搜索“AWS”

证明了自己。Anthropic正在Trainium2和Trainium3上运行生产推理和RL rollout。从历史上看，Trainium在推理方面表现出色，但并非研究训练的最佳选择。在推理中，模型架构的变化速度比训练慢得多；在训练中，研究人员会对模型架构进行大量不同的实验和消融，需要一个覆盖广泛API表面的技术栈。过去，这正是Trainium的短板所在。 AWS Neuron团队正积极努力改变这一缺陷，最大的转变是迈向一流的原生PyTorch训练体验。在训练循环中到处撒xm.step()、与定制的XLA式执行模型较劲的日子已经一去不复返。Trainium现在以PyTorch用户所期望的方式运行PyTorch——eager模式，配合torch.compile和标准API。 SemiAnalysis工程团队过去几周一直在试用Trainium3机架，发现体验很棒——我们很喜欢它整体的发展方向。需要说明的是，它还不完美，我们自己也遇到了几个bug。它远未达到CUDA生态的成熟度，但方向是对的。他们的团队借助智能体编码正在快速推进。 此外，与其他加速器公司不同——我们曾不得不费尽周折才能让他们

匹配字段正文

ne. Its tool description calls it a last resort. For long tasks I'd reach for it first. The model is yours. In practice that means an OpenAI key, an OpenAI-compatible endpoint, or AWS Bedrock with MODEL PROVIDER=bedrock. The docs also mention an Anthropic key, but the server code doesn't read it; on the OpenAI path, without OPENAI API KEY the agent tool fails. The default config it writes on first run uses gpt-4.1-mini, and on Bedrock that config model wins, so also set BROWSER USE LLM MODEL to

匹配字段正文

in the Middle、Judging the Judges）、协议规范（MCP 固定到 2025-11-25 版本、W3C Trace Context、OpenTelemetry、RFC 8693 与 RFC 9700）、厂商与标准组织的工程文档（Anthropic 的 Agent 与上下文工程文章、LangGraph、Temporal、Stripe、AWS、PostgreSQL、Google SRE、OWASP、NIST）。论文结果只在原研究任务、模型和预算下成立；厂商文档用于确认机制，不代表跨产品的能力保证；动态 API、模型价格和产品套餐不作为长期前提。 法律、司法解释与部门规范性文件：民事诉讼法、登记立案规定、在线诉讼规则、最高人民法院人工智能司法应用意见、个人信息保护法、医疗卫生机构网络安全管理办法、互联网诊疗监管细则、卫生健康行业人工智能应用场景参考指引。它们在文中只用于说明 Agent 的职责边界、人工确认要求与数据边界，正文分别标注文件性质，相关表述一律是本系列对规则的工程理解，不构成法律意见；具体适用仍需法务与业务负责人判断。 作者的参考设计与演算：两个案例、全

匹配字段正文

player and enemies. Water also affects combat: an eel’s discharge travels through connected water, so stepping onto dry stone protects the player from that discharge. Hollowflux draws its game art in code, with water that reacts to movement and combat. Building and sharing games What I like about working with Astra is that I can start with the experience I want, use images to make the visual direction concrete, and give feedback from actually playing. A complaint about a disappearing planet can

匹配字段正文

behind only GPT Image 2 (high), up from 8 for Nano Banana 2. That lines up with its Layout and Text Rendering gains. Its largest use-case gain is Live-Action Film, now 3, which draws on its Human Anatomy. It is also 3 for Retail & Ecommerce. Architecture & Real Estate is the weak spot, at 7. ➤ Productivity & Knowledge Work covers diagrams, infographics, charts and slides. ➤ Live-Action Film covers cinematic scenes, film stills, storyboards and character sheets. ➤ Retail & Ecommerce covers produ

匹配字段正文

is in the public anthropics/claude-code repository under mods/, so you can read how the team builds them. Token Weather reads how full the context window is after each turn and draws one line above the prompt: a weather icon, the percentage, the tokens used out of the window, a small chart of recent turns, and how much the last turn added. Here it is in a real session. Each turn reads more files, and the band fills from ☀ Clear to ☂ Showers to ☇ Storm: The shortcut: let Claude build it You can

匹配字段正文

etwork NAD, for hardware-offloaded Open vSwitch; rdma ib / rdma roce: rdma/ib, rdma/roce, or nvidia.com/rdma , with one NAD per rail or a host-network fallback; Provider-specific: AWS EFA (vpc.amazonaws.com/efa and libfabric), DOKS (rdma/fabricN with roce-net-fabricN@fabricN), and GKE DRANET (DRA claim templates and pod resourceClaims) Device setup and the NCCL plugin on top of it can change job performance. On Google’s GB300, the built-in NCCL library picked an unroutable link-local GID and hun

匹配字段正文

cording — it’s Chrome resizing the page, not the handoff from the static composer to the real one (that measured 0 px on all 49 of your loads today). On the new-tab page, Chrome draws its own 56 px footer below the page (“Managed by anthropic.com · Customize Chrome”). When the tab navigates to claude.ai the footer goes away and the page gets 56 px taller, but only 100 ms after our first paint; /new puts the greeting and composer 18% of the page height from the top, so they drop 0.18 × 56 ≈ 10 px

匹配字段正文

s with their own customers: Salesforce, Zocdoc, SAP, telli. Pipecat's lean toward companies that build tooling or reference architectures for other developers: NVIDIA's Blueprint, AWS, Anthropic 3. Can I get a working agent going today? When evaluating each framework it's important that you can easily build (and reason about the code for) a voice or video agent. Given AI-augmented development, a developer should be able to get an agent working in a day with either. Independent write-ups comparin

匹配字段正文

to use a tool-augmented reflection pattern, the model may access external systems, such as a search engine, to complete its evaluation. The model catches and catalogs potential flaws that need to be fixed before responding to the customer. 3.Refine The agent feeds its original draft and critique back into the generative model. It uses the additional context to revise its response. It corrects errors and removes irrelevant information to produce a higher-quality output. It’s important for the ag

匹配字段正文

reasoning There’s a useful distinction between storing information and using it to solve a problem. For instance, the Beyond Parameters: Exploring Virtual Logic Depth for Scaling Laws paper from June 2025 investigates this by measuring memorization and reasoning in an LLM separately. First, in the memorization experiments, looping leaves the amount of stored information nearly unchanged when the parameter count stays fixed. Increasing the number of distinct parameters does increase this capacity

匹配字段正文

This episode is a learning‑focused podcast. We walk through the Kimi K3 technical report, hoping to appreciate “the beauty of technology” together. Yutao draws connections to more than ten related papers as he breaks down the report. Fair warning: he speaks really fast. https://t.co/7D9O7cd5ff

匹配字段正文

tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

匹配字段正文

ion of Rust's "unsafe" code blocks and concurrent code with custom locking schemes, re-establishing machine-checked safety guarantees for performance-critical implementations like AWS's Nitro Isolation Engine; Amazon uses Verus to prove correctness of key primitives in critical infrastructure, and the tool has been adopted by open-source projects including certificate validation libraries, data format parsers, and distributed systems like Kubernetes controllers Many open-source and industry soft

匹配字段正文

le are stable enough to guide future work. Standardization follows proven practice; it does not attempt to predict every path in advance. 4.2.2 Starting Context Starting Context draws the line between known state and assumption. A Task may begin from a blank state, a prepared environment, or an upstream result. What matters is that the source and verification status of that state remain explicit. Custom Setup records conditions prepared for the current Task, such as the model, container image, d

匹配字段正文

ith a minimal attack surface and a focus on security, like Firecracker . I had the AI agent run against Firecracker. It was able to hardlock the machine due to more Linux kernel flaws (all patched in upstream), but could not successfully escape. It may have, given even more time, but Firecracker is obviously a substantially harder target. In general, we have to become much more attentive to security fundamentals: least privilege (regarding network access, credentials, available features, etc.),

匹配字段正文

mulation path) Python 3.12+, on Linux or macOS (Apple Silicon supported for the MuJoCo backend). A Strands-compatible model provider for the agent's reasoning. Amazon Bedrock with AWS credentials, the Anthropic API , OpenAI, or Ollama running locally. Strands Robots with the dataset extras: uv pip install -U "strands-robots[sim-mujoco,lerobot] =0.5.1" . The lerobot extra pulls in LeRobot ( =0.6.1), datasets , av , and torchcodec , so recording and video decode both work without further setup. Re

匹配字段正文

t be carefully secured. While frontier models make adversarial manipulation more difficult, with sufficient time and expertise, nearly all of them can still be subverted. Common flaws we observed include: weak access control (permitting any user to access the agent), execution and file-write tools that create opportunities for RCE, insufficient network egress controls permitting data exfiltration and reverse shells, and secrets in plaintext inside the execution environment accessible by the agen

匹配字段正文

mory. It’s completely changed how our security team works. The RAG layer: Giving alerts a memory The first thing we built was a retrieval-augmented classification system on top of AWS Bedrock Knowledge Bases and Amazon Kendra. Again, our initial goal was just to surface historical context about what had happened the last time the same alert fired, and maybe suppress duplicate alerts. When a Panther alert fires, our Lambda handler converts it into a standardized document and indexes it into Kendr

匹配字段正文

That is the unusual part. Firecracker is normally run on bare-metal servers, where you rent the whole physical machine. To reduce customers' cost, we run it on regular EC2, where AWS has already put your server inside a VM. This should be slow. Nested VMs make memory and CPU operations more expensive, and Chromium takes time to start. This post is about how we made this setup fast and efficient. But first, why did we rebuild our infrastructure? When we first built our browser infrastructure on

匹配字段正文