The reason enterprises have been slow to connect AI agents to internal APIs and databases isn't the models — it's the credentials. In most production deployments, the agent carries authentication tokens with it as it executes tool calls, which means a compromised or misbehaving agent takes the keys with it.Anthropic is addressing that problem with two new capabilities for Claude Managed Agents: self-hosted sandboxes, which let teams run tool execution... Read more ›
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For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On Tuesday, Google will formally retire that paradigm.At its annual I/O developer conference, Google announced a sweeping redesign of the search box itself — the literal text field where billions of queries begin every day... Read more ›
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Google on Tuesday unveiled Gemini Spark, a personal AI agent designed to work around the clock — drafting emails, assembling documents, monitoring inboxes, and eventually making purchases — even when a user's laptop is closed and their phone is locked.The announcement, made at Google I/O 2026, is the company's most ambitious attempt yet to transform its AI assistant from a tool that answers questions into one that autonomously completes tasks.... Read more ›
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Google unveiled Gemini 3.5 Flash at its annual I/O developer conference on Tuesday, a new artificial intelligence model that the company says shatters what had become a seemingly iron law of the AI industry: that the smartest models must also be the slowest and most expensive to run.The model sits at the center of a sweeping set of announcements — from a video-generating "world model" called Gemini Omni to a... Read more ›
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Although it was already discovered by intrepid AI power users weeks ahead of the official unveiling today at Google's annual I/O developer conference, the company's new Gemini Omni model marks a significantly new paradigm in the wider AI and tech marketplace.That's because as its "omni" (from the Latin omne — meaning "all") prefix would suggest, this is Google's first truly native, multimodal model, that is "a model that can create... Read more ›
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Andrej Karpathy, the influential 39-year-old Slovak-Canadian AI researcher and one of the original 11 co-founders of OpenAI, and former head of Tesla's AI division, announced on Tuesday, May 19 that he's joining rival lab Anthropic.As Karpathy posted from his account on the social network X: "Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to... Read more ›
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Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents failing not because the models are wrong, but because the data underneath them is scattered, stale and structured for humans rather than machines. Retrieval pipelines built for single queries cannot absorb the volume agents generate.The gap... Read more ›
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Four supply-chain incidents hit OpenAI, Anthropic and Meta in 50 days: three adversary-driven attacks and one self-inflicted packaging failure. None targeted the model, and all four exposed the same gap: release pipelines, dependency hooks, CI runners, and packaging gates that no system card, AISI evaluation, or Gray Swan red-team exercise has ever scoped.On May 11, 2026, a self-propagating worm called Mini Shai-Hulud published 84 malicious package versions across 42 @tanstack/*... Read more ›
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Enterprises building and deploying agents have a problem: it’s taking their engineers too long to find out that an agent made a mistake, and the loop has continued to perpetuate, especially without a human at every step. LangSmith, the monitoring and evaluation platform from LangChain, launched a new capability in public beta that could make that issue more manageable. LangSmith Engine automates the entire chain by detecting production failures, diagnosing... Read more ›
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Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via cosine similarity — is effective for unstructured semantic search.However, for enterprise domains characterized by highly interconnected data (supply chain, financial compliance, fraud detection), vector-only RAG often fails. It captures similarity but misses st Read more ›
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For AI systems to keep improving in knowledge work, they need either a reliable mechanism for autonomous self-improvement or human evaluators capable of catching errors and generating high-quality feedback. The industry has invested enormously in the first. It's giving almost no thought to what's happening to the second.I’d argue that we need to treat the human evaluation problem with just as much rigor and investment as we put into building... Read more ›
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The company formerly known as Intercom just did something that no major customer service platform has attempted at scale: it built an AI agent whose sole job is to manage another AI agent.Fin Operator, announced Thursday at a live event in San Francisco, is a new AI-powered system designed specifically for the back-office teams that configure, monitor, and improve Fin, the company's customer-facing AI agent. Rather than replacing human support... Read more ›
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One of the key challenges of current multi-agent AI systems is that they communicate by generating and sharing text sequences, which introduces latency, drives up token costs, and makes it difficult to train the entire system as a cohesive unit. To overcome this challenge, researchers at University of Illinois Urbana-Champaign and Stanford University developed RecursiveMAS, a framework that enables agents to collaborate and transmit information through embedding space instead of... Read more ›
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New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger fight over who controls the infrastructure where AI agents run.For the last two years, the enterprise AI race has mostly been framed as a model war: OpenAI’s GPT series versus Anthropic’s Claude versus Google’s Gemini, with smaller and open-source alternatives also coming in from the U.S. and China. But... Read more ›
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Observability startup Raindrop AI’s new open source, MIT Licensed "Workshop" tool, launched today, gives developers something that they've likely wanted, perhaps subconsciously, since the agentic AI era kicked off in earnest last year: a local debugger and evaluation tool specifically designed for AI agents, allowing devs to see all the traces of what their agent has been doing in a single, lightweight Structured Query Language (SQL) database file (.db)It functions... Read more ›
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Cerebras Systems, the Silicon Valley chipmaker that built the world's largest commercial AI processor, erupted onto the Nasdaq on Wednesday, opening at $350 per share — nearly double its $185 IPO price — and rocketing past a $100 billion market capitalization in its first hours of trading. The debut instantly crowned Cerebras as one of the most valuable semiconductor companies on Earth and validated a decade-long bet that the AI... Read more ›
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Anthony Grieco, Cisco’s SVP and chief security and trust officer, did not hesitate when VentureBeat asked whether rogue agent incidents are reaching Cisco’s customer base."A hundred percent. We see them regularly," Grieco told VentureBeat in an exclusive interview at RSAC 2026. "I've heard some that I can't repeat, but they do get to the places of, you know, agents are doing things that they think are the right things to... Read more ›
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A code migration agent finishes its run, and the pipeline looks green. But several pieces were never compiled — and it took days to catch. That's not a model failure; that's an agent deciding it was done before it actually was.Many enterprises are now seeing that production AI agent pipelines fail not because of the models’ abilities but because the model behind the agent decides to stop. Several methods to... Read more ›
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Every query an enterprise AI application processes, every correction a subject matter expert makes to its output — that interaction is training data. Most organizations are not capturing it. The production workflows companies have already built are generating a continuous signal that improves AI models, and it is disappearing.San Francisco-based Empromptu AI on Thursday launched Alchemy Models with a straightforward premise: the AI applications enterprises are already building are generating... Read more ›
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For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaphor to artificial intelligence, assigning estimated intelligence quotients to more than 50 of the world's most powerful language models and plotting them on a standard bell curve.The result is a set of interactive visualizations at aiiq.org that have... Read more ›
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25.07.2026 18:52
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