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#开源/仓库

今日 0 条
10月15日周四
  1. Cloudflare的Clef决策模型家族现可在Merge API上使用,平均响应时间39毫秒,在4项工作流程评估中3项领先于Jev。可用于快速处理工单、标记风险上传或选择代理下一步操作。试用链接:http://gateway.merge.dev

    引用Merge@merge_api

    Clef, the new decision model family from Cloudflare (@Cloudflare), is now available on Merge Gateway. Clef-flash answers in a median 39ms, and in Cloudflare's tests Clef came out ahead of Jev on 3 of 4 workflow evals. Use it to route a ticket, flag a risky upload or pick an agent's next step, all faster than you can blink. Try it out: http://gateway.merge.dev

    Cloudflare Developers产品产品更新模型发布评分 35
10月14日周三
  1. Cloudflare与Cursor Origin合作,为开发者提供更多连接工具和可能性。Cursor Origin(Cursor的代码托管平台)现已支持超过20种集成,可连接仓库到CI、部署、代码审查、安全、监控和项目管理工具。

    引用Cursor@cursor_ai

    Origin, Cursor’s code hosting platform, now supports over 20 integrations. Connect your repos to tools for CI, deployments, code review, security, monitoring, and project management.

    Cloudflare Developers产品产品更新开源/仓库评分 22
10月13日周二
10月12日周一
  1. 研究者应考虑公开分享自己的RL环境,以促进整个领域的发展。尽管美国前沿实验室分享面临困难,但相信这将对领域和世界产生巨大影响!开源社区会将研究成果迅速转化为可用训练环境。

    引用Naveen@NaveenKumar__T

    This is how open source should work. A closed lab publishes research, and within days the community turns it into training environments anyone can use. Early and rough, as Clem says, but the direction is lovely. #OpenSource #AI

    clem 🤗观点开源/仓库大佬观点评分 5
  2. "约75%的人未曾接触LLM,20%的人偶尔使用ChatGPT等免费产品,0.2%的人使用前沿LLM进行复杂项目,0.00006%的人内部访问前沿系统,认知差距因问题规模、领域和技术细节等因素扩大。"

    引用Andrej Karpathy@karpathy

    Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

    Andrej Karpathy观点大佬观点现象/趋势评分 45
10月11日周日
10月10日周六
10月9日周五
  1. OpenAI 开发者宣布,为 Windows 用户更新 Codex,采用微软执行容器(MXC)实现更快的设置、更强的网络控制和更细粒度的文件访问控制。需兼容 Windows 11 设备。

    引用Pavan Davuluri@pavandavuluri

    Today, we announced new @Windows platform capabilities and @surface devices built to empower people and organizations for the era of hybrid intelligence. Here are some of the highlights: - It all starts with trust. Microsoft Execution Containers (MXC) is now generally available on Windows 11, keeping agents contained within boundaries the operating system enforces. - HydraFusion brings hybrid intelligence to life, allowing models to run locally while seamlessly accessing the cloud when more scale or capability is needed. We're working with @github to extend HydraFusion to Windows. - This fall, Search on the taskbar adds thousands of quick actions, making it easier to adjust settings and get things done as fast as you can type. - @MSFTCopilot is getting more powerful on Windows. With hybrid intelligence, it can tap into your PC's local capabilities and turn your requests into action, while keeping you in control. - Local agents are coming to Windows too. Muse is on its way as a native Windows app with MXC integration, and Hermes, OpenClaw, and Perplexity are already building local experiences on Windows. - Surface Laptop Ultra, built with NVIDIA RTX Spark, is the most powerful Surface we've ever built. It's available for pre-order today, along with the Surface RTX Spark Dev Box and new RTX Spark PCs from our partners. Call of Duty is coming to RTX Spark in 2027. Read more on the Windows Blog: https://blogs.windows.com/windowsexperience/2026/10/07/building-windows-for-hybrid-intelligence/

    OpenAI Developers产品产品更新开源/仓库评分 35
  2. 爱这栋公共建筑! 我们不知道Microduck的电池能持续多久。 我们的Radxa原型在热管理上存在问题:仅20分钟后就开始降频,随后过热关闭。 我们用新的定制板解决了这个问题。为了测试它,我们让Microduck在一个专用区域内自主漫游,走来走去,站立和坐着,直到电池耗尽。 结果比我们希望的还要好: - 在2600mAh电池上超过3小时。 - 估计平均电池电流从约1.13A降至约0.82A,大约降低了28%。 - 峰值CPU温度从114°C降至60°C,在整个测试过程中没有热降频。 这次,电池耗尽之前冷却还没有完成呢! 对进度非常满意!

    引用Matthieu Lapeyre@matth_lapeyre

    We did not know how long Microduck would actually last on battery We had thermal management issues with our Radxa prototypes: throttling after just 20 minutes, followed by an overheating shutdown. We addressed this with the new custom board. To test it, we let Microduck roam autonomously in a dedicated area, walking around, standing and sitting until the battery ran out. The results are way better than we hoped :) - Over 3 hours on a 2600 mAh battery. - Estimated average battery current dropped from ~1.13 A to ~0.82 A, roughly 28% less. - Peak CPU temperature dropped from 114°C to 60°C, with zero thermal throttling throughout the test. This time, the battery ran out before the cooling did :) Very happy with the progress!

    clem 🤗产品产品更新开源/仓库评分 22
  3. GPT-6 在洗碗基准测试中取得最佳结果,解决流体运动方程问题,用时 88 小时。

    引用Joma Tech@jomatech

    Introducing ChatGPT for Dishwashing GPT-6 achieves state-of-the-art results on dishwashing benchmarks for long-running jobs and difficult stains. The Navier–Stokes Millennium Prize Problem is a $1 million challenge about whether the equations describing fluid motion can break down. In this video, I accidentally found a counter-example while trying to optimize my dishwasher. But in reality, OpenAI used 10,000 AI agents to find a proof in 88 hours: https://openai.com/index/navier-stokes-solution/ Parody of the original GPT-6 Astra ad @OpenAI #ChatGPT_Partner #chatgpt Credits: Written and Directed by Joma Co-Writer - Henry Connor Coan IV @coan_henry Production by Dauntlus Studios @dauntlus.studios Producer/Co-Director - Marcus Liew @dauntlus Camera Operator - Amos Lee @amoselijahlee Art Director - Alethea Soo @aletheasoo Art Assistant - Alicia Lim @aliciatkl_ Assistant Editor - GPT-6 Astra Music: Tensions Run High by Soundridemusic https://www.youtube.com/watch?v=Ly9H63SLJJo

    OpenAI Developers模型模型发布评测/基准评分 17