Deploying AI Solutions in Healthcare and Life Sciences
We recently caught up with Bill Fox, Healthcare and Life Sciences Lead at SambaNova Systems, to ask him to share his thoughts on what excites him about AI, the biggest challenges for organizations adopting AI, and the most interesting projects he’s worked on in his career.
Q: You have an interesting background—from law to AI. How did that happen?
A: My legal career increasingly focused on two areas, healthcare and fraud. I litigated hundreds of healthcare-related cases and spent thousands of hours poring over medical records and talking to doctors. I was Deputy Chief at one of the first cybercrime units in any District Attorney’s Office in the country and began to understand how the internet, data, and predictive analytics really worked, and that was it, I knew I wanted to focus on understanding and explaining how those capabilities can be used to improve healthcare and drug manufacturing.
Q: What excites you about AI and how it’s advancing?
A: The most exciting shift is what is being called Software 2.0. Many of the most complex and compelling challenges in healthcare and life sciences are too complex to address with rules-based coding and legacy hardware and software. The ability to use neural networks and deep learning to address these challenges creates a tremendous opportunity to do things, such as advance drug discovery and expand access to diagnostics.
Q: What is the biggest challenge in your industry?
A: I think many people are too glib in simply saying, “healthcare is slow to adopt new technology.” Not that it’s not true, but as recent news around Haven and Watson demonstrates, healthcare, and life sciences, are not like other “industries.” The stakes are higher, the outcomes are all serious, and regulation and reimbursement play a significant role in gating innovation. We need to work very closely with clinicians, scientists, and regulators to make innovation a reality. This is really what I do in my role, helping drive cutting-edge AI capabilities into our industry.
Q: How has the pandemic affected this trajectory?
A: The consensus seems to be that the pandemic moved technology adoption, and in particular, telehealth and virtual care, five years forward in a few months. I don’t believe we will ever go all the way back. What we have in place is V.1 of what healthcare will look like in 5-10 years. AI will improve every aspect of telehealth, from symptom checking to doctor matching to virtual assistants. Further, let’s not forget the amazing work done by science and pharma in developing and delivering multiple highly effective vaccines in a timeline many said was impossible. Driving AI into every aspect of drug discovery can hopefully make this rapid development the industry standard.
Q: What’s on the minds of Healthcare and Life Sciences companies these days?
A: We’re talking about the tremendous progress that has been made using AI in both healthcare and pharma, using real-world examples across NLP, computer vision, and recommendation models, but also on what organizations need to do to prepare for next-generation AI. We’re answering questions around how higher resolution computer vision can be used to improve diagnostics, how we can improve NLP models to personalize communications, and even addressing what “Netflix”—more specifically state-of-the-art recommendation models—has to do with drug discovery.
- Watch the CNBC video. CEO Rodrigo Liang explains how SambaNova makes it easier for organizations of all sizes to deploy AI technology.
- Read the solution brief. Dataflow-as-a-Service provides comprehensive services, models, and a platform to help companies deploy customized AI solutions with confidence.
- Visit our website to learn how organizations can deploy AI up to 18 months faster with fully managed, expert application services.