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Kyield offers systems and services surrounding the Kyield OS, which is based on a new theorem Mark Montgomery developed in 1990s "yield management of knowledge", which is substantially covered by an AI system patent issued in 2011: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. The standard modular Kyield OS provides several critical functions across distributed networks, including network governance, proprietary security, enhanced productivity, and continuous improvement.
Yield Management of Knowledge
Optimizing knowledge yield across digital networks requires a highly specific AI system architecture reflected in the now realized system design goals of the Kyield OS:
- In order to be relevant and produce value the system must tailor data to each entity in a timely and appropriate manner.
- For ease of use the system must be automated and operating in the background with a simple to use natural language interface.
- Must include rules-based governance (CKO Engine) across the network for access, security, compliance, and relationship-management.
- Data structure and quality must be created and populated in an optimal manner automatically in the course of natural knowledge work or with machine sensors across the network.
- The entire system including each module must be continuously adaptive and continuously learning and improving.
The Kyield OS
The standard Kyield OS is a distributed artificial intelligence operating system. All other products and platforms offered by Kyield operate on top of the Kyield OS, which is focused on universal needs for any organization or network. The basic components of the unified modular system are as follows:
- The CKO Engine provides governance, access and security settings for entire distributed network with a natural language interface.
- The Group Module is a light version of the CKO Engine for business units or groups that tailors data management and algorithmics to the mission of the group within the parameters determined by the CKO Engine.
- Individual Modules are provided to every person within an organization and can also be extended to customers or patients. Regardless of device, each module contains a natural language interface for semi-automated control of profiles for forward looking needs.
The standard Kyield OS current includes eight functional areas within the system. Each function is continuous, automated, and prescribed to the actual needs of each entity:
Read more about the Kyield OS technology
Download and read an eBook by Mark Montgomery Ascension to a Higher Level of Performance
Prevention of Human-Caused Catastrophes (HumCat)
Read Mark Montgomery’s article on CogWorld A Million in Prevention can be Worth Billion of Cure with Distributed AI Systems
Semantic Healthcare Platform
Read Mark Montgomery’s use case scenario Diabetes and the American Healthcare System
View videos here: Kyield YouTube Channel
Summary of Best Use Cases:
Kyield has performed several dozen use case scenarios across most industries and sectors. Two examples are provided.
Accelerated Discovery, Automation, and Augmentation in Pharma
A major pharma company had outsourced much of their IT effort with internal teams of contractors managing the key tasks including drug development within R&D. The company was facing a serious patent cliff that threatened the future of the company, requiring either significantly improved internal R&D efficiency or external acquisitions and licensing at historically high valuations facing considerable uncertainty. A senior scientist at the company reported that it was taking up to a year to have key queries returned from the IT team for critical research.
The Kyield OS provides the ability of each individual to perform their own queries within the security and permission parameters set with the CKO Engine. The Kyield OS also provides prescriptive discovery to expedite both human discovery as well as algorithmically, with machine learning employed to support a continuously improving process. In addition the Kyield OS can be extended to partners in R&D, clinical trials, healthcare providers and payors for improved efficiency and new business opportunities. In this particular case the scenario included a special focus on biomarker discovery and future delivery of real-time diagnostics and therapies, which requires significant additional collaborative work on top of the Kyield OS.
Third party estimates of the unnecessary operational and productivity costs alone due to these backups were approximately $1 billion annually, not including future value of the drug development pipeline or impact on the future value of the company. A cost-plus performance model can be negotiated for shared risk-reward.
AI Platforms for the Enterprise
Many organizations are now faced with the decision of buy or build an AI system platform. The combination of strategic risk and opportunities, high cost and scarcity of competitive talent, and high values in M&A for AI companies represents a serious challenge. In the auto industry multiple leading companies have determined that autonomous driving technology was a priority to master internally, resulting in aggressive multi-billion USD investments in autonomous tech. However, most organizations are not yet faced with such a clearly defined threat in AI systems and very few can afford to make such large investments with a 5-10 year period prior to revenue. In addition, most organizations need to focus on core organizational issues such as productivity, security and competitiveness. Building AI systems from scratch moving forward will result in recreating universal functions in the enterprise that are very costly, redundant and likely not as competitive.
How do organizations compete in AI and seize the cost benefits of commoditization while enhancing differentiation?
The standard Kyield OS tailors data to each entity based on the unique self-managed profiles of each entity. Data is structured and populated in the natural course of workflow, operating in the background. Knowledge work is automatically enhanced with algorithmics for optimized cognitive ability. Data governance, ownership and control remains with the customer.
The cost of the system is spread over many customers while retaining unique differentiality down to the molecular level when needed such as with healthcare or R&D, thus overcoming the IT commoditization paradox. The Kyield healthcare and HumCat products can then be integrated in a friction-free manner, operating on top of the same Kyield OS for prevention, efficiency and optimized AI augmentation.