AI 英文奏折

2026/01/09 | 共收录 30 篇原创情报

👤 (3) X 上的 Rohan Paul：“Super interesting. The author argues compute alone is no longer a reliable path, because efficiency wins on real tasks. The core idea is that better data, plus after training steps that teach models to follow instructions and use facts, can raise quality faster than simply https://t.co/Tlqwd9qI7f” | 行业资深观察员
发布于【2026年01月08日 17时】

数据与训练优化比单纯扩大规模更能提升模型性能，效率优于算力扩张

📊 ❤️ 58 | 📝 122 词 | 🔗 深度阅读

👤 (3) X 上的 Ksenia_TuringPost：“DeepSeek’s : Manifold-Constrained Hyper-Connections (mHC) shook the AI community with a real mathematical wake-up call: We are running into architectural limits. For a decade, the “just add more layers” strategy on the residual connection: By forcing every layer to preserve https://t.co/76EospGby2” | 行业资深观察员
发布于【2026年01月09日 05时】

DeepSeek提出流形约束超连接，突破残差网络架构限制，实现深度网络的稳定与高效表达

📊 ❤️ 3 | 📝 139 词 | 🔗 深度阅读

👤 (3) X 上的 @levelsio：“Not making this up but I had to manually remove @Cobratate from the Photo AI robot that generates samples for the Dubai photo pack Because 🍌 Nano Banana Pro would automatically insert him in every 10th photo or so without me ever prompting for him And I don’t wanna infringe on https://t.co/LrVCLVsCNR” | 行业资深观察员
发布于【2026年01月09日 04时】

AI模型被强制训练生成Cobratate形象，为避免侵权需手动移除

📊 ❤️ 379 | 📝 92 词 | 🔗 深度阅读

👤 (3) X 上的 Marcio Lima 利真 マルシオ 💎：“Even in the darkest alleys, her eyes never lost their fire. 🎬 By @grok imagine✨ { “camera”: { “type”: “handheld 35mm film”, “lens”: “85mm prime lens, shallow depth of field”, “position”: “low angle close-up, tilted slightly”, “focus”: “sharp on character’s https://t.co/yvMTnUER0B” | 行业资深观察员
发布于【2026年01月08日 12时】

暗巷中，短髮女戰士眼神堅毅，霓虹背光映照淚光與決絕

📊 ❤️ 95 | 📝 199 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“Today’s edition of my newsletter just went out. 🔗 https://t.co/RNAKpYierS This should be absolutely great. OpenAI is launching ChatGPT Health, a separate space in ChatGPT for health and wellness conversations. 🚨 Anthropic is lining up another mega funding round of $10B at a https://t.co/fFYouDdZiz” | 行业资深观察员
发布于【2026年01月09日 04时】

OpenAI推健康版ChatGPT，Anthropic拟融资百亿，中国暂停H200芯片订单，大模型存在文本泄露风险

📊 ❤️ 3 | 📝 110 词 | 🔗 深度阅读

👤 (3) X 上的 Nina Lopatina：“Last month, I dove deep with @swyx on @latentspacepod about the state of context engineering, and scaling it as a full-stack discipline with benchmarks, tooling, and enterprise deployments. Hosted by @LaudeInstitute on the rooftop of the Hard Rock Cafe during @NeurIPSConf (my” | 行业资深观察员
发布于【2026年01月09日 03时】

上月深度探讨上下文工程发展，涵盖基准测试、工具链及企业级部署，并展望2026年端到端系统设计趋势

📊 ❤️ 8 | 📝 154 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“New Stanford paper argues that LLMs already provide the raw skills for AGI, but they still need a coordination layer on top. Here the LLM is a fast pattern store, while a slower controller should choose which patterns to use, enforce constraints, and keep track of state. To https://t.co/jPEL5HGsh4” | 行业资深观察员
发布于【2026年01月09日 04时】

斯坦福研究提出，LLM已具备AGI底层能力，需通过协调层实现模式选择、状态跟踪与约束控制以提升可靠性

📊 ❤️ 11 | 📝 176 词 | 🔗 深度阅读

👤 (3) X 上的 Nick St. Pierre：“Midjourney v8 training is ~50% complete with expected delivery this month, and will come alongside a major redesign of the web app. Faster creation, style improvements, enhanced editing, new simplified interface, and more. Here’s what to expect: > Much better prompt accuracy >” | 行业资深观察员
发布于【2026年01月09日 04时】

Midjourney v8本月发布，训练完成过半，将显著提升图像生成准确度、手部细节及文本渲染能力，并同步推出界面重构与更快工作流

📊 ❤️ 129 | 📝 136 词 | 🔗 深度阅读

👤 (3) X 上的 Google AI：“We’re bringing @gmail into the Gemini era by making it a personal, proactive inbox assistant that accelerates your day. Here’s how it gets more done: — AI Overviews turn conversational questions into instant answers (e.g. “Who was that plumber that gave me a quote last year?”) https://t.co/yKYJ3DYfnq” | 行业资深观察员
发布于【2026年01月09日 04时】

Gmail引入Gemini AI，新增智能摘要、邮件辅助及任务优先级功能，率先面向美国用户推出

📊 ❤️ 267 | 📝 110 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“A frozen LLM can still improve if it learns which memories help, then reuses them next time. MemRL lets an agent improve after deployment by learning which memories help, while its text generating LLM stays fixed. The paper starts from a common problem: retraining an LLM on new https://t.co/1sGF7zMgOq” | 行业资深观察员
发布于【2026年01月08日 15时】

MemRL通过外部记忆库优化任务执行，无需调整大语言模型参数即可提升智能体性能

📊 ❤️ 217 | 📝 243 词 | 🔗 深度阅读

👤 (3) X 上的 Ksenia_TuringPost：“.@BostonDynamics and @GoogleDeepMind are teaming up to put real brains behind those robotic biceps Unveiled at #CES2026, this partnership fuses DeepMind’s Gemini Robotics AI with the next-gen Atlas humanoid. DeepMind’s visual-language-action models let robots: – perceive – https://t.co/okqAySUc30” | 行业资深观察员
发布于【2026年01月09日 03时】

波士顿动力与谷歌DeepMind合作，将AI视觉语言模型植入新一代Atlas人形机器人，推动工业自动化变革

📊 ❤️ 0 | 📝 73 词 | 🔗 深度阅读

👤 (3) X 上的 Riley Brown：“Me to Claude Code: “Can you please Create a skill that allows you to use Nano Banana, so that if I ask you for an image, you can generate it and put it in the public images folder” Yeah sure i’ll create that skill… *Creates the skill Since Claude Code running on https://t.co/zhkCTqKLyI” | 行业资深观察员
发布于【2026年01月08日 15时】

Claude Code获Nano Banana技能，可通过API网关生成并保存图片

📊 ❤️ 846 | 📝 70 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“This paper shows that training on mistakes, not perfect demos, can make tool using LLM agents much stronger. HardGen turns tool use failures into hard training data, letting a 4B LLM agent compete with much bigger models. An LLM is a text model that predicts the next words, and https://t.co/wrPptRZarB” | 行业资深观察员
发布于【2026年01月08日 14时】

本文提出HardGen方法，通过将工具使用失败案例转化为训练数据，使4B小模型在复杂工具调用任务中达到大模型性能

📊 ❤️ 129 | 📝 226 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“The authors show faster LLM fine-tuning on A100-40GB by cutting padding waste and avoiding huge intermediate outputs. Chronicals speeds up LLM fine-tuning by cutting wasted data movement and padding waste, so more runs fit on 1 GPU. In its main benchmark, it finishes the same https://t.co/RDc13uTpH8” | 行业资深观察员
发布于【2026年01月08日 11时】

Chronicals框架通过优化内存与计算，在A100上实现LLM微调速度提升3.51倍

📊 ❤️ 63 | 📝 214 词 | 🔗 深度阅读

👤 (3) X 上的 AI Guides：“95% of LinkedIn users saw their reach drop in 2025. Most have no idea what to post or when. So I built a LinkedIn Content Plan Generator Mega-Prompt that turns ChatGPT into your personal content strategist: → Full 30-day content calendar → Post formats matched to algorithm https://t.co/uoL1Cg3NGw” | 行业资深观察员
发布于【2026年01月09日 02时】

2025年领英触及率普遍下降本提示工具可生成30天内容策略与发布计划，提升互动

📊 ❤️ 2 | 📝 91 词 | 🔗 深度阅读

👤 X 上的 Rohan Paul：“This paper shows how to automatically generate attacks that expose hidden LLM security gaps before real users do. Manual tests rely on a few experts writing attack prompts by hand, so lots of risky behaviors never get checked. The framework asks an LLM to invent attack prompts https://t.co/mJjJ7iR5Li” | 行业资深观察员
发布于【2026年01月08日 09时】

本文提出一种自动化红队框架，通过模板引导生成多样化攻击提示，检测大语言模型的六类安全风险，将漏洞发现效率提升3.9倍

📊 ❤️ 30 | 📝 160 词 | 🔗 深度阅读

👤 (3) X 上的 Sharyph：“Stop paying for simple marketing assets. Here is how I built a $12k launch kit in 3 hours. If you are a solopreneur, a launch usually means dropping $2k-$5k on a designer or spending two weeks fighting with iterations… Last week, I needed a full suite of assets for a new” | 行业资深观察员
发布于【2026年01月08日 18时】

利用AI模型，3小时零成本生成专业营销素材，替代高额设计外包

📊 ❤️ 4 | 📝 207 词 | 🔗 深度阅读

👤 (3) X 上的 Lukáš Eršil：“The precision we’ve been waiting for! 🎨 The new FLUX.2 model partner in Adobe Firefly is a game changer. What I like most is its incredible “prompt adherence” – you simply type a specific HEX code into the prompt and the result is pixel-perfect. From now until January 15th, https://t.co/2xemDsiA1b” | 行业资深观察员
发布于【2026年01月08日 23时】

Adobe Firefly新推FLUX.2模型，支持HEX色码精准生成，特定用户享无限生成权益至1月15日

📊 ❤️ 16 | 📝 95 词 | 🔗 深度阅读

👤 (3) X 上的 AshutoshShrivastava：“Great breakdown from @kilocode on GLM 4.7 vs MiniMax M2.1 – two open-weight models that can actually handle real coding work now. Both built a complete 20-feature CLI task runner autonomously. No human intervention. Just planning, coding, testing, debugging on their own. The https://t.co/UgIO6o9DVN” | 行业资深观察员
发布于【2026年01月09日 01时】

GLM 4.7与MiniMax M2.1对比：开源模型能以极低成本自主完成复杂编码任务

📊 ❤️ 17 | 📝 102 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“A massive Stanford+Oxford and other top universities study found significant flaws in AI benchmarking. Says 84% of AI benchmarks lack clear definitions Benchmarking falls apart when the score on a test does not reflect the real skill people care about, and the paper calls this https://t.co/4QPGQlCoyu” | 行业资深观察员
发布于【2026年01月09日 01时】

斯坦福牛津等顶尖大学研究发现，当前84%的AI基准测试存在定义模糊、任务代表性不足、评分脆弱等结构效度缺陷，建议采用八步校验流程提升评估可靠性

📊 ❤️ 10 | 📝 186 词 | 🔗 深度阅读

👤 (3) X 上的 @levelsio：“This guy @iangcarroll makes $7M per year with his own bootstrapped business What I find interesting about people that make so much money on their own is that their physiognomy is almost always happy and likeable and friendly It’s same with billionaires, most of them are https://t.co/EgVJ8IWmWt” | 行业资深观察员
发布于【2026年01月09日 01时】

年入千万的创业者常具亲和力，与网络塑造的富豪刻板形象截然不同

📊 ❤️ 1758 | 📝 92 词 | 🔗 深度阅读

👤 (3) X 上的 Aakash Gupta：“Most people miss this. The real barrier in AI isn’t coding—it’s knowing how to work with agents. No-code tools like n8n let you build that skill fast, by actually doing it. .@PawelHuryn reveals why n8n is the secret weapon for aspiring AI PMs. Most people think you need to be https://t.co/wLJ5aGANoa” | 行业资深观察员
发布于【2026年01月09日 01时】

n8n无代码工具助AI产品经理快速掌握智能体协作核心技能

📊 ❤️ 10 | 📝 132 词 | 🔗 深度阅读

👤 (3) X 上的 swyx：“not actually surprising if you understand how coding agents is deployed at very large (>10k users per org) scale.* dont be surprised that ai crossing the chasm means that not every coding agent user is a “cracked” gen z mit dropout slinging CURRENT_THING” | 行业资深观察员
发布于【2026年01月08日 18时】

企业级AI编码代理规模化部署（超万人）揭示巨大商业潜力，技术普及需超越硅谷思维，实际应用与集成能力是关键

📊 ❤️ 157 | 📝 199 词 | 🔗 深度阅读

👤 (3) X 上的 Zeely AI：“PixVerse with Zeely brings characters into your product videos. Instead of freezing a product in one perfect shot, you can let it live inside a scene. Characters move, outfits change, moments unfold — even something as simple and playful as making snow angels becomes part of the https://t.co/Sz6MGs0F6u” | 行业资深观察员
发布于【2026年01月08日 23时】

PixVerse联合Zeely为产品视频注入动态角色与场景叙事，提升视觉吸引力

📊 ❤️ 23 | 📝 83 词 | 🔗 深度阅读

👤 X 上的 @levelsio：“We actually do shotgun to sniper in life all the time In dating you go on dates with different people to find a match, then when you find them you double down In getting a job you apply to lots of companies, then when you get the job you focus on that Digital nomading” | 行业资深观察员
发布于【2026年01月09日 01时】

人生策略：广撒网筛选，再专注深耕

📊 ❤️ 270 | 📝 102 词 | 🔗 深度阅读

👤 (3) X 上的 Rohan Paul：“Super cool release from Google 👏 They are putting Gemini 3 inside Gmail in 3 places: reading, searching, and prioritizing, instead of only offering basic canned “Smart Reply” style helpers. Gmail can now summarize long email threads as an “AI Overview,” a short recap of the https://t.co/4QUbMiiIeb” | 行业资深观察员
发布于【2026年01月09日 01时】

谷歌将Gemini 3集成至Gmail，新增邮件总结、智能搜索与撰写辅助功能，付费用户还可体验AI收件箱等高级工具

📊 ❤️ 11 | 📝 217 词 | 🔗 深度阅读

👤 (3) X 上的 Salman Paracha：“🚀 So excited to announce that Arch is now Plano: Delivery infrastructure for agentic apps. A framework-agnostic data plane that helps you build agents faster, and ship reliably https://t.co/ExfeiBqnwm. On the ground AI practitioners will tell you first hand that calling an LLM https://t.co/JnSYsN9fSS” | 行业资深观察员
发布于【2026年01月09日 00时】

Arch框架更名为Plano，专注为智能体应用提供框架无关的数据平面，解决生产部署中的编排、模型路由、信号采集与性能优化等核心问题

📊 ❤️ 16 | 📝 279 词 | 🔗 深度阅读

👤 X 上的 Hasan Toor：“China’s cockpit tech just hit a new milestone. The Geely Galaxy M9 has officially killed the legacy ASR-TTS bottleneck. By using StepFun’s Native E2E Audio LLM, it processes raw acoustic signals directly no clunky middleman. – Zero transcription loss: It hears nuance, not just https://t.co/3Sr5M7tKGx” | 行业资深观察员
发布于【2026年01月09日 00时】

吉利银河M9采用端到端音频大模型，实现零转录损失、亚秒级响应的实时智能座舱交互

📊 ❤️ 0 | 📝 71 词 | 🔗 深度阅读

👤 (3) X 上的 Qwen：“🚀 Introducing Qwen3-VL-Embedding and Qwen3-VL-Reranker – advancing the state of the art in multimodal retrieval and cross-modal understanding! ✨ Highlights: ✅ Built upon the robust Qwen3-VL foundation model ✅ Processes text, images, screenshots, videos, and mixed modality https://t.co/EXE2AeQG3u” | 行业资深观察员
发布于【2026年01月08日 22时】

Qwen3-VL多模态检索模型开源，支持图文视频跨模态理解与检索，性能领先

📊 ❤️ 1059 | 📝 129 词 | 🔗 深度阅读

👤 (3) X 上的 AshutoshShrivastava：“Alibaba Group’s Tongyi Lab open-sourced Fun-Audio-Chat-8B from their Tongyi Fun voice model family – a speech-to-speech (S2S) voice model that uses 50% less GPU while understanding emotional tone without explicit labels. Unlike traditional ASR→LLM→TTS pipelines, S2S processes https://t.co/ZLwXJ5xNpr” | 行业资深观察员
发布于【2026年01月09日 00时】

阿里开源Fun-Audio-Chat-8B语音模型，GPU消耗减半且能无标签识别情感，直接语音处理保留情感韵律

📊 ❤️ 11 | 📝 77 词 | 🔗 深度阅读