Category: Artificial Intelligence

Latest Read: AI Superpowers

Post author By Don Kasprzak
Post date December 10, 2021

AI Superpowers: China, Silicon Valley, and the New World Order
by Kai-Fu Lee. He developed an advanced continuous speech recognition system during his Ph.D. work at Carnegie Mellon University in the early 1980s. He landed at Apple in 1990 for a decade, then went to SGI.

Since 2000 Kai-Fu served as the founding director of Microsoft Research Asia, then president of Google China, He departed to launch Sinovation Ventures, a venture capital firm in Beijing.

This book weaves in and out of AI technology developments. It is both surprising and disappointing. Many have certainly noted this is more or less propaganda for China. By the fourth chapter, I began wondering if Kai-Fu is considering a run for Chinese President.

Kai-Fu addresses in chapter 5, the four waves of AI: Internet AI, Business AI, Perception AI, and Autonomous AI. Elements of each wave appear even today, a bit far fetched for a democracy. However within a state controlled economy, China can force changes described across all four. With the US Population at 331 million compared to China’s 1.4 million, statements that China produces more data for AI system is certainly not a watershed thought. Certainly China will produce more data for AI systems than many country populations combined.

The AI shopping cart?

The idea of an AI enhanced shopping cart with a built-in LCD display and recognizes your shopping history upon touch, as you enter any Chinese local Yonghui superstore referenced in “Where every shopping cart knows your name” seems to still be a foreign concept across America’s grocery stores. Too many privacy concerns for the West. In addition, this was published prior to COVID. Today this idea certainly will be replaced by AI-enhanced mobile apps, or Internet AI as Kai-Fu is referencing above.

Tags AI Superpowers, Artificial Intelligence, china, Kai-Fu Lee

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Latest Read: The Ten Equations That Rule the World

Post author By Don Kasprzak
Post date November 24, 2021

The Ten Equations That Rule the World by David Sumpter. He is a professor of Applied Mathematics at the University of Uppsala, Sweden. David was awarded the UK’s Institute of Mathematics 2015 prize for communicating mathematics to a wider audience in his research How to Model Honeybee Colonies.

David provides a deep overview of ten equations: Betting, Judgement, Confidence, Skill , Influencer, Market, Advertising, Reward, Learning, and The Universal Equation. Each equation (algorithm) includes stories that certainly provide deeper understanding.

On the other hand, the opening chapter did not really connect with me. The Betting Equation focuses on UK soccer and for reveals how betting odds can be adjusted against reality.

Nevertheless, I am not sure why this did not resonate as the rest of the book is just delightful to read.

In addition, the second chapter, Judgement Equation is the basis of Bayesian statistics and this storyline really stuck with me.

Furthermore, it is great to see David reference The Signal and the Noise by Nate Silver within the third chapter, The Confidence Equation.

Tags algorithms, David Sumpter, The Ten Equations That Rule the World

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Latest Read: Artificial Intelligence HBR Insights

Post author By Don Kasprzak
Post date November 5, 2021

Artificial Intelligence: The Insights You Need from Harvard Business Review by Thomas H. Davenport, Erik Brynjolfsson, Andrew McAfee, and H. James Wilson. This HBR series is certainly a very good collection of essays from leading AI experts.

Thomas H. Davenport is a Distinguished Professor in Management and Information Technology at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior adviser at Deloitte Analytics. Erik Brynjolfsson is the director of MIT’s Initiative on the Digital Economy, Professor of Management Science at the MIT Sloan School of Management, and a research associate at NBER. H. James Wilson is a managing director of information technology and business research at Accenture Research. Andrew McAfee is a principal research scientist at MIT, studies how digital technologies are changing business, the economy, and society.

Indeed, this is not a general introduction to AI for business. At the same time, this does present readers with business advantages and challenges. There is no coding and the book is not full of technical jargon.

The messaging across this book is direct and startling for some: if your organization is not using AI you will soon be obsolete. This should not be a surprise since AI was ‘born’ in 1956. Yes, the last decade’s computing performance both on-prem and in the cloud have pushed AI further into markets. Yet the competitive lessons are valuable.

Tags Artificial Intelligence, Automation, Data management, Innovation, Organizational learning

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Latest Read: Artificial Intelligence

Post author By Don Kasprzak
Post date October 28, 2021

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell. Melanie holds a PhD in computer science from the University of Michigan. Melanie is a professor of computer science at Portland State University. In addition, she is an external professor at the Santa Fe Institute.

It is certainly very rare that a book makes an impact like Melanie’s effort. Actually, this is one rare event: I would recommend everyone read her prologue “Terrified” regardless of their life’s path. Yes, this book is that powerful.

Furthermore, Melanie studied with a leading cognitive scientist Douglas Hofstadter at Michigan and collaborated to create the Copycat program, which makes creative analogies in an idealized world.

Upon finishing the prologue, everyone should certainly continue reading. This is an easy to read, yet deep examination of the current state of artificial intelligence.

In addition, Melanie provides a good history of artificial intelligence (AI), from inception in 1954 to multiple “freezes” in AI funding to the promise of amazing breakthroughs and shocking failures. Every element for better or worse is evenly written. Bravo!

Certainly the most impressive points across each chapter is how Melanie grounds user’s expectations of AI versus the hype. This is both from the consumer to artificial intelligence engineers.

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Artificial Intelligence Education Innovation Reading

Latest Read: How Smart Machines Think

Post author By Don Kasprzak
Post date October 23, 2021

How Smart Machines Think by Sean Gerrish. Sean is a Senior Engineering Manager at Google leading machine learning and data science teams. He holds a PhD in machine learning from Princeton.

This book is providing readers with a wonderful overview to advances in artificial intelligence, and specifically how machine leaning is now the most popular subset of AI.

How Smart Machines Think is addressing three key areas that reveal the leaps in advancements of machine learning development: The DAPRA Grand Challenge, the Netflix recommendation engine, and Neural Networks.

Each section is well written, providing above all, deep insights tied to objectives driving new business models.

While Sean is certainly providing a solid grounding in algorithms and their methodologies, I was certainly surprised at the depth of autonomous vehicles, recommendation engines, and game-playing. The larger lessons from his book include amazing progress in neural networks.

Machine Learning for autonomous vehicles

Clearly Sean understands the full picture of how this emerging technology began. The 2004 initial contest found team only to achieve a small distance, perhaps less than twenty five percent of the course before their AI systems failed.

Tags Artificial Intelligence, Innovation, machine learning, Sean Gerrish, Smart Machines