GDIT Emerge

AWS’ Balaji Iyer on Public Sector’s Top AI and ML Uses Brought to Life


By Balaji Iyer, Business Development Manager, AI/ML, Amazon Web Services

Changing the World, One AI Application at a Time

There is no one-size-fits-all profile of the ideal artificial intelligence (AI) and machine learning (ML) customer, user, or developer. AWS is making AI and ML technologies more accessible with managed services that let anyone embed intelligence into their applications, whether IT professionals – not experienced data scientists, AI PhDs, or AI engineers. It is why some of the most exciting uses for AI and ML are coming from unexpected places – public sector organizations with a mission to make the world a better place.

Predicting Famines and Crisis

Today, 124 million people live with crisis levels of food insecurity, relying on urgent humanitarian assistance to survive. Over half of these populations live in conflict zones, resulting in the World Bank, United Nations, and International Committee of the Red Cross teaming with cloud service providers to identify areas at risk for famines –to save lives before a crisis evolves.

AWS provides conflict-related data, and a machine-learning pipeline from data ingestion and storage in Amazon S3, to AI model deployment using Amazon SageMaker. The data includes causes of famine, satellite imagery, conflict data, weather forecasts, local food prices, and agricultural production.

Identify Fraud and Anonymous Activities

The Financial Industry Regulatory Authority (FINRA) oversees more than 3,900 securities firms with approximately 640,000 brokers. FINRA is able to capture, analyze, and store a daily influx of 135 billion records in order to identify fraud and other anonymous activities on AWS. Every day, FINRA watches over nearly 6 billion shares traded in U.S. equities markets—using technology powerful enough to help detect fraud, abuse, and insider trading. FINRA processes approximately 6 terabytes of data and 135 billion records on an average day to build a picture of market trading in the U.S.

ML Improving Patient Care

Beth Israel Deaconess Medical Center has launched a multi-year, innovative research program on how machine learning can improve patient care, supported by an academic research sponsorship grant from AWS. The Harvard Medical School-affiliated teaching hospital will use a broad array of AWS machine learning services to uncover new ways that machine learning technology can enhance clinical care, streamline operations, and eliminate waste, with the goal of improving patient care and quality of life.
Beth Israel Deaconess Medical Center also uses Amazon Comprehend Medical to identify completed history and physical forms before a surgery, lowering the number of delayed or cancelled procedures.

ML for Predictive Maintenance

Defense Innovation Unit Experimental (DIUx) is a U.S. Department of Defense organization focused on accelerating adoption of innovative commercial technologies for national defense. DIUx selected C3 IoT to provide an AI and IoT software platform for delivering a new AI-based predictive maintenance solution that increases asset availability and reduces maintenance expenditures associated with their aircraft platforms. DIUx, the U.S. Air Force, and C3 IoT have prototyped the C3 Predictive Maintenance™ application on the E-3 Sentry (AWACS) aircraft platform, running on AWS GovCloud (US).

AI and ML Make a Difference

Many examples exist, whether technology is used to reduce the time a victim spends in an abusive situation in trafficking situations, or making vital information available to blind people with speech-to-text-technology.

Learn more about AI and AWS.

Continue the conversation and hear AWS’ Balaji Iyer’s insight during the “Future-Minded Analytics – Improving Data through AI” session at Emerge on April 23. Register today.