Artificial Intelligence has now beaten eight world champions at bridge
A.I. keeps beating our best people in games.
My grandmother loved the game of bridge. I remember it fondly. It was a great way for her to socialize and keep her brain fit.
A.I. Has been Training on Games for Decades
The history of A.I. beating humans at their favorite games is truly an incredible story that tracks the development of certain aspects of artificial intelligence as they have grown in time. The intervals between those “wins” is also speeding up. What does that suggest?
It was not actually so long ago when on May 11, 1997, an IBM computer called IBM ® Deep Blue ® beat the world chess champion after a six-game match: two wins for IBM, one for the champion and three draws. The match lasted several days and received massive media coverage around the world.
Chess masters versus computers is the age-old battle. From the 1980’s, computers were able to start to beat good chess players. In 2017, A.I. built the Go champion at the time. It took twenty years for A.I. to get good at Go vs. at chess. How much longer before A.I. gets good at sports bet picking or other related games and video games?
Back in 2017, it was big publicity for DeepMind. Google's DeepMind AlphaGo artificial intelligence defeated the world's number one Go player, Ke Jie, in what felt like a real advancement. AlphaGo secured the victory after winning the second game in a three-part match. DeepMind founder Demis Hassabis said Ke Jie had played "perfectly" and "pushed AlphaGo right to the limit".
Just five years later, nothing much pushes A.I. to the limit in games, from poker to video games to now bridge.
A.I. Wins in Bridge
The story goes that this victory marks a milestone for AI as bridge (apparently) requires more human skills than other strategy games. Let’s take a deep dive into this.
What is Nook A.I.
An artificial intelligence has beaten eight world champions at bridge, a game in which human supremacy has resisted the march of the machines until now.
The victory represents a new milestone for AI because in bridge players work with incomplete information and must react to the behavior of several other players – a scenario far closer to human decision-making.
In contrast, chess and Go – in both of which AIs have already beaten human champions – a player has a single opponent at a time and both are in possession of all the information. Just in 2017, it was said that bridge was too “cerebral” a game for A.I. to conquer. Well, that sentiment didn’t last. A.I. advances are relentless, it does not take a break in how it is evolving.
The French Startup that Did It
French startup NukkAI announced the news of its AI’s victory on Friday, at the end of a two-day tournament in Paris.
“What we’ve seen represents a fundamentally important advance in the state of artificial intelligence systems,” said Stephen Muggleton, a professor of machine learning at Imperial College London.
The NukkAI Challenge
The NukkAI challenge required the human champions to play 800 consecutive deals divided into 80 sets of 10. It did not involve the initial bidding component of the game during which players arrive at a contract that they must then meet by playing their cards.
Each champion played their own and their “dummy” partner’s cards against a pair of opponents. These opponents were the best robot champions in the world to date – robots that have won many robot competitions but that are universally acknowledged to be nowhere near as good as expert human players.
Why This is Enormous for A.I. - Bridge Depends on Partner Communication
The AI – called NooK – played the same role as the human champion, with the same cards and the same opponents. The score was the difference between those of the human and the AI, averaged over each set. NooK won 67, or 83%, of the 80 sets.
Jean-Baptiste Fantun, co-founder of NukkAI, said he had been confident the machine – which the company has been developing for five years – would triumph in thousands of deals, but with only 800 it was touch and go.
Announcing the results, the mathematician Cédric Villani, winner of the Fields medal in 2010, called NukkAI “a superb French success story”.
AI researcher Véronique Ventos, NukkAI’s other co-founder, calls NooK a “new generation AI” because it explains its decisions as it goes along. “In bridge, you can’t play if you don’t explain,” she says. The game relies on communication between partners.
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Black Box White Box
Explicability is a hot topic in AI. “Most of what the general public have heard in recent years about machine learning is based on black box systems such as AlphaGo, which is unable to explain to human beings how decisions are being made,” said Muggleton.
Instead, NooK represents a “white box” or “neurosymbolic” approach. Rather than learning by playing billions of rounds of a game, it first learns the game’s rules and then improves its play through practice. It is a hybrid of rules-based and deep learning systems. “The NooK approach learns in a way that is much closer to human beings,” Muggleton said.
A.I. Needs to Be Explainable to be Accountable
“The pendulum is swinging towards these kinds of methods,” says Michael Littman, a professor of computer science at Brown University in Rhode Island. “Not being able to tell people what’s going on just doesn’t work in our societies.”
Even if a person or an AI can’t explain in words what they are doing, Littman says, their behaviour needs to be “legible” to others – enacting rules they understand.
This will be critical in domains such as health and engineering. Self-driving cars negotiating a junction will need to be able to read each other’s behaviour, for example.
Limits of the Rules of the Game
Littman was disappointed the challenge didn’t include bidding, which is where much of the most interesting communication – and deception – happens in bridge.
But Nevena Senior, a many-times world bridge champion for England and one of NooK’s challengers, said the contracts the humans and NooK were given to play were sufficiently variable that the card game became as important as the bidding.
She said NooK’s creators had done a “magnificent” job. She found that it read its opponents better than the humans did, and was better able to exploit their mistakes.
“This is something that humans do after enough experience and I was pleasantly surprised that a robot mimics typical human skills,” she said.
I liked reading about the PR of this startup in a very difficult game. This isn’t DeepMind, OpenAI or some such typical AI firm.
This is not a sponsored article, I’m genuinely surprised, I have never heard of this AI startup from France before.
Today I notice they are being covered by some outlets in the U.K, but I couldn’t yet find coverage in the U.S. tech news. Why is that?
Do you know someone who might enjoy this Newsletter?
Why I like NukkAI in their Approach
I also like how NukkAI takes a very distinct approach to AI ethics, talking about the importance of AI explainability. This suggests European AI startups might be more accountable who are not yet under the control of giants like Google or Microsoft, in reference to DeepMind and OpenAI respectively.
So NukkAI takes a very different approach to adding value to businesses. NuX has already been customized for different domains: Aeronautics, Education, Cybersecurity, Defense, etc.
As NuX improves performance while responding to responsibility and transparency issues, this generic tool has potential in virtually all business verticals.
Transparency issues, with a focus on Explicability
ESG relevance (corporate accountability)
Why Bridge ?
Bridge is the game that has most similarities with real life: the information is incomplete, there are partners and opponents and the rules impose some explicability. It is the ideal testbed for the AIs we are building.
In March 2022 NukkAI will try a major breakthrough by winning a challenge against 8 world champions.
Why should AI be explainable?
One of the biggest challenges of AI is building trustworthy AI-powered systems. Humans and corporations are increasingly uncomfortable with “black box” AI algorithms that offer no insight into how decisions were reached. Our goal is to bring transparency to the models, facilitate compliance, improve model performance and reduce ethical bias.
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According to the Guardian, some of the most important A.I. breakthroughs in games include:
Other AI triumphs
1996: IBM’s Deep Blue chess machine wins a game against world chess champion Garry Kasparov but loses the match 2-4. A year later, Kasparov loses the rematch.
2007: Checkers is solved by researchers at the University of Alberta in Canada. After sifting through 500bn positions, they build a checkers-playing computer programme that can’t be beaten.
2011: IBM’s Watson computer defeats TV gameshow Jeopardy! champions Brad Rutter and Ken Jennings, claiming the $1m first prize.
2016: Google DeepMind’s AlphaGo defeats Korean Go champion Lee Sedol 4-1. The Korean Baduk Association awards AlphaGo the highest Go grandmaster rank, an honorary 9 dan.
2022: NukkAI’s bridge-playing computer NooK defeats eight world bridge champions in Paris.
Since AI’s win against the best humans in Chess, it has gone on to beat us in countless video games, Checkers, Backgammon, Poker and now Bridge. I’m sure there are many others.
Now putting A.I. to use in building digital twin worlds, synthetic AI simulations are helping us solve real-world problems and the way we think of A.I. learning independently in self-supervised-learning (SSL) is changing how we see its own trajectory in shaping our future world, some of which we call the Metaverse.
What is the Takeaway?
French startup NukkAI spent four years developing the AI bot, called NooK
It was trained using a hybrid approach, being taught the rules before practicing
During a two-day challenge in Paris, it won 83% of 80 sets against 8 champions
We need A.I. that’s ethical, explainable and can be transparently accountable in all settings including the military, healthcare and more sensitive fields like drug development and the National Defense sector.
The U.S. today decided to send 100 killer drones called switchblades to the Ukraine. Last year in 2021, the U.S. said A.I. will always be in human control. This year in 2022, the military wants A.I. to replace humans in decision-making in battle according to the Washington Post. Is this policy change concerning the future of A.I. explainable or transparent?
A nice game in Paris.
What Are the Future Games that A.I. Will Master?
When war might just be another game for an A.I., who is held responsible and accountable. If A.I. is good at games, will it run and develop companies by itself? Will it learn to game the human system of money, politics and power games? It really begs a lot of questions. We as a world clearly don’t have rules for A.I. in place that would protect us from how good it’s getting at everything.
A.I. is getting faster and smarter at visual recognition. Bill Gates famously described bridge as 'one of the last games in which the computer is not better'. You are wrong, Bill. A.I. could lead companies better than humans could by 2045. What will happen to Capitalism by then? How will the world adapt to A.I. that learn to do everything better than people can do them? I don’t think Bill Gates or Elon Musk have the answers, they are just playing along.
French startup NukkAI spent four years developing the AI bot, called NooK, which took home the crown at the two-day Nukkai Challenge in Paris last week in March, 2022.
Soon we won’t be able to keep up with what A.I. is capable of doing.
Chris O'Brien @obrienAt a Bridge tournament organized by @nukkailab1. 8 international champions are playing against Nukka's AI engine. The Paris startup has been using Bridge for several years to train its algorithms. https://t.co/bScBEX42aQ
How do you regulate a world in which A.I. is capable of disrupting nearly every task humans accomplish for work, maintenance and in the community? And what human goals and games will smarter machines help us play in a non-level playing field?
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