全部 AI 动态

利用 Amazon SageMaker AI 并发扫描功能优化生成式 AI 端点算力配置

Amazon SageMaker AI 推出并发扫描功能，帮助用户在不同负载水平下系统性基准测试生成式 AI 端点，以实现算力资源的合理配置（Right-sizing）。文章详细介绍了模型部署流程，以及如何利用 CreateAIBenchmarkJob API 运行自动化并发测试，并根据测试结果在算力集群规模（Fleet Size）和容量规划上做出基于数据的决策。

Trane基于Amazon Bedrock AgentCore将建筑诊断洞察效率提升60倍

Trane Technologies在约四周时间内，基于Amazon Bedrock AgentCore构建了一套AI智能体解决方案。该方案将原本需要花费20分钟、涉及多个屏幕的传统建筑诊断复杂工作流，简化为仅需20秒的自然语言交互，使获取建筑运行洞察的时间效率提升了60倍。相关内容详细介绍了该解决方案的系统架构方法与关键设计决策。

Tata Elxsi 基于 AWS 构建工业安全平台 IRIS，实现秒级风险检测

Tata Elxsi 基于 AWS 构建了实时工业安全平台 IRIS。该平台通过在边缘端对摄像头视频进行过滤，利用 Amazon Kinesis 传输元数据，并在 Amazon SageMaker AI 上运行计算机视觉模型，将检测结果关联为高置信度警报。该系统将不安全工况的检测时间从数分钟缩短至数秒，显著提升了工业现场的安全响应效率。

结合 Agentforce 与 AWS MCP 扩展公共部门智能数据处理能力

公共部门机构日常需处理大量如执法记录仪视频和扫描文档等非结构化证据。本文介绍了如何将 Amazon Bedrock 数据自动化与模型上下文协议（MCP）相结合，将这些非结构化多模态数据转化为结构化洞察，并通过自然语言在 Salesforce Agentforce 智能体平台中实现无缝查询与交互分析。

Worker Previews 推出：为智能体的每次代码变更提供独立隔离预览环境

Worker Previews 宣布推出独立预览环境功能，可为 AI 智能体提交的每个分支变更分配专属 URL、独立配置、状态以及可观测性支持。该功能支持开发者与智能体在不影响生产环境的前提下并行测试并验证各项修改，有效提升 AI 辅助编程与自动化开发流程的安全性和协作效率。

Parallel 利用 GPT-6 Astra 将数据调研时间和成本减半

Parallel 宣布采用 GPT-6 Astra 模型赋能其智能体应用。与先前的模型相比，搭载该模型的智能体在调研和整合劳动力市场数据时，将所需时间缩短了一半，同时计算与调研成本也降低了50%，显著提升了特定场景下的工作效率与经济效益。

The Reliability Layer for Healthcare AI: Common LangSmith Use Cases

How to Evaluate AI Agents From Tool Calls to Task Completion

When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and...

Run Positron on Amazon SageMaker AI for data science workflows

Positron, Posit's IDE for data science, now runs on Amazon SageMaker AI. This post shows how a data scientist explores an Amazon Athena table, validates features in R, trains an XGBoost model in Python, deploys a real-time SageMaker AI endpoint, and reports results with Quarto, all in one governed SageMaker Studio Space.

How Benchling secured multi-tenant AI agents with Amazon Bedrock AgentCore

Learn how Benchling built a defense-in-depth security architecture to run untrusted, AI agent-generated scientific code across thousands of life sciences tenants using Amazon Bedrock AgentCore Code Interpreter in VPC mode, combined with Amazon Route 53 Resolver DNS Firewall and VPC endpoint policies to block data exfiltration, including through DNS.

Reducing medical claims review time with AI on AWS: The EXL Medical IDP solution

EXL built an AI-powered Medical intelligent document processing (IDP) solution on AWS, combining IDP with domain-specific large language models on Amazon SageMaker and Amazon Bedrock to extract, summarize, and query medical records at enterprise scale and cut claims review time from over 100 minutes per case.

Announcing vllm-metal: Concurrent Serving on Apple Silicon

vllm-metal brings vLLM's paged, continuously batched serving stack to Apple Silicon, with flatter TTFT under concurrent agent load, batched MTP, and automatic M

AI Security Is an Engineering Problem — How to Solve It at Every Layer of the Agent Stack

AI security is an engineering problem. That means defined security requirements, enforceable controls, named owners and evidence that protections work. As AI becomes more capable, the industry must accelerate security engineering, broaden access to defensive tools and share what works faster. Technology Changes, Security Fundamentals Endure The internet and cloud computing changed how software operates, […]

Higgsfield AI ships new video features in a day with GPT-6 Astra

With GPT-6 Astra, Higgsfield AI makes video ad creation easier for small businesses and brings new creative tools to market faster.

How V7 gives AI agents institutional memory

Using GPT-5.6, V7 turns scattered company files into context agents can use to complete complex, source-linked work.

Jev is now available in LangSmith Evals

MCP was always a bad idea?

My comment on MCP was always a bad idea? — Hacker News. This article entirely misses the value that MCP brings today. Sure, there's almost no reason to use MCPs if you are running a full-blown terminal agent (Claude Code, Codex, Meta Muse, OpenClaw etc) with unfettered internet access - just let it call APIs directly. If you want to operate something that's less YOLO than that, you'll find yourself wanting: Control over exactly which external services it can access A way to handle authentication that doesn't allow the agent to directly access API keys A sensible UI to allow users to connect and authenticate further services Strong audit loggi

llm-keys-ui 0.1

Release: llm-keys-ui 0.1 This plugin solves a very specific problem. I've started using Codex Remote to run coding agents on various machines while controlling them from my phone. Sometimes I use those machines to hack on LLM projects, and occasionally that means I need to configure an API key. I don't like pasting API keys into agent sessions, so I wanted a way to get those keys onto a machine without pasting them into the ChatGPT app directly. With this plugin, I can tell Codex to run: uvx --with llm-keys-ui llm keys-ui --all Then have it tell me the URL - including local network or Tailscale device IPs - for an interface to save additional

Pocock plans with notecards, Pi 0.86 rewrites the transcript, JevBench ranks the clones, Anthropic's IPO slips to November

A quiet Saturday with one honest confession at the centre: Matt Pocock spent weeks trying to make agents better at planning his course, then did it with notecards, pen, paper and scissors and found that the slow medium let him make decisions at human speed, while the agent distracted him, jumped to conclusions and drowned his thinking in commentary. Armin Ronacher asked what people struggle with most in AI-assisted engineering, called Sunil Pai's senior engineer death spiral mandatory reading, and warned that Pi 0.86.0 may regress because mid-conversation system messages now live in the transcript. Theo is tired of being asked for a harness t

Jev-as-a-Judge for Agent Evals

v2.1.278

What's changed Changed auto mode for Claude API and Enterprise users, and on Bedrock, Vertex, Foundry and gateways, to default to the server-side classifier, which does not charge for classifier overhead ( CLAUDE_CODE_AUTO_MODE_SERVER=0 opts out on Bedrock, Vertex, Foundry and gateways); warns on billed fallback. See https://code.claude.com/docs/en/auto-mode-classifier-billing Added an Auto mode server row to /status showing whether this session's auto mode classifier runs on the server

v0.34.3-rc0

api: expose model thinking levels and defaults ( #18473 )

Quoting Thariq Shihipar

We're adding support for AGENTS.md to Claude Code. Starting today in version 2.1.277, if there is no CLAUDE.md in a folder, Claude will check for and use AGENTS.md. AGENTS.md support is built off of Claude Code mods, our upcoming way to customize the Claude Code harness. This is a built-in mod, but you’ll be able to build custom versions of project instructions yourself as you’d like too. You can see the source for the mod here ! — Thariq Shihipar , there are more mods here Tags: thariq-shihipar , coding-agents , anthropic , claude-code , generative-ai , ai , llms

v2.1.277

What's changed Added AGENTS.md support: in a project with no CLAUDE.md, Claude Code reads AGENTS.md instead; change it under "Project instructions" in /config (not yet on Bedrock, Vertex or Foundry) Added CLAUDE_GATEWAY_PROXY_IS_EGRESS_BOUNDARY=1 for Claude apps gateways whose only egress is a forward proxy: every outbound request hands the proxy the hostname instead of resolving it locally Added an optional headers: map on Claude apps gateway upstreams, to send static headers to a proxy you run in front of a provider Added a line saying a background task's update is waiting when it finishes while a panel such as /tasks is open Fixed claude -

Should you read the code, is RAG dead, and did Skills kill MCP?

We dive into these questions and other AI hot takes on the latest episode of the GitHub Podcast. The post Should you read the code, is RAG dead, and did Skills kill MCP? appeared first on The GitHub Blog .

Co-creating the future of fashion with Google

Jane Wade and Sergio Hudson

v2.1.276

What's changed Fixed every request failing with 400 … Input tag 'advisor_20260301' when ANTHROPIC_BASE_URL points at a proxy or gateway (2.1.275 regression)

How To Write With An LLM

How To Write With An LLM Thomas Ptacek on using LLMs as copyeditors, not as writing assistants: Rule Number One: You may not use a single word an LLM suggests to you. [...] I think that as a form of intellectual personal protective equipment you should adopt the rule that any specific turn of phrase an LLM suggests is off limits. Be strict about the rule! I won't let LLMs write content for my blog, but I use them for fact-checking, spelling and grammar and as an occasional thesaurus (see my proofreading prompt ). The rule to never use a turn of phrase suggested by an LLM feels good to me. The text has that weird smell to it, and it's also a g

v0.34.2

What's Changed Added first-run setup when running ollama , with options to sign in or continue locally. Setup completion is shared with the desktop app on macOS and Windows. Added ollama://apps to open the desktop app’s Apps page directly on macOS and Windows. Fixed excessive memory growth during long generations with MLX speculative decoding. Updated llama.cpp. Full Changelog : v0.34.1...v0.34.2

v2.1.275

What's changed Added the signed-in account to Claude apps gateway sign-in: when the gateway names it, you confirm it before the credential is saved, and /status shows it Added a send-now key (ctrl+enter, or ctrl+x ctrl+s) that interrupts the current turn and sends all queued messages at once; sent and queued messages show in gray until the model receives them Added a startup warning when a configured otelHeadersHelper fails, so sessions that silently export no telemetry are noticed Added syncing of the skills and plugins enabled on your claude.ai account to terminal sessions signed in with it; opt out with syncClaudeAiSkills: false or syncCla