they've had to do this to fight off the threat from Big Strawberry

first 2 links are the same - do you have the one for CNNs inductive bias?

ChatWSB when?

the world awaits a new superhero/villain: Naked Mole Rat Man!

I'm thinking indestructible toothpicks

https://www.youtube.com/watch?v=VRbRVlX7Ql0

Or couldn't we use its strength to make bigger wooden structures? How much stronger is it? And actually, don't different types of wood already have different strengths? So what is this engineered wood being compared to?

Maybe it can give us better hardwood floors

engineered wood can also be used to build taller wooden ladders to help us deal with the towering skyscraper infernos when the wooden buildings catch on fire

I thought bamboo already absorbs massive amounts of carbon

You think it's pulling all that plant mass out of thin air?

oh... wait...

wood 2.0

we cluttering the biome with bio-spam now

got wood?

Yeah, expensive wood is expensive -- it's not like it grows on trees

... oh... wait...

What exactly is Validation data?
I know what Training data is for, and I know what Testing data is for.

But what is Validation data, and what is Validation for?

Since a 3D object is a vector object, it would be nice if they could also come out with AI that generates 2D vector art as well, since that would also help to reinforce the 2D art in general. Then 2D vector art could be seamlessly integrated with the 2D raster art.

I wonder if there'll be a new budding industry for SEO with GPT, just like there is for SEO with Google search? I'm not sure how that would work though, since it might be harder to integrate spam/ads into GPT responses.

Open Source is only free when it's running off your own computer. Otherwise, if it's running off some infrastructure, then that has to be paid for - typically with ads or something like that.

Well, remember when Youtube was totally free without any ads whatsoever? And of course we all wondered how they were going to continue offering their service for free. Then one day the ads crept in, and we knew.

I'm thinking OpenAI hasn't made this thing free just for generosity. They're using us as free beta-testers to shake down the product for them, so that they can iron out the kinks and bugs. Once that process has run its course, they'll just cut off our access and only allow paying customers to use it.

Do we know when ChatGPT itself will cease to be free, or cease to be available to the general public? I kind of like using this thing - I find it really convenient, so I'd like to know when I'm going to lose access to it.

Is it possible to have Machine Learning for CAD designs? Could it be possible to train a model on a repository of CAD files?

Is highly structured vectorized data more efficient to train on compared to rasterized image repositories? How much more efficient?

How to Handle Lots of Missing/Null Values in Data?

There's a data set that I've been given to analyze, and it's got a lot of missing data. Typically, I should replace missing values with mean, or mode, etc. But one particular column has nearly 70% null values. What is the threshold to reject a column as unsuitable for analysis, instead of trying to replace those missing values? How large a proportion of missing values is acceptable before I have to reject/discard the column altogether? Is there some rule of thumb for this?

What Are Latest Cutting-Edge Applications in Generative Modeling?

Like everyone else, I've been playing with the new release of Stable Diffusion recently, and marveling at its output. I want to know what else is out there that makes use of Generative Modeling. What are the newest and most exciting things in development? I really want to know.

I can already see Generative Modeling being used for music. But beyond just artwork, what are other big fields or practical applications? What about CAD, for example? If a Machine Learning model was trained on enough CAD files of various types, could it learn how to design machinery, equipment, vehicles, buildings, etc? If a Machine Learning model was trained on lots of DNA samples categorically labeled according to their phenotypes, then could it learn how to make living things?

How Can I Boost PyTorch Performance On My Cheap Laptop?

Hi, I have a cheap laptop running Windows 10 and Intel Core I5-5300u processor with Intel 5500 GPU.

How can I find a way to make Pytorch code run faster on it? I tried looking at Intel Extensions for Pytorch, but they say 10th-gen processor is minimum requirement. I read about something called Zluda which claims to be able to run CUDA-enabled code without modifications, but that seems to only be for Linux and I don't know what the minimum processor requirements are.

Is there some way to use my Intel GPU to help out my execution time?

xylitol significantly raises your blood glucose, though - I've heard keto dieters advise against taking it