We can finally talk about it:
We found a way to extract hidden reasoning of frontier models using a vulnerability in the APIs of every frontier AI company.
We verified that our reasoning token count matches billed API thinking tokens 1:1 for most of the prompts we queried.
Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
>be me
>grind for a decade trying to help make superintelligence to cure cancer or whatever
>mostly no one cares for first 7.5 years, then for 2.5 years everyone hates you for everything
>wake up one day to hundreds of messages: "look i made you into a twink ghibli style haha"
Zizheng was one of our interns at NVIDIA back in summer 2023. Later, when we were considering to make him a FT offer, he chose to join DeepSeek without much hesitance. Back then, the DeepSeek multimodal team only has 3 people.
I am still very much impressed by Zizheng’s decision at that time. He has been an important contributor of several important works at DeepSeek, including DeepSeek-VL2, DeepSeek-V3, and DeepSeek-R1. I am personally very happy for his decision and the great achievements.
Zizheng’s case is a very typical example of what I have witnessed in recent years. Many of our best talents come from China, and these talents don’t have to succeed only in a US company. Instead, we learn a lot from them. The same Sputnik Moment has already happened in AV back in 2022, and it will continue to happen in Robotics and LLM industry as well.
I love NVIDIA and want to see her as a continued major contributor to the path of AGI and general autonomy. But if we keep cooking up geo-political agendas and creating hostile opinions to Chinese researchers, we will shoot ourselves in the foot and lose even more competitiveness. We need more talent density, professionalism, learnings, creativity and stronger execution. We don’t need political narratives and clowns like Alexandr Wang.
do not, my friends, become addicted to cracked engineer culture. that way lies building mountains of cancerous abstractions that amount to nothing, yakshaving for decades until you are forgotten by history. follow instead your natural curiosities and your pursuit of divine glory
“I don’t even see the R’s. All I see is 302, 1618, 19772, 198, 3504, 1134, 19772, 198, 101830, 198, 138322, 198, 1100, 302, 1618, 19772, 25644, 1100, 3504, 1134, 19772, 1100.”
Thanks a lot Ian, greatly appreciated!
This is the first result of my 12 years of ML carrier and the one I am still most proud of, on the other hand I found this paper did not do justice to it.
The "lessons learned" slide at the end of the presentation might be worth checking out, especially.
https://t.co/SaKIOLRuVZ
@goodfellow_ian@ChrSzegedy I wrote my bachelors thesis about the application of adversarial examples in computer vision. The topic is super interesting! It’s cool to see variations of these methods now being used in LLMs