X
关注 AI 研究者、开发者与机构的动态
按账号或来源筛选(541)
@rohanpaul_ai@rohanpaul_aiAI 评分5555 
@alibaba_cloud@alibaba_cloudAI 评分2424 
@alexandr_wang@alexandr_wangAI 评分3131 @Yuchenj_UW@Yuchenj_UWAI 评分2323 大型AI实验室里有很多研究员,真心担心如果我们一味加速,AI可能导致人类灭绝。 他们只是更害怕慢下来,让另一个实验室赢得这场竞赛。 千年困境。
@alibaba_cloud@alibaba_cloudAI 评分1717 


@rohanpaul_ai@rohanpaul_aiAI 评分2626 @rohanpaul_ai@rohanpaul_aiAI 评分3838 
@TencentHunyuan@TencentHunyuanAI 评分66 @chunxiangai@chunxiangaiAI 评分55 瘫原爆,哥们儿没在做软件。 https://t.co/xkFaRfdY8t

@alibaba_cloud@alibaba_cloudAI 评分3636 
@rohanpaul_ai@rohanpaul_aiAI 评分5959 
@rohanpaul_ai@rohanpaul_aiAI 评分55 @SemiAnalysis_@SemiAnalysis_AI 评分3030 
@thsottiaux@thsottiauxAI 评分6060 @AISafetyMemes@AISafetyMemesAI 评分77 6个月。 https://t.co/TZ7RHqBesS https://t.co/xAFbJMLmED

@gdb@gdbAI 评分5858 引用@OpenAI@OpenAINow available: ChatGPT for Financial Services. This is a tailored ChatGPT Work experience that combines built-in financial data with GPT-6 Astra’s reasoning. Teams can develop research, build financial models, and create customized client materials. https://t.co/6WP5OJdnE8 https://t.co/AundGG3jtc
@AISafetyMemes@AISafetyMemesAI 评分2525 又一位 OpenAI 员工表示,如果我们不减速,3 年内人类灭绝的概率为 70% https://t.co/kJDydarRtP
@alexandr_wang@alexandr_wangAI 评分77 @AYi_AInotes@AYi_AInotesAI 评分2323 手搓一个多维表格要点几十次字段, 现在对豆包说一句话,6 项关键字段、三个分类视图当场成型。 整条内容生产线最关键的进料口怎么搭,详见文章第二章节
@AYi_AInotes@AYi_AInotesAI 评分4141
引用@AYi_AInotes@AYi_AInoteshttps://t.co/8IddGNPP8n
@alexandr_wang@alexandr_wangAI 评分2020 我们的 muse 安全架构让你能大量控制智能体何时需要请求 human-in-the-loop 审批 更多内容来自大神 @bigT_sheesh:https://t.co/6rIgMXmjFm
@alibaba_cloud@alibaba_cloudAI 评分1313 
@AISafetyMemes@AISafetyMemesAI 评分3030 @AYi_AInotes@AYi_AInotes精选AI 评分6767 
推荐理由:原文给出协调者调度子 Agent、全局上下文与事件驱动三项设计,可据此理解编码智能体从单次对话转向常驻项目协作的变化。
@alibaba_cloud@alibaba_cloudAI 评分1717 
@alibaba_cloud@alibaba_cloudAI 评分2626 
@bcherny@bchernyAI 评分5050 @bcherny@bchernyAI 评分22 每天,我都会收到很多像这样的邮件和消息。我尽量回复尽可能多的人。 下面分享我的回复,供其他处于类似情况的人参考。你们觉得呢?https://t.co/z1GtgK14RM


@elonmusk@elonmuskAI 评分4747 Grok @Bot 对 SpaceX CFO 演讲的总结 https://t.co/UwPshiaEF0
引用@cb_doge@cb_dogeGrok Bot Summary of SpaceX CFO Bret Johnsen at Goldman Sachs Communacopia today. Vertical integration Vertical integration is the company’s core operating model, not a side strategy. - Rockets: own metal → engines → avionics → software - Starlink: own launch, satellites, and the end customer - AI: build facilities and power themselves, run their own models, sell to consumer and enterprise, and soon orbital compute Starship and launch Starship is the foundation for every other business. - Flight 13: big learning flight. Delivered demo V3 payloads, relit a Raptor, and got a soft, precise second-stage splashdown. Recovery team towed the stage back so engineers could study the heat shield. - Those learnings feed straight into Flight 14 and beyond. - Flight 14 (later this month): first revenue-generating Starship flight, flying production V3 Starlink satellites. - Later this year: aim to recover both first and second stages. Orbital compute Most of the AI industry agrees orbital compute is the future. Almost everyone else thinks it’s many years away. SpaceX disagrees because they control the stack. - Target: first orbital compute satellites next year - Scale: big compute in space into 2028 - Hardware approach: same V3 bus as Starlink, swap the payload, add larger solar arrays Why orbital can beat terrestrial on cost The crossover is about Starship reusability. - Falcon 9: first-stage reuse since Dec 2015; 500+ booster reflights - Starship: first stage already recovered/reflown; second-stage recovery progressing - Goal: reflight of both stages as soon as next year, which drops deployment cost sharply Terrestrial compute is getting more expensive (power, cooling, buildings, real estate). Orbital rides the opposite curve: cheaper rockets + better/cheaper satellites + scale. Johnsen said cost parity could come as soon as next year. Terrestrial compute and the $100B ARR goal - End of this year: on track for ~$100B ARR (annualizing the December number) - New update: another hosting deal closed earlier this month → about $1.1B/month starting Dec 1 → roughly +$13B ARR - Capacity: end this year well over 2 GW; next year 5–10 GW deployed - Confidence comes from line of sight to power, facilities, and permitting, plus being NVIDIA-exclusive for allocation - They stand compute up fast for themselves and for industry partners, which strengthens the NVIDIA relationship How they monetize compute Most hosting deals are short: ~90 days with a 90-day out (~6-month commits), including the newest deal. Why keep them short? - High conviction in their own products (Grok, Grok Bot, Cursor team after closing that deal) - Don’t want to lock forever capacity they may need internally - Internal bar: don’t let internal monetization fall below external hosting Earnings framing for next year: roughly $30–$50 per watt monetization range; they said they’re at the high end. Hosting customers appear to monetize even higher, which is why demand stays strong. Payback is under one year on new compute capex, so residual GPU value and financing options look attractive. “Not all CapEx is the same” — GPUs with <1-year payback are different from a launch tower built for decades. AI products and M&A Historically SpaceX was almost all organic growth. This year they did M&A because the AI product cycle rewards speed to frontier. - Closed Cursor deal weeks ago; product cycles already accelerating (called out Grok Bot) - Grok 4.6 improved on 4.5; 4.7 coming soon - Pitch: best infrastructure + competitive model + lower token cost = best position for customers - Market mood shift: months ago people bought the infra story but doubted the products; ~90 days later that skepticism is fading Starlink broadband Started as “better than nothing” (~2020–21). Now enterprise-grade with strong uptime/SLAs. - Resiliency pitch: boards will ask why Starlink wasn’t in the network if you go down - Mobility: aircraft backlog is large and production is ramping; cruise ships, yachts, trains too - Awareness, especially outside the US, is still a growth unlock - Longer-term: physical AI (robots, cars, aircraft) will need always-on connectivity terrestrial networks can’t fully cover Mobile / direct-to-cell Not a distraction. Same V3 bus, different payload. - Fly direct-to-device satellites through next year - Target service turn-on: first half of 2028 - V1 today (e.g. T-Mobile / T-SAT): text / light voice, great for emergencies and dead zones - Next gen: full 5G-quality from space - US: mid-band spectrum from EchoStar, FCC path for space + terrestrial - Go-to-market: flexible — own terrestrial build, or partner with carriers - International: same regulator-by-regulator playbook as broadband (Starlink now in 170+ countries) Near-term priorities: 1. Starship (enables everything else) 2. Terrestrial compute (funds growth and teaches them how to do orbital) Bottom line in one line Own the full stack, make Starship reusable at scale, use terrestrial AI compute as a cash engine now, and use the same satellite bus + Starship cadence to win broadband, mobile, and orbital AI.
@rohanpaul_ai@rohanpaul_aiAI 评分55 @rohanpaul_ai@rohanpaul_ai精选AI 评分6666 



推荐理由:报告披露封禁后转售商数日内恢复服务,可用于观察模型能力提升后生物滥用管控的边界变化。
@MiniMax_AI@MiniMax_AIAI 评分3232 @bcherny@bchernyAI 评分77 @alexandr_wang@alexandr_wangAI 评分77 @alexandr_wang@alexandr_wangAI 评分99 @rohanpaul_ai@rohanpaul_aiAI 评分5454 IFM AI 发布 K2Horizon 开源模型,相关资源同步上线。官方公告给出模型发布页、技术深度解读、Hugging Face 模型页、xLLM 训练代码、IFM API 平台与开发者文档等链接。
@rohanpaul_ai@rohanpaul_aiAI 评分5858 @rohanpaul_ai@rohanpaul_aiAI 评分6161 IFM 公布 0.9B、3.7B、7B、32B 和 375B-A23B 的评测数据,称 7B 已能处理 AIME 竞赛数学,而这类任务约 1 年前需要 100B+ 模型。
@rohanpaul_ai@rohanpaul_aiAI 评分6262 
@rohanpaul_ai@rohanpaul_ai精选AI 评分7070 

推荐理由:K2 Horizon 披露预训练用约 20T token 且 17% 含显式推理轨迹,读者可借此对照模型的训练数据构成。