粉丝与涨粉
快照 11月3日 · 7 日榜 272 个账号可排本期浏览最高的帖子
- 1
Meet NVIDIA Nemotron 3.5 Transcribe 🎙️ An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint. Watch it keep track of who said what when everyone’s talking at once. 1/ 🧵
- 2
How do you make a chip design agent more reliable and efficient? The @Siemens EDA team used NVIDIA NeMo Gym to check the engineering files its agent produced, trace errors, and improve the agent’s skills and tool descriptions. In its standard cell characterization benchmark, those changes raised the composite verification score from ~55% to ~95%, with 66% fewer agent turns and 64% fewer output tokens. We just published a new techblog that walks through what the team measured, what they changed, and how other engineering teams can apply the approach → https://nvda.ws/4Beujcb
- 3
How do you assess cyclone risk beyond what a few decades of historical data can reveal? @AXA researchers are using NVIDIA Earth-2 to help fill that gap. Using FourCastNet 3, one of Earth-2’s open, global weather forecasting models, the team generated more than 1,000 simulated cyclone seasons to study possible storm activity around the globe. These simulations help researchers understand where cyclones travel, how often they occur, and how storms affect multiple regions within the same season. Those insights can inform AXA’s risk assessments and help customers target prevention efforts. Learn how AXA and other organizations are applying Earth-2 to weather forecasting, risk assessment, and environmental modeling: https://nvda.ws/4hPfG7z
- 4
Congrats @MistralAI team on the next gen Le Chonk! 🙌 1T-parameter MoE multimodal model trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs. Our day 0 support: NVFP4 on @huggingface → https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B-NVFP4 Scale distributed inference using performance-optimized Dynamo → https://docs.nvidia.com/dynamo/recipes/mistral-large-4
- 5
CUDA Live: Introduction to CUDA Rust https://x.com/i/broadcasts/1RKZzBapWDvKB
本周涨粉观察
全部观察每周一生成；中文区、7 日涨粉超过 1000 的账号会有条目。
发布节奏
最近 12 周每周中位浏览
最近 12 周发布时间
颜色 = 中位浏览爆款 vs 日常
爆款 = 浏览前 10%| 指标 | 爆款 | 日常 |
|---|---|---|
| 帖子 | 9 | 72 |
| 带媒体 | 22.2% | 65.3% |
| 回复 | 0% | 0% |
| 平均字数 | 236 | 247 |
| 中位浏览 | 3.4万 | 1,864 |
打法建议
只陈述相关性- 互动最好的时段是 05:00 前后（北京时间），中位浏览 1,484。
- 一周里 周一 的中位浏览最高。
- 形式上 纯文字 的中位浏览更高（1,922 vs 2,031）。
- 爆款里带媒体占 22.2%、回复占 0%；日常分别是 65.3%、0%。
- 当前节奏约 2.1 条/天，日均浏览 5,625。
内容结构
按本站分析的分类（近 120 天）- 模型19
- 产品16
- 产业16
- tip9
- 观点2
- 论文2
形式与语言
帖子占比- 视频36
- 纯文字32
- 图片13
回复占比 0% · 引用 25.9% · 带媒体 60.5%
互动最高的帖子
按浏览排序- 1
Engineer-to-engineer collabs are the best 🙌 Congrats to @AIatMeta on Muse Realtime Avatar! We worked with their team to make the model more efficient so the avatar can keep up when you talk to it.
- 2
Congrats to the OpenClaw community on OpenClaw Enterprise! 🦞 Organizations can use NVIDIA OpenShell as an open source option for governing agents with OpenClaw Enterprise. Glad to keep working with the community to make agents safer.
- 3
AI agents need clear limits on what they can do, and those limits need to hold up while they’re working. @JensenHuang was on CNBC this morning to talk about the safety measures we’re building to help make that happen. 🎥 from @SquawkCNBC:
- 4
Agents can run for days, calling tools, hitting errors, and trying again. The security policy has to keep working through all of that. NVIDIA OpenShell enforces it while the agent runs. Teams can add NVIDIA Sentry on BlueField-4 for independent monitoring and enforcement.
- 5
Huge congrats to the Kumo team 🙌 A new open foundation model for tabular data.
- 6
A video world model can make a convincing clip and still get the physics wrong. Our researchers just released Physis-Lang, an open self-evolving framework that adds physics reasoning to video captions. The captions explain why and how a scene unfolds. We use them to fine-tune world models and add that reasoning to prompts when generating video. Adding physics reasoning to the prompt alone improved NVIDIA Cosmos 3’s PhyGenBench score by 5.62 points without retraining. Paper and project: https://physis-intelligence.github.io/physis-lang-web/
- 7
Local AI: Running Nemotron on DGX Spark & Station | Nemotron Labs https://x.com/i/broadcasts/1RKZzBOEWMNKB
- 8
How a Small Korean Team Hit a Top 5 AA II Score in open model | Nemotron Labs https://x.com/i/broadcasts/1XxygwaaApbGM
- 9
Welcome Beam! Congrats to @ReflectionAI on launching their first open-weight model. The 501B MoE model was trained on NVIDIA GB300 NVL72 and delivers over 70K tokens/sec/GPU on Blackwell Ultra out of the box on day 0. 🤗 Beam 1.0 NVFP4 checkpoint on @huggingface: https://huggingface.co/reflection/Beam-1.0-501B-A23B-NVFP4
- 10
Meet NVIDIA Nemotron 3.5 Transcribe 🎙️ An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint. Watch it keep track of who said what when everyone’s talking at once. 1/ 🧵
- 11
Barcelona showed up ready to build 🦞. The road to #NVIDIAGTC Berlin is officially underway.
- 12
Available now: NVIDIA Nemotron 3.5 Bolt E4B 4GB ⚡️ Our newest small open model is built for local assistants, interactive characters and robots that can carry on a conversation and use tools to get things done. Watch Reachy Mini chat and move, with Bolt handling conversation and NVIDIA Cosmos handling vision. Both models run locally on Jetson Orin Nano 8GB. Learn more: https://research.nvidia.com/labs/nemotron/NVIDIA-Nemotron-3.5-Bolt-E4B-4GB/
点赞、转发、浏览是采集那一刻的快照，不是帖子最终数据；时间为北京时间。KPI 卡片里的同比只在账号有 8 周以上数据时显示， 否则只看近 4 周。“打法建议”只说明数据里的相关性，不代表因果。