Argon: Why 3.5 Pro Was Cut

    Google CEO Pichai revealed in the "Sources" interview that Gemini 4 Argon processed about 25 trillion tokens in 72 hours of launch, 3 times that of Gemini 3.0 in the same period, and is still rate-limited due to compute constraints. He explained for the first time the reason for cutting Gemini 3.5 Pro: the team found a gap in the model on Agentic Coding, first used the Flash version to complete intensive iterations from 3.5 to 3.8 in about 3 months, while Argon pretraining had already been completed at that time, so they injected the accumulated gains into Argon post-training. He also mentioned that Google internally has entered the RSI stage of researchers and models collaborating, and said the next-generation Gemini 5.0 will be much stronger than Argon.

    Google CEO Pichai revealed in the "Sources" interview that Gemini 4 Argon processed about 25 trillion tokens in 72 hours of launch, 3 times that of Gemini 3.0 in the same period, and is still rate-limited due to compute constraints. He explained for the first time the reason for cutting Gemini 3.5 Pro: the team found a gap in the model on Agentic Coding, first used the Flash version to complete intensive iterations from 3.5 to 3.8 in about 3 months, while Argon pretraining had already been compl

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    #hot-signal#Industry news#Google#DeepMind

Tuesday

Sunday