Every engineering leader watching the agentic coding wave is eventually going to face the same question: if AI can generate production-quality code faster than any team, what does governance look like when the human isn't writing the code anymore?Most teams don't have a good answer yet. Treasure Data, a SoftBank-backed customer data platform serving more than 450 global brands, now has one, though they learned parts of it the hard... Read more ›
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Anthropic dropped a bombshell on the artificial intelligence industry Monday, publicly accusing three prominent Chinese AI laboratories — DeepSeek, Moonshot AI, and MiniMax — of orchestrating coordinated, industrial-scale campaigns to siphon capabilities from its Claude models using tens of thousands of fraudulent accounts.The San Francisco-based company said the three labs collectively generated more than 16 million exchanges with Claude through approximately 24,000 fake accounts, all in violation of Anthr Read more ›
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As agentic AI workflows multiply the cost and latency of long reasoning chains, a team from the University of Maryland, Lawrence Livermore National Labs, Columbia University and TogetherAI has found a way to bake 3x throughput gains directly into a model's weights.Unlike speculative decoding, which requires a separate drafting model, this approach requires no additional infrastructure — just a single special token added to the model's existing architecture.The limits of... Read more ›
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Anthropic pointed its most advanced AI model, Claude Opus 4.6, at production open-source codebases and found a plethora of security holes: more than 500 high-severity vulnerabilities that had survived decades of expert review and millions of hours of fuzzing, with each candidate vetted through internal and external security review before disclosure. Fifteen days later, the company productized the capability and launched Claude Code Security.Security directors responsible for seven-figure vulnerability manag Read more ›
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Anthropic dropped a bombshell on the artificial intelligence industry Monday, publicly accusing three prominent Chinese AI laboratories — DeepSeek, Moonshot AI, and MiniMax — of orchestrating coordinated, industrial-scale campaigns to siphon capabilities from its Claude models using tens of thousands of fraudulent accounts.The San Francisco-based company said the three labs collectively generated more than 16 million exchanges with Claude through approximately 24,000 fake accounts, all in violation of Anthr Read more ›
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Presented by DigitalOceanFrom refactoring codebases to debugging production code, AI agents are already proving their value. But scaling them in production remains the exception, not the rule. In DigitalOcean’s 2026 Currents research report, based on a survey of more than 1,100 developers, CTOs, and founders, 67% of organizations using agents report productivity gains. Meanwhile, 60% of respondents say applications and agents represent the greatest long-term value in the AI stack.... Read more ›
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Traditional software governance often uses static compliance checklists, quarterly audits and after-the-fact reviews. But this method can't keep up with AI systems that change in real time. A machine learning (ML) model might retrain or drift between quarterly operational syncs. This means that, by the time an issue is discovered, hundreds of bad decisions could already have been made. This can be almost impossible to untangle. In the fast-paced world... Read more ›
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OpenClaw, the open source AI agent that excels at autonomous tasks on computers and which users can communicate with through popular messaging apps, has undoubtedly become a phenomena since its launch in November 2025, and especially in the last few months.Lured by the promise of greater business automation, solopreneurs and employees of large enterprises are increasingly installing it on their work machines — despite a number of documented security risks.Now,... Read more ›
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For four weeks starting January 21, Microsoft's Copilot read and summarized confidential emails despite every sensitivity label and DLP policy telling it not to. The enforcement points broke inside Microsoft’s own pipeline, and no security tool in the stack flagged it. Among the affected organizations was the U.K.'s National Health Service, which logged it as INC46740412 — a signal of how far the failure reached into regulated healthcare environments. Microsoft... Read more ›
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For the past three months, Google's Gemini 3 Pro has held its ground as one of the most capable frontier models available. But in the fast-moving world of AI, three months is a lifetime — and competitors have not been standing still.Earlier today, Google released Gemini 3.1 Pro, an update that brings a key innovation to the company's workhorse power model: three levels of adjustable thinking that effectively turn it... Read more ›
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CX platforms process billions of unstructured interactions a year: Survey forms, review sites, social feeds, call center transcripts, all flowing into AI engines that trigger automated workflows touching payroll, CRM, and payment systems. No tool in a security operation center leader’s stack inspects what a CX platform’s AI engine is ingesting, and attackers figured this out. They poison the data feeding it, and the AI does the damage for them.The... Read more ›
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Late last year, Google briefly took the crown for most powerful AI model in the world with the launch of Gemini 3 Pro — only to be surpassed within weeks by OpenAI and Anthropic releasing new models, s is common in the fiercely competitive AI race.Now Google is back to retake the throne with an updated version of that flagship model: Gemini 3.1 Pro, positioned as a smarter baseline for... Read more ›
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Despite growing chatter about a future when much human work is automated by AI, one of the ironies of this current tech boom is how stubbornly reliant on human beings it remains, specifically the process of training AI models using reinforcement learning from human feedback (RLHF). At its simplest, RLHF is a tutoring system: after an AI is trained on curated data, it still makes mistakes or sounds robotic. Human... Read more ›
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Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving operational data for model inference in real-time. Empromptu calls this distinction "inference integrity" versus "reporting integrity." Instead of treating data preparation as a separate discipline, golden pipelines integrate normalization directly into the AI application workflow, collapsing what typically require Read more ›
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Agents built on top of today's models often break with simple changes — a new library, a workflow modification — and require a human engineer to fix it. That's one of the most persistent challenges in deploying AI for the enterprise: creating agents that can adapt to dynamic environments without constant hand-holding. While today's models are powerful, they are largely static.To address this, researchers at the University of California, Santa... Read more ›
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Alibaba dropped Qwen3.5 earlier this week, timed to coincide with the Lunar New Year, and the headline numbers alone are enough to make enterprise AI buyers stop and pay attention.The new flagship open-weight model — Qwen3.5-397B-A17B — packs 397 billion total parameters but activates only 17 billion per token. It is claiming benchmark wins against Alibaba's own previous flagship, Qwen3-Max, a model the company itself has acknowledged exceeded one trillion... Read more ›
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Typically, when building, training and deploying AI, enterprises prioritize accuracy. And that, no doubt, is important; but in highly complex, nuanced industries like law, accuracy alone isn’t enough. Higher stakes mean higher standards: Models outputs must be assessed for relevancy, authority, citation accuracy and hallucination rates. To tackle this immense task, LexisNexis has evolved beyond standard retrieval-augmented generation (RAG) to graph RAG and agentic graphs; it has also built out... Read more ›
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Anthropic on Tuesday released Claude Sonnet 4.6, a model that amounts to a seismic repricing event for the AI industry. It delivers near-flagship intelligence at mid-tier cost, and it lands squarely in the middle of an unprecedented corporate rush to deploy AI agents and automated coding tools.The model is a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It features a 1M token context... Read more ›
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The chatbot era may have just received its obituary. Peter Steinberger, the creator of OpenClaw — the open-source AI agent that took the developer world by storm over the past month, raising concerns among enterprise security teams — announced over the weekend that he is joining OpenAI to "work on bringing agents to everyone." The OpenClaw project itself will transition to an independent foundation, though OpenAI is already sponsoring it... Read more ›
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Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has also become increasingly clear that agentic AI systems need memory, sometimes referred to as contextual memory, to operate effectively.The complexity and synchronization of having different data layers to enable context can lead to performance and accuracy issues. It's a challenge that SurrealDB is... Read more ›
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26.07.2026 06:50
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