chess


Man Vs. Machine: The 6 Greatest AI Challenges To Showcase The Power Of Artificial Intelligence

#artificialintelligence

As artificial intelligence (AI) research and development continues to strengthen, there have been some incredibly intriguing projects where machines battled man in tasks that were once thought the realm of humans. While not all were 100% successful, AI researchers and technology companies learned a lot about how to continue forward momentum as well as what a future might look like when machines and humans work alongside one another. Here are some of the highlights from when artificial intelligence battled humans. World Champion chess player Garry Kasparov competed against artificial intelligence twice. In the first chess match-up between machine (IBM Deep Blue) and man (Kasparov) in 1996 Kasparov won.


First, Second and Third Wave AI: Is It Possible to Build an AI That Thinks Like a Human? By Aubrey Hansen - Irish Tech News

#artificialintelligence

Bill Gates says that the company that cracks the Third Wave of AI will be worth 10 Microsofts. But what is this'Third Wave', anyway? AI isn't as newfangled as we'd like to think, and over the years upgrades in existing hardware and techniques have periodically energized interest and development in the field, similar to the jumps in VR technology. Our progress in the AI field is significantly greater than where it was even just ten years ago. When we talk about'waves', we're talking about these jumps.


Bet On The Bot: AI Beats The Professionals At 6-Player Texas Hold 'Em

NPR Technology

During one experiment, the poker bot Pluribus played against five professional players. During one experiment, the poker bot Pluribus played against five professional players. In artificial intelligence, it's a milestone when a computer program can beat top players at a game like chess. But a game like poker, specifically six-player Texas Hold'em, has been too tough for a machine to master -- until now. Researchers say they have designed a bot called Pluribus capable of taking on poker professionals in the most popular form of poker and winning.


Meeting the Challenge of Artificial Intelligence

#artificialintelligence

For example, one national firm leader reported that more than 25% of its new entry-level hires are science, technology, engineering, and math (STEM) majors (Allan Koltin, opening remarks at Advisory Board's Winning is Everything Conference, Dec. 13, 2017, http://bit.ly/2wrh091). Specifically for the accounting profession, the integration of artificial intelligence (AI) with robotic process automation (RPA) can create intelligent virtual workers to improve productivity. On facing the challenge of AI, Barry Melancon, AICPA CEO and president, has said, "With AI the whole ramification of jobs in society is a huge issue, and those that embrace it will be the most successful" (Michelle Perry, "AICPAs Barry Melancon on the Challenge of Change in Accountancy," ICAS website, Oct. 6, 2017, http://bit.ly/2Wajgkm). While AI is still an evolving technology, many applications have recently made impressive leaps. For example, computers can defeat chess champions, help drive cars, instruct drones to return automatically, provide medical diagnoses, perform as virtual assistants, and navigate vacuum cleaners through a furnished house.


Will Artificial Intelligence Replace Your SOC? - SecurityRoundTable.org

#artificialintelligence

Artificial intelligence no longer is the "next new thing." AI, machine learning, deep learning and other forms of algorithmic-based, automated processes are now mainstream and on their way to being deeply integrated into a wide range of front office, back office and in-the-field operations. And we certainly have seen a lot of great examples of AI being used to spot potential cybersecurity threats and preventing their infection on an organization. As business leaders, you have given at least some consideration to the notion that AI will completely replace soon your security operations center (SOC). After all, you've probably calculated the money it takes to run your SOC 24/7/365, and what it means when your CISO comes to an executive lunch or the board meeting and explains that we need more resources – i.e., people, technology and money – to fight new and more security threats.


Machine Learning and Artificial Intelligence –the next foundational technology

#artificialintelligence

When the US Library of Congress ranked history's most important innovations, it gave a foremost place to the printing press. While the mechanics behind the printing press weren't far more sophisticated than the other machines of its era, the consequences of its invention were world changing; finally, mankind had a means for the mass distribution of information, improving literacy and changing every industry in the world. Technologies such as these are known as foundational technologies, inventions that can be applied to solve a multitude of problems across a vast number of industries. More contemporary examples include the internet which is now used nearly constantly in all industries and in our personal lives and smartphones, which are so completely integrated with our lives it seems impossible to live without them. As we peer into the near future, we can already see some of the next great potential foundational technologies arising.


Six Things That A.I. and Computers Still Can't Do Very Well Digital Trends

#artificialintelligence

Throughout A.I.'s 60-year history, skeptics have attempted to single out tasks that they think machines will never be able to achieve. Such tasks have ranged from playing a game of chess to generating pieces of music to driving a car. In almost every instant, they have been proved wrong -- sometimes profoundly so. But as amazing as A.I. is here in 2018, there are still things that it is most assuredly not able to do. While some are more frivolous than others, they all showcase some part of machine intelligence that's currently lacking.


The Three Breakthroughs That Have Finally Unleashed AI on the World

#artificialintelligence

A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here--it's about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines' backs. It is surprisingly warm inside, as if the cluster were alive. Today's Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred "instances" of the AI at once. Like all things cloudy, Watson is served to simultaneous customers anywhere in the world, who can access it using their phones, their desktops, or their own data servers.


What is Artificial Intelligence?

#artificialintelligence

The term artificial intelligence (AI) refers to computing systems that perform tasks normally considered within the realm of human decision making. These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications. AI systems leverage this knowledge repository to make decisions and take actions that approximate cognitive functions, including learning and problem solving. AI, which was introduced as an area of science in the mid 1950s, has evolved rapidly in recent years. It has become a valuable and essential tool for orchestrating digital technologies and managing business operations.


How to use machine learning

#artificialintelligence

You may not be using machine learning, often referred to as artificial intelligence, for business applications yet, but there is little doubt you have read or heard about how it could or should be used. The issue is not that there are not legitimate business uses for machine learning (ML) options, the challenge is knowing which types of ML may work best for your business needs and finding the right provider or recruiting the right people to implement it. Initially understanding machine learning is hard, but with a few big concepts under your belt, it becomes easy. It then gets complicated again, but by then you will be ready to deal with generative adversarial networks! This is the most basic version about the content and should get you ready to listen to our special A Word On Artificial Intelligence podcast hosted by Primedia Broadcasting Head of Digital Allan Kent.