Will AI Infrastructure Help Enhance Healthcare Outcomes?

– Enabling Transparent Privacy in Healthcare

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Original Documentation and Analysis – SBIR Opportunities Report for AI Healthcare Infrastructure prepared by Josh Banks, then Developed into a Technical White paper by Michael Noel and the DeReticular Team.

Named Data Home Repository DeReticular/Confidential

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Table of Contents

1. Introduction and Location Context

2. Executive Summary

3. NVIDIA CLARA Healthcare System Overview

4. Opportunities by Focus Area

Grant Funding Opportunity 1

Open Topic for Outdoor Capable Perception System for Autonomous Medical Applications (Direct to Phase II)

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 2

Wearable Sensors to Monitor Environmental and Occupational Impacts on Brain Health

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 3

Accelerate the commercialization of technologies targeting heart, lung, blood, and sleep disorders.

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 4

Commercialization of technologies for heart, lung, blood, and sleep

disorders

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 5

Artiﬁcial Intelligence for Aided Driving of Ground Combat Vehicles

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 6

AI-Enabled Source Selection Solution for Contract Proposal Evaluation

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 7

AI-enabled Healthcare Portfolio Management

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Grant Funding Opportunity 7 Bonus

Medical Services to accelerate the commercialization of technologies targeting heart, lung, blood, and sleep disorders.

Local Healthcare Outcomes

NVIDIA CLARA Medical Services

Implementation Strategy

Application Tips

Glossary of Terms

Meeting the growing demand for improved outcomes, better efficiency, lower costs, and more patient-centered care is the ultimate objective for the healthcare industry.

The increasingly complex and technologically driven Healthcare environment is a multifaceted response to this demand.

For decades, this Healthcare System has been adding and accruing complexity, increasing costs, obfuscating results for providers and Patients, and insulating payor networks.

Today, the risks are no longer just about improving outcomes, but also about enhancing the quality of life, reducing morbidity, promoting faster recovery, and preventing disease and its progression.

Global populations are aging, leading to a higher prevalence of chronic conditions and a greater overall demand for healthcare services, straining existing resources and capacity, necessitating more efficient patient flow, bed management, and resource allocation to ensure timely and appropriate care.

As Patients are becoming more informed and engaged in their healthcare decisions. They are beginning to expect transparency, convenience, personalized care, and a seamless Patient experience. This drives the need for more efficient scheduling, communication, access to information, and streamlined patient journeys.

There is a significant and growing shortage of healthcare professionals across various disciplines (nurses, doctors, specialists). This, coupled with high rates of clinician burnout, means that existing staff are often stretched thin. Improving efficiency is crucial to reducing workload, preventing burnout, and enabling healthcare workers to focus on direct patient care and enhancing patient experiences. I think this is important enough to repeat, – Improving efficiency is crucial to reducing workload, preventing burnout, and enabling healthcare workers to focus on direct patient care and enhancing patient experiences.

Increasing complexity requirements for Providers are pressuring margins.

Providers need radically more efficient revenue cycle management processes, from patient registration to claims processing and denial management, to maintain financial stability.

Technology offers immense opportunities to Integrate new diagnostic tools, treatment modalities, and digital health solutions such as EHRs, telemedicine, and AI.

Artificial Intelligence’s (AI) potential impact on healthcare is particularly profound. The promise of AI to revolutionize healthcare outcomes has become a central topic of discussion.

This Technical White Paper, “Will AI Infrastructure Help Enhance Healthcare Outcomes?” delves into the intricate relationship between AI and healthcare, exploring not only the pathways through which AI can improve the quality of medical care but also focuses on the hardware and infrastructure necessary to operate AI Enabled Healthcare Campuses.

A critical aspect of integrating AI into healthcare lies in addressing the paramount concern of patient privacy, a challenge that necessitates innovative approaches to data management and algorithmic design. A transparent AI infrastructure can not only enhance diagnostic accuracy, personalize treatment plans, and streamline operational efficiencies but also safeguard sensitive patient information, thereby fostering trust and improving the Healthcare Patient Experience.

This Technical White Paper focuses on meeting the needs of underserved American Rural Areas.

Why?

Well, technology seems to grow faster in areas where there is no incumbent technology.

Also, there is an abundance of Grant funding available for communications infrastructure which is necessary for most medical-AI-enabled workflows in Rural Areas.

Network Effect Growth, Grant Funding for Communications Infrastructure, and a Very Large Underserved Market make Rural areas attractive from this perspective.

The Data to follow was developed based on actual Grant Availability for a Small Rural Town in Texas along Highway 64 and was first generated on March 28, 2025.

Since that time, using a recently developed proprietary Agentic Workflow and Multiple AI Applications, the DeReticular Team has generated Grant availability, location-specific qualifications, and supporting documentation for a few hundred locations in the United States and South Africa.

The results are similar across the board for almost any location in Rural America. A dozen or so locations are currently under MVP development as AI Innovation Campuses with a WIFI 7 Mesh Network connecting a Cluster of 1,000 NVIDIA AI servers, H100 or equivalent.

Here, Private funds are leveraged along with Grant funding in a unique managed service agreement to fund infrastructure based on the revenue earned from the leasing of the same very high high-demand AI Compute, Storage, and Communications network.

The DeReticular team is available to discuss any questions you might have.

Contact information is available on our Public Website, dereticular.com.

Please just remember, there is no spoon here.

Location Context

This report focuses on SBIR opportunities applicable to developing AI-powered healthcare infrastructure for a small town in Texas along Highway 64 we can call this location Texas64Campus1. There are 2 locations nearby with similar characteristics. We can refer to them as Texas64Campus2 and Texas64Campus3.

Executive Summary

The opportunities identiﬁed are particularly relevant for establishing advanced medical services leveraging the NVIDIA CLARA AI Healthcare platform by first Deploying Decentralized Public Infrastructure Networks (DePIN) (go ahead and google it I will wait) to support the advanced healthcare applications enabled only inside the Mesh network (InNet}. The Goal here is to Enhance access to healthcare and improve outcomes in rural Texas.

This report identiﬁes 7 SBIR Grant Funding opportunities across 2 focus areas relevant to implementing AI-powered healthcare infrastructure for the 3 Texas Campuses along Highway 64. The opportunities span multiple agencies with a speciﬁc focus on leveraging NVIDIA CLARA for medical services and healthcare applications.

NVIDIA CLARA Overview – NVIDIA CLARA is a healthcare application framework for AI-powered medical imaging and genomics.

Key capabilities include:

Medical Imaging: AI-assisted diagnostic tools, image reconstruction, and

workﬂow enhancement.

Genomics: Accelerated genomic analysis and precision medicine

applications.

Smart Medical Campuses: Infrastructure for connected medical devices and real-time patient monitoring, logistics, communications, diagnosis, treatment, and transportation.

Deployment Flexibility: Edge-to-cloud Mesh Network allowing for deployment in resource-constrained settings

For rural and small-town applications, CLARA oﬀers potential for bringing

advanced diagnostic capabilities to underserved areas through optimized Infrastructure deployments.

7 Grant Opportunities by Focus Area Healthcare

Grant Funding Opportunity 1

Open Topic for Outdoor Capable Perception System for Autonomous Medical Applications (Direct to Phase II)

Agency: DOD

Deadline: April 23, 2025

Description: OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Combat Casualty Care.

The SBIR opportunity titled Open Topic for Outdoor Capable Perception System for Autonomous Medical Applications could signiﬁcantly improve outcomes in rural Texas by enhancing healthcare delivery and AI infrastructure in several ways.

Improved Emergency Response: The perception system could enable autonomous medical vehicles to navigate eﬀectively in outdoor

environments, ensuring timely medical assistance during emergencies. This is particularly crucial for small towns where access to healthcare facilities may be limited.

Telemedicine Integration: By leveraging AI capabilities, the system could facilitate remote consultations and diagnostics, allowing residents to receive medical advice without the need to travel long distances. This would be especially beneﬁcial for elderly or mobility-impaired individuals.

Data Collection and Analysis: The perception system could gather health-related data from the community, enabling local healthcare providers to analyze trends and improve public health initiatives. This data could inform preventive measures and resource allocation.

Training and Education: The implementation of such advanced technology could provide opportunities for local healthcare professionals to receive training in AI and autonomous systems, enhancing their skills, and improving the overall quality of care.

Economic Development: Establishing a healthcare-focused AI infrastructure could attract tech companies and startups to the area, fostering economic growth and job creation. This could lead to a more robust local economy and improved healthcare services. Overall, the integration of an outdoor capable perception system for autonomous medical applications could transform healthcare delivery making it more eﬃcient, accessible, and responsive to community needs.

Telemedicine and Remote Diagnostics: By leveraging NVIDIA CLARA’s AI capabilities, healthcare providers can conduct remote consultations and diagnostics, allowing patients in rural areas to receive timely medical advice without the need for long-distance travel or infrequent exams.

AI-Powered Imaging: CLARA can enhance medical imaging processes, such as X-rays and MRIs, by providing advanced image analysis and interpretation, leading to quicker and more accurate diagnoses.

Predictive Analytics for Patient Care: Utilizing CLARA’s machine learning

algorithms, healthcare providers can analyze patient data to predict health trends and potential emergencies, enabling proactive care and resource allocation.

Training and Simulation: CLARA can be used to create realistic

training simulations for local healthcare professionals, improving their skills in emergency response and medical procedures relevant to casualty care.

Integration with Wearable Devices: By integrating CLARA with wearable health monitoring devices, healthcare providers can continuously monitor patients’ vital signs and health metrics, ensuring immediate response in case of emergencies.

Implementation Approach: To implement an outdoor capable perception

system for autonomous medical applications in a small town in Texas, we can leverage decentralized networks, AI infrastructure, and mesh networks as follows:

Decentralized Network Architecture: Establish a decentralized network that connects various medical facilities, emergency responders, and community health workers. This network will facilitate real-time data sharing and communication, ensuring that all stakeholders have access to critical information during emergencies.

AI-Driven Decision Support: Integrate AI algorithms that analyze data from various sources, including patient health records, environmental sensors, and real-time location data. This AI infrastructure will assist in making informed decisions regarding patient care, resource allocation, and route optimization for emergency medical services (EMS). This provides for

Mesh Network Deployment: Implement a mesh network to ensure reliable communication in areas with limited connectivity. This network will allow devices to communicate with each other directly, creating a resilient communication system that can operate even if some nodes fail. This is particularly important in rural areas where traditional cellular networks may be unreliable for High data throughput Medical applications.

Autonomous Medical Units: Develop autonomous medical units (AMUs)

equipped with perception systems that can navigate the town

independently. These units can be deployed to provide immediate care, transport patients, or deliver medical supplies.

The perception system will utilize AI to identify obstacles, assess environmental conditions, and make real-time navigation decisions.

Community Engagement and Training: Engage the local community in the implementation process by providing training on how to use the new

systems and technologies.

This will ensure that residents are familiar with autonomous medical units and can eﬀectively communicate with the

decentralized network during emergencies.

Pilot Program and Feedback Loop: Launch a pilot program to test the

system in a controlled environment, gather feedback from users and

stakeholders to reﬁne the technology and processes before full-scale

implementation.

This iterative approach will help address any challenges

and improve the overall eﬀectiveness of the system.

By combining decentralized networks, AI infrastructure, and mesh networks, this approach aims to enhance the responsiveness and eﬃciency of medical services in any small town, ultimately improving patient outcomes and community health globally.

In this manner, the Dereticular team develops Locally and globally.

Grant Opportunity 2

Wearable Sensors to Monitor Environmental and Occupational Impacts on Brain Health

Agency: DOD

Solicitation Number: Confidential

Deadline: April 23, 2025

Description: OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Integrated Sensing and Cyber.

Relevance to Highway 64 Town: The SBIR opportunity signiﬁcant beneﬁts for a small town in Texas, particularly in the realms of healthcare and AI infrastructure.

Enhanced Healthcare Monitoring: The wearable sensors can provide real-time data on environmental factors such as air quality, noise levels, and exposure to harmful substances. This data can be crucial for local healthcare providers to monitor the health of residents, especially those with pre-existing conditions or vulnerable populations such as children and the elderly. By identifying environmental risks, healthcare professionals can implement preventive measures and tailor health interventions more eﬀectively.

Data-Driven Decision Making: The integration of AI infrastructure with

wearable sensors can facilitate the analysis of large datasets collected from the community.

This can lead to insights into how environmental factors correlate with brain health issues, enabling local health authorities to make informed decisions regarding public health policies and resource allocation.

Community Engagement and Awareness: The implementation of such

technology can foster community engagement by raising awareness about environmental health impacts.

Educational programs can be developed to inform residents about the importance of monitoring their environment and how it aﬀects their health, leading to a more proactive approach to personal and community health.

Economic Development: By positioning the town as a leader in health

technology and environmental monitoring, it could attract investments and partnerships with tech companies and research institutions.

This could lead to job creation and economic growth, enhancing the overall quality of life in the community.

Research Opportunities: The data collected from these wearable sensors

can also provide valuable research opportunities for local research institutions, potentially leading to innovations in healthcare and

environmental science that could beneﬁt not just the town but also

contribute to broader scientiﬁc knowledge.

In summary, the integration of wearable sensors to monitor environmental and occupational impacts on brain health can signiﬁcantly enhance healthcare delivery, promote community awareness, drive economic growth, and foster research opportunities in any rural community,

NVIDIA CLARA can be utilized to enhance medical services by integrating wearable sensors that monitor environmental and occupational impacts on brain health.

The platform can analyze data collected from these sensors in real-time, providing healthcare professionals with insights into how local environmental factors, such as air quality and occupational hazards, aﬀect the brain health of residents.

Data Integration and Analysis: CLARA can aggregate data from various

wearable sensors, enabling comprehensive analysis of individual and Community health trends.

This can help identify at-risk populations and tailor interventions accordingly.

Telehealth Services: By leveraging CLARA’s AI capabilities, healthcare

providers can oﬀer remote consultations, allowing residents to receive

timely medical advice without the need to travel long distances to

healthcare facilities.

Predictive Analytics: The platform can utilize machine learning algorithms to predict potential health issues based on environmental data, allowing for proactive healthcare measures and early interventions.

Personalized Health Monitoring: CLARA can facilitate personalized health monitoring by providing tailored recommendations based on individual sensor data, helping residents manage their health more eﬀectively.

Community Health Programs: The insights gained from CLARA can inform community health programs aimed at reducing environmental risks improving overall brain health, and fostering a healthier community.

In summary, NVIDIA CLARA can signiﬁcantly enhance medical services in any rural town by providing advanced data analysis, telehealth capabilities, predictive analytics, personalized health monitoring, and support for community health initiatives.

Implementation Approach:

To implement a system for monitoring environmental and occupational impacts on brain health in a small town we can leverage decentralized networks, AI infrastructure, and mesh networks as follows:

Decentralized Sensor Deployment: Deploy wearable sensors among the

town’s residents, particularly targeting workers in high-risk occupations

(e.g., agriculture, construction).

These sensors will collect real-time data on environmental factors such as air quality, noise levels, and exposure to hazardous materials.

Mesh Network Connectivity: Establish a mesh network to facilitate

communication between the wearable sensors and a central data

processing unit.

This network will ensure that data can be transmitted even in areas with poor connectivity, as each device can relay information to others, creating a robust communication system.

AI-Driven Data Analysis: Utilize AI algorithms to analyze the collected data for patterns and correlations between environmental factors and brain health indicators.

This analysis can help identify speciﬁc risks associated with diﬀerent occupations and environmental conditions.

Community Engagement and Feedback Loop: Involve the community by

providing them with access to the data and insights generated.

Create a feedback loop where residents can report their health conditions and experiences, which can be integrated into the AI model for continuous improvement.

Health Monitoring and Alert: Develop an application that provides real-time health monitoring and alerts to users based on the data collected.

For instance, if air quality drops below a certain threshold, users can receive notiﬁcations to take precautions.

Collaboration with Local Health Authorities: Partner with local health

authorities and organizations to ensure that the ﬁndings from the data

analysis are used to inform public health policies and interventions aimed at protecting brain health in the community.

Scalability and Adaptation: Design the system to be scalable, allowing for the addition of more sensors and nodes as needed. Then adapt the AI models based on new data and emerging environmental concerns to ensure ongoing relevance and eﬀectiveness.

Grant Opportunity 3

Accelerate the commercialization of technologies targeting heart, lung, blood, and sleep disorders

NHLBI SBIR Phase IIB Bridge Awards

Agency: NHLBI

Solicitation Number: Confidential

Deadline: February 27, 2027

Description: This funding initiative is designed to accelerate the

commercialization of technologies targeting heart, lung, blood, and sleep

disorders. The open date is January 26, 2025, with a close date of February 27, 2027. This program is particularly relevant for healthcare innovations that can improve Medical Outcomes.

Relevance to Highway 64 Town: The NHLBI SBIR Phase IIB Bridge Awards present a signiﬁcant opportunity for small towns to enhance their healthcare services, particularly through the integration of innovative technologies targeting heart, lung, blood, and sleep disorders.

Given the program’s focus on improving medical services in rural areas,

local healthcare providers can leverage this funding to develop and

implement AI-driven solutions that address speciﬁc health challenges faced by the community.

Additionally, telemedicine solutions powered by AI can facilitate remote consultations, making healthcare more accessible for residents who may have diﬃculty traveling to larger medical facilities.

By enhancing healthcare infrastructure with advanced technologies, small towns can improve the quality of life for their residents and ensure that they receive timely and eﬀective medical care.

–

NVIDIA CLARA Application: NVIDIA CLARA can be utilized to enhance medical services in several ways:

Telehealth Solutions: CLARA can power telehealth platforms that enable

remote consultations between patients and healthcare providers.

This is particularly beneﬁcial in rural areas where access to specialists is limited. By using AI-driven diagnostics, healthcare providers can oﬀer accurate assessments and treatment plans without the need for patients to travel long distances.

AI-Powered Imaging: The platform can enhance medical imaging services by providing advanced AI algorithms for analyzing X-rays, MRIs, and CT scans. In Agentic, or Agent to Agent workflows, Test results for most, analyzing X-rays, MRIs, and CT scans are delivered to the patient in the initial exam, by the exam provider.

This can lead to quicker diagnoses of heart, lung, and blood disorders, which are critical in rural settings where timely intervention is essential.

Predictive Analytics: CLARA can analyze patient data to identify trends and predict potential health issues before they become critical. This proactive approach can help healthcare providers in rural areas manage chronic conditions more eﬀectively, reducing hospital visits and improving patient outcomes.

Training and Education: The platform can be used to train local healthcare professionals in the latest medical technologies and practices. By providing access to AI-driven simulations and educational resources, CLARA can help upskill the workforce in rural areas, ensuring they are equipped to handle complex medical cases.

Remote Monitoring: CLARA can facilitate remote patient monitoring through wearable devices that track vital signs and health metrics. This data can be analyzed in real-time, allowing healthcare providers to intervene early if any concerning trends are detected, thus improving patient care in rural communities.

Resource Optimization: By utilizing AI to streamline administrative tasks,

CLARA can help rural healthcare facilities operate more eﬃciently. This

includes optimizing scheduling, managing patient ﬂow, and reducing wait

times, which can signiﬁcantly enhance the overall patient experience.

In summary, NVIDIA CLARA can play a pivotal role in transforming healthcare delivery by leveraging AI to improve access, eﬃciency, and

quality of care for heart, lung, blood, and sleep disorders.

–

Implementation Approach: To implement a healthcare innovation strategy in a small town in Texas leveraging decentralized networks, AI infrastructure, and mesh networks, the following approach can be adopted:

Community Engagement and Needs Assessment: Begin by engaging with local healthcare providers, community leaders, and residents to assess speciﬁc health needs related to heart, lung, blood, and sleep disorders. This will help tailor the technology to address the most pressing issues.

Decentralized Health Data Management: Establish a decentralized health data management system that allows patients to securely store and share their health data with healthcare providers. This can be achieved using blockchain technology to ensure data integrity and privacy, enabling patients to have control over their own health information.

AI-Driven Health Analytics: Implement AI algorithms to analyze the

collected health data for predictive analytics. This can help identify at-risk

populations, track disease outbreaks, and personalize treatment plans. AI

can also assist in remote diagnostics and monitoring, reducing the need for patients to travel for care.

Mesh Network Infrastructure: Develop a mesh network to ensure reliable

connectivity throughout the town, especially in rural areas where

traditional internet services may be lacking. This network will facilitate real-time communication between patients and healthcare providers, enabling telehealth services and remote patient monitoring.

Telehealth Services: Launch telehealth services that utilize the AI-driven

analytics and mesh network to provide remote consultations, follow-ups,

and health education. This will improve access to healthcare for residents,

particularly those with mobility issues, chronic conditions, or other high-risk diagnosis.

Training and Support: Provide training for healthcare providers on using the new technologies and data management systems. Additionally, oﬀer

support for patients to help them navigate telehealth services and understand their health data.

Partnerships and Funding: Seek partnerships with local universities, tech

companies, and healthcare organizations to secure additional funding and

resources. This can enhance the technological infrastructure and expand

the reach of the initiative.

Monitoring and Evaluation: Establish metrics to monitor the eﬀectiveness of the implemented technologies and services. Regularly evaluate the impact on health outcomes, patient satisfaction, and overall community health to make necessary adjustments and improvements.

Grant Opportunity 4

Commercialization of technologies for heart, lung, blood, and sleep

disorders

Also Relevant To: Medical Services NHLBI SBIR Phase IIB Small Market Awards

Agency: NHLBI

Solicitation Number: Confidential

Deadline: February 27, 2027

Description: Similar to the Bridge Awards, this program focuses on the

commercialization of technologies for heart, lung, blood, and sleep

disorders, with the same timeline as the Bridge Awards

Relevance to Highway 64 Town: The NHLBI SBIR Phase IIB Small Market Awards program can signiﬁcantly beneﬁt a small town by fostering advancements in healthcare and AI infrastructure.

Firstly, the focus on the commercialization of technologies for heart, lung,

blood and sleep disorders align with the pressing healthcare needs of

rural communities, which often face challenges in accessing specialized

medical care.

By supporting local startups or businesses that develop innovative healthcare solutions, the program can enhance the availability of

advanced diagnostic tools and treatment options, ultimately improving

patient outcomes. Moreover, the integration of AI in healthcare can streamline operations in local clinics and hospitals, enabling better patient management, predictive analytics for disease outbreaks, and personalized treatment plans.

This can lead to more eﬃcient use of resources and reduced healthcare costs for residents. Additionally, the program can stimulate economic growth by attracting investments and creating jobs in the healthcare technology sector, which can be particularly beneﬁcial for a small town. As local businesses thrive, the community can experience an uplift in overall quality of life, making it a more attractive place for families and professionals.

In summary, the NHLBI SBIR Phase IIB Small Market Awards can catalyze a transformation in healthcare delivery and economic development in small towns all over America.

NVIDIA CLARA Application: NVIDIA CLARA can be utilized in a rural town to enhance medical services by providing advanced AI-driven solutions for the diagnosis and treatment of heart, lung, blood, and sleep disorders.

The platform can facilitate remote patient monitoring through AI algorithms that analyze data from wearable devices, enabling healthcare providers to track patients’ vital signs and detect anomalies in real-time. Additionally, CLARA’s imaging capabilities can assist in the interpretation of medical images, such as X-rays and MRIs, improving diagnostic accuracy and reducing the need for patients to travel long distances for specialized care.

Furthermore, CLARA can support telemedicine initiatives, allowing healthcare professionals to conduct virtual consultations and provide timely interventions, thereby increasing access to quality healthcare in underserved areas.

By leveraging NVIDIA CLARA, Rural America can enhance its healthcare infrastructure, improve patient outcomes, and foster a more eﬃcient healthcare delivery system.

–

Implementation Approach: To implement a decentralized network leveraging AI infrastructure and mesh networks for a small town in Texas under the NHLBI SBIR Phase IIB Small Market Awards, the following approach can be adopted:

Community Engagement and Needs Assessment: Begin by engaging with local healthcare providers, community leaders, and residents to assess the speciﬁc needs related to heart, lung, blood, and sleep disorders. This will help tailor the technology solutions to the community’s unique challenges.

Decentralized Health Data Network: Establish a decentralized health data network that allows for the secure sharing of patient data among local healthcare providers. This network can utilize blockchain technology to ensure data integrity and privacy, enabling real-time access to patient

information for better diagnosis and treatment.

AI-Driven Health Analytics: Integrate AI infrastructure to analyze health

data collected from the decentralized network. AI algorithms can identify

patterns and predict health risks, allowing for proactive interventions. This

can include personalized health recommendations and alerts for patients at risk of developing serious conditions.

Mesh Network for Connectivity: Deploy a mesh network to ensure reliable internet connectivity throughout the town, especially in areas with limited access. This network will support telehealth services, enabling remote consultations and monitoring for patients with chronic conditions.

Telehealth and Remote Monitoring Solutions: Develop telehealth platforms that utilize the decentralized network and AI analytics to provide remote monitoring and consultations. Patients can use wearable devices to track their health metrics, which are then analyzed by AI to provide insights and alerts to healthcare providers.

Education and Training Programs: Implement training programs for

healthcare providers and community members on using the new

technologies eﬀectively. This will ensure that the community is equipped to leverage the beneﬁts of the decentralized network and AI tools.

Pilot Program and Feedback Loop: Launch a pilot program to test the

implementation in a controlled environment. Gather feedback from users to reﬁne the technology and address any challenges before a full-scale rollout.

Partnerships and Funding: Seek partnerships with local universities, tech

companies, and healthcare organizations to enhance the project’s capabilities and secure additional funding. Collaborating with stakeholders can also facilitate knowledge sharing and resource pooling.

Sustainability and Scalability: Plan for the long-term sustainability of the

project by exploring funding opportunities, including grants and local

government support. Additionally, design the system to be scalable,

allowing for expansion to neighboring towns or regions as needed.

Grant Funding Opportunity 5

Artiﬁcial Intelligence for Aided Driving of Ground Combat Vehicles

Agency: Not speciﬁed

Solicitation Number: Confidential

Deadline: March 26, 2025

Description: Open from February 5, 2025, to March 26, 2025.

Relevance to Highway 64 Town: The SBIR opportunity titled ‘Artiﬁcial

Intelligence for Aided Driving of Ground Combat Vehicles could signiﬁcantly beneﬁt a small town in Texas along Highway 64 in several ways, particularly in healthcare and AI infrastructure.

Enhanced Emergency Response: AI-driven vehicles can improve emergency medical services (EMS) by enabling faster and more eﬃcient transportation of patients to healthcare facilities. With AI navigation, ambulances can avoid traﬃc and optimize routes, ensuring timely medical assistance, which is crucial in rural areas where distances to hospitals can be signiﬁcant.

Telemedicine Accessibility: The development of AI infrastructure can

support telemedicine initiatives. AI can facilitate remote consultations and

diagnostics, allowing residents to access healthcare services without

needing to travel long distances. This is particularly beneﬁcial for elderly or mobility-challenged individuals.

Data Collection and Analysis: AI systems can gather and analyze health

data from the community, identifying trends and health issues that may

require attention. This data can help local healthcare providers tailor their

services to meet the speciﬁc needs of the population, improving overall

health outcomes.

Job Creation and Training: The introduction of AI technology in the town can create new job opportunities in the tech and healthcare sectors. Local educational institutions can develop training programs focused on AI and healthcare, equipping residents with skills for future employment in these growing ﬁelds.

Infrastructure Development: The focus on AI for combat vehicles may lead to improvements in local infrastructure, such as better roads and

communication systems, which can also beneﬁt civilian transportation and healthcare logistics.

Community Engagement: The integration of AI in local services can foster community engagement and awareness about technology’s role in

improving quality of life, and encouraging residents to participate in discussions about future developments in healthcare and technology.

–

NVIDIA CLARA Application: NVIDIA CLARA can be utilized in a rural

town to enhance medical services by providing advanced AI-driven

healthcare solutions.

The platform can facilitate remote patient monitoring through AI algorithms that analyze data from wearable devices, ensuring timely interventions for chronic conditions.

Additionally, CLARA’s imaging capabilities can support teleradiology services, allowing local healthcare Providers to send medical images to specialists for accurate diagnosis without the need for patients to travel long distances. Furthermore, CLARA can assist in training local healthcare professionals by providing access to AI-powered simulations and educational resources, improving their skills in emergency response and patient care. Overall, NVIDIA CLARA can bridge the healthcare gap in rural areas by delivering high-quality, accessible medical services.

Implementation Approach: To implement an AI-driven aided driving

system for ground combat vehicles in a small town in Texas, we can

leverage decentralized networks, AI infrastructure, and mesh networks as

follows:

Decentralized Network Architecture: Establish a decentralized network that connects various vehicles, sensors, and control systems within the town. This network will allow for real-time data sharing and decision-making without relying on a central server, enhancing resilience and reducing latency.

AI Infrastructure: Develop an AI infrastructure that utilizes machine learning algorithms to analyze data from vehicles and the surrounding environment based on Proof of Location {POL) based on proof of proximity (POP). Additional data is available in the Technical White Paper Carbon Consuming Circular Economies also written by the DeReticulat team members Michael Noel and Ash Aly. This infrastructure will be capable of processing inputs from various sensors (e.g., cameras, LIDAR, POL networks, GPS) to assist in navigation, obstacle detection, and threat assessment.

Mesh Network Deployment: Implement a mesh network to ensure robust

communication between vehicles and ground control units. This network

will facilitate seamless data exchange, allowing vehicles to share

information about their status, location, and any detected hazards. The

mesh network will also support redundancy, ensuring that communication

remains intact even if some nodes fail.

Local Data Processing: Utilize far-edge computing to process data locally on the vehicles, reducing the need for constant communication with a central server. This will enable faster response times and allow the vehicles to operate eﬀectively in areas with limited connectivity.

Community Engagement: Involve local stakeholders, including town oﬃcials, law enforcement, and residents, in the development process. This will ensure that the system meets the speciﬁc needs of the community and addresses any concerns regarding safety and privacy.

Pilot Program: Launch a pilot program to test the AI-aided driving system in a controlled environment. Gather feedback and data to reﬁne the

algorithms and improve the overall system before full-scale deployment.

Training and Support: Provide training for local operators and support staﬀ to ensure they are equipped to manage and maintain the AI systems

eﬀectively.

By integrating these components, the small town in Texas can create a cutting-edge AI-driven aided driving system for ground combat vehicles that enhances safety, eﬃciency, and operational eﬀectiveness.

Funding: Grant Opportunity 6

AI-Enabled Source Selection Solution for Contract Proposal Evaluation

Agency: Not speciﬁed

Solicitation Number: Confidential

Deadline: March 26, 2025

Description: Open from February 5, 2025, to March 26, 2025.

Relevance to Highway 64 Town: The ‘AI Enabled Source Selection Solution for Contract Proposal Evaluation’ SBIR opportunity could signiﬁcantly beneﬁt a small town in Texas along Highway 64 by enhancing the eﬃciency and eﬀectiveness of healthcare procurement processes. By leveraging AI technology, the town could streamline the evaluation of healthcare service proposals, ensuring that the best options are selected based on data-driven insights rather than subjective criteria.

This could lead to improved healthcare services, as the town would be able to attract high-quality providers and negotiate better contracts.

Moreover, the implementation of AI infrastructure would not only modernize the town’s healthcare system but also create opportunities for local businesses to engage in tech-driven healthcare solutions.

This could foster a culture of innovation, attract talent, and potentially lead to job creation in the tech and healthcare sectors.

Overall, this SBIR opportunity could catalyze a transformation in the town’s healthcare landscape, making it more responsive to community needs and enhancing the quality of life for its residents.

–

NVIDIA CLARA Application: NVIDIA CLARA can be utilized in a rural Texas town to enhance medical services through the following applications:

Telemedicine: By leveraging NVIDIA CLARA’s AI capabilities, healthcare providers can oﬀer remote consultations, allowing patients to receive medical advice without the need to travel long distances.

This is particularly beneﬁcial for elderly patients or those with mobility issues.

Medical Imaging: CLARA’s advanced imaging algorithms can assist local healthcare facilities in analyzing medical images (like X-rays, MRIs, and CT scans) more accurately and quickly. This can lead to faster

diagnoses and treatment plans, especially in emergencies.

Predictive Analytics: The platform can analyze patient data to predict health trends and outbreaks, enabling proactive measures to be taken in the community. This is crucial in rural areas where healthcare resources may be limited.

Training and Education: CLARA can be used to create virtual training programs for local healthcare providers, ensuring they are up-to-date with the latest medical practices and technologies.

Resource Optimization: By analyzing patient ﬂow

and resource utilization, CLARA can help optimize the allocation of medical staﬀ and equipment, ensuring that the rural healthcare facility operates eﬃciently.

Overall, NVIDIA CLARA can signiﬁcantly improve the quality and accessibility of healthcare services in rural Texas, addressing the unique challenges faced by these communities.

Implementation Approach: To implement an AI-enabled source Selection Solution for Contract Proposal Evaluation in a Small Town in Texas, we can leverage decentralized networks, AI infrastructure, and mesh networks through the following approach:

Decentralized Data Collection: Establish a decentralized network where

local businesses, contractors, and community members can submit their

proposals and relevant data. This can be facilitated through a blockchain-

based platform that ensures transparency and security in data submission.

AI Infrastructure Development: Develop an AI-driven evaluation system that utilizes machine learning algorithms to analyze the submitted proposals.

This system can be hosted on cloud infrastructure to ensure scalability and accessibility. The AI can be trained on historical data and criteria speciﬁc to the town’s needs, ensuring that the evaluation process is tailored and eﬃcient.

Mesh Network Implementation: Create a mesh network within the town to facilitate communication between local stakeholders. This network can

support real-time data sharing and collaboration among contractors,

evaluators, and community members, ensuring that everyone has access

to the necessary information for proposal evaluation.

Community Engagement and Training: Conduct workshops and training

sessions for local businesses and community members to familiarize them

with the new system. This will encourage participation and ensure that all

stakeholders understand how to eﬀectively use the platform for proposal

submissions and evaluations.

Feedback Loop and Iteration: Implement a feedback mechanism where

users can provide insights on the AI evaluation process. This feedback will be crucial for the continuous improvement of the AI algorithms and the overall system, ensuring it meets the evolving needs of the community.

Pilot Program: Launch a pilot program to test the system with a limited

number of proposals. This will allow for adjustments and reﬁnements

before a full-scale rollout, ensuring that the solution is eﬀective and user-friendly.

By integrating decentralized networks, AI infrastructure, and mesh networks, this approach aims to enhance the eﬃciency and transparency of contract proposal evaluations in the small town, fostering local economic growth and community involvement.

Funding: Grant Opportunity 7

AI-enabled Portfolio Management

Agency: Not speciﬁed

Solicitation Number: Confidential

Deadline: March 26, 2025

Description: Open from February 5, 2025, to March 26, 2025

Relevance to Highway 64 Town: The ‘AI-enabled Portfolio Management’ SBIR opportunity could signiﬁcantly beneﬁt a small town in Texas along Highway 64 by enhancing healthcare services and improving AI infrastructure.

Healthcare Optimization: By leveraging AI in portfolio management, local

healthcare providers can better allocate resources, manage patient data,

and optimize treatment plans. This could lead to improved patient

outcomes, reduced wait times, and more eﬃcient use of medical facilities.

Telehealth Services: The integration of AI can facilitate telehealth services, allowing residents to access healthcare remotely. This is particularly beneﬁcial for a small town where access to specialists may be limited. AI can help in triaging patients and providing preliminary diagnoses, ensuring timely care.

Data-Driven Decision-Making: AI-enabled tools can analyze healthcare

trends and patient data, enabling local health authorities to make informed decisions about public health initiatives, vaccination drives, and resource allocation, ultimately leading to a healthier community.

Economic Growth: The development of AI infrastructure can attract tech

investments and create job opportunities in the town. This can lead to a

more robust local economy, with potential partnerships between healthcare providers and tech companies.

Education and Training: The initiative could also foster educational

programs focused on AI and healthcare, equipping the local workforce with skills needed in the evolving job market, thus enhancing the town’s long-term sustainability and growth.

Overall, the ‘AI-enabled Portfolio Management’ opportunity presents a chance for the small town to modernize its healthcare system, improve community health outcomes, and stimulate economic development.

NVIDIA CLARA Application: NVIDIA CLARA can be utilized in a rural Texas town to enhance medical services through several innovative applications.

Firstly, CLARA’s AI capabilities can facilitate remote diagnostics by analyzing medical imaging data, such as X-rays and MRIs, allowing healthcare providers to identify conditions like fractures or tumors without needing a specialist on-site. This is particularly beneﬁcial in rural areas where access to radiologists may be limited.

Secondly, CLARA can support telemedicine initiatives by providing AI-driven decision-support tools for primary care physicians. These tools can analyze patient data and suggest treatment options, ensuring that patients receive timely and accurate care even when specialists are not available locally.

Additionally, CLARA’s predictive analytics can be employed to monitor

community health trends, enabling local health departments to proactively address potential outbreaks or health crises. By analyzing data from various sources, including social determinants of health, CLARA can help prioritize resources and interventions eﬀectively.

Finally, CLARA can enhance patient engagement through personalized health management applications, allowing residents to track their health metrics and receive tailored recommendations.

This can lead to improved health outcomes and greater community involvement in health initiatives. Overall, the integration of NVIDIA CLARA in a rural Texas town can signiﬁcantly improve healthcare accessibility, quality, and eﬃciency.

Implementation Approach: To implement an AI-enabled portfolio management system in a small town in Texas, we can leverage decentralized networks, AI infrastructure, and mesh networks through the following approach:

Decentralized Data Collection: Establish a decentralized network of IoT

devices throughout the town to collect real-time data on various

parameters such as energy consumption, traﬃc patterns, and local

economic activities. This data will be crucial for AI algorithms to analyze

and make informed decisions.

AI Infrastructure Development: Set up a cloud-based AI infrastructure that can process the data collected from the decentralized network. This

infrastructure will utilize machine learning algorithms to analyze trends,

predict future needs, and optimize resource allocation for the town’s

portfolio management.

Mesh Network Implementation: Create a mesh network to ensure reliable communication between IoT devices and the AI infrastructure. This will enhance connectivity, especially in areas with limited internet access, allowing for seamless data transmission and real-time updates.

Community Engagement: Involve local stakeholders, including residents,

businesses, and government oﬃcials, in the development process. Conduct workshops to educate them about the beneﬁts of AI and decentralized systems, ensuring their input is considered in the implementation.

Pilot Program: Launch a pilot program in a speciﬁc area of the town to test the AI-enabled portfolio management system. Monitor its performance, gather feedback, and make necessary adjustments before a full-scale rollout.

Sustainability and Scalability: Design the system with sustainability in mind, ensuring it can adapt to future technological advancements and scale as the town grows. This includes regular updates to the AI algorithms and infrastructure based on new data and community needs.

Performance Metrics: Establish clear performance metrics to evaluate the success of the implementation. This could include improvements in

resource eﬃciency, cost savings, and overall community satisfaction.

By integrating decentralized networks, AI infrastructure, and mesh networks, the small town can enhance its portfolio management capabilities, leading to improved resource allocation and community well-being.

Funding: Grant Opportunity 7 Bonus

Medical Services to accelerate the commercialization of technologies targeting heart, lung, blood, and sleep disorders.

NHLBI SBIR Phase IIB Bridge Awards

Agency: NHLBI

Solicitation Number: Confidential

Deadline: February 27, 2027

Description: This additional funding initiative is designed to accelerate the development of Medical Services and their commercialization of technologies targeting heart, lung, blood, and sleep disorders.

The open date is January 26, 2025, with a close date of February 27, 2027.

This program is particularly relevant for healthcare innovations that can improve Medical outcomes. Relevance to Highway 64 Town: The NHLBI SBIR Phase IIB Bridge Awards present a signiﬁcant opportunity for small towns in Texas along Highway 64 to enhance their healthcare services, particularly through the integration of innovative technologies targeting heart, lung, blood, and sleep disorders.

Given the program’s focus on improving medical services in rural areas, local healthcare providers can leverage this funding to develop and implement AI-driven solutions that address speciﬁc health challenges faced by the community.

For instance, AI can be utilized to analyze patient data and predict health risks, enabling early intervention for conditions such as heart disease or sleep apnea. This proactive approach can lead to better health outcomes and reduce the burden on local hospitals. Additionally, telemedicine solutions powered by AI can facilitate remote consultations, making healthcare more accessible for residents who may have diﬃculty traveling to larger medical facilities.

Furthermore, the funding can support the establishment of local health tech startups that focus on creating tailored solutions for the unique needs of the community, fostering economic growth and job creation. By enhancing healthcare infrastructure with advanced technologies, small towns along Highway 64 can improve the quality of life for its residents and ensure that they receive timely and eﬀective medical care.

–

NVIDIA CLARA Application: NVIDIA CLARA can be utilized in a rural Texas town to enhance medical services in several ways:

Telehealth Solutions: CLARA can power telehealth platforms that enable

remote consultations between patients and healthcare providers. This is

particularly beneﬁcial in rural areas where access to specialists is limited.

By using AI-driven diagnostics, healthcare providers can oﬀer accurate

assessments and treatment plans without the need for patients to travel

long distances.

AI-Powered Imaging: The platform can enhance medical imaging services by providing advanced AI algorithms for analyzing X-rays, MRIs, and CT scans. This can lead to quicker diagnoses of heart, lung, and blood disorders, which are critical in rural settings where timely intervention is essential.

Resource Optimization: By utilizing AI to streamline administrative tasks,

CLARA can help rural healthcare facilities operate more eﬃciently. This

includes optimizing scheduling, managing patient ﬂow, and reducing wait

times, which can signiﬁcantly enhance the overall patient experience.

In summary, NVIDIA CLARA can play a pivotal role in transforming healthcare delivery in rural Texas towns by leveraging AI to improve access, eﬃciency, and quality of care for heart, lung, blood, and sleep disorders.

Community Engagement and Needs Assessment: Begin by engaging with local healthcare providers, community leaders, and residents to assess speciﬁc health needs related to heart, lung, blood, and sleep disorders. This will help tailor the technology to address the most pressing issues.

AI-Driven Health Analytics: Implement AI algorithms to analyze the

collected health data for predictive analytics. This can help identify at-risk

populations, track disease outbreaks, and personalize treatment plans. AI

can also assist in remote diagnostics and monitoring, reducing the need for patients to travel for care.

Mesh Network Infrastructure: Develop a mesh network to ensure reliable

internet connectivity throughout the town, especially in rural areas where

Telehealth Services: Launch telehealth services that utilize the AI-driven

analytics and mesh network to provide remote consultations, follow-ups,

and health education. This will improve access to healthcare for residents,

particularly those with mobility issues or chronic conditions.

Training and Support: Provide training for healthcare providers on using the new technologies and data management systems. Additionally, oﬀer

support for patients to help them navigate telehealth services and

understand their health data.

Partnerships and Funding: Seek partnerships with local universities, tech

companies, and healthcare organizations to secure additional funding and

resources. This can enhance the technological infrastructure and expand

the reach of the initiative.

Also Relevant: Healthcare Implementation Strategy

For successful implementation of AI healthcare infrastructure in a small Texas town:

Phased Deployment Approach:

– Begin with critical infrastructure needs assessment

– Deploy basic NVIDIA CLARA diagnostic capabilities ﬁrst

– Expand to more advanced features as adoption increases

Connectivity Foundation:

– Establish mesh network infrastructure to ensure reliable access

– Implement edge computing nodes for local processing of medical data

– Create redundant connectivity paths to ensure healthcare system

resilience

Community Integration:

-Partner with local healthcare providers for needs assessment and training

– Create community awareness programs to drive adoption

– Develop local technical expertise through training programs

Sustainability Planning:

– Design for hybrid power solutions (including renewable energy)

– Implement predictive maintenance for infrastructure components

– Create tiered service models to support operational costs

Application Tips

When applying for these SBIR opportunities to support your Texas Highway 64 project:

Emphasize Rural Impact: Clearly articulate how NVIDIA CLARA

implementation addresses healthcare disparities in rural Texas

communities.

Quantify Beneﬁts: Include metrics such as reduced travel time for medical services improved diagnostic accuracy and economic beneﬁts.

Address Technical Challenges: Acknowledge rural-speciﬁc challenges

(power, connectivity, etc.) and provide detailed mitigation strategies.

Include Real Stakeholders: Partner with local healthcare providers,

community leaders and Texas state agencies to strengthen your

application.

Highlight Scalability: Demonstrate how your Highway 64 implementation

could serve as a model for other rural communities across Texas and

beyond.

Technology Integration: Detail how NVIDIA CLARA will interface with existing healthcare systems and infrastructure.

Long-term Vision: Include a 5-10-year vision for how the infrastructure will evolve and expand to meet changing healthcare needs.

Summary

The Medical Industry is reeling from a mass exodus of talent. A sobering new survey released by Elsevier Health, called “Clinician of the Future,” reveals a prediction that up to 75% of healthcare workers will be leaving the healthcare profession by 2026. For those of you doing the math, that’s only one short year away.

Both nurses and doctors are burned out.
Both nurses and doctors are at risk of leaving the profession.
The majority of healthcare workers don’t feel like they have a good work-life balance.
Many healthcare workers responded that dealing with families can be very stressful.

All of the healthcare workers also pinpointed specific challenges that will only continue to grow in the coming years:

An aging population with increasing healthcare needs
Patients that are becoming more empowered
The fast pace of healthcare technology
A transition to home-based healthcare

The US spends more of its gross domestic product (GDP) on health care than other high-income countries yet ranks last in access to care, administrative efficiency, equity, and healthcare outcomes, according to an analysis by the nonprofit Commonwealth Fund.

ABSTRACT Issue: No two countries are alike when it comes to organizing and delivering health care for their people, creating an opportunity to learn about alternative approaches.

Goal: To compare the performance of health care systems of 11 high-income countries.

Methods: Analysis of 71 performance measures across five domains — access to care, care process, administrative efficiency, equity, and health care outcomes — drawn from Commonwealth Fund international surveys conducted in each country and administrative data from the Organization for Economic Co-operation and Development and the World Health Organization.

Key Findings:

The top-performing countries overall are Norway, the Netherlands, and Australia. The United States ranks last overall, despite spending far more of its gross domestic product on health care. The U.S. ranks last on access to care, administrative efficiency, equity, and healthcare outcomes, but second on measures of the care process.

Conclusion: Four features distinguish top-performing countries from the United States:

1) they provide universal coverage and remove cost barriers;

2) they invest in primary care systems to ensure that high-value services are equitably available in all communities to all people;

3) they reduce administrative burdens that divert time, efforts, and spending from health improvement efforts; and

4) they invest in social services, especially for children and working-age adults.

The rankings are based on surveys conducted in 2017, 2019, and 2020 of nationally representative samples of patients and primary care physicians in Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the UK, and the US. About 5,500 people were included in the US samples.

The healthcare CX is manipulative, expensive, and full of friction. But today, all of that is acceptable. We just smile and pay more than we did, and get less than we did. The time for change has long passed.

I could go on, there are hundreds of instances where CX is horrible and demand is increasing. Poor CX is the best that is available for just about every industry, globally. And today, all of that is acceptable. We just smile and pay more than we did, and get less than we did.

This is the honeymoon period, which will come to an end soon.

The technology supporting human interaction must be seamless and unobtrusive across platforms. By knowing when and where to automate touchpoints and balancing digital with human elements, service & experience leaders can facilitate frictionless digital experiences for their customers.

World-class CX cannot be achieved without an extensive, modernized process for collecting, analyzing & utilizing data (feedback loop). From executing Voice of the Customer programs to leveraging AI & Data Analytics, holistic data-driven strategies will hold the key to success.

Questions? Engagements? Corrections? Contact –

Michael Noel Founder DeReticular

http://linkedin.com/in/michaelnoel

Mike@BizBuilderMike.com

End of hashed data

DeReticular Glossary —–NOT HASHED

Accounts: (digital) representation of an end user’s set of claims, real or financial.

Application programming interface (API): a set of rules and specifications followed by software programs to communicate with each other, and an interface between different software programs that facilitates their interaction.

Atomic settlement: instant exchange of assets, such that the transfer of each occurs only upon transfer of the others.

Central bank public goods: goods and services provided by the central bank that serve the public interest, including payment infrastructures and trust in the currency.

Composability: the capacity to combine different components on a programmable platform.

Customer Experience (CX) The 3 main components of customer experience.

Discovery. How companies contact customers and how they make that contact relevant and meaningful
Engagement. How customers initially interact with the company or company products.
Delivery. How the company handles fulfillment.

Decentralized finance (DeFi): a set of activities across financial services built on permissionless DLT such as blockchains.

Digital wallet: an interface that allows users to make transfers or otherwise transact in digital money and assets. These interfaces are built on non-programmable platforms. Not to be confused with a token wallet.

Distributed ledger technology (DLT): a means of saving information through a distributed ledger, ie a repeated digital copy of data available at multiple locations.

Delivery versus payment (DvP): A settlement mechanism that links an asset transfer and a funds transfer in such a way as to ensure that delivery occurs if and only if the corresponding payment occurs.

End users: individuals, households, and firms that are not participants in a platform

Homomorphic encryption (HE): a technique that allows data to be encrypted in such a way that they can be processed by third parties without being decrypted.

Internet of Things: software, sensors, and network connectivity embedded in physical devices, buildings, and other items that enable those objects to: (i) collect and exchange data; and (ii) send, receive, and execute commands, including payments.

Market integrity: the prevention of illicit activities in the monetary system, such as money laundering and terrorism financing, as well as market manipulation.

Monetary system: the set of institutions and arrangements around monetary exchange. This consists of two components: money and payment systems.

Oracle: a service that provides outside (“off-chain”) information for use by smart contracts in a DLT system.

Programmability: a feature of programmable platforms and other technologies whereby actions can be programmed or automated.

Programmable platform: a technology-agnostic platform that includes a Turing machine with an execution environment and a ledger and governance rules.

Payment versus payment (PvP): a settlement mechanism that ensures that the final transfer of a payment in one currency occurs if and only if the final transfer of a payment in another currency or currency takes place.

Ramps: protocols that connect non-programmable platforms to programmable platforms. Ramps lock assets in their platform of origin as collateral for the tokens that are issued on the programmable platform.

Secure multi-party computation (SMPC): a cryptographic technique that allows multiple parties to jointly compute a function on their private data without revealing the data to each other.

Smart contract: self-executing applications of programmable platforms that can trigger an action if some pre-specified conditions are met.

Stablecoin: a cryptocurrency that aims to maintain a stable value relative to a specified asset, or a pool or basket of assets.

Token: a digital representation of value in a programmable platform. Tokens can be tokenized, ie derived from claims in traditional ledgers, or can be issued natively in the platform, ie “native” tokens.

Tokenization: the process of recording claims on real or financial assets that exist on a traditional ledger onto a programmable platform.

Tokenized asset: a digital representation of a claim of an asset in a programmable platform.

Tokenized deposit: a digital representation of a bank deposit in a programmable platform. A tokenized deposit represents a claim on a commercial bank, just like a regular deposit.

Customer Centricity in the Platform Revolution | Sangeet Paul Choudary

In his 2016 keynote, he discusses the shift from asset-centric business models to consumer-centric platform business models. From Pipes to Platforms.

ChatGPT: Optimizing Language Models for Dialogue – We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its m istakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.

Distributed computing security “Can it be secure?”

In the distributed environment, when the system is connected to a network, and the operating system firewall is active, it will take care of all the authentication and access control requests. There are several traditional cryptographic approaches that implement authentication and access control. The encryption algorithms such as Rijndael, RSA, A3, and A5 are used for providing data secrecy. Some of the key distribution techniques such as Diffie Hellman key exchange for symmetric key and random key generation (LCG) technique is used in red-black tree traversal which provides the security of the digital contents.

You can use pFsence for routing, there is a community version that is open-source and free. Secure networks start here.™ With thousands of enterprises using pfSense® software, it is rapidly becoming the world’s most trusted open-source network security solution. Get Started Now

Named Data Networking (NDN) – Named Data Networking is a Future Internet Architecture research project supported by the National Science Foundation, which has received over $13.5M in funding from NSF from 2010-2016.

UCLA Professor and Jonathan B. Postel Chair in Computer Science Lixia Zhang leads the project along with Internet Hall of Fame inductee and UCLA adjunct professor Van Jacobson.

Van Jacobson is an American computer scientist, renowned for his work on TCP/IP network performance and scaling. He is one of the primary contributors to the TCP/IP protocol stack—the technological foundation of today’s Internet. Wikipedia

The NDN project is developing a new fundamental architecture for the global Internet that leverages thirty years of empirical evidence of what has worked (and what has not). It aims to provide a practically deployable set of protocols replacing TCP/IP that increases network trustworthiness and security, addresses the growing bandwidth requirements of modern content, and simplifies the creation of sophisticated distributed applications.

Workshop on Named Data Networking (NDN) at NIST, 2016

The Inter Planetary File System – IPFS, https://ipfs.tech/ – IPFS powers the creation of diversely resilient networks that enable persistent availability — with or without internet backbone connectivity. This means better connectivity for the developing world, during natural disasters, or just when you’re on flaky coffee shop wi-fi.

IPFS is a DNS replacement that finds information by its contents, not its location this is called content addressing (Kinda like Named Data Networking, but still different). With IPFS, you don’t just download files to network storage, IPFS also helps distribute them. When your friend a few blocks away needs the same Wikipedia page, they might be as likely to get it from you as they would from your neighbor or anyone else using IPFS (Napster except much more disruptive to more industries).

LDNS, https://www.nlnetlabs.nl/projects/ldns/about/LDNS is a DNS library that facilitates DNS tool programming. Translations in LDNS can come from any database. Even a distributed ledger database (Blockchain). If you use a permanent, distributed ledger database to record your DNS, you have persistent Lifetime DNS, when the payment is made to record it, then that’s it, no payments for a lifetime. Domain Registrars like Go Daddy, have become so 1990s.

And you can use multiple storage mediums to store a single document, which can only be assembled through your LDNS instance which may only be in a single node. Security is built into the platform. Node communications are all encrypted and Quantum Resistant.

Mesh Network A mesh network is a local area network topology in which the infrastructure nodes (i.e. bridges, switches, and other infrastructure devices) connect directly, dynamically, and non-hierarchically to as many other nodes as possible and cooperate to efficiently route data to and from clients.

This lack of dependency on one node allows for every node to participate in the relay of information. Mesh networks dynamically self-organize and self-configure, which can reduce installation overhead. The ability to self-configure enables the dynamic distribution of workloads, particularly in the event a few nodes should fail. This in turn contributes to fault tolerance and reduced maintenance costs.

Zero-knowledge proof – In cryptography, a zero-knowledge proof or zero-knowledge protocol is a method by which one party (the prover) can prove to another party (the verifier) that a given statement is true while the prover avoids conveying any additional information apart from the fact that the statement is indeed true. The essence of zero-knowledge proofs is that it is trivial to prove that one possesses knowledge of certain information by simply revealing it; the challenge is to prove such possession without revealing the information itself or any additional information.

Content Delivery Network (CDN) – A content delivery network (CDN) refers to a geographically distributed group of servers that work together to provide fast delivery of Internet content.

A CDN allows for the quick transfer of assets needed for loading Internet content including HTML pages, javascript files, stylesheets, images, and videos. The popularity of CDN services continues to grow, and today the majority of web traffic is served through CDNs, including traffic from major sites like Facebook, Netflix, and Amazon.

A properly configured CDN may also help protect websites against some common malicious attacks, such as Distributed Denial of Service (DDOS) attacks.

LTE-4, Mobile Data, LTE-5, In telecommunications, Long-Term Evolution is a standard for wireless broadband communication for mobile devices and data terminals, based on the GSM/EDGE and UMTS/HSPA technologies. It increases the capacity and speed using a different radio interface together with core network improvements. The LTE data structure remains consistent Globally. We leverage the Catagory 18 LTE modem’s LTE data access capabilities. The modem is available on the Jungle website. They are carrier specific, and if your carrier goes down, your down. There are carrier fallback options that deliver 3 or 4 carrier options, which if one goes down, moves to the next (automatic failover). These options are currently providing fiber speeds (1 gig or better) for 50 cents a gig. Miners sell that bandwidth for 1 dollar a gig (50% margins).

One Tri Carrier option is TriFiWireless.com. For $279.00 plus shipping, you can buy the LTE 4 to Wi-Fi modems. You need 2 to start a Platform. The Tri-Fi units also have SDN. In most cases where cellular reception is very good, these devices provide over 1 gig of mobile data connectivity speeds. Just Plug them in and you are good to go. Sometimes we might need to augment the signal with an antenna. Most often we can estimate requirements using Google Earth.

An intelligent eSIM platform goes beyond the initial SIM activation. Its primarily used to manage a device and customize variables that greatly enhance an IoT device operator’s control of a subscriber over the long term. The key difference between a standard eSIM platform and an intelligent eSIM platform starts with the concept of “control”. That is the ability of device operators to determine how and where they get connected for the duration of a device’s lifespan.

Access more networks (i.e. AT&T, T-Mobile, and Verizon in the US)

Access more network types (i.e. 3G, 4G, 5G, NB-IoT, CAT-M)

Access more device types (i.e. devices that take a standard SIM or embedded SIM) Seamlessly deploy devices in more countries around the world Control devices over the long term with enhanced feature sets.

Web3 is decentralized. And it is Distributed as well. Nodes on your network are distributed and use technology, like IPFS, and LDNS.

Nodes are local, and owned by the miners. The miners provide W3 services to the platform, and collect economic rents when members use the platform,

What services you are asking for?

We can start with,

Persistent Lifetime DNS – Multiple ways to do this –

Network Security – This is a Distributed Network –

Know your customer, Anti Money Laundering, Proof of Identity as a Service – Nodes can connect to verify the single instance of an identity network-wide, which provides proof of identity (POI).

With POI comes imputed KYC and AML. KYC, AML, as a service (KYC, AML, AAS) – In network, Legal, Regulated peer-to-peer trading of Securities, Automobiles, Homes, Digital Assets, NFT, Payroll, Payments, and anything that can be digitized (NFT, Digital Twin)

Peer to Peer, Member to Member. – services provided at near Zero Marginal cost to the platform – Transportation in the network provided by Autonomous Transportation tracked on the network (Lease a Tesla) – Basically Zero Marginal Cost Transportation.

Access to shelter and food, immediate settlement both ways and at Zero Marginal cost to the platform. Spoiler alert – When you apply this to Medical Campuses things change immediately.

DeReticular: of, relating to, or forming a Decentralized Network.

Search DeReticular

Will AI Infrastructure Help Enhance Healthcare Outcomes? – Enabling Transparent Privacy in Healthcare

Will AI Infrastructure Help Enhance Healthcare Outcomes?

– Enabling Transparent Privacy in Healthcare

7 Grant Opportunities by Focus Area Healthcare

Grant Funding Opportunity 5

This is the honeymoon period, which will come to an end soon.

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Will AI Infrastructure Help Enhance Healthcare Outcomes?

– Enabling Transparent Privacy in Healthcare

7 Grant Opportunities by Focus Area Healthcare

Grant Funding Opportunity 5

This is the honeymoon period, which will come to an end soon.

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