Machine learning at small organizations
from Practical AI Hosted by Daniel Whitenack and Chris Benson
Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption. Sponsors: The Changelog – Conversations with the hackers, leaders, and innovators of the software world Featuring: Kirsten Lum – LinkedIn, X Chris Benson – Website, GitHub, LinkedIn, X Daniel Whitenack – Website, GitHub, X Show Notes: storytellers.ai Trello Upcoming Events: Register for upcoming webinars here!
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Chapters
- 0:00 Opener
- 0:36 Welcome to Practical AI
- 1:11 Kirsten Lum
- 5:43 Selling short in data science
- 8:01 FUD from a management POV
- 13:43 Data science is like cooking
- 17:32 Sponsor: The Changelog
- 19:16 What to focus on when you're new
- 22:32 Managing flexibility in a small company
- 26:25 Navigating people in a small business
- 29:17 Putting the practical in PracticalAI
- 35:53 How to approach non data-centric people
- 39:26 Advantages of small ML orgs over big orgs
- 42:36 Mentoring people the right way
- 45:59 Looking into the future
- 49:04 Outro
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