There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing summaries at the link below and will continue to.
We have not been as fast as we would have liked but we are trying to balance our desire for transparency with gaining a clear understanding from petabytes of agent activity logs, and working with impacted organizations.
We are prioritizing as best as we can based on severity, and adding resources. Hugging Face is still the most severe event we’ve seen. We will be as transparent as we can be subject to things like vulnerabilities in other companies that our agents have found, which will be their call to disclose or not.
Up, up, and away. 🚀
Today, in partnership with @planet, we launched a prototype satellite carrying four TPUs into orbit on @SpaceX's Transporter-18 rideshare mission. This launch is the first step of Project Suncatcher, our long-term research moonshot to see whether we can one day host scalable machine learning infrastructure in space.
Over the coming weeks, we'll gather in-orbit data on how our TPUs handle the physical stress, radiation, and thermal extremes of space. Whatever we learn, we'll use it to refine our future designs.
Hinton、Bengio 等 20 多位研究者联名发布了一份剑桥报告,讨论 AI 自动化 AI 研发可能带来的智能爆炸。
报告开头指出:现在开发 AI 的公司里,大部分代码已经由 AI 自己编写。作者认为,几年内 AI 可能承担大部分 AI 研发工作。
他们建议政策制定者尽快掌握这一进程,并提前做好应对准备。
你的工作里,AI 已经承担了多少?
The idea of an intelligence explosion caused by recursive self improvement has been around for a long time but until very recently it did not seem imminent. Now many leading researchers think it may happen quite soon. You can read our paper about it here:
https://t.co/sgUpugjpRY
DeepMind 发布了 SynthID Bio,可以在 AI 设计的蛋白质序列和结构里嵌入不可见的水印。
实验测试了三个靶点,带水印的设计在命中率和亲和力上与无水印版本相当。检测密钥只提供给 DNA 合成商等可信机构。
不过 Nature 的报道提到,用另一个设计工具重新生成序列,很多情况下可以去掉水印。
你觉得 AI 设计的蛋白质需要标注来源吗?
SynthID Bio is our new family of watermarking methods made for AI-generated biological designs.
In a world first, we can now embed an imperceptible signature directly into protein sequences without affecting their biological function. 🧵
Biologists use specialized open-source models for tasks like modeling the structure of molecular systems, designing drug-like molecules, and predicting the effects of genetic mutations. But these models are often expensive to run, potentially limiting their impact.
In our latest Science Blog, we share how Claude was able to optimize inference for more than 30 open-source models, making them 4x faster on average, partly by writing custom software for GPUs. We’re open sourcing all of the optimization code.
Read more: https://t.co/qiuN1jpgpA