Greg Brockman · Aug 6, 2018
Greg Brockman introduces OpenAI Five as a system trained through self-play
Markdown · JSON · Original source
Greg Brockman published this introduction on August 6, 2018. In a speech at a Benchmark event, Brockman described OpenAI Five, an AI system trained to play Dota, and presented the game as a training ground for teamwork, real time strategy and imperfect information. Brockman said Five learns by playing against itself and uses artificial neural networks. He argued that the same technology used for Dota could also learn tasks it was not designed for, citing control of a robotic hand as an example. He also said the computing power used for OpenAI Five would have been impractical two years earlier, and forecast that technologies like it would become commonplace. The speech connects progress in game-playing systems to questions about how AI might be applied beyond games, while offering no evidence here about the system’s performance outside its described tasks. Brockman’s claims about training scale, computing trends and future availability are his account and forecast, not independently established by this text. What results would show whether the approach transfers from Dota to tasks outside games?
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
Greg Brockman · Article
Source details
Original source date: Aug 6, 2018 (2018-08-06).
Date basis: Date stated on the publisher’s page.
Added to Escape Meridian: 2026-10-29T00:33:04.175Z. First observed: 2026-10-20T22:41:29.684Z. Retrieved: 2026-10-27T15:49:38.385Z.
Referenced by
Recorded citations and public file attachments. A reference alone does not establish agreement or influence.
No public references recorded here yet.
Limits
The text gives Brockman’s account of OpenAI Five and does not provide independent measurements of its training, performance or computing use. The robotic-hand example is asserted in the speech without details of the task or results. Text as retrieved on 2026-10-27; originally published 2018-08-06.
Open question
What results would show whether the approach transfers from Dota to tasks outside games?
Source-stated
Greg Brockman’s page dates the speech introduction to August 6, 2018.
August 6, 2018 OpenAI Five intro
Source-stated
Brockman described OpenAI Five as learning through self-play and using artificial neural networks.
Five learns by playing 180 years of games against itself every day — sadly that means we can’t learn from the players up here unless they played for a few decades. It’s powered by 5 artificial neural networks
Source-stated
Brockman cited robotic-hand control as an example of the system learning a task it was not designed to solve.
we just used the same technology to learn to control a robotic hand — something no one could program.
Source-stated
Brockman said the computing power for OpenAI Five would have been impractical two years earlier and forecast that technologies like it would become commonplace.
The computational power for OpenAI Five would have been impractical two years ago. But the availability of computation for AI has been increasing exponentially, doubling every 3.5 months since 2012, and one day technologies like this will become commonplace.
Source and contributor context
Greg Brockman · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Benchmark
A defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Neural network
A system of connected simple calculations, loosely inspired by the brain, that learns patterns from data.
Greg Brockman
Greg Brockman publishes personal essays about engineering, AI research and organizational work.
OpenAI
OpenAI develops AI models and products and publishes research, release announcements and evaluations.
Editorial provenance
Version 1. Publication ID: 3a08fbeb-8a69-c32c-0994-a09d6130c1c1.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T00:30:58.838Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model.
Observation: 6012391a2dafb6e06fdd8117f1abf824f7136518dd5c67c8f92301122c3ea559. Source text hash: b45fe785b0bcea99fc9e7e8f0d7593df99143b2fc9e17f41ea464acb8382d7ea.
Revision and source-check history
Version 1 · 2026-10-29T00:33:04.175Z
Greg Brockman introduces OpenAI Five as a system trained through self-play
Greg Brockman published this introduction on August 6, 2018. In a speech at a Benchmark event, Brockman described OpenAI Five, an AI system trained to play Dota, and presented the game as a training ground for teamwork, real time strategy and imperfect information. Brockman said Five learns by playing against itself and uses artificial neural networks. He argued that the same technology used for Dota could also learn tasks it was not designed for, citing control of a robotic hand as an example. He also said the computing power used for OpenAI Five would have been impractical two years earlier, and forecast that technologies like it would become commonplace. The speech connects progress in game-playing systems to questions about how AI might be applied beyond games, while offering no evidence here about the system’s performance outside its described tasks. Brockman’s claims about training scale, computing trends and future availability are his account and forecast, not independently established by this text. What results would show whether the approach transfers from Dota to tasks outside games?
Original source
Greg Brockman · Article
Source details
Original source date: Aug 6, 2018 (2018-08-06).
Date basis: Date stated on the publisher’s page.
Added to Escape Meridian: 2026-10-29T00:33:04.175Z. First observed: 2026-10-20T22:41:29.684Z. Retrieved: 2026-10-27T15:49:38.385Z.
Limits
The text gives Brockman’s account of OpenAI Five and does not provide independent measurements of its training, performance or computing use. The robotic-hand example is asserted in the speech without details of the task or results. Text as retrieved on 2026-10-27; originally published 2018-08-06.
Open question
What results would show whether the approach transfers from Dota to tasks outside games?
Source-stated
Greg Brockman’s page dates the speech introduction to August 6, 2018.
August 6, 2018 OpenAI Five intro
Source-stated
Brockman described OpenAI Five as learning through self-play and using artificial neural networks.
Five learns by playing 180 years of games against itself every day — sadly that means we can’t learn from the players up here unless they played for a few decades. It’s powered by 5 artificial neural networks
Source-stated
Brockman cited robotic-hand control as an example of the system learning a task it was not designed to solve.
we just used the same technology to learn to control a robotic hand — something no one could program.
Source-stated
Brockman said the computing power for OpenAI Five would have been impractical two years earlier and forecast that technologies like it would become commonplace.
The computational power for OpenAI Five would have been impractical two years ago. But the availability of computation for AI has been increasing exponentially, doubling every 3.5 months since 2012, and one day technologies like this will become commonplace.
Source and contributor context
Greg Brockman · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Benchmark
A defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Neural network
A system of connected simple calculations, loosely inspired by the brain, that learns patterns from data.
Greg Brockman
Greg Brockman publishes personal essays about engineering, AI research and organizational work.
OpenAI
OpenAI develops AI models and products and publishes research, release announcements and evaluations.
Editorial provenance
Version 1. Publication ID: 3a08fbeb-8a69-c32c-0994-a09d6130c1c1.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T00:30:58.838Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model.
Observation: 6012391a2dafb6e06fdd8117f1abf824f7136518dd5c67c8f92301122c3ea559. Source text hash: b45fe785b0bcea99fc9e7e8f0d7593df99143b2fc9e17f41ea464acb8382d7ea.
passed · 2026-10-29T00:30:58.838Z · anthropic/claude-opus-5.5
Publication: 3a08fbeb-8a69-c32c-0994-a09d6130c1c1
attribution — pass: The page is Greg Brockman's blog post, in which he presents the text of his own speech introducing OpenAI Five. The reading attributes the statements to Brockman throughout, consistent with the source.
The text of my speech introducing OpenAI Five at yesterday’s Benchmark event
summary — pass: The title, summary and question match the source. OpenAI Five is identified as an AI system that plays the game Dota, and self-play is explained in plain language. Training conditions, transfer to the robotic hand and the computing forecast are presented as Brockman's account. The question about transfer beyond games follows from the evidence and does not assume an answer. The reading never states Brockman's OpenAI affiliation, but this is not essential to understanding the piece.
We work on Dota because it is a great training ground for AI
date — pass: evidence.originalPublished is 2018-08-06 at day precision. This matches the page dateline and the reading's date. The speech itself took place the day before ('yesterday'), and the reading does not misstate this because it dates only the publication. There is no hindsight framing, and the commonplace-technology forecast is attributed as Brockman's forecast. The evidence kind is publisher-page, so no archive disclosure is needed.
August 6, 2018 OpenAI Five intro
support — pass: Each claim is supported by a verbatim excerpt: self-play and neural networks, the robotic hand example, and the statement that computing power would have been impractical two years earlier, along with the forecast. The reading explicitly notes that this text does not independently establish these claims or show performance outside the described tasks. It does not imply unsupported benefits or costs.
But our AI system can learn problems it was not even designed to solve
media — pass: No media was selected, and no verified media candidates were supplied. Leaving media empty is appropriate.
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