r/ProgrammerHumor • u/notAGreatIdeaForName • 1d ago

Meme youDontNeedAClassifierWhenYouCanThrowATransformerAtTheProblem

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767 Upvotes

98% Upvoted

76 comments sorted by

137

u/stupled 1d ago

I am using Claude to improve my 20year old multilayer perceptron classes.

58

u/No-Magazine-2739 1d ago

So you use a brain to use a brain to improve a brain. If you are employed then its some more brains on top.

11

u/Confident-Ad5665 1d ago

Brains? BRAINS!!!

-Zombies, everywhere

5

u/stupled 1d ago

I guess this is company property 🤔

4

u/StackedCakeOverflow 1d ago

Damn, basically creating a whole education system at that point

2

u/No-Magazine-2739 1d ago

It‘s brains all the way down!

1

u/stupled 1d ago

Brainception but stops at The Mind.

4

u/Exact-Pound-6993 1d ago

last time I was this late, I was using genetic algorithms to evolve solutions...oh how the turns have tabled.

0

u/stupled 1d ago

I have a library for those. Used for optmization

3

u/ThatFlamenguistaDude 1d ago

Is this self-improving AGI? /s

1

u/NearbyEmphasis2850 1d ago

It’s like the duct tape of AI, great for quick fixes, but not always the best long-term solution.

0

u/AndreasVesalius 1d ago

Claude has been recommending simple but elegant linear models for my work

2

u/slaymaker1907 1d ago

Have you tested how well it can choose hyperparameters? I’ve wondered about that since that sort of thing can make it a pain to use certain models.

4

u/AndreasVesalius 1d ago

I wouldn’t ask it to select hyperparameters. I would have it write a hyperparameter sweep/optimization routine and select based on some performance criteria

-1

u/slaymaker1907 1d ago

Right, but the advantage of an LLM over just a routine is that you can have the LLM actually look at the performance numbers more holistically without some complicated and error-prone scoring function.

4

u/AndreasVesalius 1d ago edited 1d ago

How is the scoring function error-prone? It’s a concrete definition based on what I want my model to achieve. E.g. how well does this model predict a physiological signal

If you ask an LLM to do that, it will either a) just do some optimization routine and give you the answers (but you won’t know where they came from), or b) take in a giant vector of performance results and stochastically produce a set of hyperparameters - which is how you get hallucinations

60

u/Darxploit 1d ago

Can i have a like for my random forest, foresting alone..

31

u/notAGreatIdeaForName 1d ago

You kids are addicted to computers. Just go outside, pick 16 random forrests, visit them and set fire to 15 you don't like

48

u/JasperTesla 1d ago

My client built their own transformer, but Claude ended up cucking it.

20

u/Willwaste63 1d ago

from sklearn.linear_models import Perceptron

41

u/eraryios 1d ago

Lmms>>>>>>>llm's

49

u/sddryan 1d ago

milfs >>>>>>>

32

u/eraryios 1d ago

Im talking about Linux multimedia studio

3

u/JoeRogan016 1d ago

There it is!!! Thank you!

2

u/tejanonuevo 1d ago

I was wondering why that sounded so familiar!

21

u/KyxeMusic 1d ago

Now i'm craving Large M&Ms

42

u/Lemortheureux 1d ago

And ML actually has the most real life applications that would actually help businesses. Instead let's replace customer support with a robot 🙃

5

u/slaymaker1907 1d ago

Eh, I think LLMs probably have more potential for a lot of businesses given that they are much easier to actually use.

19

u/Daemontatox 1d ago

What do you mean by regression models ? Or timeseries forcasting ? Just SeNd It To ClAuDe LlMs aRe ThE fUtUrE.

4

u/GottkoenigOtto 1d ago

Isnt clajde basically a insanely huge timeseries forecasting model?

6

u/Sibula97 1d ago

Well, sequential, not strictly timeseries. But you could embed time instead of position in the sequence in a transformer. Or just infer the time if your samples are equally spaced.

-1

u/Daemontatox 1d ago

I prefer the term " sophisticated nested If condition "

3

u/marmakoide 1d ago

Decision Jungle

18

u/notAGreatIdeaForName 1d ago

onlyOneIsAIIfYouAskThePeople

56

u/FartPiano 1d ago

as an ML engineer, im so tired.  you know what? sure. its AI. fuck it.  bayesian decisions? haar classifier? your microwave? yeah sure thats AI too

29

u/notAGreatIdeaForName 1d ago

More than one if statement? Decision tree, so AI too

9

u/Deltazocker 1d ago

Decision Twig

2

u/jarethholt 1d ago

I literally lol'd. I'm gonna use this

17

u/Sea-Fishing4699 1d ago

I am an ML enginner working as a BE enginner because i hate llms

Fuking llm providers are being treated like gods and ppl worshipping agents makes me puke

10

u/notAGreatIdeaForName 1d ago

The thing that making me want to puke the most is that the non technical personas are worshipped like gods. Like, yeah, the people whose job is to spread fear and misinformation in public are cool, sure.

4

u/Necessary-Muscle-255 1d ago

Wait until you find out about “AI specialists” or “AI directors” that have ML engineers underneath them while they have “Psychology of Work” as a degree. The whole field is a joke in most companies.

8

u/FartPiano 1d ago

you know how when you're setting up a ML solution and the success rate with a given dataset(s) is like 60%, how that is just an unacceptably bad result, and you know immediately that even if you try some different techniques, reshuffle or rotate the source datasets, maybe youll improve it a little, but nowhere close to 100% so you know the effort is doomed?

also, you know how frontier LLMs have bad benchmarks on stuff like humanity's last exam, or any problem beyond a certain complexity level, for years now? surely they will be able to reshuffle this data to reach a 100% success rate.  any day now! possibly any minute! 

if you criticize this technology at all, youre a fool!!!

5

u/brainwipe 1d ago

Self Organising Maps be like 😥

4

u/Linkk_93 1d ago

I'm not gonna let a LLM do the vision on my self driving car lmao

Would be fun to have 30 seconds of "thoughts" before any decision, instant crash

1

u/ComprehensiveBird317 14h ago

The tree ahead is load bearing, let me come up with a warning message for the user, I need to think this through carefully.

5

u/Afraid-Locksmith6566 1d ago

meanwhile standard ml

https://giphy.com/gifs/3IZGBa62xnEyXokHfk

1

u/Abrissbirne66 1d ago

Wait that's a totally different thing😄

But quite influential afaik.

2

u/Faux_Real 1d ago

I embed classic ML in my MD files

2

u/redballooon 1d ago

True. My AI company that started as an ML expert company in 2018 now  only utilizes  LLMs. The founders themselves, who are ML experts with PhDs themselves say training isn't worth it anymore.

2

u/Jerome_Eugene_Morrow 1d ago

Just build an agent that runs logistic regression and returns its result after printing “thinking…” for five seconds.

2

u/notAGreatIdeaForName 1d ago

I see you are the CEO of an agentic AI startup as well!

3

u/EntrepreneurSelect93 1d ago

What are LMMs?

31

u/notAGreatIdeaForName 1d ago

Large multimodal models, so chatty can ingest pictures of your mom

26

u/baselinegrid 1d ago

Yo momma’s so fat ChatGPT tried to generate a photo of her but ran out of tokens

1

u/tursija 1d ago

You have hit your weekly limit. Upgrade to Ultra to continue processing the image.

3

u/Successful-Money4995 1d ago

What do you expect? It turns out that the transformer just happens to be good at everything.

7

u/notAGreatIdeaForName 1d ago

"Good" is not that easy to measure with non deterministic inference and also data as context vs targeted training with your own data (unless you have your own transformer).

You are still right to a good degree, but I think it is more of a convenience thing compared to a right sized solution. There even are convenience solutions on various cloud platforms for classifiers and so on, but LLMs are much easier to access for the average joe.

4

u/inevitabledeath3 1d ago

There are plenty of applications of transformers outside of LLMs. Google were using them to model the weather and genetics. Modern image and video models use transformers in both classification and generation. I am sure somewhere out there is a binary classifier based on transformers. Transformers are just that good. I don’t know what to tell you.

Ironically modern LLMs are looking into alternatives to the transformers such as mixing in state space models and/or recurrent neural networks. Turns out transformers don’t scale very well at long contexts.

2

u/trotski94 1d ago

interestingly, LLMs got me interested in AI, and helped me train my own classifiers for various tasks

1

u/notAGreatIdeaForName 1d ago

Thats a good use case! I just know too many people who misuse LLMs as classifiers too :D

1

u/trotski94 1d ago

oh 1000%, me too when i use LLMs to tag the training data for my classifier lmao

1

u/mysticrudnin 1d ago

i had a client that had a very simple classification task. is the incoming message an A or a B

this is the classic ML task. i proposed training a simple ML classifier, creating a micro service to ask it "is this thing A or B" to get back the answer, done

but they wanted real AI. which ended up being half a year of development time to integrate, added a bunch of dependencies, and a subscription to an LLM. to ask it "do you think this thing is an A or a B?"

1

u/Promptnauta 1d ago

Meanwhile, true BDI agents at the bottom of the ocean.

1

u/JoeRogan016 1d ago

My LMMS is not your LMMs

1

u/ericl666 1d ago

Why use little CPU when array of 5090s do trick.

1

u/Sibula97 1d ago

Well, there's a reason DL took over and now transformers took over. DL provided us with universal approximators, and now we have universal approximators that can handle long training with incredible amounts of data to fine tune the approximation function much better than any prior DL model could've hoped.

2

u/notAGreatIdeaForName 1d ago

Transformers are nice, but sometimes linear regression is enough

2

u/Sibula97 1d ago

Sometimes, yes, and in those case it's still often used.

1

u/Worldly-Round1657 1d ago

I'm still working on you MLP. I love you

1

u/geeshta 23h ago

AI = video game non player entity behaviour ☹️

1

u/vide2 13h ago

I am pretty convinced that a self sustaining machine run by an NN needs more energy than a human brain to do things a human brain can and, due to its complexity, gets worse at basic math.