One of the ways to see just how far artificial intelligence (AI) has come is to look at the history of when AI-powered machines battled humans in tasks and games that had previously been assumed to be the domain of humans. Here we pulled together the highlights of the history of challenges between man and artificial intelligence.

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

2. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
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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.
Man Vs. Machine:
The 6 Greatest AI Challenges To Showcase The
Power Of Artificial Intelligence

3. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
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. The next year, Deep Blue was victorious.
When Deep Blue won, many talked that it was a sign that artificial intelligence was
catching up to human intelligence and it inspired a documentary film called The
Man vs. The Machine. Shortly after losing, Kasparov went on record to state he
thought the IBM team had cheated; however, in an interview in 2016, Kasparov said
he had analysed the match and retracted his previous conclusion and cheating
accusation.
A Game of Chess

4. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
In 2011, IBM Watson took on Ken Jennings and Brad Rutter, two of the most
successful contestants of the game show Jeopardy who had collectively won $5
million during their reigns as Jeopardy champions. Watson won! To prepare for the
competition, Watson played 100 games against past winners. The computer was
the size of a room, was named after IBM’s founder Thomas J. Watson and required
a powerful and noisy cooling system to keep its servers from overheating. Deep
Blue and Watson were products that came from IBM’s Grand Challenge initiatives
that pit man against machines. Since Jeopardy has a unique format where
contestants provide the answers to the “clues” they are given, Watson first had to
learn how to untangle the language to determine what was being asked even
before it could do the work to figure out how to respond—a significant feat for
natural language processing that resulted in IBM developing DeepQA, a software
structure to do just that.
Jeopardy

5. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Could artificial intelligence play Atari games better than humans? DeepMind
Technologies took on this challenge, and in 2013 it applied its deep learning model
to seven Atari 2600 games. This endeavour had to overcome the challenge of
reinforcement learning to control agents directly from vision and speech inputs.
The breakthroughs in computer vision and speech recognition allowed the
innovators at DeepMind Technologies to develop a convolutional neural network
for reinforcement learning to enable a machine to master several Atari games using
only raw pixels as input and in a few games have better results than humans.
Atari Games

6. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Next up in our review of man versus machine is the achievements of AlphaGo, a
machine that is able to learn for itself what knowledge is. The supercomputer was
able to learn 3,000 years of human knowledge in a mere 40 days prompting some
to claim it was “one of the greatest advances ever in artificial intelligence.” The
system had already learned how to beat the world champion of Go, an ancient
board game that was once thought to be impossible for a machine to decipher. The
film about the experience is now available on Netflix. AlphaGo's success, when not
being constrained by human knowledge, presents the possibility of the system
being used to solve some of the world's most challenging problems such as in
healthcare or energy or environmental concerns.
AlphaGo

7. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
In another test of artificial intelligence capabilities, DeepMind sought out a more
complex game for artificial intelligence to battle that required the use of different
features of intelligence that are necessary to solve scientific and real-world
problems. They found the next challenge in StarCraft II, a real-time strategy game
created by Blizzard Entertainment that features multi-layered gameplay. AlphaStar
was the first artificial intelligence to defeat professional players of the game by
using its deep neural network that was trained from raw game data by
reinforcement and supervised learning.
StarCraft II

8. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Project Debater, a project from IBM, tackles another area of expertise for artificial
intelligence—debating humans on complex topics. This skill involves dissecting
your opponent’s arguments and finding ways to appeal to their emotions (or the
audience’s emotions)—something that would seem like a uniquely human ability to
do. Even though Miss Project Debater lost when it faced off against one of the
world’s leading debate champions, it was still an impressive display of artificial
intelligence capabilities. To succeed at a debate, AI needs to rely on facts and logic,
be able to make sense of an opponent’s line of reasoning and to navigate human
language fully which has been one of the most challenging feats of all for AI to
master. While not 100% successful, Project Debater gave a good glimpse of what’s
possible in the future where machines can augment human intelligence in powerful
ways.
Project Debater

9. © 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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