Voice clones — the audio counterpart to deepfaked images — are poised to invade popular media and entertainment. Professionals and amateurs alike are using AI to emulate the voices of human actors, Wired reported.

According to the lottery ticket hypothesis, the bigger the neural network, the more likely some of its weights are initialized to values that are well suited to learning to perform the task at hand. But just how big does it need to be?

A new multimedia experience lets audience members help artificially intelligent creatures work together to survive. Agence, an interactive virtual reality (VR) project blends audience participation with reinforcement learning to create an experience that’s half film, half video game.

AI has humbled human chess masters. Now it’s helping them take the game to the next level. DeepMind and retired chess champion Vladimir Kramnik trained AlphaZero, a reinforcement learning model that bested human experts in chess, Go, and Shogi, to play-test changes in the rules.

How do you control a video game that generates a host of unique monsters for every match? With machine learning, naturally. The otherworldly creatures in Source of Madness learn how to target players through reinforcement learning.

Reinforcement learning can beat humans at video games, but humans are better at coming up with strategies to master more complex tasks. New work enables neural networks to connect the dots.

Generative adversarial networks don’t just produce pretty pictures. They can build world models, too. A GAN generated a fully functional replica of the classic video game Pac-Man.

AI is contributing to paintings, music, and now a whimsical fantasy video. The Squire is an amateur romp through a snowy realm of knights in armor and damsels in distress. The script was composed by AI Dungeon 2, an interactive text-adventure game based on the GPT-2 language model.

AlphaGo Zero demonstrates superhuman performance playing Go, chess, and shogi. Models like R2D2 do the same playing classic Atari titles. A new approach to deep reinforcement learning is the first to achieve state-of-the-art results playing both board and video games.

In reinforcement learning, if researchers want an agent to have an internal representation of its environment, they’ll build and train a world model that it can refer to. New research shows that world models can emerge from standard training, rather than needing to be built separately.

Is there any reason to continue playing games that AI has mastered? Ask the former champions who have been toppled by machines.

Sony, the consumer-electronics powerhouse behind the PlayStation and other hit gadgets, is launching three research-and-design centers to focus on AI. Staffing up means competing with — and likely poaching talent from — frontrunners like Google, Facebook, and Microsoft.

Neuroevolution, which combines neural networks with ideas drawn from Darwin, is gaining momentum. Its advocates claim that they can achieve faster, better results by generating a succession of new models, each slightly different than its predecessors, rather than relying on a purpose-built model.

At the BlizzCon gaming convention last weekend, players of the strategy game StarCraft II stood in line to get walloped by DeepMind’s AI. After training for the better part of a year, the bot has become one of the world’s top players.

OpenAI trained a five-fingered robotic hand to unscramble the Rubik’s Cube puzzle, bringing both acclaim and criticism. The AI research lab OpenAI trained a mechanical hand to balance, twist, and turn the cube.