Futurism: A New AI Draws Cats, and They’re Utterly Grotesque

Okay, I promise I will calm down about these. But this one uses AI to generate CAT PICTURES. Seriously, how can I not? Futurism: A New AI Draws Cats, and They’re Utterly Grotesque. “GANs have been used for much more ambitious projects in the past. Researchers at NVIDIA harnessed the power of the technology to create uncanny faces that are almost completely indistinguishable from the real thing. But that doesn’t mean bored people on the internet shouldn’t be able to take advantage of the open-source technology for a bit of fun — that is, as long as real-world cats stay out of harm’s way.” I tested this. A fraction of the cats look something like real cats. The other ones look like the dreams you have after a meal of spicy meatballs and eggnog.

Futurism: This Site Uses Deep Learning to Generate Fake Airbnb Listings

I’m not sure how useful this is, but it’s fascinating. Futurism: This Site Uses Deep Learning to Generate Fake Airbnb Listings. “A new website called This Airbnb Does Not Exist uses machine learning to whip up plausible-yet-slightly-incoherent apartment listings — from a description to ersatz photos of the interior. The site’s creator, Christopher Schmidt, was inspired by This Person Does Not Exist, another recent viral site that uses a neural network to generate photos of nonexistent people. Schmidt trained This Airbnb Does Not Exist’s image generator using a dataset of apartment interiors and its text generator using actual Airbnb listings. The result: fully furnished figments of the digital imagination.” Also gloriously weird.

Cornell Chronicle: Study uses neural networks to define Dada

Cornell Chronicle: Study uses neural networks to define Dada. “To make a Dadaist poem, artist Tristan Tzara once said, cut out each word of a newspaper article. Put the words into a bag and shake. Remove the words from the bag one at a time, and write them down in that order. This ‘bag of words’ method is not entirely different from how artificial intelligence algorithms identify words and images, breaking them down into components one step at a time. The similarity inspired Cornell researchers to explore whether an algorithm could be trained to differentiate digitized Dadaist journals from non-Dada avant-garde journals – a formidable task, given that many consider Dada inherently undefinable.”

Wired: Neural Networks Need a Cookbook. Here Are the Ingredients

Wired: Neural Networks Need a Cookbook. Here Are the Ingredients. “WHEN WE DESIGN a skyscraper we expect it will perform to specification: that the tower will support so much weight and be able to withstand an earthquake of a certain strength. But with one of the most important technologies of the modern world, we’re effectively building blind. We play with different designs, tinker with different setups, but until we take it out for a test run, we don’t really know what it can do or where it will fail.”

Factor Daily: Data is India’s handicap in AI but help is at hand

Factor Daily: Data is India’s handicap in AI but help is at hand. “The global race in artificial intelligence is like the space race of the 20th century with large powers vying for the pole position. China currently leads the pack with countries such as the US and Israel trailing behind. India too has big ambitions in this race. The government announced last week that it plans to set up a National Centre for Artificial Intelligence to help citizens benefit from AI and related technologies.”

Fast Company: Can you tell the difference between Rembrandt and an algorithm?

Fast Company: Can you tell the difference between Rembrandt and an algorithm?. “Very few artists in the history of the world were able to capture people’s nature with the precision, humanity, and humor of Dutch masters like Rembrandt or Hals. Could a machine ever be trained to do the same? That’s the premise of Sergio Albiac’s series, You have learnt nothing. Like the work that came out of the golden age of Dutch painting, these paintings may look like the product of oil, brushes, and fingers. But, like the rest of Albiac’s work, these portraits are actually the result of the artist’s computer code.”

MIT Technology Review: We analyzed 16,625 papers to figure out where AI is headed next

MIT Technology Review: We analyzed 16,625 papers to figure out where AI is headed next. “…though deep learning has singlehandedly thrust AI into the public eye, it represents just a small blip in the history of humanity’s quest to replicate our own intelligence. It’s been at the forefront of that effort for less than 10 years. When you zoom out on the whole history of the field, it’s easy to realize that it could soon be on its way out.”