firerozen

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.

Just finished designing a 3D-printed organizer for my Kenwood pasta attachment set 🍝 No more loose parts or messy drawers — everything fits perfectly now. Simple, practical, and super satisfying to print. Check it out 👉#profileId-2069943" target="_blank" rel="nofollow noopener">makerworld.com/en/models/1928…

@wangzhian8848 什么包这么厉害，都是火腿肠么

求助： 我有台五六年前用的苹果手机，里面保存了当年我还在国内的一些照片，重要文件，但是这个手机密码我忘了，后来放到包包里蹭来蹭去，不小心被我锁定了一千年，根本打不开了。 有没有技术大神，能帮我解锁这台苹果手机。 有的话欢迎和我私信联系。 感谢🙏

It's here!!!! Everyone go get this now! ghostty.org

Is that normal that i dont even get excited about phone of the year award anymore?

BREAKING: Controlled explosion at Euston station after suspicious package found news.sky.com/story/euston-s…

#linux users right now 🐧

@SnazzyLabs Porn…hub

We promise this is not a person in a bodysuit. bit.ly/3w5XRvH

git push --force twitter.com/timecaptales/s…

Two-faced PS5, anyone? 🔴⚫️ @ColorWare will give 1 random person who follows and RTs this tweet a PS5 slim in whatever colors they want for free! Good luck 😈

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Imagine "untraining" a Large Language Model on specific content. The New York Times doesn't want its content in ChatGPT. OpenAI would have to retrain its models from scratch. Removing any content from their models would cost them millions of dollars. I just read a new paper from Microsoft Research that tries to fix this. This is the only study I've found so far that's looking into making models forget. The paper proposes a process that makes a model forget about Harry Potter without retraining it from scratch. It's a proof of concept. The researchers aren't sure whether their solution generalizes to other topics. It's a first step, but it's cool nonetheless. What they did is kind of a hack, but I like it: They fine-tuned the model using a dataset containing the original Harry Potter text as the input tokens and some generic labels as targets. They pre-generate these generic labels. For example, instead of using "Harry," they use "Jack," and instead of using "Hermione," they use "her." In other words, they don't actually delete knowledge from the model. They overwrite it. As we start using these models everywhere, the ability to forget information will become critical. Let's see how much progress we make this year on this. You'll find a link to the paper in the image ALT.

TE never disappoints. Their hardware design is top notch.

财新《2023终有一别》，纪念本年辞世的多位中外人物。已被删除。此处可访问webcache.googleusercontent.com/search?q=cache… 来自@dashengmedia

@wangzhian8848 100兆就好

确实，永远也到不了一百万了。