James Sutton is an ML Engineer focused on helping enterprise bridge the gap between what they have now, and where they need to be to enable production scale ML deployments.

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Timestamps:

0:00 - Intro to Speaker

2:20 - Scope of the coffee session

3:10 - Background of James Sutton

8:28 - One-shots Classifier Algorithm   

12:46 - Why is it a challenge from the engineering perspective with deployment?

19:20 - How to overcome bottlenecks?

30:07 - Vision of your landscape?  

34:45 - Maturity playout

38:48 - Maturity perspective of ML

41:49 - Risk of overgeneralizing system designs patterns

46:10 - Reliability, Speed, Cost

46:46 - Consistency, Availability, Partition Tolerance (CAP Theorem)

47:36 - How do you go about discussing these tradeoffs with your clients?

51: 23 - How would you deal with the PII?

58:50 - Collaborative process with clients

1:00:55 - Wrap up