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#Agent

Today 3 items
Jul 16Thu
  1. Hugging Face Blog87

    Security incident disclosure — July 2026

    Hugging Face disclosed that this week it detected and contained a production infrastructure intrusion driven end-to-end by an autonomous AI agent system, in which attackers exploited two code execution paths via a malicious dataset to gain access to processing nodes, steal some internal datasets and multiple service credentials, with over 17,000 attack event records examined.

    Why it matters: The official disclosure gives a complete account of an agent-driven intrusion and response, plus a practical lesson for defenders on self-hosting open-source models for forensics.

Jul 15Wed
  1. Hugging Face Blog80

    Welcome Inkling by Thinking Machines

    Thinking Machines has released the open-source multimodal model Inkling on Hugging Face, with about 1T total parameters (975B, a MoE with 41B active), natively accepting image, text, and audio inputs, supporting 1M context, trained on 45 trillion tokens, and shipping BF16 and NVFP4 weights.

    Why it matters: The official blog provides architecture details, VRAM requirements for each tier, and deployment configurations, letting readers evaluate multimodal deployment costs and model selection.

Jul 7Tue
Jul 1Wed
  1. Berkeley AI Research33

    2026 BAIR Graduate Showcase

    The Berkeley AI Research (BAIR) lab releases its 2026 PhD graduate showcase, highlighting graduates such as Baifeng Shi, Charlie Snell, and Hanlin Zhu and their work in robotics and embodied intelligence, LLM reasoning and test-time scaling, generative models, AI safety and human-AI interaction, and speech and medical AI.

  2. Hugging Face Blog61

    Hugging Face and Cerebras bring Gemma 4 to real-time voice AI

    Hugging Face and Cerebras jointly demonstrated a real-time speech-to-speech architecture: voice input is transcribed by Nvidia's Parakeet, reasoning is handled by Google DeepMind's Gemma 4 31B running on Cerebras, and speech output is synthesized with Alibaba's Qwen3TTS.

    Why it matters: The article lays out a complete open-source speech-to-speech stack with components at each layer, so developers can build or swap parts of their own real-time voice AI pipeline.

Jun 25Thu
  1. Google DeepMind69

    Introducing computer use in Gemini 3.5 Flash

    Google DeepMind announced that computer use is now a built-in tool in Gemini 3.5 Flash, whereas the capability was previously available only as a standalone Gemini 2.5 computer use model.

    Why it matters: The article explains that computer use has moved from a standalone model to being built into Gemini 3.5 Flash, and gives an API entry point and enterprise-grade safeguards, making it easier to evaluate automation scenarios.

Jun 24Wed
Jun 22Mon
  1. Chrome Developers · AI and Browser68

    A developer toolkit to make your website agent-ready

    Chrome released an agent-ready toolkit for developers, and Lighthouse gains a new Agentic browsing audit category from M150, checking three metrics: accessibility tree, CLS visual stability, and WebMCP integration.

    Why it matters: The article details the specific checks in Lighthouse's new Agentic browsing audit and Chrome DevTools debugging methods, so developers can directly improve how agent-friendly their sites are.

Jun 18Thu
Jun 16Tue
  1. Google DeepMind54

    Securing the future of AI agents

    Google DeepMind released the AI Control Roadmap, adding a system-level security layer on top of traditional alignment, sandboxing, and prompt injection defenses. It treats internal agents as potentially misaligned "insider threats," builds a threat modeling framework based on MITRE ATT&CK, uses trusted AI supervisors to detect and block harmful actions, and measures effectiveness by coverage, recall, and response time.

Jun 10Wed
Jun 9Tue
  1. Google DeepMind76

    Introducing Gemma 4 12B: a unified, encoder-free multimodal model

    Google DeepMind released Gemma 4 12B, a unified, encoder-free multimodal model in which vision and audio inputs go directly into the LLM backbone, positioned between E4B and the 26B MoE.

    Why it matters: The article details the encoder-free architecture, 16GB-memory runnability, and Apache 2.0 open sourcing, helping readers evaluate on-device deployment options.

  2. Chrome Developers · AI and Browser65

    Join the WebMCP origin trial

    Chrome announced the WebMCP origin trial in Chrome 149, letting developers build structured tools for web apps that declare the purpose of buttons, input fields, and other UI elements and manage page state, so agents can complete tasks without guessing.

    Why it matters: With the official WebMCP origin trial open, developers can let agents operate web forms and debugging flows via declared tools and submit API feedback.

May 29Fri
May 28Thu
  1. Mistral AI47

    AI Now Summit 2026

    At AI Now Summit 2026, Mistral unveiled a full-stack AI offering for industrial engineering, partnering with Airbus, BMW and ASML across design, simulation and production while ensuring data sovereignty. Its agent product Vibe was upgraded into a unified agent that handles long-horizon multi-step work, from deep research and coding to merging PRs. A 10 MW inference data center in Les Ulis, France, is slated to come online in Q3 2026.

  2. Mistral AI69

    Vibe gets to work.

    Mistral launched the unified AI agent Vibe, with Le Chat fully upgraded to Vibe; existing plans, history and settings migrate automatically. Work Mode targets long-horizon multi-step tasks spanning enterprise knowledge search, data analysis, document drafting and scheduled jobs; Code Mode supports remote coding sessions, parallel runs and sandbox isolation, along with a VS Code extension and an updated CLI.

    Why it matters: The official announcement fully covers Vibe's Work and Code modes, pricing and access points, letting readers assess its impact on daily workflows and coding processes.

  3. Mistral AI64

    Introducing Search Toolkit

    Mistral AI released the public preview of Search Toolkit, an open-source framework for building production-grade search pipelines for AI applications, unifying ingestion, retrieval and evaluation in a single shared-interface framework.

    Why it matters: The original details modules, evaluation metrics and enterprise case studies, helping readers judge whether it can replace their existing retrieval infrastructure.

May 22Fri
  1. Mistral AI70

    Remote agents in Vibe. Powered by Mistral Medium 3.5.

    Mistral released the 128B open-weight flagship model Mistral Medium 3.5 (public preview), combining instruction following, reasoning and coding, with a 256k context window and a SWE-Bench Verified score of 77.6%. API pricing is $1.5 per million input tokens and $7.5 per million output tokens.

    Why it matters: The original provides model specs, benchmark scores, pricing and the open-weight access point, useful for evaluating it for self-hosting and asynchronous coding use cases.

  2. Mistral AI59

    Connect the dots: Build with built-in and custom MCPs in Studio

    Mistral released Connectors in public preview for Studio; both built-in connectors and custom MCPs can be used via API/SDK with all models and agent calls. New features include direct tool calls, human-in-the-loop approval flows, and programmatic management of connectors. Once centrally registered, connectors can be reused in LeChat and AI Studio, making it easy to connect to enterprise systems like CRMs and knowledge bases.

May 20Wed
May 17Sun
May 16Sat
  1. Google DeepMind49

    Accelerating discovery of liver disease mechanisms

    University of Edinburgh bioengineer Filippo Menolascina used Co-Scientist to study metabolic dysfunction-associated steatohepatitis (MASH), screening candidate combination therapies from a vast body of literature. Addressing why the drug resmetirom works for only some MASH patients, the system proposed the hypothesis that the NLRP3 inflammasome is a molecular bridge linking inflammation and metabolism — a hypothesis later validated experimentally, pointing toward dual-target therapies.

  2. Google DeepMind84

    Gemini 3.5: frontier intelligence with action

    Google DeepMind has released the Gemini 3.5 model family, starting with 3.5 Flash, positioned for agents and coding. It outperforms Gemini 3.1 Pro on Terminal-Bench 2.1 (76.2%), GDPval-AA (1656 Elo), MCP Atlas (83.6%), and CharXiv Reasoning (84.2%), with output speed 4x that of other frontier models.

    Why it matters: The official release shares 3.5 Flash's benchmark scores, availability channels, and plans for a Pro follow-up, letting readers evaluate its trade-offs for agent and coding workloads.

May 12Tue
  1. Google DeepMind66

    Co-Scientist: A multi-agent AI partner to accelerate research

    Google DeepMind has published Co-Scientist in Nature, a Gemini-based multi-agent system that generates, debates, and evolves hypotheses to accelerate scientific research. It is being opened to individual researchers through the experimental Hypothesis Generation tool, rolling out within weeks, with sign-up at labs.google/science.

    Why it matters: The official release provides the system architecture, existing experimental results, and an open registration portal, letting readers assess its fit for research workflows.

May 8Fri
May 6Wed
  1. Google DeepMind67

    AlphaEvolve: How our Gemini-powered coding agent is scaling impact across fields

    Google DeepMind has released a one-year impact report on AlphaEvolve, the Gemini-powered coding agent that has expanded from pilots to multiple research and commercial domains.

    Why it matters: The official report details AlphaEvolve's concrete results and figures across research and commercial settings over the past year, showing the real-world reach of this kind of algorithm-discovery agent.

May 4Mon
Apr 30Thu
Apr 27Mon
Apr 22Wed
Apr 21Tue
Apr 20Mon
  1. Berkeley AI Research44

    Gradient-based Planning for World Models at Longer Horizons

    Berkeley AI Research proposes GRASP, a gradient-based world model planner that makes long-horizon planning more practical. Three core improvements: lifting trajectories into virtual states so optimization runs in parallel over time, injecting randomness directly into state iterations to support exploration, and reshaping gradients to avoid traversing fragile state-input gradients of high-dimensional vision models.

Apr 9Thu
Mar 31Tue
Mar 25Wed
Mar 18Wed