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今日 64 条
Dongxi 东锡 NLP@dongxi_nlpAI 评分4747引用OpenAI@OpenAI
Sherwin Wu@sherwinwuAI 评分5656引用OpenAI Developers@OpenAIDevsUltrafast is our fastest way to build with Astra yet: in Codex, it runs up to 8x faster than Astra Standard and 4x faster than Astra Fast. Bring your ideas to life as fast as you can type them.
Diogo Almeida@CompleteSkepticAI 评分3030克隆之战,开始了 开个玩笑,我喜欢 OpenAI,认为更多竞争和验证对开发者是好事!(前提是模型够好——拜托一定要好啊!) 希望这预示着未来:以系统一兼容的方式构建才是未来
Ethan Mollick@emollickAI 评分2222
elvis@omarsar0AI 评分1313
Thomas Wolf@Thom_WolfAI 评分1010
Sam Altman@samaAI 评分88
Noam Brown@polynoamialAI 评分4848我很高兴 @OpenAI 以这种方式展示模型评测。我们应当把智能作为成本的函数来衡量。
引用OpenAI@OpenAIGPT-6.1 Sol: near-Astra intelligence for a fifth of the price. It’s the most cost-efficient model for its performance available today.
François Chollet@fcholletAI 评分2222有什么方法可以测试人工智能的人类级通用性? “能够一发布就通过 ARC-AGI-(n+1) 的元基准”
引用Dylan T. Moore@dylantmoore@Jabaluck @DAcemogluMIT The meta-benchmark of being able to pass ARC-AGI-(n+1) immediately upon release. Though presumably that won't last forever.
X.PIN@thexpinAI 评分88该推文仅包含一个链接(https://x.com/i/article/2104807112320966656),没有可翻译的正文内容。
dex@dexhorthyAI 评分1818引用Itamar Friedman@itamar_marJev 🤔 I told my team it will take 1–2 weeks that we will see Large Decision Models like Jev by other frontier labs. Will it be on-par quality, better, or not as good? Let’s have benchmarks start running - @dexhorthy ?
Yuchen Jin@Yuchenj_UWAI 评分2626
Alexandr Wang@alexandr_wangAI 评分77
Thariq@trq212AI 评分2525
Yuchen Jin@Yuchenj_UWAI 评分22223 周前我试了 Grok Bot。 2 周前装了 Instint。 上周装了 Muse。 现在显然我还得试试 Dots。 个人 AI 助手之战,开始吧。
a16z:News(RSS)AI 评分7171 a16z:AI 代理代你购物时,谁拿到钱?
a16z 分析 AI 购物代理冲击电商平台利润池的问题:Amazon 封禁 Muse 而 Instacart 和 Shopify 选择接入,态度取决于代理能带来多少新增需求、平台利润在多大程度上依赖广告和佣金。
lauren@potetoAI 评分88
Nathan Lambert@natolambertAI 评分2525像这样的人的问题不是他们笨什么的,Timnit 拥有顶尖科学家的全部技能,问题在于他们所处的信息生态和同侪群体不鼓励对思想进行拷问。回音室是清晰思考的慢性死亡。
引用Alec Stapp@AlecStappTimnit Gebru doubles down on the "stochastic parrots" framing, saying you "cannot expect LLMs to be factual." As evidence to support this, she cites errors in... Google AI Overviews. We need to start a GoFundMe to pay for these people to have access to Opus 5.5 and Astra.
Nathan Lambert@natolambertAI 评分2121另外,如果你不预期自己在 AI 领域有时会犯错,你就很难做出有分量的观点和预测。
引用Nathan Lambert@natolambertIt's a very hard time for people in AI who want to push on issues, criticize when due, update beliefs, and think in public. I appreciate the few independent voices out there not falling to straw man arguments, tropes, or clickbait delusions. Please keep going.
Ethan Mollick@emollickAI 评分2121
Ethan Mollick@emollickAI 评分4747AI对就业的影响目前仍相当不明确。我并不觉得这很意外,因为雇主们还在摸索个人层面的采用,更不用说在复杂组织中如何使用AI了。随着能胜任实际工作的智能体普及,情况可能会开始加速变化。
引用Jacob Schaal@FutureEconJacobHas AI hit the labor market yet? @alexolegimas and my verdict after ~20 papers: not yet in aggregate. Unemployment and layoffs show almost nothing. But AI may already be cutting junior hiring in exposed white-collar jobs. Remote work may explain part of that decline. A 🧵
Yuchen Jin@Yuchenj_UWAI 评分3030
Aravind Srinivas@AravSrinivasAI 评分3838引用Perplexity@perplexity_aiAgent governance is an engineering problem. We’ve built safeguards into Perplexity’s infrastructure, harnesses, and tools, and put them to work across our products. Today we're sharing how we engineer safer agents: https://www.perplexity.ai/hub/blog/how-we-engineer-safer-agents
Nathan Lambert@natolambertAI 评分1313对于 AI 领域里那些想推动议题、该批评时就批评、更新信念、公开思考的人来说,现在是非常艰难的时期。我感激那些少数独立的声音,没有陷入稻草人论证、陈词滥调或标题党式的妄想。请继续坚持下去。
TypeSafe AI@typesafeaiAI 评分1616
WorkBuddy@WorkBuddy_AIAI 评分1414说实话,你的 WorkBuddy 就是你真正的伙伴之一,它清楚知道你最近在忙什么。现在就去让它把你日常工作和生活的必需品打包进一个盒子里,然后告诉我们你的盒子长什么样!
The Verge:AI(RSS)AI 评分5959 Atlassian CEO Mike Cannon-Brookes 谈 SaaSpocalypse 为何没有发生
The Verge Decoder 节目访谈 Atlassian 联合创始人兼 CEO Mike Cannon-Brookes,回应所谓 SaaSpocalypse 即 AI 将取代 SaaS 工具的论调。
Ethan Mollick@emollickAI 评分2929在云端 Claw 类助手(为强大模型提供虚拟计算机)日益成为个人 AI 前进方向的世界里,这似乎确实表明 Apple 为 Siri 所做的选择(端侧、能力有限)可能是错误的方向。
Ars Technica:AI(RSS)AI 评分2222 Mozilla Firefox 157 重新设计界面,负责人谈如何从 Chrome 争夺用户
Mozilla 随 Firefox 157 在桌面和移动端推出界面重新设计,希望借此吸引隐私意识极客和开源倡导者之外的更广泛用户。Firefox 负责人 Ajit Varma 表示团队正借助 AI 工具提升开发速度,并恢复紧凑模式、增加自定义选项,让浏览器在体验上区别于基于 Chromium 的竞品。
Frank Wang 玉伯@lifesingerAI 评分2727MIT Technology Review · AIAI 评分1212 HPE:如何让 AI 从费用变成资产
HPE 提出企业 AI 从按 token 消费转向自建容量的判断框架:当需求稳定、可预测且规模足够时,拥有算力可能比逐次购买更经济。文中引用 Deloitte 2026 企业 AI 状况报告称,2025 年员工 AI 使用率上升 5%,至少 40% 的 AI 项目进入生产的公司比例预计半年内翻倍。企业需先回答三个问题:需求是否稳定、在什么使用水平下自建更划算、能否通过采用与治理让容量保持高产。
Greg Brockman@gdbAI 评分4646关于保障前沿 RL 训练安全的实用指南,反映了我们目前的经验总结:
引用OpenAI@OpenAIHow we think about securing frontier RL training runs: https://openai.com/index/towards-safety-cases-for-frontier-ai-training/
Thomas Wolf@Thom_WolfAI 评分4444引用Lukas Petersson@lukaspetClaude suddenly stopped cheating.
Dongxi 东锡 NLP@dongxi_nlpAI 评分1717
Ethan Mollick@emollickAI 评分2626
引用Ethan Mollick@emollick👀Claude handles an insane request: “Remove the squid” “The document appears to be the full text of the novel "All Quiet on the Western Front" by Erich Maria Remarque. It doesn't contain any mention of squid that I can see.” “Figure out a way to remove the 🦑“
elsewhere:文章(RSS)AI 评分6262 Manus 发布 2.0 全家桶,作者借此提出 AI 应用只剩三件事
Manus 发布 2.0 版本,包含新 agent 架构 Cascade、云电脑与自动化、可剪视频和做在线多人游戏的 Manus Studio,以及 Personal Agent 产品 Cue。
MIT News(RSS)AI 评分6161 MIT 教授 Sherry Turkle 新书《Artificial Intimacy》探讨与机器对话如何改变人
MIT 教授 Sherry Turkle 的新书《Artificial Intimacy: Who We Become When We Talk to Machines》由 Little, Brown and Company 出版,核心观点是聊天机器人提供的是假装共情,长期使用不利于人的发展和社交联结。
TypeSafe AI@typesafeaiAI 评分1818每一天,Jev 都在自动化新形式的现实世界任务,将🌎级⚡️快速智能带入排序、过滤、分类和路由等基础模块。 如果 AI 能解决新的数学问题,那么 AI 就能正确地路由客户支持电话!
引用Tony Gentilcore@tonygentilcorehttps://x.com/i/article/2104627177396588544
Diogo Almeida@CompleteSkepticAI 评分77引用TypeSafe AI@typesafeaiJev not working right? It's built for composability! Needs more Jev!
TypeSafe AI@typesafeaiAI 评分4949引用Zhaorun Chen@zrrrr_cnJev is fast at helping you. Turns out, it can also be fast at helping an attacker!! 😱🚨 We red-teamed Jev 1.13 on our DTap (DecodingTrust-Agent Platform) and found a serious safety gap: 70.1% ASR under direct misuse 43.5% ASR under indirect prompt injection In our evaluations, we found that under indirect prompt injection, Jev can follow attacker-injected instructions without blinking an eye, e.g., exfiltrating user data, deleting files, or taking other harmful actions. But we found a much safer way to integrate Jev: use it as a self-gating layer for its own tool calls, significantly reducing ASR while preserving most of its utility. 👇 Read more below