Yeah the one i glanced was the ‘matrix multiplication is nlogn^0.9999999 for many more 9s’ therefore less than nlogn
The proof explicitly hand-waves some complexity by assuming lookup tables to avoid some calculations which isn’t actually possible since it’s dealing with such large numbers and it only works on incredibly large numbers.
The complexity being so close to nlogn and the handwaving by assuming lookup tables in parts should be a really really obvious smell. At the very least worthy of holding back from the broader announcement.
It us proven in lean as-is with these assumptions and it’s not one of the ones retracted but those assumptions are doing some heavy lifting. I think it’s worth adding back in those ‘by using a lookup tables for x’ complexities and seeing if we really are below nlogn on that one.
" I expect, say, 2026-level AI, when used properly, will be a trustworthy co-author in mathematical research, and in many other fields as well.
Then what? That depends not just on the technology, but on how existing human institutions and practices adapt. How will research journals change their publishing and referencing practices when entry-level math papers for AI-guided graduate students can now be generated in less than a day—and with the far better accuracy of future AI tools? How will our approach to graduate education change? Will we actively encourage and train our students to use these tools?
We are largely unprepared to address these questions. There will be shocking demonstrations of AI-assisted achievement and courageous experiments to incorporate them into our professional structures. But there will also be embarrassing mistakes, controversies, painful disruptions, heated debates, and hasty decisions."
Another cat one is that i’m pretty about is that sitting or sleeping in another's usual spot is in no way a sign of dominance.
My cats do this to each other and it’s clearly taken as an invitation for affection by the other cat. They’ll sit in my chair and be happy when i gently wiggle in with them too.
It leads to a lot of stolen dog beds due to the interspecies communication barrier but i’m absolutely convinced it’s not the assholery it’s perceived to be. Merely a miscommunication.
I posted some free little games/utilities i made just below in this thread and can attest that in general you do have to have thick skin and brace yourself for derision, abuse and downvotes on say Reddit or Linkedin if you dare to acknowledge you used AI in any way to create any form of content right now.
Which is silly because it doesn't help anything to deride creators that use the same tools the big corporations use.
I’ve taken the viewpoint that a domain is basically a cup of coffee per year in cost and static web hosting is literally free so have been putting a ton of stuff up. None of these have ads or make me any money, just listing here as an example of the ease of sharing;
tfmbot.com - an implementation of my favourite board game complete with ai that plays against you
thedailycheat.com - a save game editor for a game Newstower that was fun but a little grindy ao i asked ai to figure out the save game format and make this online save editor
grandcheaten.com - a guide and save game editor for jagged alliance 3
Basically all personal projects but i find sharing them out rewarding. Occasionally i’ll get abuse or large amounts of downvotes for daring to share ai generated content but, shrug, it’s useful to me and i’ve also had lots of messages of appreciation.
LeCunn actually wanted to pivot Meta's entire AI strategy away from LLMs just before he was ousted. He was sure they had nowhere further to go and wanted to pivot to world model generation. The LLM models have since progressed massively.
An analogy on LLMs is that you have a pretty clear straight highway ahead of you for some distance right now. Maybe that doesn't lead to AGI but it's clear there's progress to be made. For a big tech company it makes sense to push as hard and fast down that clear straight highway of LLMs asap.
Meanwhile LeCunn wanted to turn off the road and go down an unproven track. I say this as someone working on world model generation right now (creating the ability to learn game world model and have it play the game https://tfmbot.com for an example of my system pointed at a very complex board game). LeCunn wanted to pivot all of Meta into world model generation. It's good as a side track research project but the entire pivot he wanted to do was madness.
People are literally talking about an AI researcher who was fired for terrible direction here.
I think he was perhaps right and Meta was perhaps also right to replace him.
The argument is that LLMs are a local maximum that will never breakthrough to AGI. This is still very much an open question. If you are the fifth-best AI lab, does it make sense to try to outcompete everyone in a space that is already too crowded and may not ever yield their actual objective? Instead they could just use open weight models in their products, or post-train on open models like smaller labs have done, and treat that as what it is: product development.
Pure research has always been about taking chances.
I mean, it's an "open question" in the sense that there is no theory behind the idea of AGI, so there's no way to falsify any claim about whether or not any particular path will lead to it.
LeCun is a researcher, not a product guy. He's not going to be particularly interested in just working on scaling language models which every lab is already racing to burn cash on. Language models aren't the final frontier of AI.
People nowadays are the equivalent of those in the past looking at the initial stages of an airplane and saying "it cant ever fly because it has no feathers and can't flap its wings!"
You are making the mistake of classifying models on a single linear axis, or even a multi axis basis set of all benchmarks. That just isn’t true. Each model is unique in its skills and capabilities and the way it approaches problems, in a way that is not represented in benchmarks. Fable is better at reviewing things. I don’t know how to explain it well but it is true. I trust Fable to do thorough reviews (sometimes too thorough) and to present its information in a dense but ordered way. Its output is equivalent to what you used to get from security firms doing code reviews. Having Opus do the work, and have fable do reviews (of the plan and implementation) is a good combo.
Because Anthropic releases their different model level's at very different points in time, they seem to always have one model that is by far an away the best to use for everything. Haiku 4.5 is almost a year old. Sonnet is fine, but idk if it has any real benefits over Opus. It's only been since Fable has been released that you get to choose between Fable and Opus, but not with 5.5 there is no reason to use Fable.
I feel like instead of releasing fable, they should have released it as Opus 5, then their next Opus release they would call Sonnet, and their next Sonnet release they would have called Haiku. I don't know if their pricing structure would have been able to support that, but Anthropic has always been the least competitive regarding token pricing.
I find fable better at high level planning, as in planning a task without filling in all the details. Opus doesn’t seem to be great at this, but other models aren’t either.
Although we never had a Claude Opus 5.1. Fable went 5 → 5.1 and Opus went 5 → 5.5.
I assume Fable 5.1 is the first re-tuned (is there a better term for this?) version of Fable 5 and Opus 5.5 is the first re-tuned version of Opus 5, and maybe the Opus one just came out better for some reason?
> If they had 6, don't you think they'd be serving it?
No I do not. OpenAI has some hidden model that's apparently 5x or so better at certain benchmarks than GPT 6 but they're not and have no plans to release it. It is increasingly likely that these AI companies keep the best models for themselves and then release smaller, cheaper distilled models for everyone else, especially since the AI companies are vertically integrating into many fields.
You’re assuming the goal of the big AI companies is to serve models for money. That is not the goal. They have a lot of incentives not to share their best models.
To back this up we have a discord chat for the board game terraforming mars where the agent takes input and vibe codes an open source implementation of the game.
https://tfmbot.com is the link (discord and source links on the splash screen).
The results are fucking incredible to the point where people in discord are stating "I'm surprised this is working so well". I am too.
I feel like there's a group online that missed the boat. Anything negative towards AI capabilities is still upvoted but I've been in the industry for over 25years, highly respected and can't fathom the "AI dumb lololol" type of comments i see on HN. AI is superseeding all other ways to develop.
I'm restoring a game I played as a kid, that I couldn't reliably get to even start on modern Windows. The skill and speed with which Opus 5.5 got it running, while patching a bunch of bugs in the binary along the way (only some of them I knew about), has my jaw still on the floor - and few hours in, I already have whole campaign mapped out as state machine graph, and we're upscaling graphics now.
I just see the extremes. You either see people unable to recreate results and them calling people idiots for claiming those results. Or you see people saying that AI will supersede all other ways to develop and calling anyone who doesn't full embrace AI an idiot. Reality is that nobody knows nothing. There are a million factors that could cause the end result to be anywhere between both extremes. I don't know, you don't know, AI doesn't know, least of all the people inside the AI companies don't know. And really the end result will be extremely nuanced I'm sure.
One of the last things developers had to offer was being able to guide the AI to write maintainable code. Now that it can do that there's not a whole lot left
It's understandable why that's hard to accept
From just this morning i read this thread: https://news.ycombinator.com/item?id=49946321 about a linux distro no longer allowing AI code and the comments are mostly along the lines of "This will be great for maintainability, AI can't code any complexity" which is essentially what I'm getting at here.
AI writes clean code and can do so in a very maintainable way honestly.
AI is going to be big here. You previously had to create a few art assets and reuse them. Cities has to be grids of blocks of buildings. You couldn't have an agent go and design a building that curved to the block perfectly. The slope couldn't have some stairs easily.
The author of this created these images with AI and that's exactly the solution for game makers. There may be base assets but AI is pretty damn good at contextually modifying them.
I saw a city sandbox (no simulation, just a kind of zen garden) on a voronoi grid but I forgot what it was called. No AI, and you could build in random shapes.
I think that’s Townscaper. A very relaxing “cozy” city builder with no real goals or challenges. It’s just a fun sandbox that algorithmically generates the city based on your clicks on a voronoi grid.
The proof explicitly hand-waves some complexity by assuming lookup tables to avoid some calculations which isn’t actually possible since it’s dealing with such large numbers and it only works on incredibly large numbers.
The complexity being so close to nlogn and the handwaving by assuming lookup tables in parts should be a really really obvious smell. At the very least worthy of holding back from the broader announcement.
It us proven in lean as-is with these assumptions and it’s not one of the ones retracted but those assumptions are doing some heavy lifting. I think it’s worth adding back in those ‘by using a lookup tables for x’ complexities and seeing if we really are below nlogn on that one.
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