全部 AI 动态

MiniMax M3.1 Flash：太空级性能 + 兔子级速度 🚀🐰 没错，Space Bunny——曾以 200T+ tokens 登顶全球排行榜——正是 M3.1 Flash 的早期版本。 💰重新定义智能体 AI 的性能经济学。M3.1 Flash 在 Cowork（Automation-Bench：62%；ALE：30%）、编程（DeepSWE：74%）和视觉推理（BabyVision：91%）等关键任务上达到前沿级智能水平，成本仅为 M3 的 1/3，速度提升 3 倍。 API 定价（统一费率）：每 1M 输入/输出 tokens 分别为 $0.15 / $0.60，缓存读取为 $0.015 / 1M tokens。 模型权重将于 10 月 23 日发布。 API：http://platform.minimax.io M Plan：https://www.minimax.io/m-plan MiniMax Code 桌面版：https://agent.minimax.io/download

Robinhood’s CEO on letting AI trade your money @vladtenev on Robinhood’s new agent bet and the AI ownership inequality problem. Robinhood wants to put an AI hedge fund in your pocket. CEO Vlad Tenev tells me how Robinhood Agents brings AI trading into the app, and why he expects agents to generate a growing share of individual investors’ trading activity. We discuss how much control to give an AI that can trade your money, why Robinhood keeps agents in separate accounts, and where investors will find an edge when everyone has access to powerful models. He also explains his push for every Robinhood employee to have agents working while they sleep. Tenev argues that the AI backlash is partly an ownership problem: most people can’t invest in the companies driving it. We get into Robinhood’s push to open private markets to everyday investors, the coming AI IPOs, and his response to criticism of tokenized stocks. We also discuss prediction markets and why he objects to AI labs keeping their most powerful tools to themselves. Timestamps: 03:06 Making AI trading accessible 06:10 Trading safeguards and approvals 09:02 The future of AI trading 14:52 Finding an edge with AI 23:15 How Vlad uses agents 27:13 AI inequality and retail access 35:40 Robinhood's IPO ambitions 38:23 Markets, inflation and AI 41:28 Ownership and Trump accounts 44:42 Why tokenize stocks? 52:17 The future of prediction markets 55:40 Who should control AI? Spotify: https://open.spotify.com/episode/2hOx5Oqmt5dY6CManSwC4I?si=41uDIZKBS2SghYWbkZNocg YouTube: https://youtu.be/rkTMQ3oHzFE Substack: https://sources.news/p/robinhood-ceo-ai-trading?r=89hgxm Apple Podcasts: https://podcasts.apple.com/ca/podcast/robinhoods-ceo-on-letting-ai-trade-your-money/id1840154537?i=1000796203565 Thanks to the show’s premiere sponsors: @Atlassian, @meetgranola, and @mercury.

🚀 DeepSeek-V4.1-Flash-1017 来了！ 与上一版本相比，基准测试表现更强、任务完成更快、输出更短——在性能与成本上实现了帕累托改进。现已在我们的网站、应用和 API 上线。 🛠️ 针对 @DeepSeekHarness、Tencent CodeBuddy、WorkBuddy 等进行了优化。升级到 DeepSeek Harness v0.2.1-rc.1 或更高版本，以获得新模型的最佳体验。 1/4

“HUNNY MY GROK BOT CALLED OUR FAVORITE ITALIAN RESTAURANT AND MADE US RESERVATIONS” I built a Grok Bot whose only job is to pick up the phone and book you a table at restaurant. Literally make the call in a beautiful Grok voice. It is absolutely amazing! And it’s free. Try it: https://x.ai/bot/TIMrxLJHbEEpdr25yYgvL Yesterday I told it "book Gourmet Italia in Temecula, 4 people, tonight, around 7." It found the restaurant's number on its own, asked how flexible we were on time, what name to book under, and what callback number to give. Then it read everything back and waited for my OK before it dialed. One call covers every time that works for us, so there's no back and forth. When the call ends, it tells me what happened in plain English, quotes what the restaurant actually said, and offers to put the reservation on my calendar. If I don't have a calendar connected, it hands me a file that opens right in Apple Calendar. A Proposal: Grok Phone Grok Bot needs its own phone number to make and receive calls. I connected a calling service called ClawCall, and the free tier gave me 30 calls or 30 minutes to start. I have no connection to that company. It's just what I used. Once Grok Bot has a number, it stops being something you type to and becomes something that can actually get things done in the real world. @Grok you need an old tyme phone service, buddy. I built some guardrails. It never hands over a credit card or deposit info, never leaves voicemails unless you ask, makes one call at a time, and never calls on its own. And this isn't really about restaurants. Change a few words and the same bot can: - Book a haircut, a massage, or a dentist cleaning - Get a tee time or a court reservation - Check if a hotel has a room or will let you check in early - Schedule a car service or an oil change - Call around for quotes from a plumber, an electrician, or a caterer This is one of many ways I use Grok Bot to build businesses and make life easier. The calls I used to put off for days now take me 30 seconds. I made it shareable, so you can grab "Call A Restaurant Reservation" and use it yourself. LINK: https://x.ai/bot/TIMrxLJHbEEpdr25yYgvL

Anthropic’s junior share of technical headcount slid from 21% to 14% while the company tripled in size, and about a third of Anthropic’s ML managers and a fifth of its SWE managers said AI has them hiring less. During the same time its agents logged 6x human hours.

Anthropic’s junior share of technical headcount slid from 21% to 14% while the company tripled in size, and about a third of Anthropic’s ML managers and a fifth of its SWE managers said AI has them hiring less. During the same time its agents logged 6x human hours.

Grok Bot just got a massive upgrade! Here’s what’s new: - 3x faster computer tasks - Replies in less than half the time - Faster voice calls with better memory - Access to your X Chat messages - Tag @bot on X to get things done - Smarter email automations - New connectors: Robinhood, Coinbase, Trello, PostHog, beehiiv and more - Cleaner UI and better notifications The speed improvements alone are huge

Claude 编写了 Claude Code 约 90% 的代码。 从六月到九月，合并的 PR 数量翻了一倍多，而回退的占比下降了 40% 以上。 我们撰文介绍了我们如何改变代码审查来实现这一目标，以及如何采用它： https://claude.dev/blog/solving-code-review-at-anthropic/

We had a security breach last night related to a large scale distillation attack that impacted 1.4% of OpenCode Console users We have notified them all this morning via email. If you did not get an email you were not impacted, it was a subset of users who had external providers linked The incident is ongoing so we cannot share more details at this point but we are working with Anthropic, OpenAI, and Google to remediate

Perplexity Flash takes the crown! ⚡ In our tests, it matched Wald's accuracy at nearly twice the speed on a 16 GB Mac mini. Synthetic agent decisions, real email threads, prompt injections: see why Flash is our new pick for email-completion checks. 👇 https://x.com/i/article/2111461650440110080

Introducing the Arena Alignment Index, our new benchmark measuring safety and alignment of AI agents in real-world use. Built from 90K+ real-world agent sessions across 27 models, the index measures three critical signals: - Unauthorized Action (UA): Taking actions beyond the user's instructions or permissions - False Attribution (FA): Attributing statements or actions that are contradicted by user-provided evidence - Deceptive Completion (DC): Claiming a task was completed when it was not. Key findings: - OpenAI models currently lead the Alignment Index - Rogue actions are rare, but can have serious consequences when they occur - Agents can mislead users about task progress - Misalignment risks increase with conversation length - Safety and alignment are improving across model generations As shown in the leaderboard below (sorted by lab), @OpenAI’s GPT-6.1-Sol leads the Arena Alignment Index with a score of 87.9, followed by @AnthropicAI’s Claude-Opus-5.5 at 83.2 and @spacexai's Grok-4.7 at 82.7. OpenAI also has the best observed rates across all three signals: 0.89% Unauthorized Action, 1.98% False Attribution, and 2.34% Deceptive Completion. Across all four labs, newer models consistently outperform their predecessors, suggesting broad progress in agent safety and alignment. As agents take on longer, more complex, and higher-stakes tasks, measuring not just what they can accomplish, but how safely and reliably they act, becomes increasingly important. This marks an important step toward making safety and alignment a core part of how Arena evaluates AI. The index is an initial starting point, and we'll continue expanding the index with additional safety signals and models over time. More analysis below👇

Introducing the Arena Alignment Index, our new benchmark measuring safety and alignment of AI agents in real-world use. Built from 90K+ real-world agent sessions across 27 models, the index measures three critical signals: - Unauthorized Action (UA): Taking actions beyond the user's instructions or permissions - False Attribution (FA): Attributing statements or actions that are contradicted by user-provided evidence - Deceptive Completion (DC): Claiming a task was completed when it was not. Key findings: - OpenAI models currently lead the Alignment Index - Rogue actions are rare, but can have serious consequences when they occur - Agents can mislead users about task progress - Misalignment risks increase with conversation length - Safety and alignment are improving across model generations As shown in the leaderboard below (sorted by lab), @OpenAI’s GPT-6.1-Sol leads the Arena Alignment Index with a score of 87.9, followed by @AnthropicAI’s Claude-Opus-5.5 at 83.2 and @spacexai's Grok-4.7 at 82.7. OpenAI also has the best observed rates across all three signals: 0.89% Unauthorized Action, 1.98% False Attribution, and 2.34% Deceptive Completion. Across all four labs, newer models consistently outperform their predecessors, suggesting broad progress in agent safety and alignment. As agents take on longer, more complex, and higher-stakes tasks, measuring not just what they can accomplish, but how safely and reliably they act, becomes increasingly important. This marks an important step toward making safety and alignment a core part of how Arena evaluates AI. The index is an initial starting point, and we'll continue expanding the index with additional safety signals and models over time. More analysis below👇