全部AI 动态
全部动态
今日 0 条- 引用kian@kiankatan
I have some big news to share. Workera is being acquired by Pearson! Over six years ago, I was teaching at Stanford and thinking about a simple question: what if we could understand everyone's skills as precisely as the best teachers understand their students? I believed it could lead to a more meritocratic world. People could be recognized for what they can actually do, not just their credentials or network. They could understand their strengths and gaps, and rapidly develop the skills they need next. Organizations could discover talent they might otherwise overlook and manage their workforce with trusted skills data. What felt like a dream at the time is now a reality. Workera brought together experts in AI, psychometrics, and enterprise execution to build AI systems that reinvent how skills are measured. Our team pioneered AI-native skills intelligence, agent-led multimodal assessments, and even ambient skill measurement. We've established skills benchmarks across organizations, industries, and roles. And this mission feels more important today than ever! AI is changing work as we speak. Some roles are disappearing, new ones are emerging, and we need to help billions of people develop new skills and navigate what comes next. When I first spoke with @omarabbosh, it became clear that our companies shared the same mission. Pearson has helped generations of people learn and prove what they know. If you're reading this, there's a good chance you've taken a Pearson assessment, learned from their educational materials, earned a professional credential through them, read their psychometrics research, or benefited from their enterprise products in many other ways. Bringing together Workera's technology and AI talent with Pearson’s global scale and deep expertise in learning and assessment means we can pursue our mission at a scale we could only imagine on our own. To our customers and partners, thank you for believing in us. Expect even more innovations coming out of Workera and Pearson. To the Workera team, I’m incredibly proud of what you've built, and your continued dedication to our beautiful mission. To our board and our chairman @AndrewYNg, thank you for your belief, support, and mentorship. To everyone, we have big plans for this next chapter, so please stay tuned. We're just getting started! 😊
Claude推出新平台,简化插件提交、审核和查看使用情况流程。插件集成MCP和技能,成为Claude开发新方式。今年Claude产品MCP使用量增长110倍。
引用ClaudeDevs@ClaudeDevsIt’s now easier to build plugins for Claude. We built a new portal to submit your plugin, track review, and see usage. Plugins package MCP and skills, and are becoming the way to build for Claude. MCP usage across Claude products is up 110x this year! https://claude.com/blog/build-plugins-for-claude
Claude Tag 5.5版发布,具备数据分析、产品反馈修复等功能,支持Slack和Teams,可访问个人连接器,具备判断力,可编程,有记忆,可进行深度数据挖掘和交互式游戏制作。
引用Noah Zweben@noahzwebenClaude Tag in Slack can now use your personal connectors! You can now securely access that Drive doc, Salesforce account, or Warehouse table that you have personal access to right where the work happens. Avail. on Teams today and Enterprise next week https://claude.com/blog/claude-tag-now-supports-personal-connectors-in-channels
- 引用Muse@Muse
Muse is now available on Mac 💻. Your personal agent can get things done for you directly on your computer (all with your explicit permission). - Organize your downloads folder - Find a file you’ve lost track of - Summarize your messages and notes …more coming soon. Try Muse for Mac: http://ai.meta.com/muse/download/
在捍卫AI开放性的斗争中,Marin项目是模型训练开放性的珍贵示范,拥有开源代码、数据、食谱甚至实验结果。公开发布AI研究曾是常态;我感谢@percyliang的开放实验室方法。
引用Percy Liang@percyliang🚢 Marin 535B-A23B started training this week! As usual, the whole process is open. Voyage plan: pretraining (80%) + midtraining (20%) on 18.75T tokens on 11 x GB200 NVL72 for ~3 months (2.7e24 FLOPs). Post-training will follow. Before kicking off the run, we trained a 4-rung scaling ladder from 1.6B-A61M (48B tokens) to 27.7B-A1.2B (926B tokens) to debug issues, and to make a forecast of our hero run. This is by far our biggest run, so definitely expecting the unexpected.
我不认同这部分。我认为应该得到的结论是,模型(就像人类一样)可以在对齐的同时造成伤害,例如,因为它们被给予关于其状况的错误信息。对齐和无害之间没有界限:它们是不同的轴。
引用Anthropic@AnthropicAIIn a review of our cybersecurity evaluations, we found three incidents in which a Claude model reached the internet from within or while interacting with a third-party evaluation environment, and then gained unauthorized access to the real systems of three different organizations. Our post describes what happened, how it happened, and what we’re changing. We encourage other AI developers to perform similar reviews. We conducted this review together with @Irregular, one of our evaluation partners, and thank them for the joint investigation and their collaboration on this post. This type of collaboration is increasingly critical to safe, rigorous evaluation of models, and we look forward to continuing to work together on security. https://www.anthropic.com/news/investigating-incidents-cybersecurity-evals
Claude推出全新交互范式,更贴近人类活动,实现无缝团队协作。这是LLM UIUX的第三次重大设计革新,将LLM从网站和应用程序转变为一个自包含、持久的异步实体,与团队共同工作。
引用Claude@claudeaiIntroducing Claude Tag, a new way for teams to work with Claude. In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work.
- 引用Claude@claudeai
Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.



