全部 AI 动态

https://x.com/i/article/2110998085463945216

你对 Gemini 4 Argon 的早期反馈是什么？我们应该在哪里改进？我们认真对待你的意见。

【Tripo × Astra / Opus / Argon × Blender】 ３Dモデル完成しました✨ -------------------- 制作スキルはリプ欄で配布いたします! GithubURL添付いたしますので、良ければご活用ください！ -------------------- 制作期間はおよそ２週間（実質１ヶ月ですが、品質微妙で２回作り直しました💦） 簡単に制作ステップを解説すると以下の通りです。 ✅ 顔・身体・髪の毛・表情毎の３面図・アクセサリー類のイラストを作成 ✅上記のモデルをTripoで全て作成 ・全部SmartmeshP2.0 四角形5000～10000くらいのポリゴン数がおすすめ ・ポリゴン数が多すぎると、補正時に歪みやすくなります ✅各パーツをBlenderMCPで結合 ✅簡単な小物・装飾類は直接モデリングで作成してもらう ✅眼球のモデリング・手を補正 ✅リグ挿入・スキンウェイト調整、IK/FK制作 ✅揺れもの調整 ✅シェーダー調整 ちなみに翼の開閉もできるようにしました🔥 これは翼の構造自体をしっかりAstraに考えさせ、羽の配置を一枚一枚しっかりモデリングさせました！ 気合でこれくらいの品質のものまで作れるのはホント凄いですね💦 #Tripo

Exciting update: There’s a new leader in the Agent Arena among open models. MiMo V2.6 Pro by @XiaomiMiMo has landed the #1 spot with +3.8% net improvement! Earlier this week we evolved the Bash Recovery signal in Agent Arena (more info in thread). With this update, the new top 5 open models are: - #1 MiMo V2.6 Pro: +3.8% - #2 Deepseek V4.1 Flash (Max): +3.0% - #3 Hy4 preview: +2.9% - #4 MiMo V2.6 Flash: +2.5% - #5 GLM 5.2 (Max): +2.4% MiMo V2.6 Pro ($0.11 cost per task) and Flash ($0.05 cost per task) are the only two open models on the Agent Arena Pareto frontier! - Pro outperforms both #2 Deepseek V4.1 Flash while costing 15% less, and #3 Hy4 preview while costing 71% less. - Flash is 1.3 percentage points below Pro but is 55% cheaper. Congrats to the @XiaomiMiMo team on this contribution to the open ecosystem!

今天为 Chrome 用户带来几项重大升级！我们正在把 computer use 的能力带给每一位使用 Chrome 的人。 首先是：ChatGPT 现在可以使用你在 Chrome 中的标签页，让回答更有用，并帮你把事情办成。 如果你在 Chat 中，它可以查看你打开的标签页并收集信息。 如果你在 Work 中，ChatGPT 可以控制你的 Chrome 标签页来完成任务，比如发送消息、填写表单或下载文件。它甚至能帮你整理和分组那一堆打开的标签页。

Step 5 Preview from @StepFun_ai is live on DeepInfra, day zero. 600B open-weight MoE, 27B active. 1M context, text + vision. FP8. $1.00 in / $2.70 out / $0.05 cached per 1M tokens. Built for long-horizon agents: coding, frontend, finance. What would you load into 1M tokens first?

🛰️ @elonmusk 希望在 2027 年底前获得 10 吉瓦的算力。@JensenHuang 表示，Nvidia 现在将 @SpaceX 与云服务提供商客户并列计算，两家公司的工程师正在设计一款用于太空的服务器： "在我们图表的两个部分中，Elon 过去被归在企业类下。我们之前就是这样报告数字的。现在他属于我们的 CSP……他们规模巨大。 他在使用我们的技术来训练自己的 AI 模型之类的，当然还有部署模型……而 GrokBot 的需求，GrokBot 的消耗量真的是在飙升。然后，当然，他还把它租出去。所以这三件事结合在一起，他这样做相当独特…… 他热爱计算与实体建设之间的交叉领域……而且没有人比他更懂能源。 而我们将一起去探索的一个特别的新市场，就是把数据中心放到太空里。所以我们的两个工程团队正在非常紧密地合作，打造一种新型服务器、一种新型架构，它可能在太空和地球上都非常出色。" —— @JensenHuang，@nvidia 首席执行官，在 @BG2Pod 上与 @altcap 对话

interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works https://already-clean.goodfire.com/

Code Review is now generally available for Claude Team and Enterprise plans. Reviews are now faster, catch more of the bugs that matter, and admins can pick from Quick, Standard, or Deep review levels for each repo.

interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works https://already-clean.goodfire.com/

New voices. Better accents. And less "checking..." GPT-Live-1.1 brings these updates to Voice in ChatGPT, Codex, and dots, with new voices in French, German, Hindi, Mexican Spanish, Korean, and Japanese. Rolling out today to all users. Coming soon to the API.

Congratulations to @StepFun_ai on Step 5 Preview going open weights! RadixArk is proud to help power StepFun's first-party production API with SGLang at scale. Production inference means great token economics under strict latency requirements. SGLang and its cache-aware routing stack now bring that to Step 5 Preview in proven production traffic. Building with Step 5 Preview? Deploy with SGLang today!

Vibe coded hardware is here, and amazingly fun! This week I'm covering how to use @OpenAIDevs Codex, @CloudflareDev Workers and the Zectrix Note4C to build your own custom eink display. I made a train tracking screen 🤓🚂 https://jamesdevonport.com/p/can-you-vibe-code-hardware