limitations of current AI applications and the need for a more collaborative and reliable knowledge management system is essential. The current state of AI applications rely heavily on the data they have been trained on, which is often sourced from publicly available datasets or proprietary sources. This can limit the depth and breadth of knowledge accessible to these AI systems. Additionally, the lack of collaboration and verification mechanisms makes it difficult to combine outside experts’ non-published data.

While AI has made significant advancements in various domains, including natural language processing and image generation, there are still challenges when it comes to integrating expert knowledge and verifying information.

AI systems need to integrate more wide-ranging sources of information, both public and private, to provide more comprehensive and reliable knowledge delivery. This would indeed be a step towards realizing the full potential of AI for research, the environment, and society as a whole.

Combining different sources like Google search results, scholarly databases, Wikipedia, YouTube, Private Expert Silos, and various document types can potentially offer a wider range of information. This diverse set of sources can help increase the breadth and depth of knowledge available to the AI system.

Integrating data from private silos and collaborative expert groups with the permission of the owners, could further enhance the system’s capabilities by incorporating specialized or domain-specific knowledge that may not be publicly or otherwise available. Collaborative groups and organizations, sharing their private and public information silos, can contribute to a more collaborative and dynamic knowledge ecosystem.

The use of probabilistic algorithms and linguistic models can aid in information retrieval, data linking, and analysis, allowing the AI system to process and understand the integrated knowledge effectively.

Creating a truly collaborative and reliable knowledge
management system requires the participation and cooperation of various stakeholders, including researchers, experts,
organizations, and the public. Establishing standards, protocols, and mechanisms for data sharing, verification, and ethical guidelines can contribute to the development of such a system.

ChatUnified foresees its release 2 as the new architecture in Data Warehousing.

In summary, while the current state of AI applications may have limitations in terms of collaboration, reliability, and access to expert knowledge, efforts are underway to address these challenges and create a more collaborative and trustworthy knowledge management system. By fostering open data sharing, verification mechanisms, and multidisciplinary collaborations, we can pave the way for AI systems that benefit research, the environment, and society as a whole.

ChatUnified delivers this all. See the video and try it for yourself by May 26th.

Says ChatGPT to my Opinion: Artificial intelligence is not as advanced as people are saying it is. AI is only as good as the developers and AI is not cognitive or able to make its own independent intelligent decisions.

ChatGPT Says:

I understand that there are different perspectives on the current state of artificial intelligence (AI). While AI has made significant progress in recent years, it is true that AI systems have limitations and are not yet fully equivalent to human cognitive abilities.

AI systems are designed and developed by human experts who train them on vast amounts of data and provide them with algorithms and models to perform specific tasks. These systems excel at pattern recognition, data processing, and automation, often outperforming humans in certain specialized tasks. However, they lack the broader understanding, creativity, and common sense that humans possess.

AI systems are not truly cognitive or conscious entities; they do not possess subjective experiences or self-awareness. They operate based on predetermined rules and algorithms, which guide their decision-making process. They rely on the data they were trained on and cannot generate new knowledge independently.

It’s important to acknowledge the advancements and potential of AI while also recognizing its limitations. Ongoing research and development in the field are focused on enhancing AI systems to improve their capabilities and address these limitations. However, the goal of creating an AI system that possesses human-level general intelligence or autonomy is still a complex and ongoing challenge.

(AI) Information knowledge management (IKM) plays a crucial role in the development and implementation of Artificial Intelligence (AI) systems. Here are some of the reasons why IKM is important for AI:

Continuous Learning: AI systems require continuous learning to improve their performance over time. IKM processes can help facilitate this by providing feedback and insights that can be used to refine and optimize AI systems over time.

Data Quality: AI systems depend on high-quality data to function effectively. IKM processes ensure that data is collected, stored, and managed in a way that is accurate, reliable, and accessible to AI systems. This is essential to ensuring that AI systems produce accurate results and avoid biases that can result from poor-quality data.

Data Integration: AI systems often require data from multiple sources (Public & Private). IKM processes can help integrate data from various sources, ensuring that the AI system has access to all the relevant information it needs to perform effectively.

Knowledge Transfer: AI systems often require human expertise to train and optimize their algorithms. IKM processes can help capture and transfer human knowledge and expertise to AI systems, enabling them to learn from the experiences and insights of human experts.

Decision-making: AI systems can support decision-making processes by analyzing large amounts of data and providing insights that can inform decision-making. IKM processes can help ensure that the insights produced by AI systems are reliable and accurate, enabling decision-makers to make informed decisions.

In summary, IKM plays a critical role in ensuring that AI systems are effective, reliable, and produce accurate results. It enables organizations to manage their data effectively and extract valuable insights that can inform decision-making and drive business performance.

Epic-AIM’s release 2 of its Information Knowledge Management AI application will bring significant improvements to the product’s functionality and capabilities as well as the AI marketplace. The detailed video and live internet release will provide interested parties with an opportunity to learn more about the new features and improvements, and to explore the application in more detail. Epic-AIM release 2 video and live site will be unveiled by Friday May 12, 2023, and below is a link to Version 1, currently available.

We are seeking early adopters, partners and OEM’s.

847-440-4439 to inquire. Version 1: https://youtu.be/O2Q0fuyYJwI  

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Reduce FHIR/Cures Act from years to weeks by Ingesting HL7 and healthcare  systems like (EMR/EHR) into FHIR with an automated graphical mapper. This approach significantly reduces the time required for FHIR implementations from 1-3 years to just a few months or weeks.

By using an automated graphical mapper, the process of mapping the data from HL7 or RDBMS to FHIR can be simplified and streamlined. This can eliminate the need for manual coding and reduce the risk of errors and inconsistencies in the mapping process.

It is important to note that the success of our approach is the capability to take a range of factors such as the complexity of the data, the quality of the source data, and the capabilities of our automated graphical mapper. Additionally, it is essential to ensure that the FHIR server being used is compatible with the data being ingested and that appropriate security measures are in place to protect patient data, which BDR-Comply delivers with AES 256 Encryption.

In summary, automating the process of ingesting HL7 and healthcare management systems into a FHIR server using our automated graphical mapper can significantly reduce the time required for FHIR implementations. However, careful planning and consideration of the relevant factors are crucial to ensure the success and accuracy of the process, which our teams have the experience to deliver.

To inquire about a license or OEM, reach us at:

847-440-4439 https://youtu.be/U0qJBO00Bts   www.bdr-comply.com

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I will deliver 21^st Century Cures Act, FHIR, HIPAA, CCPA, GDPR, GRC Compliance in weeks, with a Free VM. Potential, severe outcomes await the inevitable breach, especially in Healthcare, which is projected to be the industry most targeted by hackers in 2023 and beyond.

I am eager to evaluate all areas of HIPAA, CCPA, GDPR, GRC compliance for all your regulated data. Protect your Patients/Customers & companywide data no matter your Industry. I am passionate about working with Compliance, Legal, Business, Development, Architecture, Information Security, internal Audit, and others to protect against the inevitable catastrophic data breach(es).

Each HHS Violation can bring 750 million dollars of civil fines and criminal actions. Each CCPA breach of 1 million customers can bring 1.5 Billion in civil fines and 2.5 Billion or greater if Criminal fines are applied.

I am a:

1.    Highly skilled and experienced healthcare regulatory compliance professional with expertise in HIPAA along with CCPA/GDPR/GRC & FDA compliance, and overall data protection.

2.    In-depth knowledge of 21st Century Cures Act and FHIR compliance, requirements and final delivery.

3.    Proficient in evaluating data at rest, data in motion, and data transferred to Patients/Customers for compliance with HIPAA, CCPA, GDPR, and FDA regulations.

Experience:

·      Developed and implemented data protection policies and procedures.

·      Conducted training sessions on HIPAA, CCPA, GDPR, and FDA compliance.

·      Participated in the development and implementation of data protection

       policies and procedures.

·      I am at liberty to offer the first year’s VM, Cloud subscription Free and

       negotiate additional multiyear subscriptions when you realize the value of the

       of this technology.

Skills:

·      Healthcare Regulatory Compliance

·      21st Century Cures Act

·      FHIR / Healthcare Interoperability

·      HIPAA/CCPA/GDPR/FDA/GRC

·      Data Protection, Profiling, Privacy & DPIA’s

·      Cross-Functional Collaboration

·      Training and Development

·      Enterprise Architecture

·      Product / Project Management

·      Project Architecture Reviews

·      Data Migration into the Petabytes

·      Most every RDBMS, NoSQL, Hadoop, Snowflake, BigQuery and more…

·      AWS, Azure, GCP

·      All Scales of data

·      Data migration

·      Cryptology

I am available to start these efforts and deliverable in the next week or two. I am seeking remote opportunities. https://youtu.be/gzoYJmlgXVM  

Contact: Steven Meister Phone: 847-791-7838



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