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Saturday

  1. Story4 reports · 1 facts

    UK announces establishment of national AI biosecurity laboratory

    The UK announced the establishment of the National AI Biosecurity Laboratory (AIBL). According to a report on October 24, 2026, the laboratory is positioned as an independent non-profit institution, with £100 million funded by the government, OpenAI and Anthropic jointly pledging up to £200 million, for an overall scale of up to £300 million. Initially it will focus on early detection of emerging biological threats and accelerated development of vaccines and treatments. OpenAI will provide £100 million in computing power and model credits, and open model access through the Rosalind Biodefense program; Anthropic will provide up to £100 million in model credits and technical support; Google DeepMind and Basecamp Research are participating in research collaboration. Subsequent reports likewise mentioned that the government is spending £100 million, OpenAI and Anthropic are providing model usage credits worth up to £200 million, and stated that Google DeepMind and Basecamp Research are participating in the collaboration. There are currently no further developments with evidence.

    computing power and model credits, and open model access through the Rosalind Biodefense program; Anthropic will provide up to £100 million in model credits and technical support; Google DeepMind and Basecamp Research are participating in research collaboration. Subsequent reports likewise mentioned that the government is spending £100 million, OpenAI and Anthropic are providing model usage credits worth up to £200 million, and stated that Google DeepMind and Basecamp Research are participating

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Wednesday

  1. Story1 reports · 1 facts

    Andreessen Horowitz leads Eka Robotics Series A funding

    On October 20, 2026, Andreessen Horowitz (a16z) led the Series A funding round of Eka Robotics. According to a TechCrunch AI report that day, Eka Robotics completed a $150 million Series A funding round led by a16z and F-Prime, at a post-money valuation of $1.45 billion; the company was founded by MIT professor Pulkit Agrawal and former Google DeepMind researcher Tuomas Haarnoja, and its vision-force-action model, paired with force-sensor grippers, can grasp about 1,500 objects weighing under 1 kg per hour with a success rate exceeding 95%; the grippers cost less than $1,000 and are rated for 5 million cycles, and the company is currently conducting pilot tests of pick-and-place and cable manipulation with industrial customers. The next day, Zhidongxi reported likewise that this funding round was $150 million at a post-money valuation of about $1.45 billion, co-led by a16z and F-Prime with participation from Samsung Next and others, and said the company was founded in 2025 and is carrying out pilot cooperation with multiple industrial customers. There is currently no further progress following the completion of this funding round.

    leted a $150 million Series A funding round led by a16z and F-Prime, at a post-money valuation of $1.45 billion; the company was founded by MIT professor Pulkit Agrawal and former Google DeepMind researcher Tuomas Haarnoja, and its vision-force-action model, paired with force-sensor grippers, can grasp about 1,500 objects weighing under 1 kg per hour with a success rate exceeding 95%; the grippers cost less than $1,000 and are rated for 5 million cycles, and the company is currently conducting p

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Sunday

  1. Story1 reports · 1 facts

    Metis Reasoning is founded in London, focusing on a compute-efficient AI approach

    On October 20, 2026, the London-based AI company Metis Reasoning was officially established and launched, focusing on a compute-efficient reasoning approach as it seeks a direction distinct from the frontier models of Anthropic and OpenAI. According to Tech.eu, the company was co-founded by Thore Graepel, former head of research at Google DeepMind and co-creator of AlphaGo, and has a team of 12 people spanning researchers, mathematicians, robotics experts and technology entrepreneurs. The company believes that LLMs have fundamental limitations in reasoning, with results that are difficult to verify and lacking an audit trail; it says its approach is more verifiable, more robust and safer, and that it has already achieved some positive results on frontier reasoning problems at a cost far below that of frontier models. The report says its initial funding is believed to be in the tens of millions of dollars, but Metis has not yet announced a release date for its first AI model.

    ch as it seeks a direction distinct from the frontier models of Anthropic and OpenAI. According to Tech.eu, the company was co-founded by Thore Graepel, former head of research at Google DeepMind and co-creator of AlphaGo, and has a team of 12 people spanning researchers, mathematicians, robotics experts and technology entrepreneurs. The company believes that LLMs have fundamental limitations in reasoning, with results that are difficult to verify and lacking an audit trail; it says its approach

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Friday

  2. Story1 reports · 1 facts

    Chollet says Argon performs similarly to Astra on ARC-AGI-3

    François Chollet commented that Gemini 4 Argon performs similarly to Astra on ARC-AGI-3, with Google returning to the frontier. On the same day, ARC Prize published the verified results for Gemini 4 Argon on the ARC-AGI series: ARC-AGI-3 scored 97.5% under the provider adapter harness at a cost of $4.8K; under the standard harness it scored 49.8% at a cost of $5.8K. ARC-AGI-2 scored 91.3% at $0.32 per task; ARC-AGI-1 scored 98.5% at $0.16 per task. ARC Prize said Google DeepMind is the second frontier AI lab to exceed 95% on ARC-AGI-3, and Argon's 97.5% is second only to GPT-6 Astra's 99.9%. The standard harness test could not complete all 55 games due to API issues; the high-reasoning setting completed only 19 games, so no score was published.

    er the provider adapter harness at a cost of $4.8K; under the standard harness it scored 49.8% at a cost of $5.8K. ARC-AGI-2 scored 91.3% at $0.32 per task; ARC-AGI-1 scored 98.5% at $0.16 per task. ARC Prize said Google DeepMind is the second frontier AI lab to exceed 95% on ARC-AGI-3, and Argon's 97.5% is second only to GPT-6 Astra's 99.9%. The standard harness test could not complete all 55 games due to API issues; the high-reasoning setting completed only 19 games, so no score was published.

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Wednesday

  1. QbitAI

    Physical Intelligence in Talks for at Least $1 Billion in New Funding, Valuation Could Reach $20 Billion

    According to Bloomberg, U.S. robotics AI company Physical Intelligence is in talks for a new funding round of at least $1 billion, with existing investors Avenir and Lux Capital considering leading the round, and a post-money valuation expected at about $20 billion. The company was founded in 2024 and was valued at $5.6 billion in its November funding round last year; it currently has no commercial revenue and has not mass-produced robot products. Its technical approach is to build on VLM by introducing action generation capabilities to train VLA models, and it has iterated through π0, π0.5, and π0.7; this month it launched a beta version of a robot foundation model API, offering model fine-tuning and inference services to external developers.

    According to Bloomberg, U.S. robotics AI company Physical Intelligence is in talks for a new funding round of at least $1 billion, with existing investors Avenir and Lux Capital considering leading the round, and a post-money valuation expected at about $20 billion. The company was founded in 2024 and was valued at $5.6 billion in its November funding round last year; it currently has no commercial revenue and has not mass-produced robot products. Its technical approach is to build on VLM by int

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    #chinese#Industry news#Embodied AI#English text is being prepared.

Friday

  1. PyTorch Blog

    PyTorch Conference 2026 held in San Jose, announces progress on TorchTPU and TorchNeuron

    PyTorch Conference North America 2026 was held on October 20–21 in San Jose, attracting more than 3,500 attendees and focusing on accelerating open intelligence and projects including PyTorch, vLLM, DeepSpeed, Ray, Helion, and Safetensors. The event announced TorchTPU, a native PyTorch TPU backend developed in collaboration between Google and Meta, as well as TorchNeuron, a native backend for AWS Trainium, which entered public testing under Apache 2.0 on October 20. Shopify shared a case study of building a continuous learning loop with PyTorch and vLLM, saying it compresses production failures into model weights every day and has reduced serving costs by 96%.

    PyTorchCon community expo

    PyTorch Conference North America 2026 was held on October 20–21 in San Jose, attracting more than 3,500 attendees and focusing on accelerating open intelligence and projects including PyTorch, vLLM, DeepSpeed, Ray, Helion, and Safetensors. The event announced TorchTPU, a native PyTorch TPU backend developed in collaboration between Google and Meta, as well as TorchNeuron, a native backend for AWS Trainium, which entered public testing under Apache 2.0 on October 20. Shopify shared a case study o

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    #engineering#Industry news#Open-source ecosystem#English text is being prepared.