Application of Artificial Intelligence Based Agents, BBots and Systems in Business - 2017 State of Affairs
July 2017
Business bots (BBots) are now being used in businesses. Chatbots are the popular bots in this category. Chatbots are able to understand speech and reply in pronounced words and people are happy to have dialogue with them.
ERIK BRYNJOLFSSON & ANDREW MCAFEE authored an article "THE BUSINESS OF ARTIFICIAL INTELLIGENCE: What it can — and cannot — do for your organization" in HBR of July 2017 and explained the potential of artificial intelligence in business applications. There are good number of applications at this movement. But still their business and revenue impact is limited. The potential is very high. But business reimagination is needed to come out with a business concept using the AI that will have a significant revenue and business impact.
Important points made in the article
The term artificial intelligence was coined in 1955 by John McCarthy, a math professor at Dartmouth and he organized a conference on the topic in 1956.
Up to the present time, the biggest advances have been made in two broad areas: perception and cognition. In the former category, voice recognition and image recognition are developed to become practical applications in Siri, Alexa, and Google Assistant. The driverless car uses image recognition in real life high risk practical application.
In the area of cognition and problem solving, machines are beating human players in games like chess, poker and Go. Google’s DeepMind team has used ML systems to solve optimization problem and improve the cooling efficiency at data centers by more than 15%, after optimization efforts by human experts.
Uniqueness of Machine Learning
Machine learning represents a fundamentally different approach to creating software. It does not use explicitly specified rules. Instead, the machine learns from examples. The learning when guided by successful answers is the most fruitful at the moment. Hence, most of the successes occurred in supervised learning systems, in which the machine is given lots of examples of the correct answer to a particular problem accompanied with lot of input data.
Another category of learning problems is emerging, reinforcement learning systems. In reinforcement learning systems the programmer specifies the current state of the system and the goal, lists allowable actions, and describes constraints. The system has to combine, the allowable actions, and the outcomes subject to constraints and figure out how to get as close to the goal as possible.
Designing and implementing new combinations of technologies, human skills, and capital assets to meet customers’ needs requires large-scale creativity and planning. This is the task of entrepreneurs or business managers employed to think like entrepreneurs. So the age of machine learning provides at the present moment, great rewarding opportunities entrepreneurs or business managers.
Risks of employing machine learning systems include, the machines' hidden biases, derived not from any intent of the designer but from the data provided to train the system.
The authors conclude that in their view, artificial intelligence, especially machine learning, is the most important general-purpose technology of the present our era. The innovations developed using the new technology will be direct applications as well as complementary innovations.
If entrepreneurs and managers aren’t doing many experiments in the area of machine learning, they aren’t doing using their time devoted to strategic planning properly. Over the next decade, entrepreneurs and managers who understand and use AI effectively and efficiently will replace those who don’t.
Important points made in the article
The term artificial intelligence was coined in 1955 by John McCarthy, a math professor at Dartmouth and he organized a conference on the topic in 1956.
Up to the present time, the biggest advances have been made in two broad areas: perception and cognition. In the former category, voice recognition and image recognition are developed to become practical applications in Siri, Alexa, and Google Assistant. The driverless car uses image recognition in real life high risk practical application.
In the area of cognition and problem solving, machines are beating human players in games like chess, poker and Go. Google’s DeepMind team has used ML systems to solve optimization problem and improve the cooling efficiency at data centers by more than 15%, after optimization efforts by human experts.
Uniqueness of Machine Learning
Machine learning represents a fundamentally different approach to creating software. It does not use explicitly specified rules. Instead, the machine learns from examples. The learning when guided by successful answers is the most fruitful at the moment. Hence, most of the successes occurred in supervised learning systems, in which the machine is given lots of examples of the correct answer to a particular problem accompanied with lot of input data.
Another category of learning problems is emerging, reinforcement learning systems. In reinforcement learning systems the programmer specifies the current state of the system and the goal, lists allowable actions, and describes constraints. The system has to combine, the allowable actions, and the outcomes subject to constraints and figure out how to get as close to the goal as possible.
Designing and implementing new combinations of technologies, human skills, and capital assets to meet customers’ needs requires large-scale creativity and planning. This is the task of entrepreneurs or business managers employed to think like entrepreneurs. So the age of machine learning provides at the present moment, great rewarding opportunities entrepreneurs or business managers.
Risks of employing machine learning systems include, the machines' hidden biases, derived not from any intent of the designer but from the data provided to train the system.
The authors conclude that in their view, artificial intelligence, especially machine learning, is the most important general-purpose technology of the present our era. The innovations developed using the new technology will be direct applications as well as complementary innovations.
If entrepreneurs and managers aren’t doing many experiments in the area of machine learning, they aren’t doing using their time devoted to strategic planning properly. Over the next decade, entrepreneurs and managers who understand and use AI effectively and efficiently will replace those who don’t.
If you are an entrepreneur or a business process/model manager register for a course of machine learning immediately if you have not done yet.
https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence
2017
Andrew Ng: Artificial Intelligence is the New Electricity
Stanford Graduate School of Business
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Published on 17 Jan 2017
http://www.weforum.org/
As business opportunities for artificial intelligence multiply, how can industry leaders design the principles and technical standards into their products that benefit society as a whole?
- Ron Gutman, Founder and Chief Executive Officer, HealthTap, USA
- Joichi Ito, Director, Media Lab, Massachusetts Institute of Technology, USA
- Satya Nadella, Chief Executive Officer, Microsoft Corporation, USA
- Ginni Rometty, Chairman, President and Chief Executive Officer, IBM Corporation, USA
Moderated by
- Robert F. Smith, Chairman and Chief Executive Officer, Vista Equity Partners, USA
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Speakers:
-Matthew Grob, Executive Vice-President and Chief Technology Officer, Qualcomm, USA.
-Andrew Moore, Dean, School of Computer Science, Carnegie Mellon University, USA.
-Stuart Russell, Professor of Computer Science, University of California, Berkeley, USA.
-Ya-Qin Zhang, President, Baidu.com, People's Republic of China.
Moderated by Connyoung Jennifer Moon, Chief Anchor and Editor-in-Chief, Arirang TV & Radio, Republic of Korea.
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2015
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MIT Open courseware Lectures 2010 - Playlist
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2017
Andrew Ng: Artificial Intelligence is the New Electricity
Stanford Graduate School of Business
___________________
___________________
Davos WEF 2017 Panel Discussion on Artificial Intelligence
Published on 17 Jan 2017
http://www.weforum.org/
As business opportunities for artificial intelligence multiply, how can industry leaders design the principles and technical standards into their products that benefit society as a whole?
- Ron Gutman, Founder and Chief Executive Officer, HealthTap, USA
- Joichi Ito, Director, Media Lab, Massachusetts Institute of Technology, USA
- Satya Nadella, Chief Executive Officer, Microsoft Corporation, USA
- Ginni Rometty, Chairman, President and Chief Executive Officer, IBM Corporation, USA
Moderated by
- Robert F. Smith, Chairman and Chief Executive Officer, Vista Equity Partners, USA
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Davos WEF 2016 Panel Discussion on The State of Artificial Intelligence
How close are technologies to simulating or overtaking human intelligence and what are the implications for industry and society?Speakers:
-Matthew Grob, Executive Vice-President and Chief Technology Officer, Qualcomm, USA.
-Andrew Moore, Dean, School of Computer Science, Carnegie Mellon University, USA.
-Stuart Russell, Professor of Computer Science, University of California, Berkeley, USA.
-Ya-Qin Zhang, President, Baidu.com, People's Republic of China.
Moderated by Connyoung Jennifer Moon, Chief Anchor and Editor-in-Chief, Arirang TV & Radio, Republic of Korea.
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_______________
2015
_______________
_______________
MIT Open courseware Lectures 2010 - Playlist
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