I certainly don’t have Eckhart Tolle’s peace of mind, but when difficult thoughts and feelings do arise, I watch them fl

As AI develops, something will have to be said about the limits to these technology and as harmful as some of the above could be, it’s interesting to see new applications in the space.

As the system is end-to-end, this model has the ability to produce high resolution surfaces which are even unseen, like the persons back. That’s the bit that I find amazing — the algorithm can develop an idea of what the back of a person looks like.

For those who don’t know, GPT3 is an autoregressive language model that can generate responses to different types of prompts. The release of this model made a stupendous amount of noise (which technically, was just a bigger neural network than before).

Facebook highlight that the problem of restoring old photos is difficult because there’s a generalisation problem. Degradation in images is quite complex and there are gaps between the synthetic images vs real images which make traditional deep learning algorithms not generalise well (as they can’t handle things they’ve not seen before).

As AI develops, something will have to be said about the limits to these technology and as harmful as some of the above could be, it’s interesting to see new applications in the space.

There are various ways to do this: by checking out what’s going on in Kaggle or Product Hunt. Maybe having a look through stack overflow trends, or even looking at GitHub trends.

The goal of Project Sherlock is to find accounts linked to a particular username across the internet. It’s super quick to download, install and play around, but takes a bit of time to run.

As such, FB take a new approach by using 2 variational auto-encoders to train the models, so gaining 2 different latent spaces. The translation between the 2 domains is then learned using synthetic data.

I found it quite useful as I was able to find some old websites where my account should have been deleted, but either way, it’s a bit creepy to think that anyone can use this tech.

The researchers at Facebook have come out with an update to their Pixel-aligned Implicit Function (PIFu) model that aligns pixels of a 2D image with corresponding pixels of a 3D image. Using PIFu, Facebook have made a Deep Learning model (end-to-end) for digitising people, with the ability to infer 3D surface and texture from either a single image, or multiple.

It makes sense for Sberbank to look at this as nailing GPT3 for a customer service function, for example, would lower costs (of customer service representatives) and improve the performance of any service they have already.

It took me too long to realize that often when they were ignored, it wasn’t because of low quality, but because the publication simply wasn’t seeking freelance submissions at the time.

The above projects are super interesting and each has their own purpose, but it’s great to see that these fun (and somewhat scary) are using data science and machine learning to the full extent.

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pajamas and sheets. Create an indulgent ritual, maybe with some candles or favorite music. Go to bed early enough to spend quality time with your partner. Doesn’t that sound like a much more fun way to spend a Tuesday night than passing out exhausted?

As someone who’s been fully sustaining myself as a freelancer for over two years, I’m all too familiar with the struggle of finding the right publications to submit to. Over the years, I’ve pitched and submitted to over 100 publications. A small portion of my submissions have been accepted, and many have been flatly rejected. But the vast majority have been completely ignored.