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 | 3 | 24 |
| 带媒体 | 33.3% | 41.7% |
| 回复 | 0% | 0% |
| 平均字数 | 360 | 370 |
| 中位浏览 | 593.9万 | 1.5万 |
打法建议
只陈述相关性- 互动最好的时段是 03:00 前后(北京时间),中位浏览 326.4万。
- 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(1.7万 vs 3.5万)。
- 爆款里带媒体占 33.3%、回复占 0%;日常分别是 41.7%、0%。
- 当前节奏约 0.5 条/天,日均浏览 84.9万。
内容结构
按本站分析的分类(近 120 天)- 产品9
- 产业7
- 观点4
- 论文2
- 模型1
形式与语言
帖子占比- 纯文字16
- 视频9
- 图片2
回复占比 0% · 引用 29.6% · 带媒体 40.7%
互动最高的帖子
按浏览排序- 1
More model choice coming to Copilot. Welcome Grok!
- 2
Great conversation with @chamath, @jason, @davidsacks, and @friedberg on all the work ahead when it comes to diffusing benefits of AI broadly, earning permission from communities, and ensuring AI safety and control.
- 3
We’re building Copilot as a new OS for work that spans every model, every form factor, and every task. Today, we’re announcing our biggest update to Copilot to date, bringing four things together: · Autopilot: proactive and long-running agent built for the enterprise · Code: build apps with Copilot, hosted inside your company’s tenant · Home: Chat + Cowork together · Office: now fully embedded in Copilot (and Copilot embedded in Office, of course!) Plus, you can invoke Copilot in Teams, and we’re introducing Today, a proactive experience that surfaces the most important information from across M365 without needing to ask for it. The way we work is changing and so are our workflows. This update brings AI into that flow, from answering a question, to building an app, to getting work done on your behalf.
- 4
Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing. We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive. And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control. So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk. The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia. This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.
- 5
The motivation behind the new Copilot: intelligence is accelerating fast. Now we need to diffuse it everywhere.
- 6
Quincy, Washington shows what’s possible when you build datacenters with communities, and grow together over time.
- 7
With the @NFL back tonight, love seeing @Seahawks analyst Brian Eayrs and coaches across the league using new Copilot and Excel tools to help with decision making in the booths and on the sidelines.
- 8
Great example from @jeffhollan showing how Foundry makes long-running agents enterprise-ready, starting with business outcomes and building security, safety guardrails, auditability, and FinOps into the system from the start, across the entire multi-agent, multi-model workflow.
- 9
Thank you, @POTUS, for this incredible honor today. I'm humbled to stand alongside so many giants of American innovation and looking forward for what we can continue to do together to advance technology and drive American prosperity.
- 10
https://x.com/i/article/2108204296286400512
- 11
Today we are announcing our biggest bet yet on our own silicon. Starting next calendar year, we will scale our Maia family to multi-gigawatt deployments, making it the primary inference system for our own product and services. And we’re introducing Maia 300, which delivers 40% more tokens per watt compared to leading GPU-based systems. We are already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot. Our goal is to build on the full-stack efficiency gains we’ve already seen, while continuing to bring the latest innovations from across the ecosystem into our fleet.
- 12
Great to meet with the @saintgobain team in Paris today and learn how they’re using Microsoft Discovery to help accelerate the development of new more-efficient construction materials.
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。
