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arden your system? RSVP here. • Entire – Git hosting, rebuilt for the agentic era. Entire hosts your code in-region, and is up to 89x faster than any other competitor. Mirror from GitHub with a single click – I’ve already done so. Sam Newman wrote one of the most-read books about microservices (“Building Microservices”), but he calls them an architecture of “last resort.” In this episode of the Pragmatic Engineer podcast, Sam explains his thinking on this, and he’s certainly well placed to do so

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s using eight B200 GPUs Next Steps Run the cuOpt mPDLP tutorial to install cuOpt, configure the solver, and compare solve times across GPU counts; Explore the cuOpt source code on GitHub for APIs, solver settings, and deployment guidance Supply chain problems are expanding across more SKUs, lanes, and constraints than ever before, while energy grids are balancing more distributed sources in real time. To meet these challenges, teams need to evaluate larger models and more uncertainty within a pr

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before executing, following the same human-in-the-loop pattern that the remediation solution itself uses. To deploy manually, follow these steps. Clone the AWS CDK code hosted on GitHub:; Navigate to the directory sample-automate-remediation-post-devops-agent-investigation:; Bootstrap the AWS CDK. This is required the first time you use the AWS CDK in a specific AWS environment (a combination of an AWS account and AWS Region); Deploy the stack: The AWS CDK automatically provisions and configure

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nt. By default, the agent gets tools for every provider connected to the project; you can limit which providers and tools it uses. This example limits the agent to Notion, Linear, GitHub, and Slack, and removes delete, archive, and merge tools: Tool entries accept globs, and new connections show up in the running app without a redeploy. Channels Connections can also put your agents in Slack, Discord, or Telegram. Pass channels() to the Mastra constructor and the platform supplies each channel's

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results. AICR v1.0 sets compatibility rules for: aicr CLI’s public commands, flags, exit semantics, and structured output; aicrd REST API and OpenAPI contract; exported API of the github.com/NVIDIA/aicr/pkg/client/v1 package; generated bundle layout and AICR artifact schemas Each public interface has a committed baseline checked before changes merge. The release policy also defines semantic breaking changes. After v1.0, removing or incompatibly changing a stable public interface requires a new m

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$2 Sonnet vision), with a built-in AWS Budget that alerts at 80 percent and 100 percent of a cap you set. The full source code is available in the sample-agentcore-memory-openclaw GitHub repository. Clean up When you are done experimenting, tear everything down to avoid ongoing charges. Because the whole system is one CloudFormation stack, cleanup is mostly a single delete: Delete the CloudFormation stack. This removes the AgentCore runtime agent, API Gateway, the Lambda functions, the Amazon Ev

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thread while Claude was still on its first request there being held until that request finished, or missed when sent seconds apart; [Claude Tag] Fixed Slack threads woken only by GitHub pull request activity or a routine staying on their original model after an admin changed the channel or workspace default model; [Claude Tag] Fixed Claude sometimes posting a spend limit notice in Slack when the real cause was that your organization had run out of usage credits; [Claude Tag] Fixed a session han

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, compare the outputs, then expand until you are comfortable making Databricks the primary home for your dbt project. Ready to try it? Set up a Databricks free trial; Install the dbt-databricks adapter; Run your first dbt compile against a Databricks Lakehouse warehouse. Afterwards, deploy a Databricks Job to execute a dbt model in production by following the Databricks documentation For more on dbt with Databricks, explore the dbt-databricks adapter on GitHub. Get the latest posts in your inbox

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at this exact point. It came after I had the chance to visit the AI labs OpenAI and Anthropic, meet innovative startups like Ramp, Uber and others, get new, unpublished data from GitHub, Factory AI and Linear. The focus of the talk is trend inside of AI labs, VC-funded startups and Big Tech. Thanks to the kind access to these teams! Before the conference, I spent weeks identifying and recording trends that didn’t exist a year ago – or were much more nascent back then – and also things that are

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onfigured with credentials; AWS CDK CLI 2.x installed with npm install -g aws-cdk, and your account bootstrapped with npx cdk bootstrap; The accompanying code from the aws-samples GitHub repository Deploy the solution with AWS CDK The solution deploys with a single CDK script. Clone the repository, configure your AWS credentials, and run the deployment script. For detailed deployment steps, see the README in the GitHub repository. The sample airline data model API Gateway publishes a REST API wi

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マイクロソフトは9月30日付けでリリースされたVisual Studio Code 1.140（以下、VS Code）で、複数のAIベンダから提供されているAIモデルをオーケストレーションすることでより高品質で低コストを実現するという「HydraFusion」機能をリサーチプレビューとして実装したことを明らかにしました（VS Codeのリリースノート、GitHubブログ）。 HydraFusion is now available in @code as a Research Preview. Instead of relying on a single model, HydraFusion orchestrates multiple models and workflows to tackle coding tasks. Give it a try today! HydraFusionとはマイクロソフトの研究プロジェクトであり、GitHubのブログ「Project HydraFusion: Frontier quality via multi-model orchestration」

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ital modes also recovered Kepler’s law with a fitted slope of −1.4991 against the theoretical −1.5. How does JEPA-Anything compare with other world models? Sources: each project’s GitHub README, linked in the header row. JEPA-Anything checkpoint status from its Hugging Face card. Verified October 5, 2026. Key Takeaways OPF splits 1 JEPA target into K orthogonal factors with dedicated predictors; It beat matched JEPA baselines on all 10 dynamics tasks; Interventional Pong single-intervention erro

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ut rather than making a bespoke tool available, Codemode just allows the agent to reach into the AI SDK and invoke those directly. Here you can see how Jev is used to mass process GitHub issues for a quick sentiment analysis: Note how in that above example we also call store() which dumps the result of that execution into the session transcript. A future invocation of Codemode can thus read back that result if it wants to. The Promise.all here is fine, because Pi limits the total number of concu

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t timestamps where matching moments occur Download the latest version of Google AI Edge Gallery app from Google Play Store or Apple App Store to try these new demos. Check-out the Github repo to learn how it’s implemented and start building your own experiences using EmbeddingGemma 2. Productivity boost and context retrieval in Google AI Edge Foresight on Mac We are excited to announce the launch of Google AI Edge Foresight for Mac, an experimental app that brings a context-aware meeting compani

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sent by themselves the next time it was restarted; Fixed sandboxed commands that pipe a heredoc into another command (cat in the terminal; Fixed a marketplace named after another GitHub marketplace's download folder stopping that marketplace from downloading; Fixed automatic compaction giving up with "Prompt is too long" when a Mac went to sleep while it was running; Fixed the rewind menu (Esc Esc / /rewind) freezing for hundreds of milliseconds per keypress when the conversation contains a ver

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lease cadence no longer matches PyTorch’s. That’s expected! If you’re still using the decoding or encoding APIs in TorchVision or TorchAudio, now is a good time to move to TorchCodec: start with our migration guide, and let us know on GitHub if something you need is missing. There is a lot more to say about the media processing libraries, and we’ll do it in a follow-up post: what’s new in each library, and how to get the most performance out of a full decoding and transform pipeline. Stay tuned!

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ills for repeatable workflows, and hooks for pre/post-action automation; Automate recurring tasks and integrate with continuous integration and continuous delivery (CI/CD) through GitHub Actions or GitLab CI/CD To learn more, see Anthropic’s articles: Claude Code tutorials and Claude Code: Best practices for agentic coding. This section provides step-by-step instructions for setting up and configuring Claude Code to work with Amazon Bedrock in AWS GovCloud (US), including prerequisites, installa

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构建的一套软件支撑框架，旨在帮助AI Agent管理和执行更加复杂的任务。简单来说，它可以被理解为让一个大模型真正成为Agent所需要的整套运行系统。 8月13日，DeepSeek Harness v0.1（简称DSH）开发者预览版正式向全球开发者开放测试，并同步以MIT协议公开源代码。项目发布后，迅速在X等社交平台引发开发者热议，不到24小时内，在开发社区GitHub狂揽超过7万颗星。 （原标题：DeepSeek Harness国庆假期上新！90后负责人回应：希望做出让世界AI巨头跟进的创新） 1; 印度尼西亚不同作物的社会经济效益：西米淀粉在生物塑料开发中的机遇 | MDPI Sustainability 2; 文献清单：2025 “神经精神病学”栏目编辑荐读 | Brain Sciences 3; 2025年高引文章荐读 | MDPI Sustainable Chemistry 4; 对话Cells最佳论文奖得主Maik Hüttemann教授：线粒体调控的未解之谜与转化前景 | MDPI 人物专访 5; AI赋能罕见眼病筛查：轻量级卷积神经网络在视网膜色素变性分类中的应用 |

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API calls; bedrock-agentcore Amazon Bedrock agent core functionality; boto3 AWS SDK for Python (Boto3) Deploy and run the solution The solution is available for download from our GitHub repo and provides a single step deployment to deploy and access the solution in your AWS environment: The outputs include runtime ARNs, AnyCompany Retail API URL, evaluator API URL, and memory ARN. Run the solution Follow these steps to run the solution: The test client/ folder contains a Python script that invo

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en3（2025 年 4 月）在 Apache 2.0 下新增混合思考、36T 训练 tokens 和 119 种语言；2026 年在 6 个月内推出 4 代模型（Qwen3.5 到 Qwen3.8），并形成开放/专有的拆分策略；Qwen 4 正在训练中；阿里巴巴的路线图将 Qwen 4.5 和 Qwen 5 定在 5 至 10 万亿参数 Qwen 博客和 GitHub 上的 QwenLM；Hugging Face 上的 Qwen；Qwen 技术报告（arXiv 2309.16609）；Qwen2.5 技术报告（arXiv 2412.15115）；Qwen3 技术报告（arXiv 2505.09388）；阿里云：2026 云栖大会路线图；阿里巴巴集团：2025 云栖大会 Asif Razzaq Asif RazzaqYandex 推出 Sona：一个取代整个推荐级联的单一生成式推荐器；Asif RazzaqGPT-6 Astra vs GPT-6.1 Sol vs Gemini 4 Argon vs Claude Fable 5.1：哪个前沿模型适合哪项工作；Asif RazzaqAl

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