Beyond Algorithms
Delivering AI for Business
1st Edition
Published on 29. May 2022
302 pages
978-1-000-58197-3 (ISBN)
Description
With so much artificial intelligence (AI) in the headlines, it is no surprise that businesses are scrambling to exploit this exciting and transformative technology. Clearly, those who are the first to deliver business-relevant AI will gain significant advantage.
However, there is a problem! Our perception of AI success in society is primarily based on our experiences with consumer applications from the big web companies. The adoption of AI in the enterprise has been slow due to various challenges. Business applications address far more complex problems and the data needed to address them is less plentiful. There is also the critical need for alignment of AI with relevant business processes. In addition, the use of AI requires new engineering practices for application maintenance and trust.
So, how do you deliver working AI applications in the enterprise?
Beyond Algorithms: Delivering AI for Business answers this question. Written by three engineers with decades of experience in AI (and all the scars that come with that), this book explains what it takes to define, manage, engineer, and deliver end-to-end AI applications that work. This book presents:
Core conceptual differences between AI and traditional business applications
A new methodology that helps to prioritise AI projects and manage risks
Practical case studies and examples with a focus on business impact and solution delivery
Technical Deep Dives and Thought Experiments designed to challenge your brain and destroy your weekends
However, there is a problem! Our perception of AI success in society is primarily based on our experiences with consumer applications from the big web companies. The adoption of AI in the enterprise has been slow due to various challenges. Business applications address far more complex problems and the data needed to address them is less plentiful. There is also the critical need for alignment of AI with relevant business processes. In addition, the use of AI requires new engineering practices for application maintenance and trust.
So, how do you deliver working AI applications in the enterprise?
Beyond Algorithms: Delivering AI for Business answers this question. Written by three engineers with decades of experience in AI (and all the scars that come with that), this book explains what it takes to define, manage, engineer, and deliver end-to-end AI applications that work. This book presents:
Core conceptual differences between AI and traditional business applications
A new methodology that helps to prioritise AI projects and manage risks
Practical case studies and examples with a focus on business impact and solution delivery
Technical Deep Dives and Thought Experiments designed to challenge your brain and destroy your weekends
Reviews / Votes
"Much has been written about the mechanics of modern AI - what it is, what it isn't, and how to build and train one - but this fascinating book is among the few that explain what it means for the enterprise - where it fit in to business needs, how it can be integrated into existing systems, and how it can create opportunities for new value." -- Grady Booch, IBM Fellow, Chief Scientist for Software Engineering"I recommend Beyond Algorithms - Delivering AI for Business to anyone that is responsible for leading and transitioning AI to achieve and maintain a competitive advantage. The book addresses many of the important issues faced in the application of AI to businesses. It is written in an easy to read style, while providing enough technical content that many people working in the field can capture the main messages." -- David R. Martinez, MIT Instructor and Laboratory Fellow
"Books about AI too often tend towards the extremes -- either praising or condemning unconditionally. Beyond Algorithms offers a more nuanced, nontechnical introduction from experienced practitioners. Filled with guiding principles and real-world examples, this book offers a balanced view of AI's strengths and limitations and provides practical advice for problem selection, project management, and expectation setting for AI initiatives." -- Emily Riederer, Senior Analytics Manager at Capital One
"Beyond Algorithmsis one of those wonderful story-driven IT books that distils decades worth of real world experience into intoxicating wisdom that is refreshingly easy to consume. The book plows through and around the hype of the 'all powerful' deep neural nets to provide an engineering approach for the field. It won't tell you how to establish the Singularity, but it's 'A to I checklist', accuracy and monitoring advice, and 'doability method' could make you an AI delivery hero." -- Richard Hopkins, FREng FIET CEng, former President of IBM's Academy of Technology
"Important and timely. A practical guide for realizing business value through AI capabilities! Rather than focusing on hard to access details of the mathematics and algorithms behind modern AI, this book provides a roadmap for a diversity of stakeholders to realize AI business solutions that are reliable, responsible, and sustainable." -- Matthew Gaston, AI Engineering Evangelist
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
24 Tables, black and white; 62 Line drawings, color; 1 Line drawings, black and white; 62 Illustrations, color; 1 Illustrations, black and white
ISBN-13
978-1-000-58197-3 (9781000581973)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
05/2022
1st Edition
Chapman & Hall/CRC
€217.40
Shipment within 15-20 days
Book
05/2022
1st Edition
Chapman & Hall/CRC
€97.10
Shipment within 15-20 days
Persons
James Luke, is an Engineer with over 25 years' experience delivering real AI solutions that solve real world problems. James is the Innovation Director at Roke, a leading UK technology company, having previously worked as an IBM Distinguished Engineer and Master Inventor. James has multiple US patents in subjects relating to AI and, for his PhD, researched the application of AI in detecting previously unseen computer viruses. James is an experienced conference speaker and has given evidence on the development of AI to both the European Commission and the House of Lords Select Committee. In 2018, James delivered a TEDx talk entitled, "How To Survive An AI Winter" ( https://www.youtube.com/watch?v=MWOkEVdITIg ). James started his career failing to deliver an AI solution for a leading Formula 1 team. This experience changed James's understanding and perspective on what it takes to actually deliver a working AI solution. James responded to his early failure by developing new methods for the definition, design and delivery of AI solutions. He has delivered projects in multiple industries from Public Sector to Insurance and Retail. Prior to joining Roke, James held a number of key positions in IBM including Chief Architect for Watson Tools, CTO of the Cognitive Practice in Europe and Leader of the Academy of Technology core team on AI.
Dr. Padmanabhan Santhanam is currently a Principal Research Staff Member at the IBM T. J. Watson Research Center in New York, working to enable AI systems in government and public sector. His personal research interest is both in the use of AI for engineering traditional software systems and the emerging field of AI Engineering (i.e. how to engineer trust-worthy AI systems). Prior to that, Dr. Santhanam worked on several aspects of AI strategy and execution in IBM Research. He holds a Ph.D. in Applied Physics from Yale University. Dr. Santhanam worked in software engineering research for two decades, having to do with the creation of tools and methodology to improve commercial software development. His interests included software quality metrics, automation of software test generation, realistic modeling of software development processes, etc. He has more than fifty published research papers in peer-reviewed journals and conferences in a variety of topics. He is a member of the ACM & AAAI and a Senior Member of the IEEE. He is also a Member of the IBM Academy of Technology.
David Porter is currently an Associate Partner at IBM Consulting. He graduated in 1995 from the University of Greenwich with a degree in Information Systems Engineering. He has worked in AI and Data Science ever since, with consultancy roles at SAS Software, Detica/BAE Systems and now IBM. Early on in his career he chose to focus on counter-fraud and law enforcement systems. This specialisation has allowed him to work with governments and organisations all over the world. Achievements in this field include the co-invention of the graph analytics software NetReveal and leading the design teams for both the UK's Insurance Fraud Bureau and the original Connect system at Her Majesty's Revenue and Customs (HMRC). He joined IBM in 2016, enticed by the Watson story; could AI be used to catch crooks? He has been putting Natural Language Processing to good use ever since.
Dr. Padmanabhan Santhanam is currently a Principal Research Staff Member at the IBM T. J. Watson Research Center in New York, working to enable AI systems in government and public sector. His personal research interest is both in the use of AI for engineering traditional software systems and the emerging field of AI Engineering (i.e. how to engineer trust-worthy AI systems). Prior to that, Dr. Santhanam worked on several aspects of AI strategy and execution in IBM Research. He holds a Ph.D. in Applied Physics from Yale University. Dr. Santhanam worked in software engineering research for two decades, having to do with the creation of tools and methodology to improve commercial software development. His interests included software quality metrics, automation of software test generation, realistic modeling of software development processes, etc. He has more than fifty published research papers in peer-reviewed journals and conferences in a variety of topics. He is a member of the ACM & AAAI and a Senior Member of the IEEE. He is also a Member of the IBM Academy of Technology.
David Porter is currently an Associate Partner at IBM Consulting. He graduated in 1995 from the University of Greenwich with a degree in Information Systems Engineering. He has worked in AI and Data Science ever since, with consultancy roles at SAS Software, Detica/BAE Systems and now IBM. Early on in his career he chose to focus on counter-fraud and law enforcement systems. This specialisation has allowed him to work with governments and organisations all over the world. Achievements in this field include the co-invention of the graph analytics software NetReveal and leading the design teams for both the UK's Insurance Fraud Bureau and the original Connect system at Her Majesty's Revenue and Customs (HMRC). He joined IBM in 2016, enticed by the Watson story; could AI be used to catch crooks? He has been putting Natural Language Processing to good use ever since.
Content
Authors. Acknowledgements. PROLOGUE. Chapter 1 Why This Book? Chapter 2 Building Applications. Chapter 3 It's Not Just the Algorithms, Really! Chapter 4 Know Where to Start - Select the Right Project. Chapter 5 Business Value and Impact. Chapter 6 Ensuring It Works - How Do You Know? Chapter 7 It's All about the Data. Chapter 8 How Hard Can It Be? Chapter 9 Getting Your Priorities Right. Chapter 10 Some (Not So) Boring Stuff. Chapter 11 The Future. EPILOGUE. INDEX.
