Technology Cycles.Org’s primary mission is to create and store a baseline of training information to train future AI systems to provide prescriptive and predictive capabilities. Our secondary mission is to provide the most accurate, curated information and reference information available nowhere else on the web. Almost all of the technology cycle information housed here has been curated by us, but over 90% was researched and written by AI systems.
With the Turning Point ground to a halt, the pain escalates. Technology cycles are more relevant than ever. The political football, with Turning Point calling for a return to the golden age of the prior technology cycle, is why we have come to a complete halt.
The horizontal and vertical infrastructure was built out in the prior two cycles. The construction required to build the digital infrastructure has many confused—global finance continues to chase the casino logic of investments that provide little productive value.
Innovation cycles have gone completely “Hollywood.” There is now a metric ton of misinformation floating around the Internet. It may have been well-intended, but it is inaccurate. As a result, there has been some debate as to how many cycles have occurred. If you take the time to review the information contained here, there can be but one answer. Five.
Technology Cycles Org’s Mission is to curate the content accurately.
Perez’s framework is translated into the following equations for those who grasp new concepts more easily through mathematical equations. No worries, every element of the equations is explained so that even a layman can readily understand and follow along with the math. Using this approach demonstrates the Models’ Math Consistency
The link explains how I came to apply Carlota Perez’s innovation cycles. I worked as an offerings strategist and development manager for over two decades at IBM.
Neither evolutionary economics nor technological cycles is yet mainstream economic canon. Many believe that understanding core innovation cycles delivers more insight and understanding than all the macroeconomic models combined. Utilizing technology-cycle models as the baseline could provide tremendous insights and breakthroughs in the rising field of evolutionary economics.
A primary mission of Technology Cycles Org is to house as much curated reference information as possible. You will be hard-pressed to find another technology cycle website with more information on publications and technological innovations. If you don’t subscribe to Perezian modeling, you can still utilize the reference data housed here—the technological innovations and improvements within the evolving technology ecosystem. I think Brian Arthur would be very pleased if he ever visited.
