Not all machine learning is AI. There are plenty of Machine Learning algorithms like Random Forests that are not neural networks. Deep learning would be big neural networks.
Comment on Squiggly Boie
HeyThisIsntTheYMCA@lemmy.world 3 weeks agoLLM models or ML in general? i’ve only known folk who worked on ML, not actually done it myself
NotANumber@lemmy.dbzer0.com 3 weeks ago
howrar@lemmy.ca 3 weeks ago
Not all machine learning is AI
The other way around. Machine learning is a subset of AI.
NotANumber@lemmy.dbzer0.com 2 weeks ago
You are correct. I had to actually look that up.
kurwa@lemmy.world 3 weeks ago
LLMs definitely, but not all machine learning uses neural networks
HeyThisIsntTheYMCA@lemmy.world 3 weeks ago
ohhhh so that’s The model for neural networks, not A model for neural networks
Tamo240@programming.dev 3 weeks ago
Its an abstraction for neural networks. Different individual networks might vary in number of layers (columns), nodes (circles), or loss function (lines), but the concept is consistent across all.
NotANumber@lemmy.dbzer0.com 3 weeks ago
Kinda but also know. That’s specifically a dense neural network or MLP. It gets a lot more complicated than that in some cases.
NotANumber@lemmy.dbzer0.com 3 weeks ago
It’s only one type of neural network. A dense MLP. You have sparse neural networks, recurrent neural networks, convolutional neural networks and more!
Aceticon@lemmy.dbzer0.com 3 weeks ago
I haven’t really done Neural Networks in 2 decades, and was under the impression that NNs pretty much dominate Machine Learning nowadays, whilst stuff like Genetic Algorithms were way less popular or not at all used anymore.
Is that the case?
howrar@lemmy.ca 3 weeks ago
Neural networks are a class of models. Genetic algorithms are a class of learning algorithms. You use learning algorithms to train models. Genetic algorithms are a valid way of training neural networks, but this is not currently in vogue. They’re typically trained via gradient descent.
Nikls94@lemmy.world 3 weeks ago
I don’t know if it is the case for the world today, but all those Models behave like genetic algorithms and IF-functions with a little RNG sprinkled on top of them.
Aceticon@lemmy.dbzer0.com 3 weeks ago
You mean that they’re actually competing multiple variants of a model against each other to see which ones get closer to generating the expected results, and picking the best ones to create the next generation?
Because that’s how Genetic Algorithms work and get trained, which is completelly different from how Neural Networks work and get trained.
Also the links in Neural Networks don’t at all use IF-functions: the output of a neuron is just a mathematical operation on the values of all it’s inputs (basically a sum of the results of a function applied to the input numbers, though nowadays there are also cyclic elements).