AI Program Running on an XSEDE Resource Overcomes Multiple Human Poker Champions

September 9, 2019

September 9, 2019 — Artificial intelligence (AI) research took a great leap forward when a Carnegie Mellon University computer program overcame the world’s best professional players in a series of six-player poker games. Experimenting with multi-player, “incomplete information” games offers more useful lessons for real-world problems such as security, business negotiations and cancer therapy than one-on-one, “complete information” games like chess or go. Running on the XSEDE-allocated Bridges system at the Pittsburgh Supercomputing Center, the Pluribus AI was the first to surpass humanity’s best at such a game.

Why It’s Important

It’s obvious, but it bears repeating: Life is not chess. In real-world problems, the pieces are not lined up neatly for all to see. Terrorists have secret plans. Businesspeople have undisclosed deal-breakers and hidden needs that can torpedo negotiations. Cancer cells evade the body and drug treatments by mutating their genes.

Poker may not be a perfect representation of these problems, but it’s a lot closer. Players keep their hands secret, and try to bluff and shift their strategies to keep opponents off-balance. In 2017, Carnegie Mellon’s School of Computer Science grad student Noam Brown and his faculty advisor Tuomas Sandholm broke through the barrier of such imperfect-information games. That’s when their artificial intelligence (AI) program, called Libratus, surpassed four of the world’s best humans in heads-up (two-player), no-limit Texas Hold’em poker, running on the XSEDE-allocated Bridges at the Pittsburgh Supercomputing Center. That victory had been the first in which an AI overcame top players in an incomplete-information game.

“Being unpredictable is a huge part of playing poker … you have to be unpredictable; you have to bluff. If you don’t have a strong hand you have to check; if you do have a strong hand you can’t tip off the other players. Humans are good at that; Pluribus is very good at that.”—Noam Brown, Facebook AI Research and Carnegie Mellon University.

One limitation of the earlier work was that the AI had only faced humans one-on-one. This is a far simpler game than the usual, multi-player poker game, in which a player has to change how to play a given combination of cards from hand to hand to deal with the shifting plays produced by multiple opponents’ strategies. At the time of Libratus’s victory, many experts felt that the multi-player game problem might not be winnable in the foreseeable future. Still, Brown (now at Facebook AI Research) and Sandholm felt it was worth a try. They essentially started over with their new project—but still used the power of Bridges to develop and run the new AI.

How XSEDE Helped

The transition from head-to-head to multi-player poker required a stronger AI approach than the researchers had used with Libratus. Like the earlier AI, Pluribus taught itself to play Texas Hold’em poker before facing the pros. Like Libratus, Pluribus also discovered strategies that humans do not normally employ. But Pluribus played and learned in a fundamentally different way than its predecessor.

Libratus had been designed to think through the entire remaining game when deciding each move. The Carnegie Mellon team realized that such a strategy would never work in multi-player poker because the game size would grow exponentially as the number of players increases. This was one reason why some experts thought the problem might not be solvable.

“You have to understand that opponents can adapt. If you only employ one strategy, you might be exploitable. In rock, paper, scissors, if we assume the other player is responding randomly, if you always throw rock you always break even. But when the other player adapts to always throwing paper, that strategy fails. Understanding that players can switch strategies is a big part of the game.”—Noam Brown, Facebook AI Research and Carnegie Mellon University.

The researchers took the good-enough strategy one step further. Would it be possible to stay ahead of multiple opponents if the AI only planned a few steps ahead, rather than to the end of the game? Such a “limited look-ahead” approach would save computing power to react to and overcome each opponent’s moves.

Pluribus compiled the data and trained itself running on one of Bridges’ large-memory nodes, each of which feature 3 terabytes of RAM—about 100 times that in a high-end laptop, and 20 times what is considered large memory on most supercomputers. Play took place on one of Bridges’ regular-memory nodes. Bridges also helped the Carnegie Mellon team by offering massive data storage.

“Many thought the multi-player game was not possible to win [by an AI]; others thought it would be too computationally expensive. I don’t think anybody thought it would be that cheap.”—Noam Brown, Facebook AI Research and Carnegie Mellon University.

While Pluribus used more power than available on commodity personal computers, its performance represented a huge savings in computing time over Libratus. The earlier AI used around 15 million core hours over two months to develop its strategies and 50 of Bridges’ powerful compute nodes to play. By comparison, Pluribus trained itself in eight days using 12,400 core hours and used just one node during live play. This promises that such AIs may be able to run on commodity computers in the not-too-distant future.

Pluribus used its limited-lookahead strategy in an online tournament from June 1 to 12, 2019, against a total of 13 poker champions, each of whom had won over $1 million in his poker career. The culmination of the Facebook-funded tournament was a series of 10,000 hands against five of the pros at once. Pluribus racked up a literally super-human win rate. The human players reported that the AI’s strategy was impossible to predict and it often made plays that experienced humans never do—probably because doing so successfully is too complicated for the human brain.


Source: Ken Chiacchia, Pittsburgh Supercomputing Center and the Extreme Science and Engineering Discovery Environment (XSEDE)

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire