全部 AI 动态

Day 1/ We have optimized the default speed to be ~50% faster across GPT-6 Astra and GPT-6.1 Sol through the subscription across all our products and partners using Sign in With ChatGPT (including OpenCode, Pi, Amp, Devin, ...). No changes needed on your end and this should be felt within the next two hours.

Anthropic 计划在未来几年内在云和算力上花费 5180 亿美元，约是其 2025 年底持有的 203 亿美元现金和短期投资的 25 倍。 其招股书草案指出，多家供应商同时也是 AI 竞争对手，这可能“不利影响”其获取算力。 在 Anthropic IPO 之后，@TradrETFs 预计将推出杠杆做多和做空 ETF，$ANTT 和 $ANTZ。 与这些证券相关的注册声明已提交给美国证券交易委员会，但尚未生效。请参阅生效前招股说明书。https://www.sec.gov/Archives/edgar/data/1587982/000121390026021796/ea0278457-01_485apos.htm

Meta and Microsoft are cutting employee use of Claude Earlier, Microsoft had projected at least $1B in internal Claude spending this year, then cut that figure by more than 33%. OpenAI's own data show the climb steepening late, with the median researcher consuming more than $600 worth of tokens per day i.e. around $1.8 mn per emplyee/per year. Those agents now log 3.1 agent-workdays for every human workday, using an eight-hour workday as the comparison. Microsoft is moving the other way, cutting most per-employee AI budgets in its 60K-person cloud and AI group from $100K to about $10K a month, roughly $333 a day. Meta's Claude Code users have likewise fallen from about 60K to about 30K, as staff shift to its in-house MetaCode and Muse Code tools.

Power users are driving consumer AI market growth. The top 1% of US consumer AI payers average $903 a month, while flat plans hold the median at $25. One top-1% payer spends as much as roughly 59 bottom-half payers, on average. Median spend has barely moved, while average spend in the top 1% climbed from $504 to $903 a month between January 2025 and August 2026. Model labs are better placed than apps built on their models to capture consumer AI's top 1% of spenders. Those users average $903 a month, up from $504, and most of it buys model usage. A lab pays only its serving cost for that usage, while an app pays API prices. Anthropic earlier said one $200 Max subscriber ran up tens of thousands of dollars in usage, a bill no API-paying app could absorb. Apps that want this tier have to own more of the model, as Cursor began doing with its Composer coding model.

The top 1% of AI spenders now outspend the bottom 50% combined They spend an average of $903/month, while the median customer spends just $25 More charts in our Top 100 Consumer AI Apps breakdown: https://www.a16z.news/p/top-100-consumer-ai-apps-seventh

OpenAI's median researcher used $601 of coding-agent inference a day at API prices, up from under $1, in January 2026. Eoch AI's new report. > OpenAI researchers' coding-agent usage, valued at API list prices, is doubling roughly every month > By mid-August 2026, the median researcher used $601 a day and about $2M a year, roughly matching or exceeding what employing a researcher costs. > This pace probably can't last, since one more year would reach about $185M per median researcher, and list-price figures reveal nothing about what OpenAI actually spends.

> Sam Altman does all his prompting on prompting on 'ultra fast' > Boris Cherny, head of Claude Code at Anthropic: “I use Fable for everything" > OpenAI's median researcher used $601 of coding-agent inference a day (about $1.8M a year, r) at API prices, up from under $1, in January 2026.

OpenAI's median researcher used $601 of coding-agent inference a day at API prices, up from under $1, in January 2026. Eoch AI's new report. > OpenAI researchers' coding-agent usage, valued at API list prices, is doubling roughly every month > By mid-August 2026, the median researcher used $601 a day and about $2M a year, roughly matching or exceeding what employing a researcher costs. > This pace probably can't last, since one more year would reach about $185M per median researcher, and list-price figures reveal nothing about what OpenAI actually spends.

The seventh edition of our Top 100 Consumer AI Apps is here. New this time: a revenue leaderboard, alongside the usual web and mobile traffic rankings. Three years ago we published the first edition. ChatGPT was #1, Claude was unranked, and the entire category was chatbots, image generators, and not much else. In today's edition: - ChatGPT still holds the throne, now with 1B+ monthly actives on mobile - Claude has climbed to #3 on web with nearly 1B monthly visits - The category has expanded to vibe coding (Lovable, Cursor, Replit), music (Suno), design (Figma), voice (ElevenLabs), video (Higgsfield, Kling), agents (Manus), and even hardware (Plaud) Full breakdown from @omooretweets: https://www.a16z.news/p/top-100-consumer-ai-apps-seventh

Your Slack group DMs can now include Claude. Add it the same way you'd add anyone else. Claude answers in a thread and keeps following it, so anyone in the DM can reply there and reach it. It can also use the personal connectors of whoever asks.

The seventh edition of our Top 100 Consumer AI Apps is here. New this time: a revenue leaderboard, alongside the usual web and mobile traffic rankings. Three years ago we published the first edition. ChatGPT was #1, Claude was unranked, and the entire category was chatbots, image generators, and not much else. In today's edition: - ChatGPT still holds the throne, now with 1B+ monthly actives on mobile - Claude has climbed to #3 on web with nearly 1B monthly visits - The category has expanded to vibe coding (Lovable, Cursor, Replit), music (Suno), design (Figma), voice (ElevenLabs), video (Higgsfield, Kling), agents (Manus), and even hardware (Plaud) Full breakdown from @omooretweets: https://www.a16z.news/p/top-100-consumer-ai-apps-seventh

🚀 We let Jev play Minecraft. And we just can't beat it! 😭 ⚡ Jev: 24 ms decisions 🧠 You: ~200 ms reactions It moves before you even see it move. Way too strong! 🎮 https://mc.alexzms.com (join the server to win)

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trained end-to-end from scratch Full weights release this month. Learn more about Beam: http://reflection.ai/beam

Hi! I work on Cowork. Probably no surprise, but we want to make our users as powerful as possible with Claude - and you're right that explaining and keeping up with the capabilities is hard. Affected users got both an email and an in-app notice, but I'm grateful for the feedback - I think this change was more surprising to people than I'd like it to be. This one will be a longer explainer, bear with me! The "old" version of Cowork runs model inference in the cloud, executing tool calls in an Anthropic-provided VM we shipped to your computer. We added the VM for capability, safety, and security reasons - mapping in just the data you explicitly added to your session. People loved what they were able to do with Claude but didn't love the disk, battery, and performance cost of running the VM locally. Also, people didn't love that closing your laptop means the work stops. The "new" version of Cowork runs model inference and the VM in the cloud. Each session gets its own sandbox, not sharing state with other sessions. When the VM needs something on the users' device (like a file), the desktop app is responsible for that file access tool call. To be clear, Claude will only access files in folders that the user explicitly added to the session, the same way Claude only saw files explicitly added to the VM in the "old" version. Sandboxes are destroyed when the session ends! We think this solves a lot of problems we've heard about (like using Cowork from a phone, keeping work running, or getting all the same power without losing battery to the VM) - but we'll keep iterating on new feedback we hear!

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trained end-to-end from scratch Full weights release this month. Learn more about Beam: http://reflection.ai/beam

llama.cpp v0.6.0 https://github.com/ggml-org/llama.cpp/releases/tag/v0.6.0

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trained end-to-end from scratch Full weights release this month. Learn more about Beam: http://reflection.ai/beam

https://x.com/i/article/2089454679130578944

OpenAI recently published data on its researchers’ coding-agent usage. We took their weekly figures from January to mid-August 2026 and fitted trends to summarize how quickly spending grew. We found that spending has been doubling about once a month.

We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the significant limitations of current text watermarking technology. Our tools already help verify whether an image or audio file was created with our models. This work builds on those efforts to help people better understand when content may have been generated or edited with an OpenAI model. In the EU, we’ll start watermarking eligible text from ChatGPT and Codex over the coming weeks to comply with the EU AI Act. Customers using our API can turn on text watermarking for select models worldwide today.