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Chess


Reimagining Chess with AlphaZero

Communications of the ACM

Modern chess is the culmination of centuries of experience, as well as an evolutionary sequence of rule adjustments from its inception in the 6th century to the modern rules we know today.17 While classical chess still captivates the minds of millions of players worldwide, the game is anything but static. Many variants have been proposed and played over the years by enthusiasts and theorists.8,20 They continue the evolutionary cycle by altering the board, piece placement, or the rules--offering players "something subtle, sparkling, or amusing which cannot be done in ordinary chess."1 Technological progress is the new driver of the evolutionary cycle. Chess engines increase in strength, and players have access to millions of computer games and volumes of opening theory.


Artificial intelligence -- saviour or monster?

#artificialintelligence

The years 2020 and 2021 have already been eclipsed by Covid-19. As we enter 2022, the Omicron variant has risen, giving a sense of deja vu. The pandemic has, however, played a critical role in giving an accelerated impetus to use of technology in our lives. For instance, BlueDot, an artificial intelligence (AI) platform, was the first to flag an "unusual pneumonia" in Wuhan. AI has been enhancing our capabilities in ways never witnessed in the past.


Global Big Data Conference

#artificialintelligence

Artificial intelligence (AI) has had a profound impact on our society in recent years, but it's been around longer than you may realize. Many people attribute the beginning of AI to a paper written in 1950 by Alan Turing titled "Computer Machinery and Intelligence." The term artificial intelligence, however, was first coined in 1956 at a conference that took place at Dartmouth College in Hanover, New Hampshire. Since then, interest in AI has wavered. Its most recent resurgence can be attributed to IBM's Deep Blue chess-playing supercomputer and its question-answering machine Watson. Today, AI is part of our everyday lives – from facial recognition technology and ride-share apps to smart assistants.



AI can't steal your job if you work alongside it -- here's how

#artificialintelligence

Whether it's athletes on a sporting field or celebrities in the jungle, nothing holds our attention like the drama of vying for a single prize. And when it comes to the evolution of artificial intelligence (AI), some of the most captivating moments have also been delivered in nailbiting finishes. In 1997, IBM's Deep Blue chess computer was pitted against grandmaster and reigning world champion Garry Kasparov, having lost to him the previous year. But this time, the AI won. The popular Chinese game Go was next, in 2016, and again there was a collective intake of breath when Google's AI was victorious.


What's the Secret To Making Sure Artificial Intelligence Doesn't Steal Your Job?

#artificialintelligence

Whether it's athletes on a sporting field or celebrities in the jungle, nothing holds our attention like the drama of vying for a single prize. And when it comes to the evolution of artificial intelligence (AI), some of the most captivating moments have also been delivered in nailbiting finishes. In 1997, IBM's Deep Blue chess computer was pitted against grandmaster and reigning world champion Garry Kasparov, having lost to him the previous year. But this time, the AI won. The popular Chinese game Go was next, in 2016, and again there was a collective intake of breath when Google's AI was victorious.


When AI Fails, the Results Are Sometimes Amusing. Sometimes Not.

#artificialintelligence

Even if artificial general intelligence (AGI) could be achieved, a problem looms: The more complex a system is, the more can go wrong. If a computer could really match human thinking, a great deal could go wrong. In "When AI goes wrong" (podcast 160), Walter Bradley Center director Robert J. Marks is joined once again by members of his research group, Justin Bui and Samuel Haug, who is a PhD student in computer and electrical engineering. The topic is, what happens if AI starts behaving in bizarre and unpredictable ways? A partial transcript and notes, Show Notes, and Additional Resources follow. I want to start out with Paul Harvey's The Rest of the Story. Either Sam or Justin, have you ever heard of Paul Harvey? Justin Bui: I have not. Sam Haug: No, I have not.


Using artificial intelligence to advance energy technologies

#artificialintelligence

Hongliang Xin, an associate professor of chemical engineering in the College of Engineering, and his collaborators have devised a new artificial intelligence framework that can accelerate discovery of materials for important technologies, such as fuel cells and carbon capture devices. Titled "Infusing theory into deep learning for interpretable reactivity prediction," their paper in the journal Nature Communications details a new approach called TinNet--short for theory-infused neural network--that combines machine-learning algorithms and theories for identifying new catalysts. Catalysts are materials that trigger or speed up chemical reactions. TinNet is based on deep learning, also known as a subfield of machine learning, which uses algorithms to mimic how human brains work. The 1996 victory of IBM's Deep Blue computer over world chess champion Garry Kasparov was one of the first advances in machine learning.


Artificial intelligence to advance energy technologies

#artificialintelligence

Hongliang Xin, an associate professor of chemical engineering in the College of Engineering, and his collaborators have devised a new artificial intelligence framework that can accelerate discovery of materials for important technologies, such as fuel cells and carbon capture devices. Titled "Infusing theory into deep learning for interpretable reactivity prediction," their paper in the journal Nature Communications details a new approach called TinNet -- short for theory-infused neural network -- that combines machine-learning algorithms and theories for identifying new catalysts. Catalysts are materials that trigger or speed up chemical reactions. TinNet is based on deep learning, also known as a subfield of machine learning, which uses algorithms to mimic how human brains work. The 1996 victory of IBM's Deep Blue computer over world chess champion Garry Kasparov was one of the first advances in machine learning.


What's the secret to making sure AI doesn't steal your job? Work with it, not against it

#artificialintelligence

Whether it's athletes on a sporting field or celebrities in the jungle, nothing holds our attention like the drama of vying for a single prize. And when it comes to the evolution of artificial intelligence (AI), some of the most captivating moments have also been delivered in nailbiting finishes. In 1997, IBM's Deep Blue chess computer was pitted against grandmaster and reigning world champion Garry Kasparov, having lost to him the previous year. But this time, the AI won. The popular Chinese game Go was next, in 2016, and again there was a collective intake of breath when Google's AI was victorious.