Episode
Oriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
1:46:07
Published: Mon Apr 29 2019
Description
Oriol Vinyals is a senior research scientist at Google DeepMind. Before that he was at Google Brain and Berkeley. His research has been cited over 39,000 times. He is one of the most brilliant and impactful minds in the field of deep learning. He is behind some of the biggest papers and ideas in AI, including sequence to sequence learning, audio generation, image captioning, neural machine translation, and reinforcement learning. He is a co-lead (with David Silver) of the AlphaStar project, creating an agent that defeated a top professional at the game of StarCraft. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations.
Chapters
A Starcraft player talks about the benefits of playing with the game's three races and how it can help you understand the nuances and strategies of each.
00:00 - 05:22 (05:22)
Summary
A Starcraft player talks about the benefits of playing with the game's three races and how it can help you understand the nuances and strategies of each. He compares the game to chess and emphasizes the importance of understanding the board/map.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The social aspect of early online games like StarCraft and World of Warcraft shaped the speaker in a profound way, opening up opportunities to interact with people from different backgrounds and cultures, and even leading to a serious passion for competitive play and attending tournaments.
05:22 - 12:42 (07:19)
Summary
The social aspect of early online games like StarCraft and World of Warcraft shaped the speaker in a profound way, opening up opportunities to interact with people from different backgrounds and cultures, and even leading to a serious passion for competitive play and attending tournaments.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The process of teaching AI to play StarCraft is far more complex than teaching it to play Go or Atari games due to the more complex nature of the game, requiring more time and dedication from the researchers involved.
12:43 - 17:43 (05:00)
Summary
The process of teaching AI to play StarCraft is far more complex than teaching it to play Go or Atari games due to the more complex nature of the game, requiring more time and dedication from the researchers involved.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The co-evolution of StarCraft and its players has created a unique opportunity for AI to learn and develop new strategies using the large dataset of replays available.
17:43 - 23:48 (06:05)
Summary
The co-evolution of StarCraft and its players has created a unique opportunity for AI to learn and develop new strategies using the large dataset of replays available. The absence of predefined rules and specializations create a challenging but exciting opportunity for AI to evolve the game beyond what was previously possible.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The structured object in gaming consisting of the list of units and their properties such as health, position, and type of unit is a natural way to encode the game.
23:48 - 30:39 (06:50)
Summary
The structured object in gaming consisting of the list of units and their properties such as health, position, and type of unit is a natural way to encode the game. However, this is not how humans perceive the game, but versions of the game that play well without this structured vision exist.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The speaker talks about how policy iteration approaches and reinforcement learning can be used in the context of StarCraft II.
30:39 - 38:37 (07:58)
Summary
The speaker talks about how policy iteration approaches and reinforcement learning can be used in the context of StarCraft II. They can train a policy of small trees, and then they will learn this policy iteration approach to resolve the problem of training a network that can play to a specific skill level.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
Even though AI agents developed for gaming are largely seen as playing human-like, the high actions per minute (APM) combined with precision have caused questions to be raised about whether the APM should be limited, with no clear set of rules currently available.
38:37 - 44:49 (06:11)
Summary
Even though AI agents developed for gaming are largely seen as playing human-like, the high actions per minute (APM) combined with precision have caused questions to be raised about whether the APM should be limited, with no clear set of rules currently available.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
In Stagrath, players use strategic gameplay involving guessing and reacting to their opponents' moves based on what units they choose to play.
44:49 - 51:01 (06:12)
Summary
In Stagrath, players use strategic gameplay involving guessing and reacting to their opponents' moves based on what units they choose to play. Professional players excel at all three races and there is never one race that dominates for long.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
While AlphaStar's performance has been impressive in the game of StarCraft 2, there is still much room for improvement due to the limitations of its prior distribution and lack of experience with certain strategies.
51:01 - 1:01:16 (10:15)
Summary
While AlphaStar's performance has been impressive in the game of StarCraft 2, there is still much room for improvement due to the limitations of its prior distribution and lack of experience with certain strategies.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
This podcast discusses how the machine learning approach is being used to advance technology through gaming, such as the recent capture the flag agents and deep learning in Atari games.
1:01:16 - 1:07:32 (06:15)
Summary
This podcast discusses how the machine learning approach is being used to advance technology through gaming, such as the recent capture the flag agents and deep learning in Atari games. The potential for human versus AI competitions is also explored.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The guest speaker feels that the current statistical approach to creating conversational AI will not be sufficient to pass the Turing test, and that we are still far away from creating a dialogue that can mimic human conversations.
1:07:32 - 1:12:56 (05:23)
Summary
The guest speaker feels that the current statistical approach to creating conversational AI will not be sufficient to pass the Turing test, and that we are still far away from creating a dialogue that can mimic human conversations.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The speaker discusses the benefits of combining rule-based systems with neural networks, specifically in the context of StarCraft, where expert systems and discrete decision-making can improve the performance of bots built with neural networks.
1:12:56 - 1:26:01 (13:04)
Summary
The speaker discusses the benefits of combining rule-based systems with neural networks, specifically in the context of StarCraft, where expert systems and discrete decision-making can improve the performance of bots built with neural networks. He also emphasizes the importance of sequence to sequence learning in allowing neural networks to learn a function that produces any output.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The process of feeding forward to success involves looking at future goals and working backwards instead of simply pursuing opportunities.
1:26:01 - 1:31:06 (05:05)
Summary
The process of feeding forward to success involves looking at future goals and working backwards instead of simply pursuing opportunities. It's important to give others the space to try their ideas, as they may turn out to be successful even if they are not initially perceived that way.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The path to achieving AGI may involve starting with limited domains and defining clear benchmarks for success.
1:31:06 - 1:44:04 (12:58)
Summary
The path to achieving AGI may involve starting with limited domains and defining clear benchmarks for success. Meta-learning could play a key role in allowing a network to solve new problems without the need to restart the learning process from scratch.
EpisodeOriol Vinyals: DeepMind AlphaStar, StarCraft, Language, and Sequences
PodcastLex Fridman Podcast
The speaker discusses how AI can manipulate players in games, citing examples such as forming belief states and tricking opponents into doing something else.
1:44:04 - 1:45:55 (01:50)
Summary
The speaker discusses how AI can manipulate players in games, citing examples such as forming belief states and tricking opponents into doing something else. They express interest in seeing more of this kind of reasoning in AI, which would demonstrate that the algorithm works for all races in the game, not just one.