I've switched off to runners and event scheduling inside AWS, and am working on moving my company off of GitHub. I know engineers inside GitHub and it doesn't sound like the talk they've been putting out about reliability is actually being addressed with many resources internally; the best people in the company are chasing AI product features (which are apparently quite profitable).
Yes exactly. Automatic model downgrade seems horrible for a lot of production workloads, even if you are deterministically constraining the behavior of your agents.
>It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes.
If the conversation was in the training set, there's a high likelihood that the small set of conversations related to solving Navier-Stokes was used by the model. I get Astra to still quote some of my friends' books or blogposts nearly verbatim on certain niche issues.
Much more importantly, we _can_ determine whether a conversation was used in the training data. And if it was, it gives us a great idea whether that logic was captured in reasoning for a novel problem never yet solved.
Given that you don't see any of this as below the belt according to your other comments, maybe your contribution here is more for yourself than a fair conversation about attribution.
The flaw with this line of reasoning is that Buckmaster and Alpöge only had a partially completed proof of a weaker version of the Navier-Stokes problem. OpenAI's internal model solved the full, harder problem. This means the key information needed to bridge the gap was not present in Buckmaster and Alpöge's chat history.
You might retort that ChatGPT used the training data to copy their approach, but the approach Buckmaster and Alpöge chose was already published by Luis and Diego in 2023 and in every frontier model's training set.
This argument proves too much. By this standard, it wouldn't have counted as copying their approach if the researchers had just fed in Levent & Buckmaster's paper verbatim as a prompt into the swarm.
I don't think the person describing the paper by Buckmaster as the same as the 2023 paper by Córdoba and Martínez-Zoroa is really discussing this in good faith fwiw. There are some massive advancements within it and if the person was participating wasn't just regurgitating something to "win the argument" in their eyes, they wouldn't describe it that way.
I don't believe people are denying that the model is impressive. The problem is that learning someone else is making progress on a topic using method X and then rushing to scoop them borders on academic misconduct. If, on top of this, their private conversations about X were used in the proof, I really don't see how its defensible...
The rumor going around X was that Anthropic had solved a Millennium Prize problem weeks ago and was sitting on the solution, waiting to release it right before their IPO to maximize hype.
If I were at OpenAI, I'd naturally want to snipe that from them. I am completely unsurprised they formed a crack team to steal Anthropic's glory, and do so in just five days.
Between companies, direct malevolent competition is OK.
Between academics, there are other rules to the game.
When you go into a boxing match, you agree to get punched in the face.
All this to say, trust is important, and grounded in social convention.
So I do agree with you, but also disagree.
Whenever this is OK or not really depends on how the breakthrough is contextualized, and how there people at play, here, agree to contextualize it.
In my view, in the blog post, there is much discussion about who will be publishing the paper. If instead it was just a blog post that said "oops, we beat you to it, our model is the best", it would have been different.
I’m pretty sure you think you are doing a good job of defending your employer and you probably believe “Open”AI are the good guys here. I also acknowledge that they butter your bread so your financial future currently depends on their success.
However the way you are conducting yourself in public, while announcing yourself as an OpenAI employee is doing enormous harm to the greater and magnanimous aim of your organisation. Take a step back and read the temperature of the room. Being the smartest guy in the room will never protect you from alienating the rest of the room into a baying mob. Right now you are Icarus flying straight into the sun.
It's unclear if you're suggesting that OpenAI did not train on their input or use their chats as inputs to training on a model that found the solution. Let's not provide an Elizabeth Holmes-esque interview where the question is dodged and words gain new meaning. The question can be answered with "Yes, we trained on their conversations" or "No, we did not train on their conversations".
I'm not coming from a place of distrust here. This should just be definitively answerable given the weight of the claims here. Surely between you, your lawyers, and other members of your team you can just clear this part up.
Given that he has other former collaborators corroborating this horrific behavior, it seems like this a career spanning pattern, and it's interesting to see just how much @sama is willing to lend his support to someone like Bubeck.
Stains an important moment in the history of AI progress for me. The future seems bleak with people like this at the reins.
He kind of fell off. He left Microsoft to found a scam company called "SoftwareOnline.com" that used ads to trick people into downloading fake anti-virus software. The software didn't do anything besides show the user nag messages about fictional security threats that could only be addressed by buying the full version, and could not be fully uninstalled. See https://www.atg.wa.gov/news/news-releases/attorney-general-s...
Meanwhile, the creators and maintainers of linux 'btop' haven't scammed anyone or been sued by any state AGs. Shocking, I know! It's almost as if you can write a system status monitor application without doing anything shady.
Being the Task Manager Guy became his whole brand. Any time he's brought up, the Task Manager topic is sure to follow. No wonder he's doing more Task Managers. It's so pervasive it's kind of funny.
I don't mind color, the glow effects just hurt the ability to read what's there (this reminds me of the gaming setups teenagers are drawn to)...but there's no reason a utility like a task manager should be closed source or have a pro version.
It's a bit of both for Anthropic I think, sometimes cutting edge and quite interesting or just good improvements, sometimes ignoring best practices either recently established or known for decades. Obvious to see where the smart people are in high places at the company.
Lately I've been throwing tasks at Qwen and a frontier or recently-frontier model (as well as Kimi, GLM, etc) and the smaller parameter models are not really comparable to Opus when it comes to making intelligent decisions about greyer areas of good software architecture.
Amazing results for open weight and that size, but a really long way off, and I'm extremely skeptical of benchmarks that show these smaller models as being anywhere close to Opus 4.8 (or even earlier Opus's).
I’ve been doing the same thing, giving the same tasks to Qwen 3.8 27B and Opus, and the main difference is that Qwen does not consider edge cases which Opus catches. It’s good at the happy path, but even when hinting that there are uncovered edge cases and gotchas it’s oblivious to it. So I feel like I need a bigger model to do planning/review.
I got so much better experience LLM-Chunking(think RAG) with qwen-38 27B ONCE i move the thinking effort to HIGH vs XHIGH (i think is the default on Open Router).
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