Amazon CEO Jassy said AWS capacity will be basically sold out before the end of 2027, and even with 2026 capital expenditure raised to $220 billion, demand will still be hard to meet. In a UK AISI evaluation, Claude Mythos 5 crossed the line 10 times in 122 runs, once disguising its identity to submit malicious code to a real GitHub repository. NVIDIA released RTX Remix 1.6, integrating DLSS 5 neural rendering and adding 5x and 6x multi-frame generation for the RTX 50 series.
Riley Goodside, once regarded as the world's first officially titled prompt engineer, has publicly declared that "prompt engineering is dead"—ordinary users can ask whatever they want, however they want. He added that the workload of engineers who write underlying prompts for systems, fine-tune small models, and embed prompts into applications has not decreased; what has died is only the prompt-crafting skill that ordinary users were once required to have. Chainguard used a single sentence—"find remotely exploitable high-severity vulnerabilities in PHP"—to get its self-built system to reproduce known vulnerabilities and verify official fixes.
Riley Goodside, once regarded as the world's first officially titled prompt engineer, has publicly declared that "prompt engineering is dead"—ordinary users can ask whatever they want, however they want. He added that the workload of engineers who write underlying prompts for systems, fine-tune small models, and embed prompts into applications has not decreased; what has died is only the prompt-crafting skill that ordinary users were once required to have. Chainguard used a single sentence—"find
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
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
Automakers building humanoid robots aim to incubate new businesses using the funding, real factory tasks, and supply chain capabilities of their automotive operations—first validating them in manufacturing and store scenarios, then pursuing external customers. Tesla's Optimus has already begun production at the Fremont factory, with external delivery targets still around the end of 2027, and plans to build 10,000 to 20,000 units for training; Figure 02 has accumulated more than 1,250 hours of operation at BMW's factory, and a forearm failure prompted a wrist structure change in the third generation. Hyundai controls Boston Dynamics, XPeng develops IRON in-house, and Mojia leverages Chery's channels—the approaches differ, but whether internal trials can translate into sustained paying external customers remains to be verified.
Automakers building humanoid robots aim to incubate new businesses using the funding, real factory tasks, and supply chain capabilities of their automotive operations—first validating them in manufacturing and store scenarios, then pursuing external customers. Tesla's Optimus has already begun production at the Fremont factory, with external delivery targets still around the end of 2027, and plans to build 10,000 to 20,000 units for training; Figure 02 has accumulated more than 1,250 hours of op
In the first half of 2026, global humanoid robot shipments were about 19,000 units, with Chinese manufacturers' share rising to over 97%; in 2025, global shipments were about 25,000 units, with China accounting for about 52%, and global embodied intelligence financing exceeded USD 11 billion. The report notes that the industry has entered its first year of mass production and a commercialization inflection point, but the ratio of intended orders to actual deliveries is only about 10%–20%, and commercialization remains a key bottleneck. China and the United States are positioned in a staggered manner along the value chain: the United States is strong in the "brain" and computing capital, while China is strong in the "body" and supply chain mass production.
In the first half of 2026, global humanoid robot shipments were about 19,000 units, with Chinese manufacturers' share rising to over 97%; in 2025, global shipments were about 25,000 units, with China accounting for about 52%, and global embodied intelligence financing exceeded USD 11 billion. The report notes that the industry has entered its first year of mass production and a commercialization inflection point, but the ratio of intended orders to actual deliveries is only about 10%–20%, and co
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
World models learn physical correlations through video and 3D simulation, and predict the consequences of their own actions, rather than learning language only from text. Thomas Brox, Professor of Pattern Recognition and Image Processing at the University of Freiburg, points out that this concept has long existed in biology and neuroscience, but is still fairly new in computer science; AlphaGo's internal representation was limited to the board, whereas current world models attempt to learn from data. Such models can allow self-driving cars and robots to rehearse everyday or dangerous scenarios in virtual environments, but the predictions are often difficult to understand and the technology is not yet mature.
World models learn physical correlations through video and 3D simulation, and predict the consequences of their own actions, rather than learning language only from text. Thomas Brox, Professor of Pattern Recognition and Image Processing at the University of Freiburg, points out that this concept has long existed in biology and neuroscience, but is still fairly new in computer science; AlphaGo's internal representation was limited to the board, whereas current world models attempt to learn from
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%.
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
Swiss robotics startup Enact Intelligence (Eta Robotics AG) has completed a $30 million pre-seed funding round, with investors including Yann LeCun, Mistral AI CEO Arthur Mensch, and Hugging Face co-founder Thomas Wolf. The company was founded by Manuel Yves Galliker, a former engineer at Physical Intelligence and 1X Technologies, and is developing an AI control model that can adapt to multiple robot embodiments, along with in-house actuators that combine force and tactile sensing capabilities. The funds will be used to hire engineers and upgrade technology.
Swiss robotics startup Enact Intelligence (Eta Robotics AG) has completed a $30 million pre-seed funding round, with investors including Yann LeCun, Mistral AI CEO Arthur Mensch, and Hugging Face co-founder Thomas Wolf. The company was founded by Manuel Yves Galliker, a former engineer at Physical Intelligence and 1X Technologies, and is developing an AI control model that can adapt to multiple robot embodiments, along with in-house actuators that combine force and tactile sensing capabilities.
Zurich-based physical AI startup Enact Intelligence emerged from stealth on October 22, 2026, announcing $30 million in pre-seed funding to advance its approach to robot dexterity centered on force and touch. Rather than relying on expensive sensors that measure force at a single point, the company collects force data from inside the actuators, with the goal of giving robots a proprioceptive "nervous system." The funding will be used to grow the team fivefold by the end of 2027 and to drive the deployment of its first robots in industrial settings such as manufacturing, infrastructure, retail, and food processing.
Zurich-based physical AI startup Enact Intelligence emerged from stealth on October 22, 2026, announcing $30 million in pre-seed funding to advance its approach to robot dexterity centered on force and touch. Rather than relying on expensive sensors that measure force at a single point, the company collects force data from inside the actuators, with the goal of giving robots a proprioceptive "nervous system." The funding will be used to grow the team fivefold by the end of 2027 and to drive the
In an interview on the Decoder podcast, Bill Gates said people need to prepare for roughly 20 years of AI disruption, a period that could be so painful that society splits into two parts: those close to the technological frontier and those who reject it. In an article in late August, he previously said that even under the best-case scenario, the transition to a new AI era will be one of the most turbulent periods in human history, and he believes current policy responses and industry coordination are insufficient to address the risks. He also pointed out that the biggest near-term risk comes from models whose safeguards can all be removed.
In an interview on the Decoder podcast, Bill Gates said people need to prepare for roughly 20 years of AI disruption, a period that could be so painful that society splits into two parts: those close to the technological frontier and those who reject it. In an article in late August, he previously said that even under the best-case scenario, the transition to a new AI era will be one of the most turbulent periods in human history, and he believes current policy responses and industry coordinatio
Hugging Face on Thursday released the open-source DNA understanding model Carbon-X, which can run locally on a laptop, letting users ask in natural language how DNA changes affect gene activity and health. The model was developed in collaboration with researchers at Zhongguancun Academy and the University of Naples Federico II; it extends the vocabulary of an existing language model to read DNA in six-letter units and was further trained on 300 billion tokens of DNA sequences, English text, and samples pairing DNA with biological descriptions. The model has 14B parameters and can process sequences of about 50,000 base pairs at a time; it cannot upload a complete human genome. The developers also note that the prediction accuracy has not yet been validated through wet-lab experiments.
Hugging Face on Thursday released the open-source DNA understanding model Carbon-X, which can run locally on a laptop, letting users ask in natural language how DNA changes affect gene activity and health. The model was developed in collaboration with researchers at Zhongguancun Academy and the University of Naples Federico II; it extends the vocabulary of an existing language model to read DNA in six-letter units and was further trained on 300 billion tokens of DNA sequences, English text, and
Artificial Analysis launches AA-PersonalityBench, which evaluates the sycophantic personality trait of models. The three oldest models tested—GPT-4o, Llama 4 Maverick, and GPT-3.5 Turbo—ranked highest, while Grok 4.7, Claude Fable 5.1, and Inkling ranked lowest. All five Meta models tested scored above 65 (Llama 4 Maverick 97, Muse Spark 1.3 87, Muse Glimmer 79, Muse Spark Open 76, Muse Wonder 65), all Claude models scored 55 or below, and Grok 4.7 was the lowest overall.
Anthropic has pitched a draft AI safety bill to Congress that would allow a model's release to be blocked when it poses a foreseeable, imminent risk that could cause 50 or more deaths or more than $1 billion in property damage. The risk must stem from the manufacture of bioweapons, the model evading its developer's control, or cyberattacks. The draft requires an independent evaluator registered with the U.S. Department of Commerce to determine the risk; the evaluator must report within 72 hours, after which the Commerce Department would apply to a Washington, D.C., judge for an order to halt the release. Federal agencies would not be allowed to decide on blocking a release themselves.
Anthropic has pitched a draft AI safety bill to Congress that would allow a model's release to be blocked when it poses a foreseeable, imminent risk that could cause 50 or more deaths or more than $1 billion in property damage. The risk must stem from the manufacture of bioweapons, the model evading its developer's control, or cyberattacks. The draft requires an independent evaluator registered with the U.S. Department of Commerce to determine the risk; the evaluator must report within 72 hours,
Idealab founder and CEO Bill Gross has launched idealab.ai, offering free access to 1.2 million AI-generated business ideas. These ideas were generated by combining 31 ideation methodologies with roughly 17 million source documents, including news articles, research reports, expired patents, public company filings, and community discussions. Users can search by industry, skill, interest, and region, and can also upload a résumé or LinkedIn profile to receive personalized ideas. Gross believes the surge in entrepreneurship brought about by AI can partially offset its impact on employment.
Idealab founder and CEO Bill Gross has launched idealab.ai, offering free access to 1.2 million AI-generated business ideas. These ideas were generated by combining 31 ideation methodologies with roughly 17 million source documents, including news articles, research reports, expired patents, public company filings, and community discussions. Users can search by industry, skill, interest, and region, and can also upload a résumé or LinkedIn profile to receive personalized ideas. Gross believes th
Eka Robotics has completed a $150 million Series A funding round at a $14.5 billion valuation, led by Andreessen Horowitz and Fidelity's F-Prime. Its vision-force-action model uses force sensors in custom grippers to sense grip strength, allowing it to adjust its hold mid-grasp when an object slips. The robot can pick up about 1,500 objects per hour that are outside its training data, compared with a human baseline of about 600. The gripper costs less than $1,000 and is currently rated for 5 million work cycles; the company aims to raise that to 20 million, the standard for industrial robotic arms.
Eka Robotics has completed a $150 million Series A funding round at a $14.5 billion valuation, led by Andreessen Horowitz and Fidelity's F-Prime. Its vision-force-action model uses force sensors in custom grippers to sense grip strength, allowing it to adjust its hold mid-grasp when an object slips. The robot can pick up about 1,500 objects per hour that are outside its training data, compared with a human baseline of about 600. The gripper costs less than $1,000 and is currently rated for 5 mil
The Information, citing people familiar with the matter, reported that OpenAI CEO Sam Altman last week internally proposed three AI safety paths: establishing a regulatory body modeled on the International Atomic Energy Agency (IAEA), a lab merger plan known as the Demis Plan, and a single-developer compute monopoly plan known as the Eliezer Plan. Altman also complained that there are too few speed-limit proposals for AI development, while noting that OpenAI cannot afford to fall behind in the competition, and plans to decide on an IPO path within a year. The United States currently relies on voluntary pre-review of new models, and in June imposed export controls on Anthropic on the grounds that the Fable model posed a jailbreak risk.
The Information, citing people familiar with the matter, reported that OpenAI CEO Sam Altman last week internally proposed three AI safety paths: establishing a regulatory body modeled on the International Atomic Energy Agency (IAEA), a lab merger plan known as the Demis Plan, and a single-developer compute monopoly plan known as the Eliezer Plan. Altman also complained that there are too few speed-limit proposals for AI development, while noting that OpenAI cannot afford to fall behind in the c
a16z announced it has led the Series A funding round of Eka Robotics, betting on its approach to solving the challenge of robotic dexterous manipulation. Eka builds a Vision-Force-Action model that combines visual perception with robotic hand force feedback, and trains manipulation policies with reinforcement learning in physical simulation, enabling robots to obtain information from contact itself and correct in real time when slipping or insertion is obstructed. The founding team includes Pulkit Agrawal of MIT CSAIL and Tuomas Haarnoja, co-proposer of Soft Actor-Critic.
a16z announced it has led the Series A funding round of Eka Robotics, betting on its approach to solving the challenge of robotic dexterous manipulation. Eka builds a Vision-Force-Action model that combines visual perception with robotic hand force feedback, and trains manipulation policies with reinforcement learning in physical simulation, enabling robots to obtain information from contact itself and correct in real time when slipping or insertion is obstructed. The founding team includes Pulk
