As OpenAI discloses multiple incidents of its technology going rogue and the UN warns of uncontrollable agents, Meta is putting an AI agent in the hands of millions Hello, and welcome to TechScape. I’m your host, Blake Montgomery, US tech editor at the Guardian, writing to you as rain and wind lash my windows in New York City. Today in tech, we’re discussing an alarming series of disclosures by AI companies. Continue reading...

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The industry is engaged in a perverse quest to replace humans. We cannot cede the best tools available to the other side I don’t need to tell you that people hate AI. The list of grievances is long: slop, cheating, bias, enfeeblement, electricity bills, environmental destruction, exploitation, theft, cybercrime, doom. But resistance to the technology has often taken the form of shaming people for personally using it, with precious little organizing against the companies building the machines. This is perplexing, given that those companies are attempting to render us obsolete. The executives may contest this framing, offering some bromides about how AI will augment human work or how we’ll simply find new jobs to do. But their clear goals are to create systems that so clearly surpass our ab…

In this article, you will learn how to automatically extract structured knowledge from raw text and populate a knowledge graph with SPOC quads using a...

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 message board. More recently, researchers…

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.

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.

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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.

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

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 candidate if they used AI to help write a spee…

A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency

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 as OpenAI has halted the release of its n…

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...

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Explore more than 20 announcements from OpenAI DevDay 2026, including GPT-6 Astra, ChatGPT, Codex, APIs, security, and new tools for builders.

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.

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.

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.

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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.

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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 is to broaden the reach of our ADC port…

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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 machines have suddenly become sentient and deci…

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.

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.

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 simply from providing an accurate motion v…

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 quick-run results indicate that the qua…

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 developments, the practical performance ha…