Lucas gives GPT-o1 the homework for Harvard’s Math 55, it gets a 90%
The linked tweet makes it look like Lucas also had an LLM doing the grading… taking this with a grain of salt!
tylerjohnston
Karma: 182
I’ve used both data center and rotating residential proxies :/ But I am running it on the cloud. Your results are promising so I’m going to see how an OpenAI-specific one run locally works for me, or else a new proxy provider.
Thanks again for looking into this.
Ooh this is useful for me. The pastebin link appears broken—any chance you can verify it?
I defintiely get 403s and captchas pretty reliably for OpenAI and OpenAI alone (and notably not google, meta, anthropic, etc.) with an instance based on https://github.com/dgtlmoon/changedetection.io. Will have to look into cookie refreshing. I have had some success with randomizing IPs, but maybe I don’t have the cookies sorted.
Sorry, I might be missing something: subdomains are subdomain.domain.com, whereas ChatGPT.com is a unique top-level domain, right? In either case, I’m sure there are benefits to doing things consistently — both may be on the same server, subject to the same attacks, beholden to the same internal infosec policies, etc.
So I do believe they have their own private reasons for it. Didn’t mean to imply that they’ve maliciously done this to prevent some random internet guy’s change tracking or anything. But I do wish they would walk it back on the openai.com pages, or at least in their terms of use. It’s hypocritcal, in my opinion, that they are so cautious about automated access to their own site while relying on such access so completely from other sites. Feels similar to when they tried to press copyright claims against the ChatGPT subreddit. Sure, it’s in their interest for potentially nontrivial reasons, but it also highlights how weird and self-serving the current paradigm (and their justifications for it) are.
ChatGPT is only accessible for free via chatgpt.com, right? Seems like it shouldn’t be too hard to restrict it to that.
A (somewhat minor) example of hypocrisy from OpenAI that I find frustrating.
For context: I run an automated system that checks for quiet/unannounced updates to AI companies’ public web content including safety policies, model documentation, acceptable use policies, etc. I also share some findings from this on Twitter.Part of why I think this is useful is that OpenAI in particular has repeatedly made web changes of this nature without announcing or acknowledging it (e.g. 1, 2, 3, 4, 5, 6). I’m worried that they may continue to make substantive changes to other documents, e.g. their preparedness framework, while hoping it won’t attract attention (even just a few words, like if they one day change a “we will...” to a “we will attempt to...”).
This process requires very minimal bandwidth/requests to the web server (it checks anywhere from once a day to once a month per monitored page).
But letting this system run on OpenAI’s website is complicated as (1) they are incredibly proactive at captcha-walling suspected crawlers (better than any other website I’ve encountered, and I’ve run this on thousands of sites in the past) and (2) their terms of use technically forbid any automated data collection from their website (although it’s unclear whether this is legal/enforceable in the US).The irony should be immediately obvious — not only is their whole data collection pipeline reliant on web scraping, but they’ve previously gotten in hot water for ignoring other websites’ robots.txt and not complying with the GDPR rules on web scraping. Plus, I’m virtually certain they don’t respect other websites with clauses in the terms of use that forbid automated access. So what makes them so antsy about automated access to their own site?
I wish OpenAI would change one of these behaviors: either stop making quiet, unannounced, and substantive changes to your publicly-released content, or else stop trying so hard to keep automated website monitors from accessing your site to watch for these changes.
I’ve asked similar questions before and heard a few things. I also have a few personal thoughts that I thought I’d share here unprompted. This topic is pretty relevant for me so I’d be interested in what specific claims in both categories people agree/disagree with.
Things I’ve heard:There’s some skepticism about how well-positioned xAI actually is to compete with leading labs, because although they have a lot of capital and ability to fundraise, lots of the main bottlenecks right now can’t simply be solved by throwing more money at the problem. E.g. building infrastructure, securing power contracts, hiring top engineers, accessing huge amounts of data, and building on past work are all pretty limited by non-financial factors, and therefore the incumbents have lots of advantages. That being said, it’s placed alongside Meta and Google in the highest liquidity prediction market I could find about this asking which labs will be “top 3” in 2025.
There’s some optimism about their attitude to safety since Elon has been talking about catastrophic risks from AI in no uncertain terms for a long time. There’s also some optimism coming from the fact that he/xAI opted to appoint Dan Hendrycks as an advisor.
Personal thoughts:
I’m not that convinced that they will take safety seriously by default. Elon’s personal beliefs seem to be hard to pin down/constantly shifting, and honestly, he hasn’t seemed to be doing that well to me recently. He’s long had a belief that the SpaceX project is all about getting humanity off Earth before we kill ourselves, and I could see a similar attitude leading to the “build ASI asap to get us through the time of perils” approach that I know others at top AI labs have (if he doesn’t feel this way already).
I also think (~65%) it was a strategic blunder for Dan Hendrycks to take a public position there. If there’s anything I took away from the OpenAI meltdown, it’s a greater belief in something like “AI Safety realpolitik;” that is, when the chips are down, all that matters is who actually has the raw power. Fancy titles mean nothing, personal relationships mean nothing, heck, being a literal director of the organization means nothing, all that matters is where the money and infrastructure and talent is. So I don’t think the advisor position will mean much, and I do think it will terribly complicate CAIS’ efforts to appear neutral, lobby via their 501c4, etc. I have no special insight here so I hope I’m missing something, or that the position does lead to a positive influence on their safety practices that wouldn’t have been achieved by unofficial/ad-hoc advising.
I think most AI safety discourse is overly focused on the top 4 labs (OpenAI, Anthropic, Google, and Meta) and underfocused on international players, traditional big tech (Microsoft, Amazon, Apple, Samsung), and startups (especially those building high-risk systems like highly-technical domain specialists and agents). Similarly, I think xAI gets less attention than it should.
Magic.dev has released an initial evaluation + scaling policy.
It’s a bit sparse on details, but it’s also essentially a pre-commitment to implement a full RSP once they reach a critical threshold (50% on LiveCodeBench or, alternatively, a “set of private benchmarks” that they use internally).
I think this is a good step forward, and more small labs making high-risk systems like coding agents should have risk evaluation policies in place.
Also wanted to signal boost that my org, The Midas Project, is running a public awareness campaign against Cognition (another startup making coding agents) asking for a policy along these lines. Please sign the petition if you think this is useful!
Thank you for sharing — I basically share your concerns about OpenAI, and it’s good to talk about it openly.
I’d be really excited about a large, coordinated, time-bound boycott of OpenAI products that is (1) led by a well-known organization or individual with a recruitment and media outreach strategy and (2) accompanied by a set of specific grievances like the one you provide.
I think that something like this would (1) mitigate some of the costs that @Zach Stein-Perlman alludes to since it’s time-bound (say only for a month), and (2) retain the majority of the benefits, since I think the signaling value of any boycott (temporary or permanent) will far, far exceed the material value in ever-so-slightly withholding revenue from OpenAI.
I don’t mean to imply that this is opposed to what you’re doing — your personal boycott basically makes sense to me, plus I suspect (but correct me if I’m wrong) that you’d also be equally excited about what I describe above. I just wanted to voice this in case others feel similarly or someone who would be well-suited to organizing such a boycott reads this.
Sorry, I’m kinda lumping your meme in with a more general line of criticism I’ve seen that casts doubt on the whole idea of extrapolating an exponential trend, on account of the fact that we should eventually expect diminishing returns. But such extrapolation can still be quite informative, especially in the short term! If you had done it in 2020 to make guesses about where we’d end up in 2024, it would have served you well.
The sense in which it’s straw-manning, in my mind, is that even the trend-extrapolaters admit that we can expect diminishing returns eventually. The question is where exactly we are on the curve, and that much is very uncertain. Given this, assuming the past rate of growth will hold constant for three more years isn’t such a bad strategy (especially if you can tell plausible stories about how we’ll e.g. get enough power to support the next 3 OOMs).
It’s true — we might run into issues with data — but we also might solve those issues. And I don’t think this is just mumbling and hand waving. My best guess is that there are real, promising efforts going on to solve this within labs, but we shouldn’t expect to hear them in convincing detail because they will be fiercely guarded as a point of comparative advantage over other companies hitting the wall, hence why it just feels like mumbling from the outside.
I’m not sure what you want me to see by looking at your image again. Is it about the position of 2027 on the X-axis of the graph from Leopold’s essay? If so, yeah, I assumed that placement wasn’t rigorous or intentional and the goal of the meme was to suggest that extrapolating the trend in a linear fashion through 2027 was naive.
Unless…
Made with love — I just think a lot of critics of the “straight line go up” thought process are straw manning the argument. The question is really when we start to hit diminishing returns, and I (like the author of this post) don’t know if anyone has a good answer to that. I do think the data wall would be a likely cause if it is the case that progress slows in the coming years. But progress continuing in a roughly linear fashion between now and 2027 seems, to me, totally “strikingly plauisble.”
Yeah, I think you’re kind of right about why scaling seems like a relevant term here. I really like that RSPs are explicit about different tiers of models posing different tiers of risks. I think larger models are just likely to be more dangerous, and dangerous in new and different ways, than the models we have today. And that the safety mitigations that apply to them need to be more rigorous than what we have today. As an example, this framework naturally captures the distinction between “open-sourcing is great today” and “open-sourcing might be very dangerous tomorrow,” which is roughly something I believe.
But in the end, I don’t actually care what the name is, I just care that there is a specific name for this relatively specific framework to distinguish it from all the other possibilities in the space of voluntary policies. That includes newer and better policies — i.e. even if you are skeptical of the value of RSPs, I think you should be in favor of a specific name for it so you can distinguish it from other, future voluntary safety policies that you are more supportive of.
I do dislike that “responsible” might come off as implying that these policies are sufficient, or that scaling is now safe. I could see “risk-informed” having the same issue, which is why “iterated/tiered scaling policy” seems a bit better to me.
My only concern with “voluntary safety commitments” is that it seems to encompass too much, when the RSPs in question here are a pretty specific framework with unique strengths I wouldn’t want overlooked.
I’ve been using “iterated scaling policy,” but I don’t think that’s perfect. Maybe “evaluation-based scaling policy”? or “tiered scaling policy”? Maybe even “risk-informed scaling policy”?
Sidebar: For what it’s worth, I don’t argue in my comment that “it’s not worth worrying” about nuance. I argue that nuance isn’t more important for public advocacy than, for example, in alignment research or policy negotiations — and that the opposite might be true.
Just came across an article from agricultural economist Jayson Lusk, who proposes something just like this. A few quotes:
“Succinctly put, a market for animal welfare would consist of giving farmers property rights over an output called animal well-being units (AWBUs) and providing an institutional structure or market for AWBUs to be bought and sold independent of the market for meat.”
“Moreover, a benefit of a market for AWBUs, as compared to process regulations, is that an AWBUs approach provides incentives for producers to improve animal well-being at the lowest possible cost by focusing producer and consumer attention on an outcome (animal well-being) rather than a particular process or technology (i.e., cages, stalls, etc.). Those issues for which animal activists can garner the largest political support (e.g., elimination of cages) may not be those that can provide the largest change in animal well-being per dollar spent. By focusing on outcomes and letting producers worry about how to achieve the outcome, markets could enable innovation in livestock production methods and encourage producers to seek cost-effective means of improving animal well-being.”
“Animal rights activists often decry the evils of the capitalist, market-based economy. Greedy corporate farms and agribusinesses have enslaved and mistreated billions of animals just to earn a few more dollars—or so the story goes. Market forces are powerful and no doubt the economic incentives that farmers have faced in the last 50 years have contributed to a reduction in animal well-being. But markets are only a means, not an end. Rather than demonizing the market, animal advocates could harness its power to achieve a worthwhile end.”
I have major concerns with this class of ideas, but just wanted to share Lusk’s proposal in case anyone looks into it further.
I agree with your odds, or perhaps mine are a bit higher (99.5%?). But if there were foul play, I’d sooner point the finger at national security establishment than OpenAI. As far as I know, intelligence agencies committing murder is much more common than companies doing so. And OpenAI’s progress is seen as critically important to both.