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Forward Edge-AI Blockchain/Digital Assets Portfolio

A brief list of Forward Edge-AI's Blockchain, Distributed Ledger, and Digital Assets Projects and Technologies

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Written by Eric Adolphe
Updated over 2 months ago

January 01, 2024

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Phase III SBIR - Business Transformation at the Department of the Treasury/IRS

Awarding Agency: Department of the Treasury/Internal Revenue Service (IRS)

Contract Number: 2032H5-24-P-00097

Relevant Phase I/II Award Numbers: AN 1938135, AN 2028451, Award #2327618 | Agency: National Science Foundation

Description: Forward Edge-AI is working with the agency's Information Technology executives, staff, and other stakeholders to provide data analytics support to the TBM program. The work includes analysis of TBM data to identify trends, patterns, and anomalies that can provide insights into the organization’s IT spending.

Forward Edge-AI is also leveraging data forensic techniques derived from a National Science Foundation SBIR to determine data sources and ownership for Servers, Data Centers, Storage, Applications and Services and other information to determine lineage and provenance of data sources.

Key Words:

  • AWS, Business Transformation, Data Analytics, Data Governance, Data and Digital Forensics, Forecasting, and Technology Business Management

Awarding Agency: National Science Foundation

Award Number: 2327618

Description: Develop a blockchain/DLT to ensure the provenance, integrity and quality of space-based Machine Learning algorithms and associated training data (counter adversarial Artificial Intelligence). The CASI-D project focuses on the development of a Blockchain solution to manage the governance and provenance of ML/AI algorithms and associated training data for CubeSats and other space infrastructure. Phase I addresses the growing concerns around adversarial AI. At the core of the CASI-D project is the development of an advanced a Blockchain to support its governance framework, including automated auditing, risk assessment, and compliance monitoring. By integrating these technologies, the project enhances the ability to detect and address potential issues in real-time, ensuring the security of ML/AI models developed for on-orbit systems.

The CASI-D project complements the Space COMSEC project by establishing robust AI governance frameworks ensure the lineage and provenance of Isidore Quantum’s ML models and training data. Together, Isidore Quantum® and CASI-D creates a secure, transparent, and sound environment for space communications, balancing technological innovation with governance.

Key Words

  • Adversarial AI AAI), AI, Blockchain/DLT, Counter Adversarial Artificial Intelligence, CubeSat, Cybersecurity, Data Drift, Deep Learning, DevSecOps, Electronic Discovery, Forensics, Internet, Physics-Based Models, Model Drift, Space, Space-Based Manufacturing, Training Data Provenance, Trustworthy Artificial Intelligence, Identity Management (ICAM), IPV6, Poison Data

Awarding Agency: National Science Foundation

Award Number: 2335995 (Subcontract to the University of Texas San Antonio)

Description: The Decentralized Autonomous Organization Collaboration Hub (DACH) is a groundbreaking national collaboration initiative to foster continuous innovation in the digital asset ecosystem. In an era where digital assets, such as cryptocurrencies, have attained over a trillion dollars in market value, the need for public and private collaboration is not just important, but essential.

Key Words

  • Not Applicable (this project is not an SBIR or STTR)

Awarding Agency: National Science Foundation

Award Numbers: AN 1938135, AN 2028451

Description: We developed a method for storing data in a blockchain in a high-performing manner, to ensure quality training of ML/AI models, training data (data governance) and production level inference. The innovation addressed the challenge of data drift and adversarial AI attacks where the provenance of the data is unknown. The blockchain also facilitates electronic discovery throughout the complaint filing and litigation process.

Key Words:

  • AWS, Android, Artificial Intelligence (AI) (CNN/RNN), AI Test and Evaluation, Blockchain/Data Governance, Data Analytics, Data Lake, Counter Adversarial AI, Deepfakes, Enterprise Knowledge Graph, Machine Learning, Microsoft Azure, Natural Language Processing (NLP), Large Language Models (Generative AI (GAI)), Honeypots, Intelligent Automation, Predictive, iPhone, Robotic Process Automation, Semantic Reasoning, Sentiment Analysis, Taxonomy

  • Cybersecurity, Digital Transformation, Financial Systems/Fintech, Electronic Discovery, Fraud Prevention, Misinformation, Disinformation, Malinformation, Identity Management (ICAM), Telecommunications, Trusted AI, Adversarial AI

  • Ethical AI, Trustworthy AI, Responsible AI, Data Engineering, Data Governance, Training Data, Validity and Reliability, Safety, Security and Resiliency, Accountability and Transparency, Explainability and Interpretability, Privacy, Fairness with Mitigation of Harmful Bias, Model Drift, Data Drift

Awarding Agency: Air Force

Contract Number: FA864921P1006

Description: In the Phase I SBIR, Forward Edge-AI, Inc. augmented a miniature, Commercial-Off-The-Shelf (COTS) Raman instrument with Machine Learning/Artificial Intelligence (ML/AI), new signal processing techniques, and Surface-Enhanced Raman Scattering (SERS) for quick stand-off identification of trace chemicals and microbes (e.g., COVID) in a field setting, thereby bringing laboratory grade science to the edge. Included a Blockchain and Distributed Ledger Technology to manage the governance of Raman Spectra and award crypto currency to researchers who contribute Raman spectra.

Key Words:

  • Artificial Intelligence (CNN/RNN), Android ATAK, Blockchain, Federated Learning Marketplace, Machine Learning, Microsoft Azure, signal processing (Wavelet and Fourier transformation), Raman Spectroscopy

  • Chemical, Biological, Radiological, and Nuclear (CBRN) detection, explosives detection, viruses, bacteria, Expeditionary Environments, field, standoff

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