Inside the world of AI that forges beautiful art and terrifying deepfakes

Most AI advances and applications are based on a type of algorithm known as machine learning that finds and reapplies patterns in data.

Deep learning, a powerful subset of machine learning, uses neural networks to find and amplify even the smallest patterns.

Neural networks are layers of simple computational nodes that work together to analyze data, kind of like neurons in the human brain.

Using one neural network is really great for learning patterns; using two is really great for creating them.

Welcome to the magical, terrifying world of generative adversarial networks, or GANs.

Their secret lies in the way two neural networks work together-or rather, against each other.

The first network, known as the generator, must produce artificial outputs, like handwriting, videos, or voices, by looking at the training examples and trying to mimic them.

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This beautiful map shows everything that powers an Amazon Echo, from data mines to lakes of lithium

Explaining how these systems join and the effect they’ve on the arena is not an easy task.

The major artwork is a huge map, two meters high and five meters across, which traces the structures used to electricity one of the maximum complex merchandise of the cutting-edge day: an AI-powered gadget, in particular, an Amazon Echo.

The print is known as Anatomy of an AI device, but its subtitle explains its scope: “The Amazon Echo as an anatomical map of human exertions, records and planetary sources.”

The Echo sits in your home, appears quite simple and small, however has those massive roots that hook up with big structures of manufacturing: logistics, mining, facts capture, and the education of AI networks.

First, it’s running at a level which begins to alternate the manner society itself works, due to the fact AI systems are being constructed into the establishments that are most crucial to us, from fitness care to crook justice.

Anatomy itself is split into three vast systems, each of that you seek advice from as an “Extractive process.” There’s an extractive manner for material assets, one for statistics, and one for human exertions.

These forms of inequality repeat at some stage in industrial history, and are not specific to AI. But massive-scale AI systems require so much statistics, infrastructure and preservation that there are very few agencies who are able to build and perform them.

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This AI app wants to make beautiful music with you

If you wander through this world with a song in your heart and a tune on the tip of your tongue, Amadeus Code might be able to help you turn it into beautiful music.

After being in a limited beta run, Amadeus Code has just opened up to the public, ready to turn would-be artists into hit-making musicians.

How it works: Amadeus Code’s AI churns through music libraries, breaking down music into tiny units and looking for patterns.

When a songwriter uses the app, the AI can then pull up those patterns and suggest new notes, slowly building the composer’s melodies into music.

“AI has this peculiar ability to find novel solutions-some successful, some not so much,” says Amadeus Code co-founder Taishi Fukuyama in a statement.

The latest version of the app comes with a new feature-the Harmony Library, which lets users search for inspiration in Spotify’s library, specifically its chord progressions.

It’s not copying per se, but instead falls into the age-old musical tradition of creating a new song inspired by someone else’s work, like how Lana Del Rey was inspired by Radiohead. Fukuyama hopes that songwriters won’t let the app do their work for them, though: “We hope that users will complete the work started by Amadeus Code by telling their own unique stories, which will continue to be what makes music truly irreplaceable by artificial intelligence.”

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