johnsmith1840

They can get with the program or be the equivalent of a genius SWE writing assembly on punchcards in 2026.

The only thing I read from this is their ego being bruised by a machine.

If these people cared more about discovery and advancement of human knowledge the only thing they should be doing is celebrating. There's no proof of plagarism but that's an independent issue.

How are they not realizing that in the future children will be able to do impossibly hard math but they will be doing something we can't even think of as of now.

One world class mathematician in the future could be advancing mathematics the equivalent of one Riemann hypothesis A DAY.

How are they not celbrating this as the achievment of the centry? Who cares about plagarism at this scale. It has been solved and it wouldn't have been without AI.

Or another way.

I enjoy seeing the fastest human on earth run.

But I'm still getting in my car to go to the shop.

I actually love the analogy that mathematicians will be the equivalent of olympic athletes.

Nobody needs to throw a rock far, or run fast, nobody gets any value except entertainment.

I think your own analogy is actually much worse than my point.

Watching people who have built their entire identity around being untouchably smart suddenly be confronted with the future that children will be able to solve the equivalent of millenium prize level math in an afternoon for 5$ is enjoyable.

Your doing that sampling/promotion automatically?

I considered an automatic promotion path but decided against it I want to actually review the data myself first.

What's your model churn rate like? I was worried about customer experience by same day maybe same work getting a totally different model response (also caching is worse)

Same experience. I migrated over and am happy but that intro was brutal.

My basics are I have a test suite that: 1. Finds newest models of my versions 2. Inferences every single model and a few providers for each with a short problem 3. Analyze latency and if a model failed the stupid simple questions drop it and the provider 4. Run larger context haystack kinds of problems.

It's cheap and fast less than 5$ so I can do this daily, hourly, whatever depending on how much I care. If it's mission critical I would say you need a two day study running once an hour to know the STD of model variance.

Then lock a top 3 contenders via latency dropping routing.

Is this easy? No. Is it cheap? Also no. Is it better than just using a trusted labs api? Also not really.

But it does give you exponentially more flexibility. Being able to run 10 unique models at the flick of a switch on a problem for pareto front analysis is amazing. And giving a dropdown for customers for multiple model options is powerful.

Thought expirement. If astra max effort made one function at a time via a heavy description by you. Would it ever produce slop? Fresh context, 1000 lines of style and content guide you personally wrote. Per function no other code context massive guides and styles and it writes a bunch of AI slop unit tests on the side for this one function.

If the answer is yes then atleast you're consistent if no then the question is why can't you scale this until breaks? Then never move beyond that limit?

My argument is there's a "break even" point when the power of the AI is larger than the problem you give it to the point it doesn' slop. You then build at that chunk rate and only try to increase it with next gen model. I usually keep a few "screw it" ideas in my back pocket when a new model arrives to see what happens.

"Go rewrite this entire pipeline in rust" "Go train me a custom x model for y"

Fable is the first model that did not just crash and burn on one of these tasks. Astra still can't do the rust migration (goodbye tokens). But I assume eventually it will. Then I'll have to make up a new ridiculous level.

The model training one was literally an identical pipeline I made before AI and it was like a 6mo process. Fable did it better than me in 1 week (with me helping of course). My theory though is that its datascience is massively higher skill than other systems.

You need to find the chunkrate for your problem and style that works.

It's actually pretty cool of these old stories how well that maps to a dangerous tyrant.

The roman empire perfectly matched that and most powerful men seem to go that path.

It would also be kinda easy to argue many moderns countries are going down that path.

Fair take.

So I totally agree if AI also cannot do the second part better than a person.

Honestly though, I wouldn't want to take that bet. I never thought that the first thing AI would become super human AGI like is math.

You ask me 10years ago and I'd think the opposite. I think we all would have said we'd have super human HR employees before a super human mathematician.

But here we are.

In that case isn't it actually more valuable to have an AI do this? It works faster and solves more math.

The random engineer looking at a funny problem 10 years later now has the literal author of the math to talk to about it and implement it.

I have never even spoken to a world class mathematician and now I can have them design with me?

How is this not better in almost everyway?

So solving and discovering math is or is not the core value a mathematician provides?

If AI can perfectly replicate their work but faster and better then what?

SWE have nobody crying for them as they've been massively disrupted.

Fun suggestion, thanks!

It's a reasonable take.

I think there's an important part which is that the nature of the beast implies there's effectively zero way to do that.

They have no idea what context, triggering this pathway, was from this guys reddit post 4 years ago.

I also assume that if any AI lab could actually do that it'd be an instant pissing context over who gives who credit the mostest. "This software engineer wrote a sick sorting algorthm everyone now uses, thank you random dude for that training contribution"

Maybe we will in the future, maybe we'll learn that the solution to this prize is from 3 peoples schizo rant on reddit a decade ago. Would be kinda sick actually.

So...why can't an AI do the exact same thing? Make AI so it understands math better for future math to understand more math.

Unless your argument is that mathematicians are effectively useless?

I am assuming that's not your point though.

Ok so if no plagarism has occured here in any sense then there's no discussion here?

I agree though if they did plagarism it's really really bad for OpenAI. They would instantly have evaporated all remaining good will to gloat over a stolen discovery.

So what happens to this world view when AI not only clears the forest of problems we couldn't solve but also in the future discovers more forest with trees bigger than anything we've ever seen before?

Not sure what the point of this argument is. Do we have mathematics for the sake of mathematicians good mental health and career or to solve and discover novel problems? Why should we care if mathematicians can understand proofs if they are correct?

If this is V0.5 of AGI/ASI then by V1 the only system that will be understanding any of this is the AI itself. If AI creates a new field of mathematics month 1, then solutions to new problems in month 2, then another field of mathematics on top of that at month 3 there's no human who will ever keep up with that.

Or the alternative is a flattening of abilities, the AI cannot proceed further than the collective intelligence of humans and in that case this is correct. We'd be in a future where nobody wants to work in a field with an AI dominating it and when AI hits the limit of no useful training data input we'd have this giant gap of nobody know wtf it's done for years and nobody willing to figure it out and advance it.

Ooo here's a dytopian story: - AI gets better at everything humans do - humans stop trying - AI cannot improve anymore than its input data + human support - AI slowly degrades itself (model collapse) for decades, it slowly hallucinates little by little until its hallucinating entire scientific fields losing quality over time - there's a mass population of people in the future who never learned to do anything and now have to relearn and figure out the equivalent of 100k years of AI work in order to prevent its slow degredation while all the systems they've come to rely on start failing around them. The AI has solved every problem but every real solution is saturated with 1000 false ones. - humanity starts from scratch?

I love the idea of an archive of every solution to every problem existing but it's impossible to figure out the correct one. Infinite library like!

AI didn't "take" anything. An openai researcher did?

The solution is also different to theirs? Literally no evidence of plagarism?

I mean, hasn't it always been this way? If something valuable is within reach and you disclose it, someone else might reach for it?

Just because the length of the arm is longer with an AI org doesn't mean it's somehow fundamentally a different system.

The future is that if you don't use AI your work is a lot easer to reach against someone else who has it.

That dude hand writing code with punchcards can be lapped by a 20yo with python, what's different?

100% not deterministic at the scale they run.

Sure? I mean the internet is just a bunch of wires and some networking code not magic but at the same completely life alteringly magical.

My logic is that you personally could never have accomplished this feat with all the non LLM tools and content in the world. These kinds of things imply these methods are stepping beyond human ability.

Sure we put walls around it and optimize but the interior of that optimization is not something we understand.

You now have access to a system that for a price could solve something you simply are unable to solve. Not something we programmed it to solve, something that has never been solved before.

Nobody gave it an example of this proof, that's magical.

Memory isolation having one tab or account open on your bank and another on this page does not mean it could leak across the sandbox and steal bank account details but anything inside of your general page content can be lost

Been running near identical tests for years now. Latest models are the only ones I don't throw away the results/code. Which is impressive, salvagable/usable is a giant step up.

A literal rock we carved patterns on and shot lightning into has accomplished something no human has.

How much more magical do you want this to be?

Tool or not it did something you could never have accomplished.

I've personally been facing this lately 5.6 at max effort and fable have done tasks for me that I previously that would be a nearly 6mo project and it took me a week. It also did it better than I would have.

The task was to build a high performance classification model. It not only helped make an entire data capture pipeline but also made the sythetic data basline needed. Then it proceeded to build and test 100 different model varients with methods and techniques I've never seen before. The results are basically SOTA based on the effeciency and compute contraints.

But this brings up something huge about these. I was there. I pushed the direction and work throughout it all. If it was entirely up to fable max or sol max the result would have been pretty bad.

All of these things are still chatgpt 3 scaled. It's identical even if the scale has gotten pretty wild. I could ask chatgpt 3 to make a single function and it worked well, 4o a file, 5, a small project, 5.6 far more, biggest improvements lately is they don't seem to get lost on long running tasks.

Is big gpt 3 AGI? I don't think so but perhaps scale can mimic it close enough our squishy brains fail to handle them correctly.

Yeah that's by far the most complex part.

Ever letter is it's own object and they stitch it into the visual view. When you type one letter is turns a single word into multiple objects all versioned objects.

Can't imagine all the crazy race condition protections baked into that.

You should go actually try to make any basic automation work around these systems.

They purposely obscured, google doc is another example they completly hide the dom!

I spent months fighting word processing systems and ended up shipping libre. There's almost zero alternatives without that becoming your entire company.

*that only microsoft has access to.

These guys puposely obscure controls and understanding of these products 100% to prevent you doing a port.

Just go open a microsoft word doc in the browser and look at the dom.

Despair! Horror!

If you've ever actually gone down this route you will try exactly this realize how much of a cluster f these products are and just use libre.

I did the exact same thing in my AI system. Spent an ENOURMOUS amount of time trying everything I could and in the end libre was the only thing even somewhat functional.

Easily 2 months of my life lost to these god forsaken systems. APIs and CLIs sound reasonable until you actually attempt anything in this space.

Computer use is exactly the same thing. Go try this: go to a google doc and dev tools check out the dom and now do the same for a word doc. Eye gouging pain of trying to get anything to work.

That's a good idea but it works from the change in context no? So you lose context from your big model. It's a good suggestion though.

Auto permission is what ya need.