同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
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Philipp Schmid@_philschmid同事件AI 评分7676
Sundar Pichai@sundarpichai同事件AI 评分7575
同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Demis Hassabis@demishassabis同事件AI 评分7373Demis Hassabis 发布 Gemini 4 Argon,称其在知识工作和编码方面表现出色,并展示用其生成的 wizard chess 游戏以体现物理理解和3D建模能力。

同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Google AI@GoogleAI同事件AI 评分7070Google 宣布前沿模型 Gemini 4 Argon 正在全球范围推出。官方称该模型面向编程、金融、法律、网络安全和科学等复杂现实任务,并附推文线索介绍如何在 Google 产品中使用。

同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Google AI@GoogleAI同事件AI 评分8080Google 宣布 Gemini 4 Argon 可用。开发者可通过 Gemini API 付费层使用,Google AI Ultra 订阅者可在 @antigravity。
同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Google@GoogleAI 评分5252Google 官方宣布 Gemini 4 Argon 正式推出。原文仅发布该推送消息,未给出更多功能或细节。

Google Gemini@GeminiApp同事件AI 评分7373
同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Google Gemini@GeminiAppAI 评分5858
Google Gemini@GeminiAppAI 评分5757
Google Gemini@GeminiAppAI 评分4444你可以将 40 多款应用连接到 Gemini,包括 @Instacart、@OpenTable、@Adobe 和 @Shopify,帮你处理订购杂货、预订餐位,到设计和搭建业务等各类任务。

Google Gemini@GeminiApp同事件AI 评分7373同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
François Chollet@fcholletAI 评分7474引用Sundar Pichai@sundarpichaiGemini 4 Argon 来了。 今天起面向全球开发者与企业开放,可通过 Gemini API 和 Gemini 平台的付费层级使用;Ultra 订阅者可在 Google Antigravity 中使用;Ultra 和 Pro 订阅者可在 Gemini 应用和搜索中使用。 希望大家喜欢!
Google DeepMind@GoogleDeepMind同事件AI 评分7474Google DeepMind 宣布 Gemini 4 Argon 现已全球可用。官方称该模型面向从始至终解决最难的问题,在编码、企业工作流和网络防御方面具备前沿能力。

同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Ammaar Reshi@ammaarAI 评分7373
Logan Kilpatrick@OfficialLoganK同事件AI 评分7676Google 宣布 Gemini 4 Argon 全球上线,覆盖 Gemini API、Gemini App 的 Pro 和 Ultra 用户,以及 Antigravity 的 Ultra 订阅用户。
同一件事,精选收录的是《Google 发布 Gemini 4 Argon:面向复杂工程与科研任务的前沿模型》
Manus@ManusAIAI 评分4040Gemini 4 Argon 已在 Manus 上线! 由 @googlecloud 联合呈现。 用它写代码、做规划、建 3D 模型,剩下的交给 Manus 搞定。
Rohan Paul@rohanpaul_aiAI 评分4343引用Eric Glyman@eglymanhttps://x.com/i/article/2109815621223358465
ElevenLabs@ElevenLabs精选AI 评分7070
推荐理由:由当事方宣布英国上议院首次有议员用 AI 重建嗓音演讲,读者可从中了解语音 AI 在医疗辅助场景的实际落地。
Manus@ManusAIAI 评分4545我们正与 OPPO 合作,将 Manus 引入 AI Mind Pilot 的全新 Agent Mode,首发搭载于 Find X10 系列与 ColorOS 17!
引用ColorOS@colorosglobalWe're thrilled to announce our collaboration with @ManusAI a leading AI agent platform, to bring next-generation AI experiences to smartphones. By integrating Manus’ agentic capabilities with OPPO AI Mind Pilot, this collaboration will help users turn complex, multi-step tasks into ready-to-use results. Find out more 🔗 https://www.oppo.com/en/newsroom/press/oppo-manus/
OpenBMB@OpenBMBAI 评分6464OpenBMB(面壁智能)发布 MiniCPM-V 4.7,35B-A3B MoE 多模态模型在手机上仅需 3GB 内存运行,可识读现实场景标识、按约束规划、解析复杂文档并对视觉数据进行推理。

Mistral AI@MistralAIAI 评分4444抬头看!Mistral 模型已进入轨道 🌍 很自豪能与 @orbitworksspace 和 @LoftOrbital 以及 @NVIDIAAIInfra 一起,加入首个此类 AI 卫星星座。
引用Loft@LoftOrbitalJust a few weeks ago, @orbitworksspace launched Altair, the first of a 50-satellite AI constellation that will enable users to receive AI-generated alerts within minutes. @NVIDIAAIInfra solutions is making this possible, supporting models like Mistral’s Ministral 3 to deliver fast, reliable answers for users' critical questions. Read more: https://lnkd.in/gGYA9hpD #SpaceMadeSimple #AIInfrastructure #AIforSpace
OpenRouter@OpenRouterAI 评分4242引用Neal Patel@neal_k_patelYou already gave the LLM the answer. So why is it writing it out from scratch? Introducing a new AI model architecture: Constrained Decoding Models (CDMs) LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable. CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive. Not just a decision model, but a family of 3 CDMs live today: • Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection. • Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction. • Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests. Built for production: • 1M tokens of multimodal (text + image) input, 31x larger than Jev • 77.2% on DecisionBench vs Jev's 72% • 200x faster, 467x cheaper than frontier LLM APIs • $0.05/M input tokens. Output is free (yes, even for summarize) Live on your favorite platforms today: @OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus Get 50M input tokens for free (for the first 50 hours) at link below 👀
Rohan Paul@rohanpaul_aiAI 评分5454
引用Neal Patel@neal_k_patelYou already gave the LLM the answer. So why is it writing it out from scratch? Introducing a new AI model architecture: Constrained Decoding Models (CDMs) LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable. CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive. Not just a decision model, but a family of 3 CDMs live today: • Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection. • Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction. • Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests. Built for production: • 1M tokens of multimodal (text + image) input, 31x larger than Jev • 77.2% on DecisionBench vs Jev's 72% • 200x faster, 467x cheaper than frontier LLM APIs • $0.05/M input tokens. Output is free (yes, even for summarize) Live on your favorite platforms today: @OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus Get 50M input tokens for free (for the first 50 hours) at link below 👀
数字生命卡兹克@Khazix0918AI 评分4646卡兹克公开自己每月约6000元的AI订阅组合:ChatGPT Pro 100刀、Claude Max 250刀、X Ultra 260刀、Suno Pro 8刀及LibTV至尊版1499元。
Tripo@tripoaiAI 评分4646仅用 16 天打造的惊艳《小王子》3D 改编作品。 @Saccc_c 用 Tripo、@Blender 和 Opus 5.5 @ClaudeDevs 构建了这个互动世界,干得漂亮。期待开源发布。
引用Sac@Saccc_c花费16天,我用 Opus 5.5 将小王子的故事制作成了3D剧情游戏 结合Tripo+Blender,Opus 5.5 将小王子故事中的每一个星球变成了可探索的3D场景 希望大家能支持一手,后续会开源整个游戏,以及详细制作流程 Welcome to The Little Prince: Across the Stars✨:https://littleprince.dev/
卡尔的AI沃茨@aiwartsAI 评分5555引用Brian Roemmele@BrianRoemmeleNEW GROK BOT! AI MEMORY TRANSFER! Your old AI knows you. Your new one shouldn't have to start from zero. 🧠➡️ Meet Memory Transfer, a @Grok @Bot that brings over what Claude or ChatGPT learned about you, so you don't spend weeks re-explaining yourself. There are two ways to bring it over: • Paste one prompt into your old chat and send me the answer. • Or drop in your full ChatGPT or Claude data export. The part that matters most is that nothing gets in automatically. We review every item together, one line at a time. Only what you keep gets saved, and each item is tagged with where it came from and when. Other AIs' guesses don't become facts, and nothing you've already saved gets overwritten unless you say so. Switch assistants and keep your context, without the junk. Try Memory Transfer on Grok Bot today. https://x.ai/bot/Ww-RXj-lLqpg_oWqzccKZ




