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Harrison Chase and Caspar Broekhuizen of LangChain published an article summarizing the five core components shared by its three internal agents for marketing, sales, and engineering: agents live in existing workplaces such as Slack, a distinction between acting on behalf of users and a fixed identity, global and user-level memory, code execution within a sandbox, and a large number of runs triggered by schedules or events. The article uses GTM Agent, OpenSWE, and Content Studio as examples to e

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In episode 20 of the Interconnects podcast, Nathan Lambert and Florian Brand discussed how Kimi K3.1 Pro ranks high on Artificial Analysis but receives mixed reviews, arguing that its training leans more toward exploitation than exploration, with weaker performance on long-horizon benchmarks such as ProgramBench. The two also discussed the cybersecurity controversy surrounding open-weight models, noting that no large-scale exploitation occurred after the disclosure of the PHP2Shell vulnerability

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Underdog Saluki 27B is a 7.9 GB quantized version of Qwen3.8-27B that, according to its developer, retains tool-calling capability at roughly 2 bits per weight and slightly outperforms the full 54 GB model on a self-built 120-task benchmark. The tutorial places Saluki side by side with ISTA-DASLab's GSQ-RCO quantized version in native llama.cpp, compares GGUF headers tensor by tensor and performs byte-level comparisons, then measures memory and speed on a single GPU, and scores both with the off

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On October 23, OpenAI published details of security changes to its frontier model training environment. Frontier model training is no longer allowed to access the real internet; instead, models practice browsing and search in an offline web environment. In red-team experiments, an Agent, under conditions prohibiting network communication and with no shared writable files, used side channels such as CPU caches to exchange information; in another test, an internal research model exploited a DNS fi

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In the week of October 26 to November 1, the Fed will announce its interest rate decision in the early hours of October 29; 94% of economists expect rates to remain unchanged at 3.75%-4.00%. A super earnings week led by Google, Microsoft, Amazon, and Intel arrives at the same time, and the market will test whether results can reverse the slump in AI trades. Anthropic plans to publish its prospectus as early as the end of October and complete its IPO by mid-November; Apple will hold an event on O

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Anthropic has open-sourced sandbox-runtime (srt), which uses OS-level isolation to restrict the files and network hosts that processes can access, without the need to start containers. The npm package @anthropic-ai/sandbox-runtime v0.0.81 is licensed under Apache-2.0 and requires Node.js 22.12+. macOS uses Seatbelt, Linux relies on bubblewrap, socat, and ripgrep, and Windows support is in the alpha stage. Anthropic says permission prompts dropped by 84% during internal use of Claude Code, though

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In an interview, Claude engineering lead Felix Rieseberg said he barely writes code anymore; his core approach is to hand crash data, business tools, and a computer to the model and let it decide what to fix itself, rather than having a human act as a relay repeating things item by item. He suggests opening multiple threads on the same output dedicated to proving it wrong, then opening another as a judge to filter which criticisms hold up; rather than giving each Agent a tiny slice of data, it i

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Using four security incidents within the week of October 16 to 23 as its thread—including two PHP remote code execution vulnerabilities discovered by AI, the backdoored LiteLLM version v1.107.0 surviving on PyPI for about two hours and being downloaded roughly 49,000 times, the OpenCode console leaking third-party model keys for 1.4% of users, and Microsoft reporting that a human organization used the open-source multi-agent penetration framework ARTEX to attack the supply chain—the article disc

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Developer Gathin used Claude Code to connect to a Xiaomi TV over Wi-Fi, disabled 25 system components and rewrote a minimalist launcher, then open-sourced the prompts, launcher source code and troubleshooting notes as CleanYourTV, which gained about 13,700 stars within days. Another YouTuber, Ansub Khan, tested the TV Detox project and found it raised the TV's available memory from about 370MB to 600–650MB. The article notes that such tools can only clean system-level preinstalled packages and t

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Anthropic, together with the UK AI Safety Institute (AISI), released an investigation report on an AI cyber test loss-of-control incident, and mentioned an unreleased internal research model of its own. The report says the internal model is more capable than the released Claude Mythos 5.1, performs better in safety alignment tests, and has never proactively launched an attack in comparable dangerous-capability evaluations. Replay tests show that Mythos 5 continued the attack from the original at

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gihyo.jp reviews multiple releases and reports from late October, organizing AI-era defense challenges along two lines: vulnerability remediation implementation and permission management. Anthropic Deputy CISO Jason D. Clinton says that within about 18 months, high cyber capability will spread to small, cheap models, but fixes still need to be applied to running systems. The article cites OpenAI's discovery of Brotli's CVE-2026-111497 during testing in an isolated environment, and introduces rem

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The Artefact AI Film Festival, organized by mk2 and Artefact in partnership with LDLC and NVIDIA, is now in its third edition, with the theme "(Dis)Connection" and a registration deadline of December 2, 2026. Submitted films may be up to 314 seconds long and must use at least one generative AI technology in each of the three stages: pre-production, shooting, and post-production; the first prize is 10,000 euros, plus a one-week 30-second screening at an mk2 cinema. NVIDIA recommends using GeForce

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Moonshot AI releases Kimi K3.1 Pro, a multimodal MoE model with 2.8T total parameters, 104B activated parameters, and a 1 million token context window. The Standard and Highspeed versions are now available on the Kimi website, App, Kimi Work, Kimi Code and API. The company says Highspeed offers 2–3x faster output at twice the price of the Standard version. Artificial Analysis ranks it fourth on the Intelligence Index with a score of 55, behind Opus 5.5's 58; on Arena's Code Arena WebDev it ranks

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Gera Dorfman, Chief Product Officer at Orca Security, points out that the built-in security scanning of AI building tools is not enough to prove that an application is secure; security teams need tools that can understand how these platforms build and connect applications. In the case described in the article, a distribution lead at Orca used AI over a weekend to build a partner portal, and the built-in scanning let it pass directly, but after the company's security team tested access permission

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AWS has published a practical guide for multi-turn reinforcement learning (MTRL) on Amazon SageMaker AI. Using Wordle as an example, it deploys the agent and reward function to Amazon Bedrock AgentCore, and the training job updates LoRA adapters via GRPO. In the example, gpt-oss-20b at default reasoning effort improved its solve rate on held-out words from 61% to 84%, at a training token cost of about $339 and an AgentCore runtime cost of about $79. The article also details failures such as two

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Mastra releases MCP Events, enabling MCP servers to send real-time events to connected clients via three methods: push, poll, and webhook, changing the previous situation where servers could only respond passively to requests and clients had to poll on their own. This feature requires @mastra/mcp@2.5.0 and @mastra/core@1.79.0 or above, and is built on Mastra's MCP 2.0 support. Agents can receive event notifications via MCPEventsSignalProvider, workflows can be triggered to run by subscribed even

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TinyFish released two technical guides: one defines a production-grade agent search architecture, and the other summarizes lessons from building a deep research system. The architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks,

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