Description
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(00:00:00) Gen AI benefits discussed.
(00:00:18) Peggy Tsai introduction.
(00:01:06) Data leadership conversation starts.
(00:01:39) Challenges for data officers.
(00:02:20) AI compliance and regulation.
(00:03:27) Merging data and AI roles.
(00:04:08) Data quality importance.
(00:05:02) Gen AI adoption strategies.
(00:06:23) C-suite collaboration impacts.
(00:07:12) Board's interest in Gen AI.
(00:08:34) Is Gen AI a hype?
(00:09:14) Gen AI's personal benefits.
(00:10:10) AI's widespread adoption.
(00:11:27) Pandemic's impact on data.
(00:12:15) Excitement for future innovations.
(00:12:55) Customized language models.
(00:13:55) Small language models' advantages.
(00:14:44) External AI models for customers.
(00:15:35) Future of Gen AI.
(00:16:08) Data foundation is critical.
(00:17:10) Importance of data governance.
(00:18:36) Consistent data definitions.
(00:19:38) Data governance challenges.
(00:20:04) Investment in data management.
(00:20:58) Unstructured data governance.
(00:21:41) Data retention policies.
(00:22:38) AI model biases.
(00:23:45) Data life cycle management.
(00:24:03) Data hoarding risks.
(00:24:34) Improving data quality.
(00:25:13) Simplify data assets.
(00:26:26) Strong cross-functional partnerships.
(00:27:15) Storytelling for data value.
(00:28:23) Mentorship and sponsorship.
(00:29:03) Peggy's mentorship experience.
(00:30:26) Advocacy for women in data.
(00:32:32) Importance of representation.
(00:33:19) Women in Data community.
(00:34:47) Conference networking benefits.
(00:36:14) Importance of community.
(00:36:33) Advice for young professionals.
(00:37:46) Broader perspective in work.
(00:38:36) High school student mentorship.
(00:39:57) Growth mindset in AI.
(00:40:20) Peggy's career advice.
(00:40:49) Supporting each other.
(00:41:02) Outro and call to action.
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