[00:05:59] Where do you see now the field of machine learning headed in the next two to five years? [00:07:41] What do you see being the biggest positive impac

[00:05:59] Where do you see now the field of machine learning headed in the next two to five years? [00:07:41] What do you see being the biggest positive impact coming from machine learning in the next two to five years? [00:08:52] What do you think would be the scariest application of machine learning in the next two to five years? [00:10:55] What are some things that we should keep on top of our mind as areas of concern so that we can kind of mitigate the risk of these scary applications? [00:13:48] What is serverless machine learning and how is it different from regular old fashioned machine learning? [00:17:10] So what is the difference between machine learning code and machine learning platform? [00:21:24] At what point then does it make sense for us to start using serverless machine learning? [00:23:05] The difference between row-oriented and column-oriented storage. [00:27:21] A hypothetical scenario where serverless machine learning would an ideal use case. [00:28:52] What tips you can share with our audience so that we can be more thoughtful with our feature engineering. [00:31:55] What are some tips that you can share with our audience so that we can be more thoughtful in our hyperparameter tuning? [00:34:17] What do we do once a model is put into production? [00:38:07] Is data science an art? Or is it purely a science? [00:39:51] The creative process in data science [00:43:19] The democratization of machine learning [00:45:21] What would you say was the biggest lesson you learned about democratization of A.I. while you're over at Google? [00:53:49] How to communicate with executives [00:55:54] How to develop your product sense and business acumen [00:57:10] Why you shouldn’t be discouraged by these insane job descriptions [00:58:16] What’s the one thing you want to people to learn from your story? [00:59:03] The lightning round