Learn about the background of Kyield and the multi-disciplinary science involved with AI systems, with a particular focus on AI augmentation for knowledge work and how to achieve a continuously adaptive learning organization (CALO). Read More
Recent investment in AI is primarily due to the formation of viable components in applied R&D that came together through a combination of purposeful engineering and serendipity, resulting in a wide variety of revolutionary functionality. However, since investment spikes also typically reflect reactionary herding, asset allocation mandates, monetary policy, and opaque strategic interests among other factors, caution is warranted. Read More
The post WW2 era we grew up in provided the best economic conditions the world has ever known. The baby boom population explosion, of which I am at the tail end of, combined with vast sequential gains in productivity to create the ‘miracles’ of economies in the U.S., Japan, Germany, and China among others, or so it seemed. Read More
This post is in response to an excellent article Tom Davenport wrote for the WSJ (now on LinkedIn) ‘Lessons from the Cognitive Front Lines: Early Adopters of IBM’s Watson’. Read More
I just completed an extensive e-book for customers and prospective customers, which should be of interest to all senior management teams in all sectors as the content impacts every aspect of individual and corporate performance.
Ascension to a Higher Level of Performance
The Kyield OS: A Unified AI System Read More
This is a clip from an E-book nearing completion titled: The Kyield OS: A Unified AI System; Rapid Ascension to a Higher Level of Performance. Read More
When you find yourself working long hours and buried with critical tasks, perhaps even behind schedule, it might just be the perfect time to spend a day volunteering. We did so this weekend and wanted to share while still fresh. My wife Betsy is participating in an employer-sponsored health management program. Although not new for… Read More
Those of us who have been through a few tech cycles have learned to be cautious, so for the second article in this series I thought it might be helpful to examine the state of AI algorithms to answer the question: what’s different this time?
I reached out to leading AI labs for their perspective, including Jürgen Schmidhuber at the Swiss AI Lab IDSIA. Jürgen’s former students include team members at Deep Mind who co-authored a paper recently published by Nature on deep reinforcement learning. Read More
Consider that learning algorithms are very likely (or soon will be) improving the intelligence quotient and operational efficiency of your chief competitors at an extremely rapid rate. Read More
While artificial intelligence (AI) has roots as far back as Greek mythology, and Aristotle is credited with inventing the first deductive reasoning system, it wasn’t until the post WWII era of computing that we humans began to execute machine intelligence with early supercomputers. The science progressed nicely until the onset of AI Winter in the 1960s, representing the beginning of severe cycles in technology. A great deal of R&D needed to evolve and mature over the next five decades prior to wide adoption of applied AI — here is a brief history and analysis of the rapidly evolving field of artificial intelligence and machine learning. Read More