You can increase the amount of your existing defect images but flipping, rotating, cropping the images in a pre-processing step.

It isn’t a perfect answer but it is a great way to augment the limited data you already have.

I feel like it should be possible to extend diffusion transformer technique to code generation for web development.

You can input a screenshot of a static webpage, then use a text prompt like 'Change the style to fit a futuristic theme', or just input a low fidelity UI wireframe and it can generate a detailed webpage with the html and css. We can get training data from the internet for self supervised learning.

Also retrieval transformers or models that know how to query APIs, databases and prompt other models.

RL has potential

Symbolic AI

Which continual learning papers are you referring to?

I just meant this would take significant amount of time. I think it is impossible to do research in a quantitative field without understanding these so I would say it is well worth the investment. But most people are not concerned with research or even understanding the methods.

I guess they're referring to GPT4's release

Why next week will be big?

Just asking (Not trying to offend you or anything)
Why you asked whether this is serious ? Are above are very basic things ?

Thank you very much.

Your comment is very helpful.

I'll refer these sources.

If you are serious, I would recommend working on Rudin's Principles of Math Analysis. It might take a day (or more...) to wrap your head around a single proof but at the end you'll be ready to read anything (of course you might need to check some definitions.)

For KL divergence, entropy etc., Info Theory book by Mackay is great.

For hessian, well it is just calculus; the second derivative of a multivariate function. To understand its uses, you would need some understanding of numerical analysis and concave programming. For the latter, Boyd's optimization book is a classic. I don't remember a good book on numerical analysis but some diff. eqn.s books have nice chapters on it.

It’s already happening and also next week will be big

First try and understand every symbol in the equation, there are cheat sheets online. Second, most math concepts have a wikipedia page you can read, go down those rabbit holes and sooner or later you will find common threads and start to build an understanding. Finally, just put the time in, math is like everything else and just takes lots and lots of practice.

The usual answer to this is "multimodal" and I think that's still true, especially with recent advances. We'll see in the next few months :)

I have an idea, maybe ask Chatgpt to make some stories to explain those abstract concepts

Do problems involving the equations on paper and also read and copy down articles that are written on them.

As fas as I know, N(Xt ; ... , BtI) means that the V(Xt) = Bt, But if it is so, the equation two equation in the picture seems to be contradictory.

So... N(Xt ; ... , BtI) doesn't mean that the V(Xt) = Bt ?

oh no, not java -_-

My primary interest is RL, because I need it for my project (I don't think, that standard NN would work, because the enviroment changes so rapidly, that I can't use multiple agents, bec the results won't be comparable). I know some basics - I used TensorFlow in python for few times and I've built my own simple NN using matrix multiplication in unity few years ago. I just don't know much about RL and I don't know anything about neural networks in java, but I am trying to mod a java game and I didn't want to write the project in two languages before asking if there is some less wired solution.

I need to add it as a mod for a java game and I am trying to avoid having a second program in a different language because I am too lazy to do it, so I was asking if there is some better solution.

Remind me 999999 years

You can learn with lower cards. I still use a GTX1050Ti for training on some models. Works great. The important thing is learning how to use resources efficiently. If you can use Collab or a lower card well, then you’ll know the moment you really, actually need a better card (or cards).

OP u ok mate?

> in Java

but why?