The Register: Good luck using generative adversarial networks in real life – they’re difficult to train and finicky to fix

The Register: Good luck using generative adversarial networks in real life – they’re difficult to train and finicky to fix. “Generative adversarial networks (GANs) are a brilliant idea: get two neural networks and pit them against each other to get a machine to generate completely new, realistic looking images. But in practice they are notoriously difficult to train and deploy, as one engineer told El Reg.”

The Next Web: This AI turns your blurry photos into creepy HD faces

The Next Web: This AI turns your blurry photos into creepy HD faces. “The tool was developed by Duke University researchers as a new approach to photo correction. It works by searching through AI-generated images of HD faces until it finds ones that look like the input image when compressed to the same size.”

Geekologie: A Website Where An Artificial Intelligence System Will Write Song Lyrics About Your Topic Of Choice

Geekologie: A Website Where An Artificial Intelligence System Will Write Song Lyrics About Your Topic Of Choice. “These Lyrics Do Not Exist is a website connected to an artificial intelligence system that will write song lyrics about your topic of choice. You just enter that topic (or a person’s name), choose a style of music from country, metal, rock, pop, EDM, or rap, and whether you want the tone of the song to be very sad, sad, neutral, happy, or very happy.” Not going to admit how long I spent here generating pop songs with my husband’s name in them.

CNN: How fake faces are being weaponized online

CNN: How fake faces are being weaponized online. “As an activist, Nandini Jammi has become accustomed to getting harassed online, often by faceless social media accounts. But this time was different: a menacing tweet was sent her way from an account with a profile picture of a woman with blonde hair and a beaming smile.”

Analytics India: 10 Free Resources To Learn GAN In 2020

Analytics India: 10 Free Resources To Learn GAN In 2020. “Generative Adversarial Networks or GAN, one of the interesting advents of the decade, has been used to create arts, fake images, and swapping faces in videos, among others. GANs are the subclass of deep generative models which aim to learn a target distribution in an unsupervised manner. The resources we listed below will help a beginner to kick-start learning and understanding how this model works. In this article, we list down 10 free resources to learn GAN in 2020.” These are informational, not tools.

Boing Boing: AI generates old-fashioned zoological illustrations of beetles

Boing Boing: AI generates old-fashioned zoological illustrations of beetles. “These beetles do not exist: Confusing Coleopterists is an AI trained on illustrations from zoological textbooks. The extreme formality of this art genre, and its placement within the public domain, makes it uniquely apt to the medium of generative adversarial networks: ‘Results were interesting and mesmerising.'”

Motherboard: This Website Texts You AI-Generated Foot Pics

Motherboard: This Website Texts You AI-Generated Foot Pics. “A generative adversarial network (GAN) machine learning system generates the feet on demand. GANs are a kind of computer program that learns how to create images by studying inputs—human feet in this case. There’s multiple sites generating fake human faces by studying millions of pictures of real human faces. That means thisfootdoesnotexist trained itself by staring at real human feet pictures.”

MIT News: Visualizing an AI model’s blind spots

MIT News: Visualizing an AI model’s blind spots . “Anyone who has spent time on social media has probably noticed that GANs, or generative adversarial networks, have become remarkably good at drawing faces. They can predict what you’ll look like when you’re old and what you’d look like as a celebrity. But ask a GAN to draw scenes from the larger world and things get weird.”

Interesting Engineering: A Database of 100,000 AI Generated Faces Is Changing the Way We Think about Stock Photos

Interesting Engineering: A Database of 100,000 AI Generated Faces Is Changing the Way We Think about Stock Photos. “Artificial intelligence can now give you a quality stock photo of a model… that does not exist. That’s right, AI can now generate imaginary faces for your next project. Dubbed Generated Photos, the collection of faces was created by Konstantin Zhabinskiy and his team.”

BBC: ‘Dangerous’ AI offers to write fake news

BBC: ‘Dangerous’ AI offers to write fake news. “The text generator, built by research firm OpenAI, was originally considered ‘too dangerous’ to make public because of the potential for abuse. But now a new, more powerful version of the system – that could be used to create fake news or abusive spam on social media – has been released.”

The Verge: Runway ML puts AI tools in the hands of creators everywhere

The Verge: Runway ML puts AI tools in the hands of creators everywhere. “Machine learning can be a fantastic tool for creators, but integrating AI into your workflow is a challenge for those who can’t code. A new program called Runway ML aims to make this process easier by providing artists, designers, filmmakers, and others with an ‘app store’ of machine learning applications that can be activated with a few clicks.”

The Next Web: This new photo AI lets you add, delete, and edit objects with one click

The Next Web: This new photo AI lets you add, delete, and edit objects with one click. “The new tool, GAN (Generative Adversarial Network) Paint Studio, lets you upload a picture and manipulate it without ruining its original details. For instance, if you add a tree or grass to the scene, related objects will be rectified so as to make the resulting image look realistic.” Limited, as you might expect, but fun to play with. An unexpected timesink.

TechSpot: Security researchers fake cancerous nodes in CT scans with machine learning

TechSpot: Security researchers fake cancerous nodes in CT scans with machine learning. “We expect that when we have a CT or MRI scan that the results are accurate. After all we are talking about equipment that can cost millions of dollars and radiologists with years of training and sometimes decades of experience. However, hospital security can be lax and researchers have now shown they can fake CT and MRI scans using a generative adversarial network (GAN).”