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关注 AI 研究者、开发者与机构的动态
按账号或来源筛选(541)
@SemiAnalysis_@SemiAnalysis_AI 评分2424 
@SemiAnalysis_@SemiAnalysis_AI 评分4444 @omarsar0@omarsar0AI 评分2121 @kimmonismus@kimmonismus精选AI 评分7676
引用@AnthropicAI@AnthropicAIWe're publishing our most detailed threat intelligence report to date. It covers how people tried to misuse Claude—for cyberattacks, influence operations, surveillance, biology, and building weapons—and how we found and stopped them. We disrupted every operation in the report, and used the lessons from them to strengthen our safeguards. Where appropriate, we also shared what we found with authorities and other AI companies. These cases are not typical: we’re highlighting some of the most sophisticated misuse we’ve seen. But they’re especially important to discuss, because they show us where AI misuse is headed, where our safeguards work, and where they need to improve. We’re publishing this report so others can spot the same activity on their own platforms, and so we can give the public a clearer view of how emerging threats develop. Read the report: https://t.co/0EJUnYEgfz
推荐理由:报告披露行为体把有害目标拆成看似无害的编码任务以绕过拦截,为理解 AI 滥用路径提供了具体案例。
@gdb@gdbAI 评分2424 @thsottiaux@thsottiauxAI 评分1313 你读它是 data 还是 data?这就是 OpenAI 所有人做看板、了解业务的方式。离不开它。https://t.co/9NAremYs1h
@emollick@emollickAI 评分5757
引用@EpochAIResearch@EpochAIResearchEvery FrontierMath Tier 4 problem has now been solved by AI, with GPT-6 Astra solving the last problem standing. Mathematicians often commented that AI found unintended shortcuts when solving their Tier 4 problems. Not so for this last one, which was created by Jay Pantone. https://t.co/ieEZaomhaE
@runwayml@runwaymlAI 评分55 @runwayml@runwaymlAI 评分00 Julian Simcock 哈佛大学外交与治国方略项目主任 https://t.co/svECAfljmk

@runwayml@runwaymlAI 评分1212 @opensauceAI Black Forest Labs 公共政策负责人 https://t.co/kmfjRm79fg

@runwayml@runwaymlAI 评分44 @alexttoshev Wayve 研究总监 https://t.co/qMSXuGXoJT

@runwayml@runwaymlAI 评分2020 
@suno@sunoAI 评分1414 @milichab@milichabAI 评分6161 @jxnlco@jxnlcoAI 评分1010 在 xhigh 上用 astra 15 分钟 https://t.co/HG9cwfs0jJ

@suno@sunoAI 评分3939 
@cb_doge@cb_dogeAI 评分5454 
@natolambert@natolambertAI 评分2020 对于那些认为蒸馏主要是 SFT 副产物、并且不清楚在 RL 定义的时代它如何变得越来越有影响力的人来说,这是一大胜利。https://t.co/PSvWtJ4Sj6
@gdb@gdb精选AI 评分7070 OpenAI 在 API 中开放 GPT-Live-1,开发者可把 ChatGPT 式的自然对话体验接入自己的应用。该语音智能体可在说话的同时持续聆听,并支持搭配开发者自选的模型与 harness。
引用@OpenAIDevs@OpenAIDevsGPT-Live-1 is now available in the API. Bring ChatGPT’s natural back-and-forth to your app, with voice agents that listen while they speak and work with the models and harness you choose. https://t.co/gIl1gwsBDV
推荐理由:GPT-Live-1 开放 API 后,开发者可把边听边说的语音智能体接入自家应用并自选模型与 harness。
@gdb@gdbAI 评分1515 @trq212@trq212AI 评分5959 @cohere@cohereAI 评分1010 把时间夺回来,留给真正推动你的事。你的自由,你的专注。我们在这里支持你:https://t.co/fXxZdfXo21 https://t.co/2MlxjJXaCZ
引用@cohere@cohereWe're building AI to help people lead better lives. Do more of what you love with Cohere. https://t.co/bodV7JRTpF
@alexandr_wang@alexandr_wangAI 评分1212 @PixVerse_@PixVerse_AI 评分1111 @PixVerse_@PixVerse_AI 评分4040 @PixVerse_@PixVerse_AI 评分2424 
@alexandr_wang@alexandr_wangAI 评分88 @alexandr_wang@alexandr_wangAI 评分77 



@jxnlco@jxnlcoAI 评分22 看看效果如何 https://t.co/FCYjiBrTBN

@EpochAIResearch@EpochAIResearchAI 评分1717 @EpochAIResearch@EpochAIResearchAI 评分4141
引用@EpochAIResearch@EpochAIResearchOpenAI GPT-5.6 models and Anthropic Claude 5 models have different pricing structures at long context lengths. GPT model costs increase in price past 272k input tokens, while Claude model costs remain fixed. Does this reflect an underlying difference in the architecture of these models? Our measurements of serving latency suggest so. We studied time to first token (TTFT) on these models and how it scales with increasing context length. We found a significant difference in how they scale, with GPT showing a noticeable quadratic component, while Claude models remain closer to linear.
@ArtificialAnlys@ArtificialAnlysAI 评分1515 查看下方 DeepSeek V4.1 Flash 的完整测试结果:https://t.co/kq5EFXjd32

@ArtificialAnlys@ArtificialAnlysAI 评分2222 前往 Artificial Analysis 将 DeepSeek V4.1 Flash 与其他模型进行对比:https://t.co/Ks6lZigqTw
@ArtificialAnlys@ArtificialAnlysAI 评分2626 AA-Omniscience 提升 9 分至 -5.3,准确率从 40% 升至 46%,但非幻觉率从 8% 降至 4%。https://t.co/50iZob5SrO

@ArtificialAnlys@ArtificialAnlys精选AI 评分8383 
推荐理由:文中给出同一套指数下的横向对比和每任务成本,可据此判断轻量模型与旗舰 Pro 之间的性价比差距。
@ArtificialAnlys@ArtificialAnlysAI 评分2020 尽管每 token 价格更低,但由于其冗长,每任务成本仍达到 $0.27,不过仍显著低于大多数开放权重同类模型。https://t.co/1CADy2wklh

@rohanpaul_ai@rohanpaul_aiAI 评分3131 
@alexandr_wang@alexandr_wangAI 评分1313 一件有趣的事——我们在打造 muse 的过程中大量使用了 muse :) https://t.co/KA1Mq9OMmZ
@leerob@leerobAI 评分2222 @rohanpaul_ai@rohanpaul_aiAI 评分1919 