Trust, Transparency & Secured Generative AI

Abstract: 

Public adoption of generative AI has shown everyone how transformative the technology can be. It holds the potential to create competitive advantage by driving the speed and efficiency of operations ranging from IT automation, digital labor, and customer care use cases. But not all AI models are created equal – the best models will depend on your industry, domain, and use case. And that’s why having options is essential for successfully adopting AI within your business, that’s grounded in trust and transparency to ensure the deployment of responsible AI. Learn about IBM’s approach to selecting the right AI foundation model for the right task to accelerate your generative AI strategy in this interactive session.

Bio: 

Kate Soule is the Program Director for Generative AI Research at IBM where she oversees the development and incubation of IBM’s Large Language Models and other Generative AI technologies. Prior to her current role at IBM Research, Kate was a leader at the MIT-IBM Watson AI Lab, a joint research partnership between MIT and IBM Research; Kate ran the Lab’s corporate membership program, supporting industry members as they co-invested in the Lab’s AI research technologies. Kate earned her MBA at MIT Sloan and previously worked at Deloitte Consulting as a Senior Consultant within the Strategy and Operations practice. Kate also holds a B.S. in Statistics from Cornell University.

Open Data Science

 

 

 

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