Domino Data Science Blog

With the ongoing generative AI hype, one concept is becoming increasingly clear: giant, generic generative AI models, by themselves, are not the key to unlocking business value. While they are excellent for experimentation, entertainment, and some limited end-user work augmentation (ChatGPT might have helped with parts of this blog), they often fall short in terms of performance, accuracy, and risk when they aren't production grade.

Generative AI has captured the public imagination, with ChatGPT contextualizing the benefits of AI for more people than ever before. OpenAI reportedly used 10,000 NVIDIA GPUs to train ChatGPT, and NVIDIA owns 88% of the GPU market powering model training.

How do you balance the need for innovation and efficiency in FSI with the need for compliance and good governance? That's a critical question for the financial services and insurance industries to answer, because AI, ML, and the hybrid/multicloud are among the most important technology trends of our time.

From early disease detection to intelligent clinical trial designs to personalized medicine, the promise of AI/ML in healthcare and life sciences is great, with “more than 57% of healthcare and life sciences organizations rating AI/ML important or very important, ” according to Ventana Research in their recent white paper Top AI Considerations for Chief Data and Analytics Executives.

Update 9/23/2022: See what we announced at NVIDIA GTC: "Domino Data Lab Announces New Ecosystem Solutions with NVIDIA to Accelerate Hybrid and Multi-cloud MLOps Journey"