There is no doubt that artificial intelligence is all the rage these days, and its applications within every industry are dominating headlines and workplace conversations. But not all AI is built the same way or deployed for the same uses. 

In general, the term “AI” (Artificial Intelligence) refers to the broader field of creating intelligent systems that can simulate human-like intelligence, while ML (Machine Learning) is a subset of AI that focuses on algorithms and statistical models that allow machines to learn and make predictions based on data. Generative AI, on the other hand, is a specific application of AI and ML techniques that aims to generate new content, such as images, music, or text, by learning from existing data and creating original output.

“AI Lite” refers to a lightweight or scaled-down version of artificial intelligence (AI) systems or technologies that implement AI capabilities with reduced complexity, resource requirements, or computational intensity compared to full-fledged AI solutions, to a variety of benefits. 

In this blog, I will define AI Lite and its applications in the healthcare industry, and share an introduction to VMware Greenplum: an open-source massively parallel processing (MPP) database designed for large-scale data warehousing and analytics that leverages AI-Lite technology. 

What is AI Lite?

While some people may perceive that the term “AI Lite” as something more flimsy or not as powerful as larger, more complex AI models, it is a misconception that the size of the model correlates to the value of outcomes. In fact, characteristics of AI Lite include simplified infrastructure, efficient implementation, and a focus on specific AI capabilities, often making it more accessible, affordable, and practical for organizations with limited resources or technical expertise or highly targeted needs to adopt and leverage AI technologies.

Some examples of instances where organizations may opt for an AI Lite approach rather than building out a giant model may include: 

• Small to Medium-Sized Enterprises: SMEs may opt for AI Lite solutions due to limited budgets, infrastructure, or in-house expertise. They can implement AI Lite to automate specific tasks, improve operational efficiency, or gain insights from data without the need for extensive resources.
• Proof of Concept: Organizations conducting PoC projects may choose AI Lite to quickly validate ideas or test the feasibility of AI applications before investing in larger-scale implementations. AI Lite allows them to experiment, gather initial results, and assess the potential value of AI in their specific use cases.
• Resource-Constrained Environments: In scenarios where computational resources or infrastructure are limited, such as remote locations or edge computing environments, AI Lite can be more suitable. It offers lightweight AI capabilities that can be deployed on edge devices or less powerful hardware, enabling AI processing closer to the data source.
• Specific Use Cases: Organizations may adopt AI Lite for targeted use cases that require specific AI functionalities. For example, implementing AI Lite for sentiment analysis of customer feedback, image recognition in quality control processes, or demand forecasting for inventory management. By focusing on specific tasks, AI Lite can deliver valuable insights without the need for more comprehensive, complex, or expensive AI systems.

Why AI Lite is a winning solution for healthcare

Targeting specific use cases is one of the main reasons AI Lite is so applicable to the healthcare industry, where challenges such as managing large volumes of patient data, improving diagnostic accuracy, and optimizing treatment plans can be addressed using narrowly focused AI and machine learning systems. Healthcare organizations often have extremely complex data environments and limited resources, making full-scale AI implementations challenging. AI Lite provides a practical and cost-effective approach to utilizing AI capabilities and derives insights from healthcare data without significant infrastructure requirements. This enables healthcare organizations to adopt AI Lite technologies in a more accessible and manageable manner, facilitating innovation and improving patient care.

VMware Greenplum 

The use cases for analytics and data processing in healthcare have expanded dramatically in recent years, and can be overwhelming for organizations. Forward-thinking healthcare organizations know they need to use the power of technology to help process and derive meaning from their data, and AI Lite platforms like VMware Greenplum are a great way to redefine an organization’s data platform by simplifying for efficiency, control, and cost optimization. Greenplum essentially plugs into what you already have without having to build from scratch or reinvent the wheel, allowing organizations to derive value from the technology sooner and avoid the inefficiencies and governance issues that may be caused by migrating data to an entirely new platform. Greenplum offers speed and scalability (with less time needed to train ML models), and rich analytics. It also harnesses the power of open source, which is increasingly more flexible than commercially available licensed databases. All this to say, Greenplum can offer healthcare organizations the benefits of cloud databases within a private cloud environment without needing to rebuild the entire system. The platform can even be used to support specific departments that require more robust machine learning applications, for example specialties that require a lot of image analysis such as pulmonology, cardiology, and oncology. 

Along with modularity, flexibility, and scalability, Greenplum’s “secret sauce” includes enablement of data sovereignty, ensuring that data is subject to the laws and governance of the jurisdiction in which it resides, safeguarding privacy, security, and compliance while granting individuals and organizations control over their data and mitigating risks associated with unauthorized access or misuse.

Some specific time- and cost-saving applications of Greenplum for healthcare organizations include: 

• Patient monitoring and data analysis
• Diagnostic assistance and decision support systems
• Predictive analytics for disease prevention and personalized treatment
• Image recognition and anomaly detection 
• Handling and analyzing large volumes of medical data
• Accelerating data processing and query performance
• Enabling predictive modeling and real-time decision-making

Ultimately, this AI Lite technology doesn’t replace the role of a provider or healthcare administrator, but rather empowers healthcare workers to excel in their roles, unlocking unparalleled potential for organizations to achieve remarkable outcomes, seize control, adapt swiftly, and unleash the full capacity of their human resources by relieving administrative burden and saving time. 

The big picture

The overall impact of AI Lite on healthcare delivery and patient outcomes is significant. By making AI more accessible and practical, AI Lite enables healthcare organizations to get more intelligence out of data analytics, predictive modeling, and decision support systems, leading to more accurate diagnoses, personalized treatment options, and improved patient outcomes. Moreover, AI Lite has the potential to make healthcare more equitable by reducing resource disparities, providing cost-effective solutions, and extending the reach of healthcare services to underserved populations, bridging the gap in access to quality care. Through its targeted and efficient approach, AI Lite has the capacity to enhance healthcare delivery, promote fairness, and contribute to improved health outcomes globally. 

As healthcare organizations continue to leverage technology, it’s important to remember that there isn’t a one-size-fits-all solution to leveraging AI and machine learning. Investing in AI-Lite-powered platforms can help organizations make use of the infrastructure they already have while making iterative improvements for the future. Learn more about the benefits of AI Lite and Greenplum here. 

Cameron Lewellen

Cameron Lewellen is the Director of Healthcare ISVs & Strategic Alliances. He has led digital transformation at VMware for 10 years, with the latest focus area being AI/ML in Healthcare.

The article was first published here:

https://blogs.vmware.com/industry-solutions/2023/06/20/revolutionizing-healthcare-with-ai-lite-and-greenplum/