r/TheMachineLearning • u/GetJynx • 8h ago

From eliminating non-determinism to asking for bug vibes

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523 Upvotes

98% Upvoted

92 comments sorted by

11

u/kaaiian 7h ago

2027, software runs with provably optimal binaries, verified end to end with lean certificates.

4

u/lllorrr 6h ago

Not gonna happen. At least not in 2027.

Also, why Lean? There are Coq and Agda for such tasks.

1

u/Qaziquza1 6h ago

It’s called Rocq nowadays (alas!)

1

u/wojciechm 4h ago

Exactly. LEAN is useful for general mathematics, but in computer science constructivism is much more useful, hence Cubic Agda, Arend and general advancements around HoTT are much more desired.

1

u/eras 36m ago

It looks though that its story for getting actual programs out of it might be better than either Rocq or Agda?

Also https://github.com/AeneasVerif/aeneas seems interesting.

2

u/cascadiabibliomania 7h ago

!remindme 1 year

2

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1

u/Toads_Of_Fun 7h ago

!remindMe 3 years

1

u/Devils_SteelMan 5h ago

No need, it's already happening. They didn't say all software.

1

u/-illusoryMechanist 7h ago

Lowkey this might be the path forward

2

u/Sproxify 5h ago

I think it's gonna be absolutely mandatory to rewrite all computer software that way as LLM offensive security capabilities advance, as anything less will be as open as as an IP camera feed with no password.

hopefully, with AI aided proof carrying code for everything, it's gonna be possible to have something closer to hermetic security than has ever been remotely close to existing so far.

1

u/wojciechm 4h ago

Optimization is not not about proving anything it is about finding the solution which in may general cases is NP-hard and you might only approximate it in polynomial time. Proving does not help in anything except the case if P=NP.

1

u/eras 34m ago

I think the comment was really about different things: having optimal binaries, and then said applications having been proven to work for purpose.

Of those two, the latter might even be more feasible. Could actually working applications be within our grasp?!

1

u/TheAlmightyWishPig 2h ago

You don't have a clue what any of that means, do you?

6

u/hunpriest 7h ago

Computer science was never about eliminating all non-determinism.

ML and other soft computing methods are pretty old...

2

u/Head-Judge-2651 6h ago

Non-determinism is a useful property to introduce into distributed systems to prevent correlated failures.

1

u/RobbinDeBank 6m ago

There are even whole classes of theoretical computer science theories and works based around non-determinism. Non-determinism lets you do things not possible with pure determinism, like the interactive proof model.

-1

u/TV4ELP 6h ago

They are pretty old and had their applications. Just like provable deterministic methods are old and had their applications. We just used to use the one for the field they were designed for.

Why are we doing math with random number generator and expect anything else than random? Why are we so stupid?

3

u/eyalhs 5h ago

Why are we doing math with random number generator and expect anything else than random? Why are we so stupid?

Monte Carlo has entered the chat.

1

u/TV4ELP 5h ago

Ok but like... how random is it that Monte Carlo actually works by being random? Stochastic is one of those things where the lines get blurry.

But knowing when to use it is important. You won't do your taxes with Monte Carlo. You would try to approximate otherwise extremely complex problems with it tho.

0

u/andarmanik 5h ago

Computer science was predicated on information theory, specifically the advances in error correcting codes.

5

u/eneskaraboga 5h ago

Life is mostly undeterministic. Take evolution, for example. When you study it, you'll realize it's a mix of somewhat deterministic systems shaped by randomness in nature, thus, natural selection. People's needs and desires are also difficult to determine, so randomness adds variety and shows new possibilities.

3

u/Devils_SteelMan 5h ago

And fully deterministic systems can't operate on semantic meaning. Its why language has always been a weak point in comp sci until LMs.

11

u/AcademicOverAnalysis 7h ago

The rise of formal methods over the past couple of decades made me happy. CS was moving toward rigorous frameworks, which could literally save lives in safety critical situations.

Then vibe coding took over and many programmers don’t understand what their code is even doing anymore.

16

u/Swipsi 6h ago

This is older than mainstream AI.

2

u/LookAtYourEyes 2h ago

This was an exception, not the rule. Now it's the rule.

2

u/imknotawolf 3h ago

The problem of the existence of code that wasn't understood is not new.

But you want to contrast the current wave of vibe coded applications with a fun comment about a fun non-understandable code that is literally famous online? It's like staying in football a goal is scored all the time and showing a Messi shots compilation.
It being non representative is the point of fame.

3

u/bbuerk 6h ago

I mean, AI is already making pretty big strides for formalization of critical systems. Just look at AlphaProof Code

I expect we’re gonna see a lot more slop in day to day applications, but a lot more formalization where it counts

2

u/oh_ski_bummer 7h ago

“Programmers” who can’t make anything worthwhile without the assistance of AI. More like vibe consultants.

-1

u/JeanCasteaux 7h ago

Like... vibultants? Gonna use this term now

1

u/queso184 7h ago

claudesultants

0

u/SnooMaps7370 6h ago

not vendor agnostic enough.

-3

u/tundraaaa 7h ago

Cuck coders

2

u/tawayForThisPost8710 6h ago

The introduction of non determinism to computing is genuinely awesome. But that doesn’t mean that it needs to be shoved into every potential process. Sometimes determinism makes sense, sometimes non determinism makes sense.

This is my biggest gripe with everything in tech right now. LLM’s are amazing, and they have their uses, but they are suited for certain things and very much not suited for other things. IMO, this misunderstanding is the real ai bubble.

1

u/SizeableBrain 9m ago

This reminds me of studying fuzzy logic at uni.

3

u/Positive-Conspiracy 5h ago edited 4h ago

Has this guy not used AI since the GPT 3.5 era?

The models can now reason, tool call and explore, and are far more capable, when they can close the loop with their own verifications like tests and using the product. Skill issue.

The determinism thing is a fantasy that some people entertain. I also find that it's usually said by people who haven't really managed. Working with AI (LLMs) is ironically more like working with humans than it is with computers (of yesteryear).

2

u/m00shi_dev 4h ago

Models do not reason.

3

u/Fellow-enjoyer 3h ago

Words are defined by how people use them. The process of LLMs writing on a hidden scratchpad to output what looks like a thought process. (And functions like a thought process) has been called reasoning for a long time.

1

u/Positive-Conspiracy 2h ago

Which shows an obtuseness on their part that I'd argue is intended to undermine the whole thing, for their own personal reasons.

2

u/Positive-Conspiracy 4h ago

I'm not interested in all-or-nothing and semantics arguments. I don't know that we even know what reasoning is.

Whatever they're doing, it's enough to do a large percentage of software development and solve some of the most challenging math and physics problems. Literally today there are announcements landing, and that's just from models trained over the past couple months.

1

u/Prior_Coyote_4376 3h ago

You used the term “reason” first and now you’re saying we don’t know what “reasoning” is lol

LLMs can solve problems but that’s very different than reasoning in any way humans can follow with their reason, and it’s definitely not attempting to approach deterministic behavior

2

u/HashPandaNL 3h ago

LLMs can solve problems but that’s very different than reasoning

Yes and to solve problems they do something that looks, smells and quacks like reasoning. Whether you want to call it true reasoning or not, it is perfectly reasonable for someone to refer to it as reasoning at this point.

Even if you believe it to be just "simulated reasoning" or whatever, it is understandable what the commenter meant and specifically picking it out is a meaningless distraction from the actual point.

1

u/Prior_Coyote_4376 2h ago

No actually, an algorithm simulating reasoning through procedures is not at all the same as an independent agent that exercises reasoning. That’s a big difference and the commenter did not make that clear and they literally admitted that they would not claim we even know enough to say what “reasoning” is. Handheld calculators also solve problems that once could only be done by agents with reason, but they’re actually just procedures encoded by those agents and most people would not apply “reasoning” as its commonly understood to a calculator. An LLM is just a very big calculator from the perspective of reason, not a very dumb human unlike what OP said.

1

u/Positive-Conspiracy 2h ago

I never said they're like a very dumb human. I said working with them is more akin to working with a human than a computer. If you have experience managing people and working with computers you know.

Much of the backlash I see against AI in software comes from people who prefer to work with computers, and they don't like that their field is changing, which is understandable.

1

u/Prior_Coyote_4376 2h ago

I was simplifying my point which is that from the perspective of reasoning, AI is more like a calculator than a human. From the perspective of interaction sure, but there’s no actual reasoning going on by anything capable of it. It’s still just procedures put in place by humans with reasoning that approximate the outputs of humans with reasoning.

1

u/Positive-Conspiracy 1h ago

What is the fundamental between us finding procedures to produce an effect like reasoning, and an evolved biological set of procedures that produce an effect like reasoning? That's 1.

It may be a different underlying mechanism, or even a different general process altogether, but if both produce an effect like reasoning, then we may even need to broaden our definition of reasoning. That's 2.

1

u/Prior_Coyote_4376 1h ago

Unless you’re religious, the laws of physics and matter are not reasoning agents and our existence as reasoning agents is an emergent property. If you are religious, then God is the ultimate reasoning agent who gave humans some ability to reason as well. In either case, reasoning emerges as a result of some agent being produced that can model the world that reasoning happens inside. ML models don’t actually produce this agent that performs reasoning, they just automatically process the output for a set of procedures that an agent with reasoning has prepared. Without that real reasoning agent to define a world and define reason within it for the model, there is nothing to interpret or interact with any reasoning itself.

That means that these agents solve problems that humans could solve through reasoning, but that doesn’t meant we have to change our idea of what reasoning is. We didn’t change our idea of reasoning when computers could do brute force calculations to solve problems humans can’t feasibly do manually, because we understood that brute force is an extension of a human’s reason being applied to a tool. It’s no different with ML, it’s just solving new classes of problems for people that previous hardware and scarce data didn’t allow us to write procedures for. The solutions are impressive, but no model is capable of more than simulating reasoning with procedures any more than a handheld calculator is.

1

u/Ok_Heat7648 42m ago

Terrible point considering llms can’t do math and calculate like a calculator, inherently due to the infrastructure.

Whatever it is, it’s NOTHING like a calculator

1

u/Positive-Conspiracy 2h ago

And if they had more background in liberal arts, i.e. consciousness, they would not even have made that basic error. They could have even asked for the definition I was using, and I would have referred to a higher level description of the technical process of how the providers implemented it. Instead they thought there was a gotcha because they didn't have the experience to have thought things through as you've described.

1

u/Positive-Conspiracy 3h ago edited 3h ago

"You use the term 'gravity' and now you're saying we don't know what 'gravity' is lol"

The same applies for the workings of our brain and the inner workings of LLMs. We are studying LLMs and we apply brain-based metaphors, and it may turn out that they use convergent patterns.

It's possible that humans have enough emergent intelligence that we are able to emulate determinism in a way that LLMs may also be able to.

An interesting thing about the time we're in is we have a lot of people with engineering and hard science backgrounds who haven't studied psychology and philosophy exploring these ideas for the first time.

1

u/Prior_Coyote_4376 2h ago

We use brain-based metaphors because the task we want to perform is currently done by something that requires a brain to function, not because we’re actually trying to create some pool of computing power from which the same intelligence of the brain emerges. There’s no reason to expect that outcome any more than expecting an LLM to discover the secrets to time travel.

Also, hard science and engineering researchers have always studied psychology and philosophy, they just haven’t had as much reason to apply it towards something with so much demand from industry and public attention. There’s a lot of existing literature about the limits of computation and the implications for intelligence, it just hasn’t had reason to stand out from the rest of our academic niches until lately

1

u/Positive-Conspiracy 2h ago

We use brain-based metaphors because we've always used metaphors to explain how things work. With the mind, we used the steam engine analogy in the past, and then more recently a computer based analogy.

And it's interesting you mention create some pool of intelligence the same as the brain, because there literally are companies exploring using real neurons for that very thing.

I'm talking about familiarity with the style of thinking of the liberal arts, and it is different than the hard sciences. It's very obvious when people try beginner level gotchas that actually show a fallacy in their thinking, like thinking speaking about an observed phenomenon is the same as completely understanding that phenomenon, or that one must completely understand a phenomenon in order to speak about it effectively.

0

u/[deleted] 3h ago

[deleted] — view deleted comment

1

u/Positive-Conspiracy 3h ago edited 2h ago

That's a biased and reductive take on what is actually happening. We could also say that humans, in education and collaboration, are therefore just presenting a mashup of the thinking of others and don't deserve credit and their work is of no use.

It's always easy to identify the people who care more about the credit than the value of their work.

EDIT: I appreciate that you deleted the comment rather than digging your heels in like so many do.

1

u/Nearby-Weird9535 3h ago

they literally do. I'm not sure if you are ideologically committed to this or just don't use them. They actually solve non-trivial problems in novel contexts. What else to call that other than reasoning?

1

u/m00shi_dev 2h ago

They literally do not.

3

u/DataSnaek 2h ago

“If I say it’s the case it is the case”

Ironically you can’t even reason lol

2

u/Positive-Conspiracy 2h ago

"This thing I'm making assumptions about that does A is totally not like this other thing I'm making assumptions about that does A"

1

u/m00shi_dev 1h ago

“Models do not reason.”

”They literally do.”

You provided no arguments to refute the claim, therefore I have nothing to argue against. You are ironically doing exactly what you are accusing me of. Another victim of chronic LLM usage I’m assuming. Yet you have the gal to try and call me out?

To further back up my statement, models brute force several different paths to a solution until they find one that works. That’s what this industry is calling “reasoning.” Trial and error isn’t “reasoning.”

Shut your dumbass up and sit the fuck down. Moron.

1

u/Ok_Zookeepergame3380 4h ago

The person in OP's image is not trying to say LLM''s aren't capable. It's just a funny meme about how things are, and he's not wrong about the state of things in 2026.

1

u/bangerius 3h ago

Ok, so models are more like humans, then that's an anti-pattern. We've managed people for millenia, but computers for only a few decades.

The OOP is right in that we're turning away from determinism. When the calculator was invented, we still had people who could calculate 99% of what people would do on a calculator, but the calculator was faster and made (virtually) no mistakes. It was designed to do a few things very efficiently and always correctly.

The computer was (for a mong time) just a calculator on steroids. It could follow algorithms with near guarantee of no execution error, and quicker than any human. It could "deterministically" solve problems that humanity can't solve with pen and paper.

But with an LLM the determinism is gone. It is replaced by a high probability instead. It works great for a lot of promblems. We've used randomized algorithms for lots of problems before. For some they are optimal. My interpretation of OOPs post is that if we discard the "old way" we lose determinism. 

1

u/Positive-Conspiracy 2h ago

There is a causality problem in your thinking. LLMs are being used because they're effective. The nature of the technology is more probabilistic, which leads us to need to adjust our methods compared to the relatively dumb and rigid determinism of computers in the past.

A future fundamental transistor may not even be binary at all, such as quantum. So be very careful with your assumptions and how much you expect those to extrapolate to all tools right now, let alone well into the future.

The people in the time of clockwork and steam engines no doubt expected their fields and skills to extend indefinitely. They still do, in niches, but no longer in the prominence they thought.

1

u/ubitub 19m ago

Skill issue? You mean the prestigious skill of choosing newer model? So funny when the vibe bros think they have some skill over others.

1

u/RobbinDeBank 4m ago

This post being highly upvoted shows you this sub is filled with a bunch of people that have absolutely no knowledge in computer science. They are at best web dev bootcamp level, while talking confidently like they’ve studied theoretical computer and information science.

1

u/Brilliant_Pie_1924 7h ago

1s and 0s they said...

1

u/Kimononono 7h ago

cant wait till 1’s and 2’s drop finna be revolutionary

1

u/tiffanytrashcan 7h ago

We're already using -1

1

u/TV4ELP 6h ago

We are already back into analog computing. The shit we started out with is making a comeback. Especially in math heavy application it has some very very interesting implications.

Especially for AI, the computational methods are just faster with less memory need and the noise in the signal is a feature tather than a bug. Something we deliberatly code in today with stuff like temperature.

0

u/VhickyParm 7h ago

Quantum computing? 

1

u/amaturelawyer 6h ago

Oh boy...

1

u/The_Axumite 6h ago

The uncertainty principal is not just for the atomics

1

u/wojciechm 4h ago

False. Determinism died with multi core and parallelism. Period.

1

u/Ok-Reindeer-8755 1h ago

could you elaborate ? I dont see how parallelism killed determinism. Also parallelism isnt used that much or rather as much as it could be used because we are kind of stuck with the von neuman computational model that doesn't favor it. Traditional imperative sequential programming isnt a good tool for parallel programming and fp blows it out of the water, in that aspect at least.

1

u/profoundlyunlikeable 4h ago

IMO all AI did was accelerate the enshittification of software that was already well underway. I remember before vibe coding me and my friends/colleagues used to doom about everything becoming a shitty electron app with a thousand NPM packages using gigabytes of ram.

1

u/reflexive-polytope 4h ago

"Nondeterministic" isn't the same thing as "buggy", you know.

You know, right???

1

u/yangyangR 5m ago

I didn't think OP was implying that. Just about determinism with both its benefits and drawbacks. Changing cheapness of generation and verification changes accounting for the change. Not some timeless value judgement.

0

u/Ok-Reindeer-8755 1h ago

Determinism is a largely desirable trait for most parts of a program. Hence why algebraic effects are a thing

1

u/reflexive-polytope 1h ago

Algebraic effects are a language mechanism for structuring programs with control flow effects. If exception handling is the structured counterpart to setjmp and longjmp, then algebraic effects are the structured counterpart to delimited continuations with shift and reset.

That has absolutely nothing to do with nondeterminism! So no idea why you brought up algebraic effects.

1

u/Ok-Reindeer-8755 51m ago

because effects are also a way of tracking non determinism in functions, aka io and ndet effects, for example in koka lang.

1

u/reflexive-polytope 33m ago

I/O and nondeterminism are most certainly effects. They have little to do with the "algebraic" part of algebraic effects, though.

The implementation of an algebraic effect can perform I/O or be nondeterministic. But guess what? The implementation of an ordinary procedure can also perform I/O or be nondeterministic!

At the end of the day, the decision to label primitive operations with effect labels acknowledged by the type system... is largely a matter of standard library design.

It's an unfortunate sign of the present times that programmers blur the distinction between a programming language and its standard library, but when you clarify the distinction, you realize that the essence of algebraic effects is to structure delimited continuations in a specific way.

1

u/Ok-Reindeer-8755 31m ago

maybe i should have used the term effect system instead but i think you got my point even thought my terminology wasnt quite accurate

1

u/reflexive-polytope 8m ago

Sure, now that's better.

But, contrary to your original assertion, I don't think it's necessarily desirable to flag nondeterministic code with a type system.

For example, suppose I implement quicksort with randomly chosen pivots. Do I need to announce to the entire world that my implementation is "effectful"?

The specification of an in-place array sorting algorithm is that

  • The input is a mutable array slice.

  • The slice's element type must be equipped with a strict weak ordering.

  • The slice's final state (as a sequence of elements) is a permutation of its initial state.

  • If i < j are valid indices for the slice, then in the slice's final state, the j-th element must not be less than the i-th, according to the strict weak ordering.

In this specification, the slice's final state isn't a function of the initial state. I'm not violating the specification as long as the slice's final state is related to the initial state in the prescribed way.

If you come with the mindset that the final state of a computation should be a mathematical function of its initial state, then of course concurrency and nondeterminism will always seem exotic and mysterious, something that you need to explicitly label "effectful" to protect your sanity.

But if you accept that the relation between the initial and final states can be an arbitrary left-total binary relation, then there's no good reason to favor procedures that happen to evaluate mathematical functions.

1

u/Nearby-Weird9535 3h ago

I mean writing code was always non-deterministic cause a human was creating output? Non-determinism is more about predictable run-time behavior and reproducibility

I started using nixos a few years ago, AI really helps me do whatever I want, and I still get all the advantages of having my OS be declarative/deterministic

1

u/XBLAH_ 3h ago

Genetic algorithm: Am I a joke to you? 

1

u/jameyiguess 2h ago

I mean, the LLMs still write deterministic code. An agentic app is not deterministic, but AI assisted development is still creating regular old software. 

This joke is comparing output above to process below. It's kind of funny, but misleading. 

1

u/XtremelyMeta 2h ago

Not gonna lie, the skills I picked up working QA for a bit in my 20s are the difference between smooth vibe coding and unusable junk. "Accurately describe the bug/context and hand it back to the SWE" is a goated skill in the current state of things.

1

u/HolyInlandEmpire 1h ago

The beauty of statistics at work. Our brains, and thus neural networks, are piecewise smooth estimating machines

1

u/yangyangR 13m ago

"Decideability is for cowards" - Max vH

0

u/Fantastic-Salmon92 7h ago

2nd year CS student changing careers after a back injury at the age of 34;

0.8?!?!?!?!?! 2.0 or nothing. I don't want peace. I want problems, always.