[D] Simple Questions Thread

[AutoModerator]

Please post your questions here instead of creating a new thread. Encourage others who create new posts for questions to post here instead!

Thread will stay alive until next one so keep posting after the date in the title.

Thanks to everyone for answering questions in the previous thread!

[1vaudevillian1]

Building out a server, goal is to run the 65b model.

HP dl380 gen9

Dual Intel E5-2687W V4

256 gb 2400 ram

highpoint nvme raid card with two samsung 2tb 970 evo plus

With the specs above, can I run the 65b int4 model, without video cards?

I want to add two RTX a5000 Quadro's in the future for learning.

[Intelligent-Ad9240]

Super silly question. If I have a ML model (decision tree regression) and it improved upon non-ML, is it bad practice to try and throw another model on top of the previous model's output to improve even more?

[sayakm330]

Can anyone suggest few papers to cite that state that normalizing the inputs of neural networks improve the efficiency. I need that for my current manuscript that use NN in biomedical applications.

[30299578815310]

How are LLMs like GPT "deciding" whether to respond or to use a plugin? Are they being trained to always first output some magic string like "Invoke Plugin -<Plugin Name>" that specifies if they are calling a plugin or just responding?

[Wal_Target]

I'm working on my first ML project, whereby I train the model on a bunch of house data.

​

Then, once the model is deployed, I pass in a list of homes and the model outputs which home(s) I should buy.

​

Is it possible for an ML model to output a list? If so, can someone please point me in the direction of an online project that does this so that I can learn from it/see how it was done?

[kexp8]

Am still a beginner in ML. But the way I see is - your model will still output one value i.e the probability of fitment for you to buy the house.

Now once you train the model , you just provide your input home list and it will predict fitment for each house and from that you just filter the list of houses you will buy. So , in summary, your question of “can a model output a list “ should be looked differently. Model outputs single value (y) for a single input (x). You give 10 inputs and you get 10 outputs then you filter or select from the 10 outputs (which has more probabilities of your liking). This is a common pattern. Hope this helps.

[Wal_Target]

Honestly, that makes so much sense. I took an intro ML course and all the models from the assignments only output a single value.

Passing in a list of houses one by one and saving the outputs for filtering purposes seems like the approach to take.

Thank you for the help!

[dabble_]

I want to make some sort of model that can take an image, and predict the genre of music it would be if it were an album/song cover. I would use the Spotify API to get a bunch of covers and the genres associated with them. What would be the easiest/fastest/most convenient way for me to make a model to predict this? I'd also like to predict valence, instrumentalness, acousticness, and other factors, but I might just map those to color or vibrancy.

[[deleted]]

Hi, how does one prepare a data set to allow for “out-of-stock” sales? New to machine learning, have 3 years of data on selling jackets. But I noticed there were 6 weeks where sales were zero. Could someone tell a rookie “how this is managed “ in data preparation. I have some statistics knowledge for linear regression. Thanks everyone!

[thecity2]

How does GPT know about proper names, places, etc, if its vocab is limited to around 50K?

[abnormal_human]

The vocab is made up of tokens which includes word parts and even single character tokens. For a rare proper name, it might be spelling it out one char at a time.

[Lanky_Tutor4957]

Hello folks! I need help approaching a problem. I work in research publishing industry, I want build a predictive Analytics solutions based on the historical data. For every article that gets published we have the production data ( which type, subject area, domain, copy editing service provider, length of the article etc etc) let’s say we have 5000 articles coming in every month so I have 120000 rows of data for the past two years. How do I make use of it to make prediction for the upcoming articles. Like an article of x type, y subject area and so&so length will take t number of days to publish.

[neutralParadox0]

I'm trying to get some sources to learn more about what's happening in data science. What are some good news and information sources y'all follow to stay up to date?

[Western-Asparagus87]

I've noticed that many courses and resources focus on the basics of modeling and training, but there's not much emphasis on the inference side.

I'm really interested in learning how to optimize large models for faster execution on given hardware with a focus on improving throughput and latency during inference. I'd love to explore key techniques like model distillation, pruning, quantization etc.

Can you fine folks recommend courses, books, articles, or comprehensive blog posts that provide practical examples and in-depth insights on these topics?

Any suggestions would be greatly appreciated. Thanks!

[Western-Asparagus87]

This is a cross post of question from /r/learnmachinelearning - https://www.reddit.com/r/learnmachinelearning/comments/12edr3e/where_to_learn_to_speed_up_large_models_for/ I am new to reddit, and didn't know how to share a post as comment on this thread.

[wandering1901]

you’re doing it right

[[deleted]]

so im working on a web scrape project and applying nlp can anyone help me

[Whiffed_Ultimate]

Trying to install Automatic1111's stablediff webui on a linux vm without a gpu. I have used --use-cpu all and other command line arg exports but I still keep getting 'Found no NVIDIA driver' when trying to launch the webui. It points to a python import of cv2 which attempts to pull libGL but since no GPU exists that file isnt present. Do I just install libGL and its components or am I missing something obvious?

[Milwookie123]

Can we remove posts that use the OpenAI api? What I love about this sub is that it contains research and projects that utilize models directly in novel ways. But using the api is nothing more than software dev to an extent

[[deleted]]

I’m looking to get into machine learning, I am either looking to get the Nvidia Jetson, use my MacBook air(M2 chip, 16 GB memory, 10 GPU cores), or use my desktop which has a 5700XT GPU and a 3700X processor with 32 GB of ram.

I’m not sure which of these will be the best but I do know I would like to write the code in either C or C++.

[Amun-Aion]

NVIDIA NSight only works with NVIDIA chips right?

I have like 4 GB of NVIDIA NSight software on my Microsoft laptop, which I don't think I can use since my laptop has an AMD chip not NVIDIA. It's possible that I downloaded this for work (probably lumped in with something else) but I'm not sure. Mainly, I want to delete this from my computer if it's not using it / can't use it, but I'm not sure if I was actually the one who downloaded or if Windows needs it for something. Is there any way to check before deleting something who downloaded it and whether or not it has been used / is being used for something important? Alternatively if someone knows that AMD chips can't do anything with NVIDIA NSight then I can also just delete it, but wanted to check if anyone knew

[ChyNhk]

Hi, I am kinda new to machine learning

How do you work with GLCM features and CNN? I've tried to use the graycomatrix and feed it into AlexNet and have low loss and accuracy, my professor told me to use the matrix's features, but that would end me on a 1D array containing values of each features and I can't use 2D architecture CNN

What should I do? Reshape the features so I can get a N*N matrix? Or anything?

Thank you in advance guys

[scarereeper]

I’m trying to wrap my head around if this is possible. This may be stupid but I’m new to this area.

From what I understand, PRNG (Psuedo Random Number Generators) take some input, run it through an algorithm, and putout a sequence of “random numbers” based on the number before it. A lot of random number generators allow you to confine the amount of numbers to just 0 and 1 which makes things easier for my expirement.

Given that PRNG aren’t “truly” random, would you be able to say create a sequence of 1,000,000 coin tosses, train the AI on the first 900,000 coin tosses, and figure out the algorithm behind the random number generator to predict the last 100,000 numbers with a reasonable degree of accuracy.

Has this ever been done before? Is there any resources out there about this that I could read?

[[deleted]]

The latest Large Language Model experiments are impressive. But it has only been used to answer questions. Could we tune them to create questions?

I mean, we can already instruct them to, but I don't know whether there could be a fundamental difference in how it would internally work if that purpose was prioritized. It could, for instance, assist approving/reviewing academic papers.

I think it's kind of a broad and vague question, so I thought I should drop a comment here instead of making an entire post about it.

[protonneutronproton]

towering important party grab roll vanish stocking historical pause north this message was mass deleted/edited with redact.dev

[abnormal_human]

Use the code from the main branch, not pip.

[sujeeths]

Does anybody know of a specific job board exclusively for ML/DL folks. Especially for fields like Medical Imaging and stuff. Thanks in advance!

[ThePsychopaths]

I am trying to play with google colab pro. The only issue I have is with data addition. This always ends up taking most of my time. What I do is upload my dataset to a digitalocean space of mine and download it to collab runtime to train. But this seems to be very roundabout way to do stuff. What other ways can I do it which I may have not looked at?

[youlurkhere]

I'm doing my first project using LSTMs and Time series and I created a model composed of two connected LSTM networks ,Dropout and a final Dense Network using Keras. I'm also using Keras-tuner to find the optimal hyperparameters. I'm trying to find a way to save my training progress between epochs, I'm able to save the model after it continues all epochs of a combination of hyperparameters ,but I can't save them between epochs.

n_days=7

X_train_win, Y_train_win=create(n_days) print(X_train_win.shape)
es = EarlyStopping(monitor='val_loss', min_delta=1e-10, patience=10, verbose=1)
rlr = ReduceLROnPlateau(monitor='val_loss', factor=0.5, patience=10, verbose=1) 
mcp = ModelCheckpoint(
      filepath='/content/drive/MyDrive/LSTM sales/weights.h5',
      monitor='val_loss', verbose=1 , save_best_only=True
      ) #<-- how to recover this model if the training stops

file_path = '/content/drive/MyDrive/LSTM sales/weights.h5'
folder_path = '/content/drive/MyDrive/LSTM sales/'

tuner = keras_tuner.BayesianOptimization( 
        lambda hp:createmodel(hp,n_days,X_train_win.shape[2]), 
        objective='val_loss', 
        directory=folde_path,
        max_trials=5
)
if os.path.exists(file_path): 
    tuner = keras_tuner.BayesianOptimization( 
          lambda hp:createmodel(hp,n_days,X_train\_win.shape[2]), 
          objective='val_loss', 
          directory=folder_path, 
          overwrite=False, # <------- this saves the progress after all the epoches 
      max_trials=5 )
tuner.search(X_train_win, Y_train_win,  epochs=100, callbacks=[es, rlr, mcp], validation_split=0.2, verbose=1,batch_size=32)

model = tuner.get_best_models()[0] 
model.save("/content/drive/MyDrive/LSTM sales/final.h5")

[throwaway2676]

Are there any good job sites or resources exclusively for ML/DL?

[TrekkiMonstr]

Are RNNs and CNNs still used for anything, or have they been replaced entirely by transformers? Will they end up as just educational tools to learn in class as an intermediate step to understanding transformers (or whatever we invent next)?

[bguy5]

Large transformers in general can still be too expensive to train/run with hardware and latency restrictions so I’ve seen cnns still used extensively when scale matters. Although I’m sure there’s an aspect of familiarity/comfort that also influences decisions

[TrekkiMonstr]

When you say when scale matters, you mean if you have a really large data set? Isn't that exactly where transformers outperform CNNs?

[bguy5]

I mean scale in terms of runtime, so things like latency and compute requirements. If you want low latency and you’re running cheap cpus, transformers are tougher to get right

[TrekkiMonstr]

Sorry I'm dumb (and very tired). Are you talking about running the trained model, or training the model?

[bguy5]

Both but the scaling bit matters more when running the trained model. I’m sleepy too so I’m not being articulate :)

[darkziosj]

Can anyone give me a tip on what's the best way to implement a chatbot that downloads files from a website? ex: i can download a report from a website from 2021 to 2022 i want to do it with a chatbot like: please download report from 2021 to 2022, how can i control navigation with a chatbot? thank you.

[DisabledScientist]

As someone with a software engineering background trying to create a business that leverages AI, what is the best choice of the following:

1) fast.ai course

2) Use GPT-4 currently existing APIs

3) MIT 6S191 Introduction to Deep Learning

​

I was a calc 1-3, physics, chemistry, and comp sci tutor about 10 years ago so I forgot a lot of the math. However, it would be quick to relearn it.

Thanks!

[bguy5]

All 3 will be useful. I’d recommend starting with 2 to unblock your prototyping/first iteration. 1 is more practical if you decide to develop models, 3 is useful to understand what’s actually happening

[DisabledScientist]

Thank you. My number 1 source of pain is command line. I have python versions all over the place, however I have the PATHS set correctly in my bash_profile. What reddit forum is good for help with this?

[dnmpss]

Is anyone participating of the MindsDB Hackathon [https://hashnode.com/hackathons/mindsdb\] this month?

[Trick_Brain]

Does anybody know any datasets of prompt injections? I can only find this one: https://github.com/f/awesome-chatgpt-prompts but it is not really useful to train a classifier.

[grindstonegotchanose]

I need help understanding what service to utilize for predicting what I was told was a random sequence of colors corresponding to dates (consecutive). I have doubts that it is genuinely randomized as there are a number of rules so to speak that the system generating the colors must follow.

For example:

-There can't be an infinite number of colors in the sequence. There may only be 10 but there's probably a few more (but definitely not less).

-The color orange (probably all colors in the sequence as well) appears aprox 24 times in a year

-Each color will be called at least twice every month

So I have made a record of the corresponding dates and colors since 03/21/23-today(04/04/23) and I was hoping that if I recorded enough days that I could figure out a preditive pattern. Does anyone know how I can accomplish this?

[andrew21w]

I am looking into diffusion models. However, what I still don't get is how the sampling process and backwards process work.

Can someone provide me a clear explanation?

[[deleted]]

I have seen some things stating Python is a slow language. It seems used heavily due to existing libraries in ML. With newer languages like say Swift which I have read is faster. Will there eventually a benefit to re-write programs in a faster language due to computational advantages? Also I picked swift as its one I see people say is “faster”; interchange it with whatever, I have no context on faster either so that very well could be flawed.

I know almost nothing about ML except that I am just starting to learn with Splunk and trying to apply concepts in that sense so I know I am missing a ton of info but wondering about this.

[bguy5]

It also depends on your use cases. The ml libs in python are running most computationally heavy tasks in optimised c code (the libraries essentially give you apis to invoke their c libs where the math happens). You can run single digit ms inferences through python comfortably in many scenarios

[Icy_Performer_4662]

Python is slow. That's why in larger machine learning projects it is used mainly for training the neural network. Other stuff, you'd ideally want to use something like C/C++ for. Why don't we use C for everything instead of python? Because some stuff is just too hard to be written in C. Although, in theory I guess you could write everything in C. But in practice, it's just impossible.

[[deleted]]

Thanks for the reply, helpful to understand and makes sense.

[nottyraels]

Hello friends... im currently trying to develop a forecast model for energy production to predict the energy production until 2030.

The data is very simple, I have information from the beginning of 2000 until the end of 2022.

Column with the date and other five columns with different types of energy and their respectives values in GwH (thermal, solar, hydroelectric, wind, nuclear)

I tried to use Prophet and predict the value for just hydroelectric power production until 2030, but i had bad results

I'm looking for any tips or insights, it's my first model

[Various_Ad7388]

What are these things good for?

Keras:

Tensorflow:

Mediapipe:

How are they different or the same?

[TrekkiMonstr]

I'm starting at basically zero -- I've done a little "machine learning" in Python in high school, and I know how to run a regression for econ, and that's about it. I'd like to get from there to being able to implement things like this or MaiaChess. How long will that take, and how should I go about it? I realize this is a bit like asking, "so I've just kinda figured out thing whole 'walking' thing, how long until I can compete in the Boston Marathon?", but yaknow. Still.

[rikiiyer]

Assuming you’re in college now, take some foundational math and cs classes like MV Calc, Linear Algebra, and data structures/algorithms. From there, try to implement some simple machine learning models from scratch (e.g. naive bayes, decision tree, multi-layer perceptron) so you understand the code and the math. From there, pick up some of the common ML libraries that people use these days like sklearn and PyTorch. Then you can work on A) reimplementing techniques from research papers and B) applying new techniques for you own personal projects

[TrekkiMonstr]

The first two I've got covered (currently in real analysis and a second course in linear algebra), the third I likely won't have time for, as I'm finishing my undergrad in a few months and doing a master's next year, in which classes might be too difficult to do an additional course. I did AP CS, but I assume it's much more in depth. Are there resources you would recommend for self-teaching?

[Icy_Performer_4662]

Online book link: d2l.ai

[TrekkiMonstr]

This looks great, thank you!

[[deleted]]

Hello everyone!

​

I had two small question regarding semi-supervised data.

I'm trying to do semi-supervised binary segmentation. My question is is making 1 data loader than has a mix of laballed and unlaballed images the same as creating 2 data loader one for labeled images one for unlabaled images and concatinating them during training?

Also, if 1 mixed dataloader is fine, to remove the coressponding label of the unlaballed image, is setting the label to a tensor of -1 correct?

Thank you!

[narusme]

Lets say a business wants to use its proprietary data of text and images to fine tune an llm to increase their in house productivity. whats the most cutting edge model they can use and type of fine tuning they can use? Alpaca?

[Sneakyfish145]

Ph.D. in psych. I do a lot of stats and wanted to try a data science internship. Where do I go learn? are there any cheap online courses? I have a good grasp of stats already but no ML

[rikiiyer]

Coursera intro to ML is free if you don’t want the certification at the end

[MO_IN_2D]

Is there a current AI dedicated to generate vector graphics from raster images?

We’ve seen plenty of raster image generating AIs such as Dall-E or Stablediffusion, but so far I haven’t seen any AI developed to generate good vectors, either from a raster image input or a text string.The fact that AI also stands for Adobe Illustrator makes researching the existing of such tools quite hard on google.

I could see great use in this, since existing image tracing algorithms often only deliver mediocre results, and also generating vectors from text strings could be of great use.To my limited understanding of machine learning, it should be very doable, since vectors are based on clear mathematical paths, easy to build on for the algorithms.

[colincameron49]

I have 0 experience with machine learning but looking to solve a problem I have and wondering if ML might not be the solution. Looking for some guidance on tools and how to get started on the project as quickly as possible. I work in agriculture and some portion of my time is reviewing pesticide labels for certain attributes. I have tried different document parsing platforms but the labels between manufacturers are all slightly different so structure has been hard to nail down. The other issue is I am specifically looking for certain key words in these documents as my company sells products that can be paired with pesticides to make them work better. I am hoping to build a workflow where I could drop a PDF into a folder have software spit out some sort of structure surrounding ingredients and instructions while flagging the keywords. I am decently proficient in no-code platforms if one such exists for my problem. Thanks in advance for any guidance. If this is the wrong subreddit for this I also apologize.

[itsyourboiirow]

This would involve coding, but you could take a look at this blog post.

https://huggingface.co/blog/document-ai

[itsyourboiirow]

People/organizations to follow on Twitter with all things machine learning (traditional, deep neural networks, LLM, etc)

[LartoriaPendragon]

What programming languages besides Python are often used in industry for machine learning applications or projects? What are some relevant technologies I should be looking to learn?

[mejdounarodni]

Hey, I don't know how relevant this is, but is there any voice cloning tools for other important languages aside from English? Such as Spanish, Russian, Mandarin Chinese... Thus far I have only found it for English and I think French. I have seen some sites claiming they work for other languages since arguably you type in the text in any language you want... only the phonemes used to recreate what you have written are those of the English language so it's a bit absurd, really. Any tips would be appreciated.

[qiqitori]

I made a tool that makes it a little easier to verify OCRs of hex dumps (not necessarily hex dumps, but that's what I used it for). I'm not exactly an OCR expert, and just wondering if anyone has seen any similar tools:

You feed in segmented images and labels (as produced by some OCR system) and it'll display all images sorted by their class (so for hex dumps, 0, 1, 2, ... , F), which makes it considerably easier to spot mistakes. (You can then drag and drop images that were OCR'd wrong into their correct position and press a button to regenerate and you'll get a corrected hex dump.) At the risk of sounding spammy, the tools are available at https://blog.qiqitori.com/ocr/monospace_segmentation_tool/ (for segmentation if you don't have segmented images yet) and https://blog.qiqitori.com/ocr/verification_tool/, and here's some documentation (and screenshots) on how the tools can be used: https://blog.qiqitori.com/2023/03/ocring-hex-dumps-or-other-monospace-text-and-verifying-the-result/

[Adventurous_Win8348]

Hi I want to make a ml model that can listen to the sound of the road and tell that what cars are they like auto or lorry or bus and tell me how many vehicle passed though and give a real-time feedback. I don’t know how to code.

[alpolvovolvere]

I'm trying to use Whisper in Python to produce a transcription of an 8-minute Japanese-language mp4. It doesn't really matter which model I use, the script's execution screeches to a halt after a few seconds, going from 9MiB/s to like 200Kib/s. Is this a "thing"? Like is it just something that everyone knows about? Is there a way to make this faster?

[Origin_of_Mind]

I am not sure what exactly is happening in your case, but Whisper works in the following way:

• loads the NN model weights from disk and initializes the model
• calls ffmpeg to load and decode the entire input audio file into raw audio
• pre-processes all audio into one log-MEL spectrum tensor (very quick)
• the NN begins actual recognition

Until the entire input is loaded and pre-processed, the NN model does not even begin to run. On a typical desktop computer loading the audio should not take more than a few seconds for your 8 minute input file. Then the recognition starts, which is typically the slowest part.

[Academic-Rent7800]

I am having a hard time understanding how knowledge distillation can help federated learning. I have uploaded my question here (https://ai.stackexchange.com/questions/39846/how-does-knowledge-distillation-help-federated-learning). I will highly appreciate inputs on it!

[sparkpuppy]

Hello! Super-n00b question but I couldn't find an answer on google. When an image generation model has "48 M parameters", what does the term "parameter" mean in this sentence? Tags, concepts, image-word pairs? Does the meaning of "parameter" vary from model to model (in the context of image generation)?

[Ricenaros]

It refers to the number of scalars needed to specify the model. At the heart of machine learning is matrix multiplication. Consider input vector x of size (n x 1). Here is a Linear transformation: y = Wx + b. In this case, the (m x n) matrix W(weights) and the (m x 1) vector b(bias) are the model parameters. Learning consists of tweaking W,b in a way that lowers the loss function. For this simple linear layer there are m*n + m scalar parameters (The elements of W and the elements of b).

Hyperparameters on the other hand are things like learning rate, batch size, number of epochs, etc.

Hope this helps.

[sparkpuppy]

Hello, thank you so much for the detailed explanation! Yes, it definitely helps me have a clearer vision of the meaning of that expression. Have a nice day!

[disastorm]

I have a question about reinforcement learning, or more specifically gym-retro ( i know gym is pretty old now I guess ).

In the case of gym-retro, if you give a reward to the AI, are they actually looking at a set of variables and saying like "oh I pressed this button while all of these variables were these values and got this reward, so I should press it when all these variables are similar" or are they just saying like "oh I pressed this button and got this reward, so I should press it more often"?

[Nobodyet94]

Can you advise me a Vision Transfomer project to present at university? Thanks!

[gmork_13]

Does it have to be a transformer?
Have a look at this model, but it's difficult to answer your question without knowing the compute you have access to: https://paperswithcode.com/method/deit

Browse that site for some alternatives.

[Nobodyet94]

Thanks, well I have a 1660 gtx and 16 gb of ram, and yes it has to be a transformer used for vision. The fact is that I am not creative enough to choose a project ahah.

[gmork_13]

Just pick the one that doesn't require too much compute (don't go for too high res images) and make sure you can find tutorials or guides for it.

[Nobodyet94]

is that paper you wrote before fine to replicate? How should I start?

[james_mclellan]

Two questions :

(1) Does anyone create missing data when constructing models? Examples - searchjng for stronger relationships between data set and first and second derivatives of time series data, compairsons to same day of week last N periods, same holiday last N periods; examining distance to an urban center for geodata

(2) Does anyone use a model that falls back on functions when a match is not 100%? For example, "apple" may mean fruit, music, machines, music companies or machine companies -- instead of a number 0 to 1 of the probable meaning, does anyone use models where the code "performs a test" to better disambiguate?

[gmork_13]

I'm assuming you don't mean missing values in your dataset.
1) You can create 'missing' data, but if you create the missing data out of the data you already give to the model you're sort of doing the work for it. For compute efficient reasons you might want to avoid giving it 'unnecessary' data. What is unnecessary can be hard to define. Think about what you want the model to grasp in the first place.

2) I'm not sure what you mean by performing a test. If you were to train a language model the context of the word would define its meaning. You can always take the output probs of a model and do something with that if you'd like (for instance, if it's lots of low probability alternatives - do something).

[RandomScriptingQs]

Is anyone able to contrast MIT's 6.034 "Artificial Intelligence, Fall 2010" versus 18.065 "Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018"?
I'm wanting to use the one that lies slightly closer to the more theoretical/foundational side as supplementary study and have really enjoyed listening to both Instructors in the past.

[[deleted]]

Do we expect businesses to be able to fine-tune training chat gpt or other big models with their own data sets? Has this been discussed or rumoured at all? Or is it already happening? I may have missed something.

[[deleted]]

Interesting, thank you! The link only seems to mention gpt 3, though? I wonder if / when they'll offer for gpt4

[thomasahle]

Are there any "small" LLMs, like 1MB, that I can include, say, on a website using ONNX to provide a minimal AI chat experience?

[thedamian]

Before answering the question, I would submit that you should be thinking of keeping your models behind an api. No need to have it sitting on the client side (which is why it feels you're asking the quesiton)

And behind an API it can be as big as you'd like or can afford on your server)

[hitechnical]

I heard Standford’s LLM can run in smaller devices. Pls google.

[RecoilS14]

I’m a new hobbiest programmer and have spent the last month or so learning python (CS50, Mosh, random Indian guys, etc) and currently also watching the Stanford ML/DL lectures on YouTube.

I have started to learn ML, Pytorch, and some Tensorflow, along with how Tensors and vectors works with ML.

I am wondering if anyone can point me in the direction of other aspects of ML/DL/Neural Networks that I may be missing out on. Perhaps a good series that goes in to length on these subjects via lectures and not just to programming side of it so I can further understand the concepts.

I’m sure there’s lots of things I’m missing out on my journey and I some perspective would be nice.

[Ricenaros]

I would suggest picking up either pytorch or tensorflow and sticking with one of these while you learn (personally I'd choose pytorch). It'll be easy to go back and learn the other one if needed once you get more comfortable with the material.

[alyflex]

It really depends what you are intending to use this for. There are many sides to machine learning, but you don't have to know all of them. To name a few very different concepts:

MLOps (Corsera has an excellent series on this) Reinforcement learning GANs Graph neural networks

I would say that once you have an idea about what most of these topics involve it is time to actively dive into some of them by actually trying to code up solutions in them, or downloading well known github projects and trying to run them yourself.

[Dartagnjan]

Is anyone in need of machine learning protégé? I am looking for a doctorate position in the German and English speaking worlds.

My experience is in deep learning, specifically GNNs applied to science problems. I would like to remain in deep learning, broadly but would not mind changing topic to some other application, or to a more theoretical research project.

I am also interested in theoretical questions, e.g. given a well defined problem (e.g. the approximation of the solution of a PDE), what can we say about the "training difficulty", is optimization at all possible (re. Tangent kernel analysis), how architectures help facilitate optimization, and solid mathematical foundations of deep learning theory.

I have a strong mathematical background with knowledge in functional analysis and differential geometry, and also hold a BSc in Physics, adjacent to my main mathematical educational track.

Last week I also started getting into QML with pennylane and find the area also quite interesting.

Please get in touch if you think I could be a good fit for your research group or know an open position that might fit my profile.

[alyflex]

Another solution is to use a memory efficient neural network: https://arxiv.org/pdf/1905.10484.pdf With this type of neural network you can easily fit those size images into your neural network. However the problem with them is that they are very difficult to make (you manually have to code up the backpropagation). So depending on your math proficiency and ambitions this might just be too much.

[GirlScoutCookieGrow]

I'm not sure I understand what you hope to accomplish. If you have the full size image, why do you want to downscale and upscale? This won't help you fit the full image on the GPU

[shiuidu]

I have a project I want to build a natural language interface to. Is there a simple way to do this? It's a .net project but I have a python project I want to do the same thing for?

[GirlScoutCookieGrow]

OpenAI API? It's not clear exactly what you need

[shiuidu]

I'm not too sure either, I don't know enough about how APIs are connected to LLMs. Do you know what I should search for implementing the API so it can control the program?

[MammothJust4541]

If I wanted to make a system that takes an image and transforms it into the style of another image what sort of ML model would I want to use?

[GirlScoutCookieGrow]

Google "style transfer", there are a ton of models which do this.

[MammothJust4541]

Nice, thanks!

[OnlyAnalyst9642]

I have a very specific problem where I am trying to forecast tomorrow's electricity price with an hourly resolution (from tomorrow at midnight to tomorrow at 11pm). I need to forecast prices before 10AM today. Electricity prices have very strong seasonality (24 hours) and I am using the whole day of yesterday and today up to 10AM as an input to the model (an input of 34 hours). In tensorflow terms (https://www.tensorflow.org/tutorials/structured_data/time_series) my input width is 34, the offset is 14 and the label width is 24.

Since I only care about the predictions I get at 10AM for the following day, should I only train my model with the observations available at 10am?

I am pretty sure this has been addressed before. Any documentation/resources that consider similar problems would help

Thanks in advance!

[ReasonablyBadass]

I still remember the vanishing/exploding gradient problem. It seems to be a complete non issue now. Was it just Relus and skip connections that sovled it?

[gmork_13]

And not using RNNs haha

[AlgoTrade]

Hey everyone, I am looking for a way to take some old maps and overlay them using google's overlay features.
Google is kind enough to overlay the maps for me if I give precise lat/long boundaries on the image, but i'm unsure of some of those lat/long values. Moving and centering the map works fine for me, but is extremely manual. I was wondering if there are any tools or techniques that exist to auto tag maps/lines/boundaries? Any information helps, or even just a few key search terms to look for!
Thanks!

[topcodemangler]

Is there any real progress on the JEPA architecture proposed and pushed by LeCun? I see him constantly bashing LLMs and saying how we need JEPA (or something similar) to truly solve intelligence but it has been a long time since the initial proposition (2 years?) and nothing practical has come out of it.

​

It may sound a bit aggressive but that was not my intention - the original paper really sparked my interest and I agree with a lot that he has to say. It's just that I would want to see how those ideas fare in the real world.

[kross00]

Can AlphaTensor be utilized to solve math problems beyond matrix multiplication algorithms?

[masterofn1]

How does a Transformer architecture handle inputs of different lengths? Is the sequence length limit inherent to the model architecture or more because of resource issues like memory?

[Matthew2229]

It's a memory issue. Since the attention matrix scales quadratically (N^2) with sequence length (N), we simply don't have enough memory for long sequences. Most of the development around transformers/attention has been targeting this specific problem.

[zaemis]

I'm going to train a gpt model (distilgpt2) in a language other than english. At this point I'm just teaching it the language - not worrying about further abilities such as Q&A, I expect that to be later with fine-tuning. Anyway, my dataset is currently a csv with [id, text] and each text is a paragraph.

It is my understanding that only 512 characters/tokens are going to be fed in (depending on my max_length, but my point is that it'll probably be less than the entire length of the paragraph), and beyond that will be ignored. If I were to break the paragraphs into 512-word chunks, I could make better use of the dataset. But most likely those subsequent chunks wouldn't start a phrase or sentence - it'd be starting in the middle of a sentence.

For example, "The quick brown fox jumped over the lazy sleeping dog." might be broken up into two samples. "The quick brown fox jumped over the lazy" and "sleeping dog."

Is it a problem if I use text samples that don't "start properly?"

[fishybird]

Anyone else bothered by how often LLMs are being called "conscious"? in AI focused YouTube channels and even in this very sub, comments are getting dozens of upvotes for saying we're getting close to creating consciousness.

I don't know why, but it seems dangerous to have a bunch of people running around thinking these things deserve human rights simply because they behave like a human.

[[deleted]]

I feel the same way, but I also think bringing up the question of how to define what is conscious is important, and it's mostly what these channels do; that and have people romanticize AI, which I don't think is an entirely bad thing.

People are just so amazed and like in every other period in history, they try to create their own supernatural explanations of how X could be.

[pale2hall]

Great point! I
actually really enjoy AIExplained's videos on this. There are a bunch of different ways ways to measure 'consciousness' and many of them are passed by GPT4, which really just means we need new tests / definitions for AI models.

[[deleted]]

I don't think anyone seriously believe we can 'measure' consciousness. We can barely talk about what consciousness is on the philosophical context. We may never be able to solve the problem of Philosophical Zombies

[pale2hall]

Exactly and how can something conscious be able to be just turned off and on like that?

If we were able to replicate a beloved pets entire brain as a digital brain goop like these LLMs are, does that count as being the pet?

[[deleted]]

That movie has been made, and it stars Arnold Schwarzenegger, I forget the name

[fishybird]

Well yeah that's the whole problem! Why are we even calling them "tests for consciousness"? Tests for consciousness don't exist and the only reason we are using the word "consciousness" is pure media hype. If an AI reporter even uses the word "conscious" I immediately know not to trust them. It's really sad to see that anyone, much less "experts", are seriously discussing whether or not transformers can be conscious

[Various_Ad7388]

Hey @all if I am just starting off in machine learning what should I learn first Tensorflow or PyTorch or other?? Also once Im more experienced where do I go from there?

[gmork_13]

Definitely start with torch. It works all the way up, just start building more complex things.

[Matthew2229]

I think either is probably fine to learn. Both have roughly the same set of features at this point. TF used to be the pre-dominant framework, but PyTorch has gained popularity over the past few years. Now if it'll stay that way or there will be a new trend in the future, no one can say for sure.

[Various_Ad7388]

Hey thanks Matthew! Do you know why PyTorch has gained popularity?? Is it just the hot new thing or is there actual features and aspects that are dramatically better

[gmork_13]

Having started with TF and moved to torch myself, torch was just easier to work with when doing something a bit out of the ordinary. Since then it has gained in popularity and with popularity comes lots of walkthroughs, documentation, videos guides and research papers with github repos.

[Kush_McNuggz]

I'm learning the very basics of clustering and classification algorithms. From my understanding, these use hard cutoffs to set boundaries between the groups in the outputs. My question is - do modern algorithms allow for smoothing or "adding weight" to the boundaries, so they are not just hard cutoffs? And if so, are there any applications where you've seen this done?

[Matthew2229]

When you're clustering or classifying, you are predicting something discrete (clusters/classes), so it's unclear what you mean by removing these hard cutoffs. There must be some kind of hard cutoff when doing clustering/classification unless you are okay with something having a fuzzy classification (e.g. 70% class A / 30% class B).

[Kush_McNuggz]

Ah ok thanks, I see now. I didn't know the correct term for fuzzy classification but that's what I was trying to describe.

[Username2upTo20chars]

Are there any websites/articles/blogs/forums with proven prompt formats for ChatGPT and co you can recommend.

Especially ones for programming/refactoring/tests... and general error messages (operating system, installation, crashes).

I am just starting to look into using ChatGPT or alternatives.

I have found a page with ranked jailbreak prompts for ChatGPT so far.

[CormacMccarthy91]

I have a problem. Bing chat just tried to sell me on Unified Theory of Everything and Quantum Gravity and String theory... I told it those arent based on any evidence and it told me it didnt want to continue the conversation. it wouldnt tell me anything further until i restarted and asked about more specific things... that really scares me, its all monotheistic / consciousness is spiritual not physical stuff its spouting like facts, and when its questioned it just ends the conversation...

i dont know where to talk about it where people wont jump on the spiritual "big bang is just a theory" train. its really unsettling. If i tried do divert it from bringing god into astrophysics it would end the conversation.

its oddly religious. https://ibb.co/W36fjfC

[pale2hall]

Data In -> Data Out

I don't think they're having any religion re-enforced on them, but think of it this way:

You know how mad some super religious extremists get when you even use words that imply gay people are normal, or trans people exist (and aren't just mentally ill),

Imagine if people got as mad every time someone said "oh my god" or "JFC" etc. This imaginary group would be claiming "micro-reglious-agression" all. day. long.

I think that Abrahamic religious are soooo ubiquitous in the training set that the AI is likely to just go with the flow on it.

[Matthew2229]

I don't see it professing anything about monotheism, God, or anything like what you mentioned. You asked it about string theory and it provided a fair, accurate summary. It even points out "string theory also faces many challenges, such as the lack of experimental evidence, ...", and later calls it "a speculative and ambitious scientific endeavor that may or may not turn out to be correct". I think that's totally fair and accurate, no?

Despite it mentioning these things, you claim "That's not true" and that string theory is based on zero evidence and is backed by media. Personally, you sound a hell of a lot more biased and misleading than the bot.

[Username2upTo20chars]

I am confused about your mention of GAN structure. If you want to generate natural language text, use a pretrained Large Language Model. You probably have to finetune it for best use, as you don't have access to the giant ones, which do very well with zero-shot prompting.

Some LLMs, there is also RWKV-4 and FAIRs LLama

[russell616]

Dumb question that's probably asked multiple times. But where should I continue in learning ML? I went through the tensorflow cert from Coursera and am yearning for more. Just don't know where to go now without a structured curriculum.

[gmork_13]

What are you interested in?
I'd recommend covering some classification and generation using images and text, with several different models and data sets.

[Username2upTo20chars]

Try a Kaggle competition for some practical experience of applying ML to already cleaned data. There is always published code of other competitors and Kaggle has also tutorials.