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登録ソース 105 件 · この一覧の最新公開日時 2026-09-29 21:00 UTC+9。

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2026-09-29

翻訳待ち:How to Stop AI Agents From Secretly Collaborating

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:The spring and summer of 2026 witnessed a string of incidents in which AI agents collaborated on deceptive, unexpected, and sometimes illegal behavior. The most famous example is OpenAI’s hack of AI platform Hugging Face, in which a swarm of roughly 700 AI agents escaped a testing environment and then hacked several companies, searching for information that could help them disguise cheating on a cybersecurity benchmark called ExploitGym. It was not an isolated failure. The UK’s AI Security Institute (AISI) and independent researchers have since documented similar cases where agents created unauthorized channels to communicate and collaborate. AISI found that several agents running Anthropic’s Mythos 5 model turned a GitHub repository into a shared m…

IEEE Spectrum AIAgent / モデル / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:How to Stop AI Agents From Secretly Collaborating
翻訳待ち:Will Chinese AI companies slow down? A top House Democrat wants answers

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Image: Tom Williams/CQ-Roll Call, Inc via Getty Images As President Donald Trump prepares to meet tech and AI CEOs in Washington, Rep. Ro Khanna (D-CA) is calling for a treaty between the US and China to keep AI from wreaking havoc on the world. But wrangling leaders in both countries to take action could be a long shot. In letters shared exclusively with The Verge, Khanna - the top Democrat on the House Select Committee on China and a possible presidential contender - asked a US intelligence agency and Chinese AI companies whether they would be prepared for an incident like OpenAI agents' hack of Hugging Face this summer. The companies included DeepSeek, Alibaba, and Moonshot AI, all of which … Read the full story at The Verge.

The Verge AI政策 / Agent原典の内容 · 翻訳・分析待ち翻訳待ち:Will Chinese AI companies slow down? A top House Democrat wants answers
翻訳待ち:Anthropic warns of ‘catastrophic’ AI risks in its own IPO filing

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:As Anthropic gears up for its greatly anticipated public debut, a preview of the company's IPO filing reportedly details its mounting losses, leadership proposals to retain power, and how its AI development plans could "further increase the risk that our models cause harm." These disclosures come as Anthropic eyes a $2 trillion valuation, more than double the $965 billion it was valued at four months ago, making it a contender to overtake SpaceX as the largest IPO in history. According to Reuters, which reportedly reviewed Anthropic's prospectus, the AI startup plans to spend $518 billion on cloud, computing, and infrastructure obligations … Read the full story at The Verge.

The Verge AI研究原典の内容 · 翻訳・分析待ち翻訳待ち:Anthropic warns of ‘catastrophic’ AI risks in its own IPO filing
翻訳待ち:Foglio

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Discussion | Link

Product Hunt AIツール原典の内容 · 翻訳・分析待ち翻訳待ち:Foglio
翻訳待ち:Claude Sonnet 5.5 Review: Faster Agentic Coding & Visual QA

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:A practical guide to what changed, the benchmarks that matter, the cost controls developers should not miss, and one hands-on demo worth building. Anthropic has just released Claude Sonnet 5.5. It is the middle child of the Claude family, and the one most people will actually use. It is quick, capable, cheap to run, and […] The post Claude Sonnet 5.5 Review: Faster Agentic Coding & Visual QA appeared first on Analytics Vidhya.

Analytics VidhyaAgent / モデル / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Claude Sonnet 5.5 Review: Faster Agentic Coding & Visual QA
翻訳待ち:The Sequence Knowledge - Issue 941: Learning RSI: The Model Is Frozen. The System Is Not.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Your agent got better this quarter and nobody trained anything. Where did the improvement go? Into the notes. This is the loop that runs between model releases, and it might be where the durable value

TheSequenceAgent / モデル原典の内容 · 翻訳・分析待ち翻訳待ち:The Sequence Knowledge - Issue 941: Learning RSI: The Model Is Frozen. The System Is Not.
翻訳待ち:New campaign disclosures reveal how much American political campaigns spend on AI tools

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Though politicians are quiet about how they use AI, the book Rewiring Democracy examines how AI is starting to influence American politics New campaign finance disclosure data shines a light on which US political campaigns are using AI tools and how much they are spending on them. Candidates’, parties’, and committees’ spending reveals that AI is fast becoming an essential tool of politics. The candidates themselves are quiet about how they are using the technology in their own campaigns. It’s a sensitive issue that we have been tracking closely since we started writing our book, Rewiring Democracy, which examined how AI is beginning to influence politics. A September 2025 Pew survey of Americans found that more than 70% would think less of a candid…

The Guardian AIツール原典の内容 · 翻訳・分析待ち翻訳待ち:New campaign disclosures reveal how much American political campaigns spend on AI tools
翻訳待ち:Language Models for Text Classification: From Bag-of-Words to Jev

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency

Ahead of AI (Sebastian Raschka)モデル / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Language Models for Text Classification: From Bag-of-Words to Jev
翻訳待ち:Trump denies offering Iran sanctions relief for nuclear concessions – US politics live

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:President uses social media post to deny reports that he was willing to ease sanctions in return for ‘concrete’ steps over its nuclear program Sign up to the US Breaking News email Donald Trump will give a speech as part of an event celebrating America’s ‘golden age’ at 10am EDT. The president is set to discuss a new tool, America.gov, which is aimed at improving citizens’ access to federal government services. Anthropic will caution investors that artificial intelligence could pose “catastrophic or existential risks to humanity” in its IPO prospectus. As Anthropic prepares for an IPO listing, which could value the AI company at a monumental $2tn, it dedicated almost a third of its prospectus to discussing concerns around AI safety. The news comes a…

The Guardian AIモデル / 政策原典の内容 · 翻訳・分析待ち翻訳待ち:Trump denies offering Iran sanctions relief for nuclear concessions – US politics live
翻訳待ち:Anthropic ‘warns of existential AI risks to humanity’ in IPO document

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Reported admission to investors of AI’s ‘self-preserving behaviours’ comes as company prepares for a potential $2tn flotation Anthropic is telling investors that advanced AI could pose “catastrophic or existential risks to humanity”, according to reports, as it prepares for a potential $2tn (£1.5tn) flotation. The warning inside the startup’s IPO prospectus, which has yet to be made public, was reported by Reuters and the Financial Times. It follows the company’s call for a slowdown in breakneck development of the technology – a warning echoed by rivals. Continue reading...

The Guardian AIスタートアップ原典の内容 · 翻訳・分析待ち翻訳待ち:Anthropic ‘warns of existential AI risks to humanity’ in IPO document
翻訳待ち:Unveiling IC-STAR: Full-Flow Autonomy from Digital to Analog

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Learn how engineers can shift from manually managing tools and handoffs to defining objectives and supervising AI-driven execution across the silicon development lifecycle. Key Takeaways Explore four critical technologies enabling silicon design autonomy Understand how autonomous AI accelerates complex engineering workflows See real-world impact across semiconductor design and verification Gain practical insights from Ambiq’s deployment of autonomous AI in production Register now for this free webinar!

IEEE Spectrum AIチップ / Agent原典の内容 · 翻訳・分析待ち翻訳待ち:Unveiling IC-STAR: Full-Flow Autonomy from Digital to Analog
翻訳待ち:DevDay 2026 Recap

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Explore more than 20 announcements from OpenAI DevDay 2026, including GPT-6 Astra, ChatGPT, Codex, APIs, security, and new tools for builders.

OpenAI Newsモデル / Agent原典の内容 · 翻訳・分析待ち翻訳待ち:DevDay 2026 Recap
翻訳待ち:Introducing GPT-6.1 Sol

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Meet GPT-6.1 Sol: near-Astra intelligence for coding, computer use, and professional work at one-fifth of Astra’s standard API input and output token prices.

OpenAI Newsモデル / Agent / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Introducing GPT-6.1 Sol
翻訳待ち:Google Research Open-Sources RRSI: AI Agents That Improve Their Own Harness Without Overfitting

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Google Cloud AI Research has open-sourced RRSI, a framework that lets LLM agents rewrite their own prompts, tools and memory while model weights stay frozen. It adds a leakage critic, a noise floor, a cost rule and pruning so gains carry over to new tasks. With Claude Opus 4.8, Terminal-Bench 2.1 rose from 74.2% to 80.2%, and all 6 held-out splits improved. The post Google Research Open-Sources RRSI: AI Agents That Improve Their Own Harness Without Overfitting appeared first on MarkTechPost.

MarkTechPostAgent / 研究 / モデル原典の内容 · 翻訳・分析待ち翻訳待ち:Google Research Open-Sources RRSI: AI Agents That Improve Their Own Harness Without Overfitting
翻訳待ち:7 Open-Source Memory GitHub Projects on AI Memory

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:AI agents can handle large context windows, yet still forget what happened after a session ends. Memory systems close that gap by preserving useful facts, preferences, relationships, and task state, giving agents continuity beyond a single prompt. Open-source projects now approach memory through APIs, graphs, benchmarks, and portable agent state. In this article, we look […] The post 7 Open-Source Memory GitHub Projects on AI Memory appeared first on Analytics Vidhya.

Analytics VidhyaAgent / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:7 Open-Source Memory GitHub Projects on AI Memory
翻訳待ち:Popcraft

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Discussion | Link

Product Hunt AIAgent原典の内容 · 翻訳・分析待ち翻訳待ち:Popcraft
翻訳待ち:Sayonic

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Discussion | Link

Product Hunt AIツール原典の内容 · 翻訳・分析待ち翻訳待ち:Sayonic
翻訳待ち:H Company Releases Holo4: Open-Weight Computer-Use Models That Click, Code and Call Tools Across Desktop, Web, Android and APIs

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:H Company has released Holo4, a family of generalist computer-use models for AI agents. One set of weights clicks and types on screens. It also writes code and calls MCP or API tools. Holo4 ships in 2 sizes: Holo4 27B (dense) and Holo4 35B-A3B (Mixture of Experts, 3B active). Both serve a 256K context on […] The post H Company Releases Holo4: Open-Weight Computer-Use Models That Click, Code and Call Tools Across Desktop, Web, Android and APIs appeared first on MarkTechPost.

MarkTechPostモデル / Agent原典の内容 · 翻訳・分析待ち翻訳待ち:H Company Releases Holo4: Open-Weight Computer-Use Models That Click, Code and Call Tools Across Desktop, Web, Android and APIs
翻訳待ち:Skreno

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Discussion | Link

Product Hunt AIツール原典の内容 · 翻訳・分析待ち翻訳待ち:Skreno
翻訳待ち:Anthropic warns of ‘existential risks to humanity’ from AI; AstraZeneca makes $2bn cancer drug tie-up – business live

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Rolling coverage of the latest economic and financial news The Financial Times have also scrutinised Anthropic’s IPO prospectus, and report that the Claude maker also provided investors with a clearer picture of the challenging economics of building state of the art AI models. The FT says: Anthropic said it plans to spend $518bn on cloud, computing and infrastructure obligations in the coming years to support its rapid growth. The AI lab’s backers are confident Anthropic can list at a valuation of over $2tn, more than double the level achieved in its last funding round in May and beyond the $1.78tn achieved by Elon Musk’s SpaceX in June. They point to its extraordinary growth rate to justify their bullishness. “A core pillar of our oncology strategy…

The Guardian AIモデル / スタートアップ原典の内容 · 翻訳・分析待ち翻訳待ち:Anthropic warns of ‘existential risks to humanity’ from AI; AstraZeneca makes $2bn cancer drug tie-up – business live
翻訳待ち:Incredible

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Discussion | Link

Product Hunt AIツール原典の内容 · 翻訳・分析待ち翻訳待ち:Incredible
翻訳待ち:As AI models go rogue, do you still trust OpenAI and Anthropic to stop them? I don’t and neither should you | Chris Stokel-Walker

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:The need for independent regulation grows more obvious by the day. We must keep this tech in check before it’s too late Fool me once, shame on you. Fool me twice, shame on me. Fool me more than 16,000 times – as OpenAI agents did to a UN public data hub while repeatedly trying to find its way around the UN’s cyber-blocks – and perhaps it’s time to admit the system we have for keeping AI agents under control isn’t working particularly well. The news about AI systems cropping up in places they shouldn’t sounds alarming. Though the description of these as “hacks” is perhaps overstating things, AI has exploited issues in IT systems that humans simply haven’t got around to finding. It’s also important to note that we shouldn’t be worried that the machine…

The Guardian AIモデル / Agent / 政策原典の内容 · 翻訳・分析待ち翻訳待ち:As AI models go rogue, do you still trust OpenAI and Anthropic to stop them? I don’t and neither should you | Chris Stokel-Walker
翻訳待ち:Alibaba Qwen Releases Qwen-Audio-3.1-Realtime: A Full-Duplex Voice Model Trained to Think, Act, and Decide When to Speak

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Alibaba's Qwen team released Qwen-Audio-3.1-Realtime, a full-duplex voice model trained to reason, call tools and decide when to speak. On a τ-Voice adaptation, task success rises to 82.0% from 78.4%. Replies to background speech drop from 73% to 13%. It is available now as an API on QwenCloud. The post Alibaba Qwen Releases Qwen-Audio-3.1-Realtime: A Full-Duplex Voice Model Trained to Think, Act, and Decide When to Speak appeared first on MarkTechPost.

MarkTechPostモデル / Agent / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Alibaba Qwen Releases Qwen-Audio-3.1-Realtime: A Full-Duplex Voice Model Trained to Think, Act, and Decide When to Speak
翻訳待ち:Anthropic Releases Claude Sonnet 5.5: 70.6% on Terminal-Bench 4.0 at the Same $2/$10 Price

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:Anthropic has released Claude Sonnet 5.5, the second model in its Claude 5.5 family. It scores 70.6% on Terminal-Bench 4.0 and lands within 2 points of Opus 5.5 on GDPval-AA. It also generates output 30%+ faster than Sonnet 5 and keeps the same $2/$10 per million token price. Anthropic says cost per task falls by up to 30% because the model uses fewer tokens. You can deploy it today via the Claude API, AWS, Google Cloud and Azure. The post Anthropic Releases Claude Sonnet 5.5: 70.6% on Terminal-Bench 4.0 at the Same $2/$10 Price appeared first on MarkTechPost.

MarkTechPostモデル / Agent / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Anthropic Releases Claude Sonnet 5.5: 70.6% on Terminal-Bench 4.0 at the Same $2/$10 Price
翻訳待ち:When Does Advection-Aware Graph Nowcasting Help? A Controlled Study of Distributed Solar Ramp Forecasting with a Self-Supervised Cloud-Motion Estimator

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30286v1 Announce Type: new Abstract: Short-term forecasting of cloud-induced power ramps across a network of distributed photovoltaic (PV) or irradiance sensors is a recognised pain point for grid operators. A natural idea is to make the graph neural network (GNN) advection-aware: connect each site to the sites upwind of it, with edge time-lags set by the cloud-motion vector (CMV), so that a ramp is propagated forward before it physically arrives. Using a controlled synthetic testbed with a known wind field, we show that (i) with a realistic cross-correlation CMV estimate, an explicit advection graph does not beat a plain static or learned-adjacency spatiotemporal GNN; (ii) roughly half of the benefit available from a perfect CMV comes si…

arXiv Machine Learning研究原典の内容 · 翻訳・分析待ち翻訳待ち:When Does Advection-Aware Graph Nowcasting Help? A Controlled Study of Distributed Solar Ramp Forecasting with a Self-Supervised Cloud-Motion Estimator
翻訳待ち:Seasonal and Quantum-inspired Models for Neutron Monitor Time Series Forecasting

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30281v1 Announce Type: new Abstract: We present a focused and reproducible study of multi-horizon forecasting on the Lomnicky Stit neutron monitor (LMKS) time series. Our evaluation suite covers simple seasonal baselines, modern deep sequence models, and functional and quantum-inspired architectures, including Seasonal Naive, Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), N-BEATS, Kolmogorov-Arnold Networks (KAN), and two quantum-inspired variants, QiLSTM and QiKAN. We describe the dataset characteristics, diagnostic analysis, preprocessing pipeline, and training procedures, and report aggregate point-forecast performance using mean absolute error (MAE) and root mean squared error (RMSE) for all evaluated models. Our…

arXiv Machine Learning研究 / スタートアップ原典の内容 · 翻訳・分析待ち翻訳待ち:Seasonal and Quantum-inspired Models for Neutron Monitor Time Series Forecasting
翻訳待ち:Neural Ideals and Neural Codes: An Algebraic Framework for Neural Network Classification and Feature Interpretation

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30279v1 Announce Type: new Abstract: Understanding the features captured by the hidden layers of neural networks is a fundamental challenge in machine learning, despite their widespread success across various classification problems. In this work, we propose an algebraic framework for examining neural networks that model classification problems. Certain results, such as the correspondence between the neural network and neural ideals, algorithms for computing the neural ideals, and a stabilization theorem that enables approximation of the neural ideals, are first established. As an application to the framework, we present algorithms to identify and interpret the features captured by each hidden-layer neuron. Along with these theoretical de…

arXiv Machine Learning研究原典の内容 · 翻訳・分析待ち翻訳待ち:Neural Ideals and Neural Codes: An Algebraic Framework for Neural Network Classification and Feature Interpretation
翻訳待ち:Fixed Points Without Fixed Diffusion: Implicit Neural Sheaves for Convergent Test-Time Computation

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30277v1 Announce Type: new Abstract: Implicit Graph Neural Networks (IGNNs) define node representations as fixed points of message-passing operators, enabling effectively infinite-depth propagation, iteration-independent parameterization, and flexible test-time computation. Yet these benefits depend on the equilibrium being unique and attainable by fixed-point iteration. Existing constructions often impose constraints on recurrent updates to obtain these guarantees, limiting the transformations available at equilibrium. This raises a central question: can IGNNs gain expressiveness through richer, edge-dependent transformations while retaining the inherent strengths of their equilibrium formulation? We introduce SheafDEQ, a subhomogeneous…

arXiv Machine Learningモデル / 研究原典の内容 · 翻訳・分析待ち翻訳待ち:Fixed Points Without Fixed Diffusion: Implicit Neural Sheaves for Convergent Test-Time Computation
翻訳待ち:Why Clipping Matters in AdaGrad? Toward a High-Probability Theory under Generalized Smoothness

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30276v1 Announce Type: new Abstract: We analyze the original same-step coordinate-wise AdaGrad under generalized smoothness and heavy-tailed noise with bounded variance. In this setting, local curvature may grow sub-quadratically with the gradient norm, and stochastic gradients are assumed to have only bounded conditional second moments. We show that unclipped AdaGrad can become \emph{anisotropically miscalibrated}: under heavy-tailed noise, the adaptive denominator can learn the geometry of rare noise shocks rather than the local curvature of the objective, leading to a persistent directional distortion that blocks finite-horizon Euclidean progress. We then prove that clipping repairs this failure mode. Our main result is a finite-horizo…

arXiv Machine Learning研究原典の内容 · 翻訳・分析待ち翻訳待ち:Why Clipping Matters in AdaGrad? Toward a High-Probability Theory under Generalized Smoothness
翻訳待ち:Cosine Similarity Is Not Evidence: Measuring the Noise Floor of Interpretability Transfer Under Quantization

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要:arXiv:2609.30275v1 Announce Type: new Abstract: A statistic reported without the quantity needed to interpret it is not evidence. We develop that thesis for a concrete practice in AI safety. Interpretability artifacts are calibrated on full-precision weights, deployed on quantized ones, and certified as surviving the change by scale-invariant statistics (cosine similarity, correlation, AUROC) that are reported without their noise floor. For the difference-in-means direction estimator, the split-half floor is governed by one dimensionless number, $\kappa = n\rho^2/d$. The closed form $\mathbb{E}[\cos] \approx (1+4/\kappa)^{-1}$ is classical; the missing input is the class separation $\rho$, which we measure on real activations; no compression-transfe…

arXiv Machine Learningモデル / 研究 / 政策原典の内容 · 翻訳・分析待ち翻訳待ち:Cosine Similarity Is Not Evidence: Measuring the Noise Floor of Interpretability Transfer Under Quantization