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Friday

  1. TMTPost · AGI

    A Brief History of Claude Account Bans: Anthropic's Three Years of Bans and the Cat-and-Mouse Game with Chinese Users

    Anthropic's IPO prospectus discloses that in the first nine months of 2026, approximately 5% to 7% of revenue came from customers later determined to have violated usage policies, amounting to $1.65 billion to $2.31 billion based on roughly $33 billion in revenue for the first three quarters. In the first half of 2026, Anthropic banned 11.4 million accounts, averaging about 63,000 per day, nearly 8 times the figure for the second half of 2025; during the same period, only 42,000 of 398,000 appeals overturned the original penalties, a rate of about 10.6%. Claude has not yet opened to mainland China, but it already supports simplified and traditional Chinese interfaces, and a UnionPay option once appeared on the payment page.

    Anthropic's IPO prospectus discloses that in the first nine months of 2026, approximately 5% to 7% of revenue came from customers later determined to have violated usage policies, amounting to $1.65 billion to $2.31 billion based on roughly $33 billion in revenue for the first three quarters. In the first half of 2026, Anthropic banned 11.4 million accounts, averaging about 63,000 per day, nearly 8 times the figure for the second half of 2025; during the same period, only 42,000 of 398,000 appea

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    #hot-signal#English text is being prepared.#Anthropic#Safety / alignment
  2. TMTPost · AGI

    What happened in the embodied intelligence industry 50 days after the release of GPT-6 Astra

    TMTPost's Digital Intelligence Frontier reviewed the impact on the embodied intelligence industry in the roughly 50 days since OpenAI released GPT-6 Astra: Astra can directly control a robotic arm to complete tasks such as drawing a bridge without training on specialized robot data, and Nvidia's Jim Fan said it pushed the benchmark of his company's robotics framework to about 99%. However, an evaluation by SenseTime together with multiple institutions concluded that while it already has the ability to complete embodied tasks, there is still a clear gap before practical use: a single inference takes an average of 18.56 seconds, and the task of putting a pen into a pen holder took more than 4 hours and cost 55 US dollars. Three usage patterns have emerged in the industry: directly serving as a policy model, reviewing and correcting VLA actions, and building simulation environments and data annotation; Unitree's Wang Xingxing said that next year GPT-7 may directly break through the embodied intelligence problem.

    TMTPost's Digital Intelligence Frontier reviewed the impact on the embodied intelligence industry in the roughly 50 days since OpenAI released GPT-6 Astra: Astra can directly control a robotic arm to complete tasks such as drawing a bridge without training on specialized robot data, and Nvidia's Jim Fan said it pushed the benchmark of his company's robotics framework to about 99%. However, an evaluation by SenseTime together with multiple institutions concluded that while it already has the abil

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    #hot-signal#English text is being prepared.#Embodied AI#OpenAI
  3. TMTPost · AGI

    Anthropic Races Toward a Trillion-Dollar Valuation While Zhipu Focuses on API Gross Margin: A Comparison of the Commercialization Paths of Chinese and U.S. Large-Model Companies

    TMTPost's Large Model Home compared Anthropic's prospectus with Zhipu's interim report, pointing out that Chinese and U.S. large-model companies are taking two different commercialization paths. In the first half of the year, Anthropic reported revenue of $16.29 billion and a net loss of $80.7 billion, of which $72.4 billion came from fair value losses on convertible notes caused by rising valuations, while its operating loss narrowed to $693 million; Zhipu reported revenue of 954 million yuan and a loss of 2.072 billion yuan in the first half, with its API business gross margin turning positive for the first time, reaching 24.6%. The article also mentioned that Anthropic's computing power procurement commitments over the next decade amount to $518 billion, about 80% of which is non-cancelable, while Zhipu's per-token inference cost dropped by 80% compared with the beginning of the year.

    TMTPost's Large Model Home compared Anthropic's prospectus with Zhipu's interim report, pointing out that Chinese and U.S. large-model companies are taking two different commercialization paths. In the first half of the year, Anthropic reported revenue of $16.29 billion and a net loss of $80.7 billion, of which $72.4 billion came from fair value losses on convertible notes caused by rising valuations, while its operating loss narrowed to $693 million; Zhipu reported revenue of 954 million yuan a

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    #hot-signal#Industry news#English text is being prepared.#DeepSeek
  4. IT Home · Artificial Intelligence

    Baidu Group Vice President Wu Tian Resigns; Sources Say ERNIE Model Will Have New Developments Next Week

    A Baidu PR manager confirmed that Group Vice President and Baidu Research Institute Deputy Director Wu Tian has ended her tenure at Baidu. Sources say the ERNIE model will have new developments to be announced publicly next week. Wu Tian worked at Baidu for about 20 years and was one of the early principal technical leads of the ERNIE Bot model. She served as head of the Foundation Model R&D Department starting in November 2025, and in May this year transferred to serve as Deputy Director of the Baidu Research Institute. The Baidu World 2026 conference is scheduled to be held on November 12, where ERNIE Unlimited OCR 2 will be showcased and the latest upgrade achievements of the "Chip-Cloud-Model-Agent" full-stack AI will be released.

    A Baidu PR manager confirmed that Group Vice President and Baidu Research Institute Deputy Director Wu Tian has ended her tenure at Baidu. Sources say the ERNIE model will have new developments to be announced publicly next week. Wu Tian worked at Baidu for about 20 years and was one of the early principal technical leads of the ERNIE Bot model. She served as head of the Foundation Model R&D Department starting in November 2025, and in May this year transferred to serve as Deputy Director of the

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    #analysis#Industry news#OpenAI
  5. Phoenix Technology

    01.AI Secures Hundreds of Millions in Funding, Headquarters to Land in Hangzhou's Linping District

    01.AI has reached a cooperation agreement with Hangzhou City and Linping District, with state-owned capital from the city and district levels jointly investing hundreds of millions of yuan. The headquarters will be located in Linping District, Hangzhou, where an industrial AI transformation base will be built. 01.AI has shifted from large model R&D to enterprise industrial AI implementation, with a product system covering foundation models, enterprise Ontology, and multi-agent applications, and has launched agents such as Boss AI, Top Sales AI, and Investment Officer AI. Hangzhou will provide local industrial scenario resources, and the two sides plan to implement AI projects in scenarios including business management, production operations, and supply chain collaboration.

    01.AI has reached a cooperation agreement with Hangzhou City and Linping District, with state-owned capital from the city and district levels jointly investing hundreds of millions of yuan. The headquarters will be located in Linping District, Hangzhou, where an industrial AI transformation base will be built. 01.AI has shifted from large model R&D to enterprise industrial AI implementation, with a product system covering foundation models, enterprise Ontology, and multi-agent applications, and

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    #chinese#Industry news#Agents
  6. t3nSelected

    Google releases Gemini 4 Carbon, just two weeks after Argon

    Google has released Gemini 4 Carbon, just two weeks after the release of the previous-generation frontier model Gemini 4 Argon. According to Google, Carbon surpassed Anthropic's Claude Opus 5.5 to take first place on Artificial Analysis's Intelligence Index, while Argon had previously ranked only sixth. Carbon mainly improves complex coding tasks and cybersecurity capabilities, scoring 88.2% on SEC-bench Pro, higher than Argon's 83.4% and OpenAI GPT-6 Astra's 85.4%; however, it still trails Claude Opus 5.5 on the Coding Agent Index, Terminal-Bench, and Frontiercode. Currently, Carbon is available only to selected users such as cybersecurity defense experts, and will be opened to developers, enterprises, and consumers only after passing the U.S. government's voluntary pre-review process.

    Google has released Gemini 4 Carbon, just two weeks after the release of the previous-generation frontier model Gemini 4 Argon. According to Google, Carbon surpassed Anthropic's Claude Opus 5.5 to take first place on Artificial Analysis's Intelligence Index, while Argon had previously ranked only sixth. Carbon mainly improves complex coding tasks and cybersecurity capabilities, scoring 88.2% on SEC-bench Pro, higher than Argon's 83.4% and OpenAI GPT-6 Astra's 85.4%; however, it still trails Clau

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    #hot-signal#Model releases#Google#Reasoning

Thursday

  1. The New Stack

    Mistral Open-Sources Mistral Large 4 Weights, Leading GLM-5.3 by 1 Point on Coding Benchmark

    Mistral released the weights of its frontier open-source model Mistral Large 4 (ML4) on Hugging Face on Thursday; the model had only been available in preview three weeks earlier. Mistral calls ML4 "the world's best open-source agentic coding model," scoring 41% on Terminal-Bench 4.0, slightly above GLM-5.3's 40%, and says it uses an average of 47% fewer tokens per task than GLM-5.3; it scored 79% on the CyberGym E2E defensive cybersecurity test, compared with 29% for GLM-5.3. Mistral Vice President of Science Pierre Stock called ML4 merely a "stepping stone" and confirmed that smaller versions will be released in the coming months, one of which can run on a laptop.

    Mistral released the weights of its frontier open-source model Mistral Large 4 (ML4) on Hugging Face on Thursday; the model had only been available in preview three weeks earlier. Mistral calls ML4 "the world's best open-source agentic coding model," scoring 41% on Terminal-Bench 4.0, slightly above GLM-5.3's 40%, and says it uses an average of 47% fewer tokens per task than GLM-5.3; it scored 79% on the CyberGym E2E defensive cybersecurity test, compared with 29% for GLM-5.3. Mistral Vice Presi

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    #hot-signal#Model releases#Open-source ecosystem#English text is being prepared.
  2. AI Business

    Chinese Open Source Models Enter the Enterprise: Red Hat Uses GLM to Handle 70% of Inference Traffic

    AI Business reported that, in the week ending October 25, Chinese models accounted for more than half of the token statistics on OpenRouter, whereas about a year ago only one of the nine models on the site's weekly usage list came from China. Red Hat is internally piloting self-hosted GLM, used by up to 1,400 engineers, with about 70% of inference traffic going to open source models, and it controls costs with a frontier model quota of $300 per person per month. DataCamp, due to latency and insufficient capacity from open source model providers, is shifting from Anthropic to OpenAI and has not yet moved its AI tutor to open source models.

    AI Business reported that, in the week ending October 25, Chinese models accounted for more than half of the token statistics on OpenRouter, whereas about a year ago only one of the nine models on the site's weekly usage list came from China. Red Hat is internally piloting self-hosted GLM, used by up to 1,400 engineers, with about 70% of inference traffic going to open source models, and it controls costs with a frontier model quota of $300 per person per month. DataCamp, due to latency and insu

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    #hot-signal#English text is being prepared.#Open-source ecosystem#English text is being prepared.
  3. Numerama

    Mistral Large 4 open-weight release: improved coding and safety capabilities, API price halved

    Mistral AI released the open weights of Mistral Large 4 (codename Le Chonk) on Hugging Face on October 29. The model has 100 billion parameters out of a total parameter scale of the 100-billion class, with about 4.9 billion parameters actually invoked per token, using a MoE architecture with 128 experts, of which 4 are activated each time plus 1 shared expert. Compared with the October 6 preview version, Mistral says it continued reinforcement learning over three weeks, raising the Terminal-Bench 4.0 score from 28% to 41%; the Artificial Analysis coding index is 48%, on par with GLM-5.3 while using an average of 47% fewer tokens per task. API pricing drops to $0.70 per million input tokens and $2.10 per million output tokens; the new Mistral Ecosystem Open-Weight License permits commercial use, but reselling model services requires a separate agreement, and the full version requires 8 Nvidia B200 or B300 GPUs.

    Mistral AI released the open weights of Mistral Large 4 (codename Le Chonk) on Hugging Face on October 29. The model has 100 billion parameters out of a total parameter scale of the 100-billion class, with about 4.9 billion parameters actually invoked per token, using a MoE architecture with 128 experts, of which 4 are activated each time plus 1 shared expert. Compared with the October 6 preview version, Mistral says it continued reinforcement learning over three weeks, raising the Terminal-Benc

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    #hot-signal#Model releases#Open-source ecosystem#Hugging Face
  4. ChinaTalk

    A Conversation with "Burying AI" Author Xianyu: How to Roast China's AI Industry

    ChinaTalk talks with "Burying AI" author Xianyu about how he satirizes China's AI industry from a subcultural perspective. Xianyu says that since the second half of 2025 he has completely stopped using AI for writing, because while mainstream models' coding abilities have improved, the originality of their writing has clearly declined. He also built a website that lets ordinary people rank video models by their meme proficiency, and he disagrees with the host over which side, China or the US, has more severe hype.

    ChinaTalk talks with "Burying AI" author Xianyu about how he satirizes China's AI industry from a subcultural perspective. Xianyu says that since the second half of 2025 he has completely stopped using AI for writing, because while mainstream models' coding abilities have improved, the originality of their writing has clearly declined. He also built a website that lets ordinary people rank video models by their meme proficiency, and he disagrees with the host over which side, China or the US, ha

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    #analysis#Industry news#Evaluations / benchmarks#Video
  5. Latent SpaceSelected

    Google DeepMind releases Gemini 4 Carbon, topping Artificial…

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1M maximum output, with input covering text, images, video, and speech, and output in text; Artificial Analysis lists a standard price of $4/$20 per million input/output tokens, plus a 50% launch discount.

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1

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    #newsletter#Model releases#Google#Safety / alignment
  6. Ed Zitron long-form article / Where's Your Ed At

    Ed Zitron's Long-Form Article Questions Anthropic IPO: S-1 Conceals Q3 Data, $430 Billion Compute Commitment About to Take Effect

    In his long-form article, Ed Zitron analyzes Anthropic's S-1, arguing that the document only discloses Q2 2026 data, and that the quarter's $974 million in profit came from two months of SpaceX compute discounts, while Q3 revenue, cash balance, and payment schedule were not disclosed. He tallies Anthropic's non-cancelable compute commitments with Google, Amazon, Microsoft, SpaceX, Broadcom, and others at approximately $269.4 billion, with an additional $125 billion to $150 billion in TPU purchase commitments not included in the contract table, and notes that Q3 revenue grew 45% quarter-over-quarter to $16.8 billion, while compute spending grew 76.3% to $9.88 billion. The article also mentions that 5% to 7% of revenue comes from customers found to have violated rules by using its models to train their own models, as well as lock-up arrangements that allow insiders to sell down relatively quickly.

    In his long-form article, Ed Zitron analyzes Anthropic's S-1, arguing that the document only discloses Q2 2026 data, and that the quarter's $974 million in profit came from two months of SpaceX compute discounts, while Q3 revenue, cash balance, and payment schedule were not disclosed. He tallies Anthropic's non-cancelable compute commitments with Google, Amazon, Microsoft, SpaceX, Broadcom, and others at approximately $269.4 billion, with an additional $125 billion to $150 billion in TPU purchas

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    #ai-news#Industry news#OpenAI#Anthropic
  7. The Rundown AI

    Google releases Gemini 4 Carbon, topping 15 of 17 benchmarks

    Google has released Gemini 4 Carbon, a frontier model aimed at cybersecurity and long-horizon coding tasks, topping 15 of Google's own 17 benchmarks, but it has not yet been made public and is available only to some cybersecurity defenders. It scores 59 on Artificial Analysis' Intelligence Index, surpassing Claude Opus 5.5 and up 9 points from Argon four weeks ago; on long-input reasoning it leads OpenAI Astra and Opus by 24 points. The introductory API price is $2 per million input tokens and $10 per million output tokens, half that of Opus 5.5, doubling after the discount period to Opus's rates. Google has not announced when it will broaden access.

    Google has released Gemini 4 Carbon, a frontier model aimed at cybersecurity and long-horizon coding tasks, topping 15 of Google's own 17 benchmarks, but it has not yet been made public and is available only to some cybersecurity defenders. It scores 59 on Artificial Analysis' Intelligence Index, surpassing Claude Opus 5.5 and up 9 points from Argon four weeks ago; on long-input reasoning it leads OpenAI Astra and Opus by 24 points. The introductory API price is $2 per million input tokens and $

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    #newsletter#Model releases#Google#Reasoning
  8. Mistral AISelected

    Mistral Releases Open Weights for Mistral Large 4 (Le Chonk)

    Mistral has released the open weights for Mistral Large 4 (Le Chonk), a 1-trillion-parameter natively multimodal model that continues reinforcement learning on top of the preview version, with improved coding and defensive cybersecurity capabilities. It scores 19.7% on FrontierCode 2.0 and 48% on the Artificial Analysis Coding Agent Index, roughly on par with GLM-5.3, but uses an average of 47% fewer tokens per task; on Terminal-Bench 4.0 it improves by 13 percentage points to 41%. The model supports three reasoning modes, uses a modified MIT-based Mistral Ecosystem Open-Weight license, and is priced via API at $0.70 per million input tokens, $0.07 for cached input, and $2.10 for output.

    Le Chonk signal

    Mistral has released the open weights for Mistral Large 4 (Le Chonk), a 1-trillion-parameter natively multimodal model that continues reinforcement learning on top of the preview version, with improved coding and defensive cybersecurity capabilities. It scores 19.7% on FrontierCode 2.0 and 48% on the Artificial Analysis Coding Agent Index, roughly on par with GLM-5.3, but uses an average of 47% fewer tokens per task; on Terminal-Bench 4.0 it improves by 13 percentage points to 41%. The model sup

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    #lab#Model releases#Open-source ecosystem#Reasoning
  9. MarkTechPost

    Infini-AI-Lab open-sources the Hermit harness adapter framework

    Infini-AI-Lab has released the open-source framework Hermit, which adapts AI agents by training external harness adapters while keeping the model and harness frozen; v0.1.0 was released on October 25, 2026. The framework is implemented in Python under the Apache-2.0 license and can be installed via pip install hermit-harness, and it includes five evolution methods: GEPA, SkillOpt, MetaWorld Model, Harness², and Continual Harness. On GLM 5.3 Flash, the MWM adapter achieved 0.795 accuracy on the CL-Bench database exploration task, higher than the in-context baseline of 0.580, but most results are self-reported data from a single run.

    Infini-AI-Lab has released the open-source framework Hermit, which adapts AI agents by training external harness adapters while keeping the model and harness frozen; v0.1.0 was released on October 25, 2026. The framework is implemented in Python under the Apache-2.0 license and can be installed via pip install hermit-harness, and it includes five evolution methods: GEPA, SkillOpt, MetaWorld Model, Harness², and Continual Harness. On GLM 5.3 Flash, the MWM adapter achieved 0.795 accuracy on the C

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    #ai-vertical#English text is being prepared.#Agents#Open-source ecosystem

Wednesday

  1. Official Pydantic AI articleSelected

    Pydantic compares code mode and tool calling across 5,276 runs

    Michael Pfaffenberger of Pydantic used 5 small Pydantic AI applications and 8 models to conduct 5,276 scored runs, comparing code mode with direct tool calling. On long tasks, code mode reduced average cost by 58%, latency by 51%, and increased success rate by 16 percentage points; however, for short tasks with 5 items, 3 out of 5 tasks were instead 21% to 38% more expensive. The author argues that models are better at writing loops than at acting as the loop, and the gap widens as tasks get longer.

    Michael Pfaffenberger avatar

    Michael Pfaffenberger of Pydantic used 5 small Pydantic AI applications and 8 models to conduct 5,276 scored runs, comparing code mode with direct tool calling. On long tasks, code mode reduced average cost by 58%, latency by 51%, and increased success rate by 16 percentage points; however, for short tasks with 5 items, 3 out of 5 tasks were instead 21% to 38% more expensive. The author argues that models are better at writing loops than at acting as the loop, and the gap widens as tasks get lon

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    #company#Evaluations / benchmarks#Agents#English text is being prepared.
  2. Latent Space

    Anthropic Abolishes Coding Interviews: Felix Reiseberg Says "Hunger beats tenure"

    Anthropic hiring manager Felix Reiseberg announced that the company will no longer use traditional coding interviews to evaluate candidates, citing the fact that Claude is already stronger than humans at both React challenges and assembly problems, and that truly impactful builders do not win through such tests. He advises junior engineers to pick an idea that can drive business impact, build a working prototype over the weekend, focus on just one good idea, and leverage their fresh perspective on users. On the same day, Google DeepMind released the Genie 4 world model, and Claude Opus 5.5 (58 points) topped the Artificial Analysis Intelligence Index v5.

    Anthropic hiring manager Felix Reiseberg announced that the company will no longer use traditional coding interviews to evaluate candidates, citing the fact that Claude is already stronger than humans at both React challenges and assembly problems, and that truly impactful builders do not win through such tests. He advises junior engineers to pick an idea that can drive business impact, build a working prototype over the weekend, focus on just one good idea, and leverage their fresh perspective

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    #newsletter#Industry news#Agents#English text is being prepared.
  3. MarkTechPost

    Polymathic AI and Princeton University Release FlashMap: Achieving 6.14x LLM Decoding Speedup with a Flow-Mapping Drafter

    Polymathic AI, Princeton University, and other institutions have released FlashMap, which replaces discrete diffusion drafters with continuous flow mapping to draft a complete block of 16 tokens in a single forward pass. On Qwen3-8B, it achieves up to 6.14x lossless speedup on GSM8K at temperature 0, with the drafter having only 0.5B parameters. The drafter weights for Qwen3-8B and Qwen3-4B are now available on Hugging Face, along with vLLM and SGLang plugins.

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    #ai-vertical#Model releases#Reasoning#Open-source ecosystem
  4. Leiphone

    Liu Rui, Director of Huawei's Xiaoyi Large Model Application Lab: AI assistants must move beyond the chat box, from passive response to proactive service

    Liu Rui, the first director of Huawei's Xiaoyi Large Model Application Lab, proposed that AI assistants must move beyond the chat box and shift from passive response to proactive service. The conversational photo-editing technology he previously failed to get approved as a project at SenseTime has already been unveiled at the 2025 Huawei Mate 80 launch event. The lab has also launched the Aura streaming video understanding model, which supports real-time video interaction and proactive service, as well as Boogu, an open-source foundational image generation model. Liu Rui believes the biggest bottleneck at present remains insufficient model capability.

    Liu Rui, the first director of Huawei's Xiaoyi Large Model Application Lab, proposed that AI assistants must move beyond the chat box and shift from passive response to proactive service. The conversational photo-editing technology he previously failed to get approved as a project at SenseTime has already been unveiled at the 2025 Huawei Mate 80 launch event. The lab has also launched the Aura streaming video understanding model, which supports real-time video interaction and proactive service,

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    #hot-signal#English text is being prepared.#Agents#Multimodal
  5. TMTPost · AGI

    Day 130 of Xiaowei's gray release: WeChat breaks mini programs into parts and hands them to AI

    It has been 130 days since WeChat's native AI assistant "Xiaowei" launched. Its entry points have expanded from the 16 officially disclosed to 28 measured by third parties, covering chat, search, official accounts, Channels, and PC. Through the developer integration guide released on June 8, WeChat requires developers to break mini programs into atomic interfaces and atomic components and write SKILL documentation; mini programs that have not integrated will be unable to be recommended and invoked by WeChat AI. The article also mentions that the development model must pass platform evaluation (80 points or above in the three items of service delivery, interaction experience, and performance quality, and 60 points or above in scenario coverage) to be eligible for invocation, while the invocation ranking rules have not yet been made public.

    It has been 130 days since WeChat's native AI assistant "Xiaowei" launched. Its entry points have expanded from the 16 officially disclosed to 28 measured by third parties, covering chat, search, official accounts, Channels, and PC. Through the developer integration guide released on June 8, WeChat requires developers to break mini programs into atomic interfaces and atomic components and write SKILL documentation; mini programs that have not integrated will be unable to be recommended and invok

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