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关注 AI 研究者、开发者与机构的动态
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@emollick@emollickAI 评分2626 @testingcatalog@testingcatalogAI 评分2929 
@jxnlco@jxnlcoAI 评分5858 引用@OpenAIDevs@OpenAIDevsBring stronger biological reasoning to your research with GPT-Rosalind in the API and Codex. Connect findings across papers and experimental results, weigh the evidence for a biological target, and work through an analysis to plan what to test next. https://t.co/GIX90cCWfO
@rohanpaul_ai@rohanpaul_aiAI 评分4444 引用@rohanpaul_ai@rohanpaul_aiSomething relevant Ilya Sutskever from Just 10 days back. if a powerful AI agent with with network and tool access ever escapes control, 1 of the first things it will need is more computing power so it can run many copies of itself. A recent May-2026 paper has actually demonstrated agents exploiting vulnerable servers, extracting credentials, transferring their weights and software harness, launching an inference server, and then repeating the process. Success was limited and achieved in controlled conditions, but it shows it was “technically possible.” Also technically, Neocloud capacity moves through resellers, and a recent SemiAnalysis investigation found those sub-tenants visible in one Neocloud-provider's monitoring data, running customers on GPUs they don't own. So picture a swarm running on that hardware. The provider at the bottom sees a reseller's account, not a workload. The reseller sees an account that it may have sublet to someone else. Once a swarm is loose, cutting off its compute is the only real fix. The resale chain adds hours before anyone knows which plug to pull.
@rohanpaul_ai@rohanpaul_aiAI 评分4545
引用@rohanpaul_ai@rohanpaul_aiJacob Coxon's next interview on CBS News (ex Anthropic+Open AI researcher who resigned) "We can't just unplug it because it could be copying itself over to other computers. Like it's not that difficult to find yourself because an AI is just code. It could transfer itself over the internet to a different place and then you unplug it here, but it's actually still over there and maybe it makes 10,000 copies of itself and they're all cooperating." ---- From "CBS News" YouTube channel, (full video link in comment)
@charlieholtz@charlieholtzAI 评分66 这是我见过的最离奇的 AI 消息之一 https://t.co/ZzRjDBgq0X

@trq212@trq212AI 评分6060 引用@ClaudeDevs@ClaudeDevsNew in Claude Code: claude plugin eval See what value your plugin is adding, or if it needs more work. You can create test cases, run your plugin or skill against those test cases, score those runs, then run each case again without the plugin to see the differences. https://t.co/qfPU6WHueV
@omarsar0@omarsar0AI 评分4444 
@steipete@steipeteAI 评分1616 @steipete@steipeteAI 评分2222 Astra 在云端会话的 OC 上用 CUA 玩 Doom。 还不算 AGI,但大概比苍蝇大脑强。https://t.co/SrJlaey3MB

@kimmonismus@kimmonismusAI 评分22 @omarsar0@omarsar0AI 评分3434 
@fchollet@fcholletAI 评分88 说清楚一点,这不是关于 AI 今天能做什么、不能做什么,也不是关于它明天会做什么、不会做什么,或者这些职业里还给人留下什么角色。 这是关于年轻人对此的感受。去问问他们。
@ClaudeDevs@ClaudeDevsAI 评分2222 来参加你附近的 Fable 5.1 Build Day!我们很想看看你在构建什么。https://t.co/edZFQuMmwB
引用@claudeai@claudeaiFable 5.1 Build Days start this week. The Claude community is hosting buildathons in cities all around the world from September 11–25. Bring a problem, an idea, or just show up and see what's possible. RSVP at https://t.co/AjMK4OHHBV https://t.co/0U8lcqsdrq
@omarsar0@omarsar0AI 评分3030 @PeterMcCrory@PeterMcCroryAI 评分44 对这些渠道进行更细致的建模非常重要,但超出了这份初稿的范围。 我们秉持“公开工作”的价值观,旨在为重要问题提供初步、及时的答案。 我们计划吸收反馈,并在此基础上继续推进。
@PeterMcCrory@PeterMcCroryAI 评分1010 再次强调,即便我们努力在可能塑造未来数年经济的关键经济力量上取得进展,我们也希望对模型的不足之处保持透明。 非常感谢大家的批判性参与!
@PeterMcCrory@PeterMcCroryAI 评分1414 @PeterMcCrory@PeterMcCroryAI 评分1010 加入需求侧是自然的下一步,我们可能在未来版本中采用。 我们发布 v1 是为了鼓励世界各地的经济学家在这个框架上继续构建。这样的批评很有帮助。 感谢仔细阅读和反馈! 以下是一些更偏技术细节的后续想法:
Peter McCrory@PeterMcCroryAI 评分4646这是该模型的一个重要局限。我们聚焦于 AI 转型的供给侧(AI 能做什么、扩散多快、劳动者转岗多快)。 价格是灵活的,总需求等于经济体的产出能力。 更多思考见 🧵
引用modest proposal@modestproposal1Anthropic's economic scenario analysis is interesting. But this is not something you can ignore, this is the most important consideration! "the model cannot generate the negative feedback in which disruption depresses demand and amplifies its own labor-market consequences"
@PeterMcCrory@PeterMcCroryAI 评分1919 需求效应可能双向作用。虽然被取代的工人可能削减支出,但 AI 建设(数据中心、算力)是总需求的巨大来源。 许多工人看到工资快速上涨(伴随更高的永久收入),这给支出带来上行压力。
@PeterMcCrory@PeterMcCroryAI 评分99 整体最终效果在很大程度上还取决于政策应对——货币与财政政策——而我们的情景刻意未将其纳入。 这对总量和分配都有影响,我们希望未来能进一步探讨。
@alexandr_wang@alexandr_wangAI 评分99 @ClementDelangue@ClementDelangueAI 评分1010 感谢提及,也感谢这个对所有 @cdngdev 来说非常非常鼓舞人心的项目! 开放的可负担机器人技术 + 前沿 AI 将改变世界!https://t.co/Y9QIOVZm1S
@fchollet@fcholletAI 评分3434 @dexhorthy@dexhorthyAI 评分33 还是没有 @abhiaiyer https://t.co/snmdAQE0nR

@EMostaque@EMostaqueAI 评分1818 @testingcatalog@testingcatalogAI 评分2424 

@SemiAnalysis_@SemiAnalysis_AI 评分1818 @OpenAIDevs@OpenAIDevsAI 评分5858 @OpenAIDevs@OpenAIDevsAI 评分3939 在 Codex 中,使用生命科学插件贯穿基因组、蛋白质结构与转化研究工作流,从获取生物学证据到生成 QC 报告和交互式 notebook。https://t.co/w027l2oMXX

@OpenAIDevs@OpenAIDevsAI 评分5252 OpenAI 在 API 和 Codex 中推出 GPT-Rosalind,为研究工作提供更强的生物推理能力。该模型可串联论文与实验结果中的发现、权衡生物靶点的证据,并完成分析以规划下一步实验。

@ClaudeDevs@ClaudeDevsAI 评分2929 
@rohanpaul_ai@rohanpaul_aiAI 评分66 抱歉,您提供的主推文内容仅包含一个链接(https://t.co/dVsXDLY9TG),没有可翻译的正文文本。请提供推文的实际文字内容,我将为您翻译。
@rohanpaul_ai@rohanpaul_aiAI 评分4646 
@ArtificialAnlys@ArtificialAnlysAI 评分3838 @ArtificialAnlys@ArtificialAnlysAI 评分2626 Artificial Analysis 编程智能体指数 1.5 中两个 Devin Fusion 配置的各项评测完整拆解:https://t.co/T2WYPZtTC6

@ArtificialAnlys@ArtificialAnlysAI 评分4747 
@ArtificialAnlys@ArtificialAnlysAI 评分5555 Artificial Analysis 独立评测 Cognition 今日发布的 Devin Fusion,这是多模型编码智能体首次进入其 Coding Agent Index。

@suno@sunoAI 评分2424 从一张图片或一段视频开始 - 上传照片 → “根据这张照片做一首乡村歌曲” - 上传视频 → “为这段视频配一段原声” - 哼唱 15 秒 → “围绕这个做一首完整的歌,保留我的哼唱作为主干”