KYield is a pioneer in AI systems, data physics, and knowledge systems, with decades of experience in basic and applied research. We've engaged in deep-dive use cases in applied AI with dozens of leading organizations. Our flagship product is the KOS, which is the first enterprise-wide AI operating system. The KOS is a universal system tailored to the needs of each entity according to input from each.
Introduction Different Types of EAI OS Compex Adaptive Organizational System (CAOS)EAI OS ArchitectureSecurity | Differentiation | SovereigntyContinuously Adaptive Learning Organization (CALO)Discussion & ConclusionReferences
Letter from our Founder & CEO Introduction Generative AI: Necessary but Insufficient Rules-based Governance Metamorphic Transformation: GIGO to QIQO Learning Networks KOS ProcessAffordability & ROI ConclusionReferences
The purpose of this article is to provide clarity on obstacles to ROI in enterprise AI (EAI) based on a quarter of a century in R&D and engagement with hundreds of leading organizations over the past decade (COGNITIVE WORLD) .....→
Metamorphic Transformation with Enterprisewide Artificial Intelligence
KYield Genesis A presentation by KYield's founder & CEO Mark Montgomery at the ExperienceITNM technology conference on September 13th, 2019. The title of the talk is 'Metamorphic Transformation with Enterprise-wide Artificial Intelligence'. Mark also unveiled his new patent-pending invention titled 'Synthetic Genius Machine and Knowledge Creation System'. The length of the video is 47 minutes including Q&A.
Synthetic Genius Machine and Knowledge Creation System
Accelerating superintelligence
This video starts with the unveiling of KYield's new patent-pending invention titled 'Synthetic Genius Machine and Knowledge Creation System'. The length of the discussion on the genius machine is 3-4 minutes (press release).
Despite the results in a small group of startups and superstars that are achieving an attractive return on investment (ROI) from AI, delivering double-digit productivity growth, and rapidly increasing market power, the super majority of companies are still reporting low levels of ROI. The purpose of this article is to provide clarity on obstacles to ROI in enterprise AI (EAI) based on a quarter of a century in R&D and engagement with hundreds of leading organizations over the past decade.....→
Among the most perplexing challenges facing CEOs in recent years is how best to compete in a data-driven economy that is becoming increasingly dominated by large and rapidly growing companies, often described as “superstar” firms.[1] Although the most valuable superstar firms are in the technology industry, the group includes hundreds of corporations in other industries that have grown rapidly during globalization.....→
The situation and capabilities of companies we’ve dealt with vary across a wide spectrum, ranging from a very few at the top tier in strategic competency, to a few more in a fatal tailspin. The vast majority of companies are somewhere in-between, representing the bulk of companies that need help that are also in a position to receive it. The following represent AI strategies that have emerged over the past decade. Some have proven to be much more successful than others.....→
AI systems create value by converting human knowledge to digital form that can then be converted to other forms of energy, including kinetic. At the atomic level knowledge created by human intelligence and augmented by machine learning can be viewed and expressed as an extension of relativity discovered by Einstein more than a century ago....→
The Amazon acquisition of Whole Foods represents yet another confirmation of our rapidly changing business environment driven by opportunities at the confluence of technology and network dynamics. Although only the latest in a powerful trend initially impacting in this case the grocery industry, the business and technology issues driving the strategy are relevant to most and serves as a reminder that digital convergence is not confined to traditional thinking or industry lines.. Please keep that in mind while reading......→
Every year, natural catastrophes (nat cat) are highly visible events that cause major damage across the world. In 2016 the cost of nat cats were estimated to be $175 billion, $50 billion of which were covered by insurance, reflecting severe financial losses for impacted areas.[i] The total cost of natural catastrophes since 2000 was approximately $2.3 trillion.[ii] Much less understood is that human-caused catastrophes (hum cat) have resulted in much greater economic damage during the same period and have become increasingly preventable.......→
While it may be an interesting question whether the seasons are changing in artificial intelligence (AI), or to what extent the entertainment industry is herding pop culture, it may not have much to do with future reality. Given recent attention AI has received and the unique potential for misunderstanding, I thought a brief story from the trenches in the Land of Enchantment might shed some light.....(Wired)
George Strasburg is a 64 year old retired scientist living with his wife Cynthia in the southern United States. The couple recently celebrated their 40th anniversary at home, which was attended by several dozen friends and family members from all over the world. Five years ago George was diagnosed with diabetes mellitus (type 2), with a fasting blood glucose level at 153 mg/dL. The diagnosis was not a surprise; members on both sides of his family had died from complications from diabetes, including his father.........→
Much of the discussion surrounding the emerging field of knowledge management (KM) is like stirring a vat of "jello with a slinky", little firms up. KM concepts seem to float in a jello- like environment without form, density, or direction making it difficult for practitioners to grasp key KM concepts. A common refrain in corporate boardrooms and executive offices in federal agencies is that "I'd be happy to embrace KM if I only knew what it is and how it will help us meet enterprise objectives".....→
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