Machine learning is a subset of artificial intelligence that involves generating programs based on data to solve specific problems.

General-purpose technologies like supervised learning and generative AI are valuable for a wide range of applications, and there is still much work to be done in identifying and executing concrete use cases.

The rise of generative AI presents opportunities to create deep, complex applications that can provide long-term value, unlike simpler applications that may not be defensible in the long run.

Generative AI is just another step in the journey of using machine learning technologies in finance.

The most compelling generative AI applications will emerge from innovative uses of technology that differ from traditional software applications, creating new business opportunities.

Generative AI excels when there are many possible answers and it's a matter of opinion. It allows for creative choices, like selecting different designs or summaries, which can change the world of content creation.

The emergence of generative AI has led to more collaborative and expansive applications, requiring new approaches to testing and evaluation.

AI is both a general-purpose and highly specialized technology, requiring local expertise to fine-tune models for specific needs.

The company leverages both traditional AI and generative AI to provide a seamless customer experience across various platforms.