Short video on tech clusters.
Baby boomers like myself clearly recall the tumultuous years leading up to the Bicentennial of the United States. The world we grew up in was near the peak of the industrial revolution, dominated by the aftermath of the Great Depression, WW2, and the Cold War. We were raised in a culture that had witnessed first-hand the power of a unified government, which led to the victory of fascism in our parent’s generation, followed by a round trip to the moon in our own. In the childhood of my generation, nothing was impossible with sufficient government power. Read More
Given the systemic nature and scale of the financial crisis, and in consideration of the poor ongoing economic conditions, it’s clear that the industry, political process, and regulators have all fallen short of achieving the individual mission of each, particularly in consideration of current technological capabilities.
For the past several months financial institutions have been trying to convince regulators that they should not be labeled a Systemically Important Financial Institution (SIFI). The process of implementing the 2010 Dodd-Frank law in the U.S. has resulted in spin offs in an attempt to avoid increased U.S. regulation, while the new global rules for multi-national banks on top of Basel III, including surcharges and increased capital ratios, is resulting in a comprehensive rethink of the fundamental assumptions surrounding the global banking model. Read More
I wanted to share a project I initiated earlier this year that we have temporarily named the New Mexico Analytics Cluster. Essentially the project relates to organizing the broad analytics cluster here in NM into a functional global leader worthy of the science and technology. Initial feedback from quite a few of the related companies,… Read More
Structural integrity in organizations, increasingly reflected by data in computer networking, has never been more important. The decision dimension is expanding exponentially due to data volume, global interconnectedness, and increased complexity, thus requiring much richer context, well-engineered structure, far more automation, and increasingly sophisticated techniques. Read More
Above is a screen capture of an internal Kyield document that displays a graphic and text illustration of the high costs of data silos to individual organizations, regions, and society based on actual cases we have studied; in some case based on public information and in others private, confidential information. This is intended for a slide-show type of presentation so does not go into great detail. Suffice to say that human suffering, lives lost, and wars that could have been prevented that were not are inseparably intertwined with economics and ecology, which is why I have viewed this issue as one ultimately of sustainability, particularly when considering the obstacles of silos to scientific discovery, innovation, and learning as well as crisis prevention.
Most professors I know are using twitter, but not for the consumer noise most are familiar with, but rather to share information easily and quickly. Similarly, on Facebook the most intelligent people I know have the most friends. It’s a more functional replacement for email that bogged us all down– that isn’t discussed here, and should have been.
The author also misses several other points in this otherwise good piece, not least of which is the need to share information with customers and partners, monitor feedback, and importantly; introduce advanced analytics that wouldn’t be available otherwise…… continued
As I was reading articles about Watson winning Jeopardy, I was thinking about one of my wife’s favorite TV shows; “House” . The main character, Dr. Gregory House, played brilliantly by Hugh Laurie, is an emotionally unstable genius who leads a team of physicians in a diagnostic unit at a fictional teaching hospital in Princeton, New Jersey.
In most episodes of House, the diagnostician tortures this viewer, the patient, and the patient’s family, with a game much like Jeopardy when each of the experts draw on their memory over days and weeks to match symptoms with disease and therapy. As if this isn’t painful enough for someone who has been focused on applying semantic technologies to improving healthcare efficiencies, the team invariably nearly kills the patient multiple times during the diagnostic Q & A before House has an epiphany when his pain-killer addicted mind finally connects the dots between Jungian philosophy, tropical parasites, chemical toxicity, and/or genetic disorders to miraculously save the patient (usually). Read More
A 2 min elevator pitch on enterprise semantics for semanticweb.com Read More
I recall first asking this question in leadership forums in our online network in 1997, hoping that a Nobel laureate or Turing Award winner might have a quick answer. A few weeks earlier I had escorted my brother Brett and his wife from Phoenix Sky Harbor airport to the Mayo Clinic in Scottsdale, seeking a better diagnosis than the three-year death sentence he had just received from a physician in Washington. Unfortunately, Mayo Clinic could only confirm the initial diagnosis for Amyotrophic lateral sclerosis (ALS).
In my brother’s case, the health care system functioned much better than did the family; it was the dastardly disease that required a cure, along with perhaps my own remnant hubris, but since his employer covered health care costs we were protected from most of the economic impact. I then immersed myself in life science while continuing the experiential learning curve in our tech incubator. It soon became apparent that solving related challenges in research would take considerably longer than the three years available to my brother, his wife, and their new son. Close observation of health care has since revealed that research was only part of the challenge. Read More