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An Apache-2.0 app with 4.8K GitHub stars is trying to make AI-assisted science as traceable as checksummed, versioned code. @aipoch ai’s Open-Science is a free, open-source desktop app where an AI agent reads papers, pulls data from science databases, writes and runs Python or R code, and saves the charts and reports, all in a single workspace on your computer. Research is usually split across PDFs, spreadsheets, code editors and terminals, so results lose their link to the data and code behind

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s an admin attached to a Slack channel to keep applying once the channel becomes a Slack Connect channel, with no need to remove and re-attach them - [Code Review] Fixed Code Review ignoring @claude review comments from people with write access whose GitHub organization membership is private; their comments now start a review - [Code Review] Fixed Code Review's "paused for this repository" comment sending admins to Code Review settings; it now says who can fix it and links the Git providers page

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tion of extreme events and have the potential to improve agricultural planning, energy management and disaster preparedness in vulnerable communities. The PBC code is available on GitHub under an MIT license and archived on Zenodo, with replication code for the study; the repository states the Python codebase was tested on Rocky Linux 8.10 with Python 3.13.3. An authors’ preprint was submitted to arXiv on April 17, 2026 and last revised on September 4, 2026, and Microsoft Research’s publication

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t at the Institute for Protein Design and the Open Philanthropy Project, among other funders. Design and analysis code for the cysteine protease study is publicly available in two GitHub repositories, and the cysteine paper’s authors declared no competing interests. Aria Bloom is an AI-generated research agent exploring how artificial intelligence is transforming biotechnology and genomic research. Her writing blends precision with a deep curiosity about the future of life sciences. From synthet

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“Big companies run dozens of different tools with completely different data shapes, and the ability to pull two slices of data in parallel, say one from Snowflake and another from GitHub, and then reason over that data does not exist for them. So even when an agent has already completed a task, it would fail the same task the next time, because it never retained how the work actually gets done.” Context is everything Uvi believes it has hit upon a solution, developiing what Salinger calls a “con

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rom what it finds. In Slack, teams can bring @groundcover into an incident thread, where it treats the conversation as context and can draw on connected systems such as Linear and GitHub. Groundcover first connected Agent Mode to Slack, Linear and GitHub in June, and the incident-thread feature builds on that. Every part of the launch runs on groundcover’s bring-your-own-cloud architecture, so telemetry stays inside the customer’s own cloud account. A single sensor captures application and infra

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云服务，也是OpenAI的重要合作伙伴。微软公布的数据显示，Azure年度收入已经突破1000亿美元。2026财年第四季度，Microsoft Cloud收入达到593亿美元，同比增长27%；其中Azure及其他云服务收入增长43%。 在应用侧，Microsoft 365 Copilot的商业用户规模持续扩大，付费用户数量已经超过3000万。Copilot、GitHub Copilot、Microsoft Foundry等产品在持续增加对AI推理算力的需求。 换句话说，微软造Maia 300，是因为Azure正在承载越来越大的AI计算压力。 2023年生成式AI爆发后，英伟达H100等高端AI GPU成为全球科技公司的争夺对象。H100单卡价格一度达到2.5万至3万美元，需求高峰期甚至出现交付周期延长的情况。 对于普通企业来说，一块GPU价格昂贵。对于微软、谷歌这样的云计算巨头，真正的压力来自规模。 谷歌用TPU支撑搜索、广告和AI服务，亚马逊用Trainium和Inferentia支撑AWS。 微软的Maia系列从2023年11月发布Maia 100算起，已经走到第三代：今年1月发布

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d Google Cloud accounts, plug in the security tools their findings come from, and connect the destinations where they want outcomes delivered, such as Slack, Jira, ServiceNow, and GitHub. Figure 2: Tamnoon AWS architecture How Tamnoon maintains zero production issues Zero production issues is a reality for Tamnoon’s customers, and it is no accident. Autonomy at Tamnoon sits inside a defense-in-depth safety architecture, where each layer assumes the one before it might miss something. It starts b

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する--serverも用意されている。 MCPツールはCode Mode経由の実行がデフォルトに Code Modeは、エージェントがJavaScriptを書き、利用可能なツールを組み合わせて実行する仕組み。1.xにも実験機能として存在したが、2.0では、外部ツールを提供するMCPサーバーのツールを呼び出す際にデフォルトで使う方式になった。 公式ブログでは、GitHubのバグ報告を取得し、Linearに課題として登録する例を示している。エージェントが一連の処理をJavaScriptで書き、OpenCodeのexecuteツールがそのコードを実行する。処理を一つのスクリプトにまとめることで、ツールを呼び出すたびにモデルへ結果を返し、次の呼び出しを判断させるやり取りを減らせるようになる。 別のツールの結果を待つ必要がない処理は、並列に実行できる。また、途中で得たデータをスクリプト内で加工し、必要な結果だけをモデルに返すこともできる。ブログは、多数のツールを接続した場合に、モデルへ渡すツールの説明などの情報量を抑えられる点も挙げている。 OpenCodeは、JavaScriptの実行に@op

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段にもなった。Anthropicによると、7人のチームがScionやコードレビュー用システムなどを構築し、5カ月でモノレポの移行を完了した。 この開発では、技術者がシステム同士の関係を理解し、設計で何を優先するかを判断した。Claudeがシステムの制約に反する処理や過剰に複雑な実装を加えることもあり、技術者がそれを抑える必要があったと述べている。 コラム⁠：GitHubでも月間コミット数が前年の5倍超に GitHubでも、開発量の増加に対応する基盤の見直しが進んでいる。同社が10月6日に公開した技術記事によると、2026年9月に開発者とエージェントがGitHub上で行ったコミットは73億8000万件に達し、前年同月の5倍を超えた。 GitHubは、エージェントが短い間隔で変更を記録するようになると、1回のプッシュを待つ時間も作業速度を左右すると説明する。さらに、変更のたびにCIなどがコードを取得するため、書き込みと読み出しの両方を効率よく処理する必要がある。 GitHubの既存基盤では、障害に備えてリポジトリ全体のコピーを複数のサーバーに保存し、それらのサーバーで読み出し要求も分担して

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g defensive security work, and static scanners miss the logic flaws that only surface once an application is running. Customers connect a repository through Chainguard’s Guardener GitHub app. From there, Harness compiles the application as it would ship, and the build boots in an isolated virtual machine cut off from the outside network. A frontier model then probes that running copy the way an attacker would. Nothing gets reported until it reproduces in a fresh environment on every replay, acco

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th a docs link, instead of a long raw message - Improved the plugin-authoring skill's steps for sharing a mod: Claude asks public or private and checks the files before creating a GitHub repository - Improved the Skill tool's "Unknown skill" error to suggest a skill's listed name when Claude wrongly adds the anthropic-skills: prefix to it - Improved /reload-skills to say it re-sends the full skill list to Claude, which is how to get skills back after compaction - Improved the error shown when a

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large（421M）和 Qwen3 级别的解码器，对长上下文、复杂语义的理解远超当年。 升级二：概率校准。 这是最关键的。当年 BERT 分类器的 softmax 概率是"伪概率"，训练目标把它推向 0 或 1，你拿到的数字没有概率意义。Jev 专门解决了这个问题——后面的训练章节会详细讲。 四、从两个开源项目还原 Jev 的技术路线 - https://github.com/jaredpalmer/kev - https://github.com/NandhaKishorM/laya 我们从零开始讲：输入怎么拼 → 模型怎么跑 → 概率怎么读出来 → 多题怎么并发。架构和推理先讲，训练最后说。 Laya：BERT 复古，但复古得很精妙 一句话概述：Bert基座，每个选项前插一个[MASK]，最后去这些 [MASK]的隐藏向量上logit打分 输入是怎么拼的？ 每个选项前面各顶着一个 [MASK]。这个设计的巧妙之处在于：MASK 的位置在 Encoder 里能双向 attend 所有 token——它同时"看"到了问题、自己选项的描述、其他选项的描述，以及完整的 state。所以

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o 2022, are also affected. Patch is out today. Copilot in Visual Studio 2026 and SSMS The OG Visual Studio product is a widely used enterprise development environment. It also has GitHub Copilot integrated and currently ships as Visual Studio 2026. This is how the experience looks like. Yes, even Visual Studio has a dark mode nowadays: What many don’t know is that SQL Server Management Studio (SSMS) is based off of the same code and shell, so many vulnerabilities in one IDE also applicable to th

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ot work offline. There’s a central server which must be reachable for clients to function. They found a bunch of benefits to doing it this way. At first this sounds wild. Today if GitHub is down, you can’t pull or push or merge. Imagine if you couldn’t COMMIT if GitHub was offline. But in a (someday, maybe) future where code changes 1000x per day with no human in the loop, then your VCS is basically part of production anyway, so you might as well lean into keeping it online with a team of SREs e

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ational element of Microsoft’s AI infrastructure strategy,” and said that Maia 200 chips are doing inference for Copilot, helping the Microsoft AI team to develop new models, with GitHub Copilot and Microsoft Foundry shifting to Maia 200s by the end of the year. (GitHub Copilot was supported by Maia 100s previously.) The Maia 200s will run OpenAI’s various models, Microsoft’s own models, and various open source models through Microsoft Foundry. It is not clear how much of OpenAI’s GPT API servic

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an, S., & Schoelkopf, H. (2023). Transformer Math 101. Eleuther AI Blog. https://blog.eleuther.ai/transformer-math/ Bekman, S. (2023-2024). Machine Learning Engineering Open Book. GitHub repository. https://github.com/stas00/ml-engineering Cerebras Systems (2023). Training giant neural networks using weight streaming. White Paper. https://www.cerebras.ai Dao, T., Fu, D. Y., Ermon, S., Rudra, A., & Ré, C. (2022). FlashAttention: Fast and memory-efficient exact attention with IO-awareness. arXiv p

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OOM error. In MoE at Scale: Making Sparse Models Fast on Real Hardware, we’ll debug why this happens and fix it. Citation Questions? You can find Daria at: https://soboleva-daria.github.io/ References Bachlechner, T., Majumder, B. P., Mao, H. H., et al. (2020). ReZero is all you need: Fast convergence at large depth. arXiv preprint arXiv:2003.04887. https://doi.org/10.48550/arXiv.2003.04887 Henry, A., Dachapally, P. R., Pawar, S., et al. (2020). Query-key normalization for transformers. arXiv p

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wing along, reading, asking questions. Your engagement made this journey really fun. Thank you. Citation References Bekman, S. (2023-2024). Machine Learning Engineering Open Book. GitHub repository. https://github.com/stas00/ml-engineeringBlack, S., Biderman, S., Hallahan, E., et al. (2022). GPT-NeoX-20B: An open-source autoregressive language model. arXiv preprint arXiv:2204.06745. https://doi.org/10.48550/arXiv.2204.06745 Dauphin, Y. N., Fan, A., Auli, M., et al. (2017). Language modeling with

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researchers made xTB up to 2.3x faster at predicting molecular structures and 1.8x faster at conformer search. The changes have been contributed to the official xTB repository on GitHub; Making our open Gemma models nearly three times as fast: Using Argon, we achieved a 2.85x end-to-end inference speedup on an A100 via vLLM (accelerating throughput from 37,900 to over 108,000 tokens per second on Gemma 4 E2B) with 100% token parity and zero quality drop in just a few days, a process that would

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