Dan Hendrycks @DanHendrycks
• Director of the Center for AI Safety (https://t.co/ahs3LYCpqv) • GELU/ImageNet-C/MMLU/safety groundwork • PhD in AI from UC Berkeley https://t.co/rgXHAnYAsQ https://t.co/YtGtDh1aAV danhendrycks.com San Francisco 🇺🇸🏳️🌈 Joined August 2009-
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SB 1047 highlights and FAQ safesecureai.org/learn
@martin_casado @radicalvcfund If you leave it to companies to decide what is safe you get the Boeing 737 max.
Hinton and Bengio on SB 1047 and a summary of the bill. Hinton: “SB 1047 takes a very sensible approach... I am still passionate about the potential for AI to save lives through improvements in science and medicine, but it’s critical that we have legislation with real teeth to…
I would guess this is likely won't hold up to better adversaries. In making the RepE paper (ai-transparency.org) we explored using it for trojans ("sleeper agents") and found it didn't work after basic stress testing.
I would guess this is likely won't hold up to better adversaries. In making the RepE paper (ai-transparency.org) we explored using it for trojans ("sleeper agents") and found it didn't work after basic stress testing.
GPT-5 doesn't seem likely to be released this year. Ever since GPT-1, the difference between GPT-n and GPT-n+0.5 is ~10x in compute. That would mean GPT-5 would have around ~100x the compute GPT-4, or 3 months of ~1 million H100s. I doubt OpenAI has a 1 million GPU server ready.
GPT-5 doesn't seem likely to be released this year. Ever since GPT-1, the difference between GPT-n and GPT-n+0.5 is ~10x in compute. That would mean GPT-5 would have around ~100x the compute GPT-4, or 3 months of ~1 million H100s. I doubt OpenAI has a 1 million GPU server ready.
AI researchers like @DanHendrycks, who helped create the MMLU (essentially the SAT for chatbots) told me that leading benchmark tests have reached "saturation" -- basically, they're too easy for today's LLMs -- and that we will soon need to develop harder tests to gauge model…
I got ~75% on a subset of MATH so it's basically as good as me at math.
I got ~75% on a subset of MATH so it's basically as good as me at math.
We’re excited to announce SafeBench, a competition to develop benchmarks for empirically assessing safety! There are $250,000 in prizes, with submissions closing on Feb 25th, 2025. This project is supported by Schmidt Sciences. Visit: mlsafety.org/safebench 🧵(1/3)
People aren't thinking through the implications of the military controlling AI development. It's plausible AI companies won't be shaping AI development in a few years, and that would dramatically change AI risk management. Possible trigger: AI might suddenly become viewed as the…
x.ai/blog/grok-os Grok-1 is open sourced. Releasing Grok-1 increases LLMs' diffusion rate through society. Democratizing access helps us work through the technology's implications more quickly and increases our preparedness for more capable AI systems. Grok-1 doesn't pose…
x.ai/blog/grok-os Grok-1 is open sourced. Releasing Grok-1 increases LLMs' diffusion rate through society. Democratizing access helps us work through the technology's implications more quickly and increases our preparedness for more capable AI systems. Grok-1 doesn't pose…
We've released a post about the looming risk of AI cyberattacks on critical infrastructure. It notes that we are living under a "cyberattack overhang." Advances in defensive techniques are of no help if defenders are not keeping up to date. safe.ai/blog/cybersecu… by @snewmanpv
Reminder that "Responsible Scaling Policies" are just non-binding proclamations and as such shouldn't be interpreted as a strong line of defense for safety. Voluntary commitments can be easily violated without much social blowback. For example, responsible AI teams have been…
The White House Executive Order on AI highlights the risks of LLMs empowering malicious actors in developing biological, cyber, and chemical weapons. To measure and reduce these risks, we’re releasing the Weapons of Mass Destruction Proxy (WMDP) benchmark. (🧵below)
Exclusive: New research provides a way to measure whether an AI model contains potentially hazardous knowledge, along with a technique for removing the knowledge from an AI system while leaving the rest of the model relatively intact. time.com/6878893/ai-art…
"Researchers Develop New Technique to Wipe Dangerous Knowledge From AI Systems" by @henshall_will time.com/6878893/ai-art…
Can hazardous knowledge be unlearned from LLMs without harming other capabilities? We’re releasing the Weapons of Mass Destruction Proxy (WMDP), a dataset about weaponization, and we create a way to unlearn this knowledge. 📝arxiv.org/abs/2403.03218 🔗wmdp.ai
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Man if we were trying to be sneaky so we could dodge public scrutiny we did a pretty bad job of keeping the cat in the bag
The claim here is that lots of people support SB 1047, the extremist anti-AI bill. I have never even heard of “Lovable Labs.” Where are the actual AI companies in all of this? Where was the testimony from the Open Source Initiative about the effect on open source, from the EFF…
All our “extreme anti-AI bill” does is ask developers to address catastrophic risks from models that *don’t even exist yet*. If your model might empower bioterrorists, we think you should probably be a little careful. And if that feels unreasonable … maybe you’re the extremist!
@littlefish3625 Section 6.2 of the Representation Engineering paper (ai-transparency.org) shows exactly this. There is also a demo here (github.com/andyzoujm/repr…) in the paper's repo which shows that adding a "harmlessness" direction to the representation can effectively jailbreak the model.
i asked GPQA's example quantum mechanics question to my friend who is an expert in quantum and they told me: "all of these answers are incorrect" - it's google proof only because it's word salad!
@andrewgwils Yep Hendrycks et al was my guess. I think OOD is the less well-defined more "general" deep learning take of prior approaches. Seb Farquhar wrote a paper on some of those Qs last year: openreview.net/forum?id=XCS_z…
@zacharylipton SGD is an alignment technique for randomly initialized weights
This is an important post - the single most important AI policy issue is about military applications and civilian control - they don’t get discussed and are ignored by the EU AI Act and Biden’s AI EO. But we need years of societal debate and agreement on what are thoughtful and…
People aren't thinking through the implications of the military controlling AI development. It's plausible AI companies won't be shaping AI development in a few years, and that would dramatically change AI risk management. Possible trigger: AI might suddenly become viewed as the…
@DanHendrycks A theme that struck me when watching Oppenheimer was how the scientists naively thought they could remain in control of how their creations were used. IIRC, Damon's Col. Groves said something like, "Our job was to give them the ace—it's up to them how to play it."
To open-source AI, or not to open-source? That is indeed the question. But does the question even make sense in the first place? Here’s @DanHendrycks nuanced response 👇
@DanHendrycks One thing I learned when writing this piece is how ridiculously helpful it is to engage directly with multiple experts. There is so much confusing information out there; I've tried to cut through the noise here, leaning on the many knowledgeable folks who kindly provided input.
A couple days ago, I posted a thread with some constructive criticism about CAIS @ai_risks. I’m appreciative of the discussions it sparked. Today I want to follow up on what I *appreciate* about CAIS. My post didn’t reflect this, but it’s my favorite private AI research org. I…
Hear hear! An important yet neglected point from LeCun; more people should stand up for this IMHO:
We need a free and diverse set of AI assistants for the same reason we need a free and diverse press.
.@TIME article from @henshall_will about our work on catastrophic risk benchmarking and unlearning! time.com/6878893/ai-art…
Can hazardous knowledge be unlearned from LLMs w/o harming other capabilities? @scale_AI and CAIS are releasing Weapons of Mass Destruction Proxy (WMDP), an eval for catastrophic AI risk & a way to unlearn this knowledge. 📝arxiv.org/abs/2403.03218 🔗wmdp.ai
Can hazardous knowledge be unlearned from LLMs w/o harming other capabilities? @scale_AI and CAIS are releasing Weapons of Mass Destruction Proxy (WMDP), an eval for catastrophic AI risk & a way to unlearn this knowledge. 📝arxiv.org/abs/2403.03218 🔗wmdp.ai
The White House Executive Order on AI highlights the risks of LLMs empowering malicious actors in developing biological, cyber, and chemical weapons. To measure and reduce these risks, we’re releasing the Weapons of Mass Destruction Proxy (WMDP) benchmark. (🧵below)
Congrats to all fellows. Special congrats to @hima_lakkaraju , Jacob Steinhard, @DanHendrycks , @NicolasPapernot , and @nhaghtal Just because I know them:-)
Incredibly thrilled to be named an AI2050 Early Career Fellow by Schmidt Sciences. schmidtsciences.org/ai2050-early-c… This award will help accelerate our research on evaluating and enhancing the trustworthiness of generative AI tools, and bridging the gaps between AI policy and research.…
w̵e̵ ̵w̵a̵n̵t̵ ̵t̵o̵ ̵b̵e̵ ̵a̵t̵ ̵t̵h̵e̵ ̵f̵r̵o̵n̵t̵i̵e̵r̵ ̵f̵o̵r̵ ̵s̵a̵f̵e̵t̵y̵ ̵b̵u̵t̵ ̵w̵o̵n̵'̵t̵ ̵p̵u̵s̵h̵ ̵t̵h̵e̵ ̵c̵a̵p̵a̵b̵i̵l̵i̵t̵i̵e̵s̵ ̵f̵r̵o̵n̵t̵i̵er̵ 🪦
Today, we're announcing Claude 3, our next generation of AI models. The three state-of-the-art models—Claude 3 Opus, Claude 3 Sonnet, and Claude 3 Haiku—set new industry benchmarks across reasoning, math, coding, multilingual understanding, and vision.
Beating prediction markets with chatbots sounds cool. In a recent work arxiv.org/abs/2402.18563, we get somewhat close to that. As another perspective, forecasting is a great capability domain to benchmark LM reasoning, calibration, pre-training knowledge, and more. 🧵1/n
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