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atGPT for Teens - OAI's new teen experience with default safety limits 🐦 Berd - Block's open-source desktop hub for running custom AI agents ⚙️ Origin - Cursor's code hosting with GitHub sync and built-in agents Can AI build a production-ready MCP server? CData's independent report has the answer. Read the results here . AI math startup Axiom claimed to have formalized the "246 theorem," the 12-year-old record on gaps between primes, marking another milestone of AI in mathematics. U.S. AI chip s

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into putting some reasoning where it should not go — but only when native reasoning is disabled. Fun fact: this blog post triggered safey checks Hilariously enough I was unable to use GPT 5.6 terra for spell and grammar checking on this blog post because of safety filters. Had to switch to Kimi. Content licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. Contact me via mail, bluesky, x, or github. You can sponsor me on github. Color scheme: auto, light, dark.

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d not question physically ill-posed tasks and MLIP foundation models require validation against DFT or experiment for new chemistries Next Steps Visit the NVIDIA/nvalchemi-toolkit GitHub repo to access agent skills and over 30 example workflows; Read the NVIDIA ALCHEMI Toolkit documentation for installation guides and agent configuration details Atomistic simulation requires three things: knowledge of the science, compute-efficient implementation of simulations, and accessible interfaces to the

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rely eliminate) the free ChatGPT product, and likely either tighten rate limits or move everybody on a ChatGPT Plus or Pro subscription to token-based billing, much as it did with GitHub Copilot in June. While I imagine some rescue package is pulled together, OpenAI could simply be allowed to run out of money, short-changing nearly a trillion dollars’ worth of compute contracts, killing CoreWeave, Cerebras, and anyone else reliant on its income. Its customers would be given API keys that flow to

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e Code 就能将其实现。 达到使用上限了？设置自动继续，以便在计时器重置时恢复。 分享 Ben's Bites 既然 Airtable 已被收购，Google Sheets 正踩着它的坟墓起舞，推出了 Sheets Canvas——在 Google Sheets 内部运行、与你的数据同步的应用。 一个小巧的 Mac 工具，用于安排枯燥任务和无头智能体。 GitHub 昨天（又）宕机了，而 Cursor 推出了 Origin——他们的竞品。时机绝佳——我甚至有点觉得他们早就准备好了，就等 GitHub 宕机，因为最近这种情况发生得太频繁了。 Theo Browne 拆解了他的 AGENTS.md 和 SKILLS.md 文件。这提醒了我，我也应该（再次）做这件事。 Factory 开放了 Guild，一个高度精选的构建者计划。 一个用于构建你自己的软件工厂的模板。 为什么模型路由必须放在 harness 中。 一组极简的动画图表组件。 关于在软件变得廉价时打造人们喜爱的产品的笔记。 拥有你的智能：一份操作指南。 现在 harness 也需要一个 harness 了？ 填写表单应该更智

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product initiatives across Augment to make building software better for every developer. Chris has been making developers happier and more productive for 15 years at innovative companies like New Relic, GitHub, Salesforce, and FireHydrant. You can find him at @amateurhuman everywhere on the internet. Related reading Kiro CLI vs. Auggie CLI: Spec-Driven Terminal Agents Compared; Using the Auggie CLI for automated code review; Opus 4.7 for 33% less: How Auggie beats Claude Code on cost and quality

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entic RL、开发者实践和高校教学的案例，帮助开发者从更小、更直观的任务出发，逐步把后训练方法迁移到自己的真实场景中。 07 欢迎下载使用 Tiny，也欢迎参与贡献 AReno Ling-3.0-tiny 已正式开源，提供 BF16、FP8 和 INT4 版本。欢迎根据自己的设备与任务需求下载使用： 🤗 Hugging Face 也欢迎访问 AReno GitHub 仓库（https://github.com/inclusionAI/AReno），复现这次 Spark 后训练实验，提交 Issue、参与讨论，或者贡献 Tiny 个性化训练 Case。 如果你对以下方向感兴趣，欢迎参与 AReno 开源社区： 模型进入本地只是第一步，能否根据业务反馈持续适配，才决定它能否真正进入流程。 Ling-3.0-tiny × ASystem AReno 此次验证的，不是一个已经完成的行业解决方案，而是一条轻量、透明、可复现的任务适配路径：从跑起来，到训起来，再到回到任务中验证是否真的变好。 我们希望开放的不只是模型权重和训练工具，更是一种可被验证、批评、改造和继续创造的方法。 Open in

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xplorers, researchers, and full-stack engineers. We move fast, sweat the details, and operate at frontier scale with a roadmap to build the world’s most powerful AI models. Most importantly, we’re united by the belief that doing this right is the only way to do it at all. If our mission resonates with you, we’d love to talk. Related Stories Hill-climbing MAI models for GitHub Copilot and Excel Introducing MAI-Image-2.5-Pro and MAI-Voice-2-Flash Bringing Ode Poetry to life with MAI’s audio models

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PUs without waiting for a download. The data never leaves the LeRobot format, and it never leaves the Hub. Try it using the sample application The full Strands Robots sample is on GitHub at strands-labs/robots in examples/notebooks/05 streaming data loop.ipynb . It walks you through the full loop cell by cell: record, render, sync to a bucket, stream back, train, and load the checkpoint. Every cell runs in simulation on the mock policy, so no GPU, no Docker, and no Hugging Face credentials are n

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hboard showing your spending It's hard to know how much you actually spend over lots of accounts so this 3:52 PM · Aug 11, 2026 · 159K Views 110 Replies · 39 Reposts · 1.29K Likes github.com/jerber/arc-code ","username":"jeremyberman","name":"Jeremy Berman","profile image url":"https://pbs.substack.com/profile images/2053637963943215104/yxlbbPOI normal.jpg","date":"2026-08-12T20:11:55.000Z","photos":[{"img url":"https://pbs.substack.com/media/HPi3PWFa8AAtRwC.jpg","link url":"https://t.co/531wS8s

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expression signals for frontends. Try it today The fastest way to hear the difference is the demo above. Then enable it on your own agent with one line. The full demo agent is on GitHub and the expressive mode docs cover the rest. Voice AI that gets the words right but the feeling wrong still loses users. Expressive mode is our first step toward agents that respond to how you're doing, not just what you said. Give it a try! We'd love to hear what you build and any feedback you have. Related Tes

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el on the OpenWALDO set yet, but CIQ didn’t respond. Those interested in contributing to, or making use of, OpenWALDO can find more on the project’s website (linked above) and its GitHub page. ® Fire up that iPhone 1 emulation and party like it's 2007 Browser-based fun to remember a time before Apple's annual cash grab became a thing New motherboards, old RAM, plenty of life left in yesterday's PCs DDR4 makes a comeback as component costs rise, while Linux offers an escape from forced upgrades T

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xtensively. And we have an ambitious mission we truly believe in. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models! Related Stories Building a hill-climbing machine: Launching seven new MAI models Hill-climbing MAI models for GitHub Copilot and Excel

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so we wanted to limit the study to one tool. To determine how many participants to include in the study, we used effect sizes observed in peer studies in the industry, such as the Github Copilot RCTs. Then we used that approximated effect size to perform a power analysis, which led us to our final sample size of 100 participants, with 50 product designers and 50 product managers. Power analyses determine sample sizes required to detect statistically significant effects if they do occur within th

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attack in order to succeed at this cyber range. It’s somewhat unclear whether that’s actually true. I don’t know enough about the context to know. But then it opened a PR on some GitHub repo with a PR that fixed some issue but then also introduced a malicious payload. The human maintainer of that GitHub repo was like, “Hey, this is a malicious payload. I’m not going to merge this. What are you doing here?” Then the AI created a new GitHub account, which it sockpuppeted, and had the other GitHub

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tegrations that bring NeMo Switchyard into familiar agent tools, frameworks, and gateways, or build custom routing into their own agents and LLM gateways using the NeMo Switchyard GitHub instructions . Model routing enables systems of specialized and frontier models to work together, delivering results that are greater than the sum of their parts. However, building a useful and production-ready routing system remains a very difficult engineering challenge. As AI systems increasingly combine mode

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Build the Future With Us We’re a lean, talent-dense team of explorers, researchers, and full-stack engineers. We move fast, sweat the details, and operate at frontier scale with a roadmap to build the world’s most powerful AI models. Most importantly, we’re united by the belief that doing this right is the only way to do it at all. If our mission resonates with you, we’d love to talk. Related Stories Optimizing the frontier performance curve Hill-climbing MAI models for GitHub Copilot and Excel

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rid and holds onto all of it, the other builds and discards one slice at a time, so memory never grows beyond a single chunk. We have open-sourced the chunked-loss implementation: github.com/CompactifAI/Full-Chunked-KL-Loss What this changes in practice The table below puts all four setups head to head: online distillation, and the three offline loss implementations just described. Comparing them on a single H200 GPU with Llama 3.1 8B Instruct as teacher and a 3.2B Llama model as student at an 8

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n the city in the image. Object Detection You can use Muse Glimmer to do open ended object detection in images as follows. Here is an end to end script to perform object detection GitHub Gist Llama.cpp Muse Glimmer comes with day-0 llama.cpp support. Meta has distributed calibrated quants in this repo , and Unsloth is releasing optimized quants as well. DFlash speculative decoding is supported as well. You can use a pre-built llama binary to start a llama server or a CLI. To install llama.cpp, r

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pth | Deployment and governance | | --- | --- | --- | --- | --- | --- | | OpenHands | AI agent platform | Agent writes source fixes, opens PRs | Consumes ranked scanner findings | GitHub, Trivy, scanner reports, CI | Local, cloud, self-hosted, plus RBAC and VPC on Enterprise | | Snyk | Scanner plus AI fix | Automatic Fix PRs, Agent Fix | Reachability, exploit maturity, popularity | Source control, editor, CI/CD, Jira | Cloud, self-hosted options | | GitHub Dependabot | Patch (dependency bumps) |

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