O’Reilly’s Generative AI in the Enterprise survey reported that people have trouble coming up with appropriate enterprise use cases for AI. Why is it hard to come up with appropriate use cases?
Chip Huyen, co-founder of Claypot AI and author of Designing Machine Learning Systems, will talk about why many companies have trouble coming up with appropriate use cases for AI, how to evaluate possible use cases, and the skills your company will need to put these use cases into practice.
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The full version of this podcast episode is on the O’Reilly Learning platform.
About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.
Timestamps
0:00: Introductions
0:49: O’Reilly’s Generative AI in the Enterprise survey reported that people have trouble coming up with appropriate enterprise use cases for AI. Why is it hard to come up with appropriate use cases?
3:02: AI is easy to demo, but hard to productize. Consistence, risk, and compliance.
5:18: How do you think about staffing teams for generative AI?
6:45: There’s less model development with generative AI, more application development
7:21: Front-end engineers and full-stack developers are very successful
