Making business decisions is hard. Making them without having all of the right information is even harder. Generative AI and your organization’s strategy around it is no exception. The space is moving at a breakneck pace, but you have to make the decisions now.
Which LLM do you choose? What kind of use cases should your team prioritize? What are vector databases and why do they matter? What is the actual path to value with generative AI? These are just some of the basic questions that you and your peers deal with every day.
Just like with everything else, you need to understand the basics and fundamentals around generative AI to answer these pressing questions and craft your generative AI strategy.
We devised this short crash course to help you do just that. We can’t build your generative AI strategy for you, but we can help by steering you in the right direction.
Watch Generative AI 101 for Executives: a Crash Course to learn about:
- The foundations, from the basic definitions to the whole generative AI value chain
- Valuable and actionable generative AI use cases that can bring value in almost any industry
- Practical examples of generative AI solutions
- How to deliver value at scale with generative AI
DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.
The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.
The value of having a single platform that pulls all the components together can’t be underestimated. Then there’s the combination of the technology and the collaborative DataRobot team. If either one of those wasn’t there, I would have looked elsewhere.