891–900 of 1001 posts
Out of curiosity, I gave it the latest project euler problem published on 11/16/2025, very likely out of the training data Gemini thought for 5m10s before giving me a python snippet that produced the correct answer. The leaderboard says that the 3 fastest human to solve this problem took 14min, 20min and 1h14min respectively Even thought I expect this sort of problem to very much be in the distribution of what the mo…
[flagged]
Out of curiosity, I gave it the latest project euler problem published on 11/16/2025, very likely out of the training data Gemini thought for 5m10s before giving me a python snippet that produced the correct answer. The leaderboard says that the 3 fastest human to solve this problem took 14min, 20min and 1h14min respectively Even thought I expect this sort of problem to very much be in the distribution of what the mo…
[flagged]
Earlier quoted context omitted.
SMBC had a pretty great take on this: https://www.smbc-comics.com/comic/summary
There was another comic where one worker uses AI to turn their prompt in to a verbose email, then on the receiver side they use AI to turn the verbose email in to a short summary.
What are we even doing.
Earlier quoted context omitted.
[flagged]
I usually ask a simple question that ALL the models get wrong: List of mayor of my city [Londrina]. ALL the models (offine) get wrong. And I mean, all the models. The best that I could, it's o3 I believe, saying it couldn't give a good answer for that, and told to access the city website. Gemini 3 somehow is able to give a list of mayors, including details on who got impeached, etc. This should be a simple answer, be…
It shows once again that for common searches, (indexed) data is the king, and that's where I expect that even a simple LLM directly connected to a huge indexed dataset would win against much more sophisticated LLMs that have to use agents for searching.
Earlier quoted context omitted.
If we've learned anything so far it's that the parlor tricks of one-shot efficacy only gets you so far. Drill into anything relatively complex with a few hundred thousand tokens of context and the models all start to fall apart roughly the same. Even when I've used Sonnet 4.5 with 1M token context the model starts to flake out and get confused with a codebase of less than 10k LoC. Everyone seems to keep claiming thes…
>documented problem in Home Assistant this evening. All it would take is 3-5 lines of YAML. The model failed miserably. I think we're all still safe. This is mostly because HA changes so frequently and the documentation is sparse. To get around this and increase my correction rate, I give it access to the source code of the same version I'm running. Then instructions in CLAUDE.md on where to find source and it must u…
It does showcase that LLMs don't truly "think" when it's not even able to search for and find the things mentioned. But, even then this configuration has been stable for years and the training data should have plenty of mentions.
Earlier quoted context omitted.
"Not a single engineer has ever been laid off because of AI." are you insane??? big tech literally make one of the most biggest layoff for the past few months
That's because of overhiring and other non-ai related reasons (i.e. Higher interest rates means less VC funding available). In reality, getting AI to do actual human work, as of the moment, takes much more effort and cost than you get back in cost savings. These companies will claim they are using AI, even if its just a few engineers using Windsurf. The companies claim AI is the reason they laid off engineers to make…
Earlier quoted context omitted.
[flagged]
Thanks for reporting these metrics and drawing the conclusion of an underlying breakthrough in search. In his Nobel Prize winning speech, Demis Hassabis ends by discussing how he sees all of intelligence as a big tree-like search process. https://youtube.com/watch?v=YtPaZsasmNA&t=1218
Earlier quoted context omitted.
I also used Gemini 3 Pro Preview. It finished it 271s = 4m31s. Sadly, the answer was wrong. It also returned 8 "sources", like stackexchange.com, youtube.com, mpmath.org, ncert.nic.in, and kangaroo.org.pk, even though I specifically told it not to use websearch. Still a useful tool though. It definitely gets the majority of the insights. Prompt: https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...
Terrence Tao claims [0] contributions by the public are counter -productive since the energy required to check a contribution outweighs its benefit: > (for) most research projects, it would not help to have input from the general public. In fact, it would just be time-consuming, because error checking Since frontier LLMs make clumsy mistakes, they may fall into this category of 'error-prone' mathematician whose net c…
Earlier quoted context omitted.
[flagged]
> This is not an incremental advance. It is a step change. This indicates a new discovery, not just more data or more compute. To succeed this well in math, you can't just do better probabilistic generation, you need verifiable search. You need to verify what you're doing, detect when you make a mistake, and backtrack to try a different approach. Loos like AI slop