- Last updated August 28, 2024
- In AI News
New research from Google and Tel Aviv University allow real-time interaction with complex game environments
On 27th August 2024, Google released a paper detailing the capabilities of their new model GameNGen. This research was authored by Dani Valevski (Researcher at Google Research), Yaniv Leviathan (Engineer at Google Research), Moab Arar (PhD candidate at Tel Aviv University), and Shlomi Fruchter (Engineer at Google DeepMind).
GameNGen’s Capabilities
Powered entirely by a neural model, GameNGen is one of the pioneer search engines that allows high-quality, real-time interactions with complex environments over long periods. “GameNGen can interactively simulate the classic game DOOM at over 20 frames per second on a single TPU. Next frame prediction achieves a PSNR of 29.4, comparable to lossy JPEG compression”, per Google. The training occurs primarily in two phases: (1) an RL agent learns to play the game, with training sessions being recorded, and (2) a diffusion model …