š® Researchers developed an AI system called Deep Q-Network (DQN) to excel at Atari games.
š§ DQN outperformed human professionals in games like 'Pong' and 'Boxing'.
ā However, DQN struggled to play the game 'Montezuma's Revenge'.
š® Playing video games like Atari involves directed learning and a reward system based on points.
š¢ The goal of the game is to learn which buttons to press and when to press them to earn the most points.
š¤ Some systems use predictive models to anticipate future outcomes based on the current screen images.
š® Learning through trial and error is essential for improving at video games.
š¶ Babies' behavior of looking longer at unfamiliar images is used to teach AI systems.
š” Researchers have cleverly applied this preference to train AI to excel at a specific game.
The video discusses how babies approach video games and their different strategies.
Babies are curious and motivated to explore their surroundings in games.
The focus on rewards based on creativity can sometimes create more problems than solutions.
š® Artificial intelligence researchers are turning to human intelligence to find ideas on how to improve at video games.
š¤ AI provides new insights into the psychological aspects of gaming, including boredom, depression, addiction, curiosity, creativity, and play.
Nandan Nilekani on India's Techade | Antler ONDC Platform
Improve Your English: I didn't know what I was missing #learnenglishthroughstory #englishstory
How to build your creative confidence | David Kelley
Most Subscribed YouTube Channels 2005 - 2023
Top 20 Microsoft OneNote Tips and Tricks 2022 | How to use OneNote effectively & be more organized
How to clear Group Discussion if you dont know the topic