

685: Tools for Building Real-Time Machine Learning Applications, with Richmond Alake
Jun 6, 2023
Richmond Alake, Machine Learning Architect at Slalom Build, discusses his startups, podcasting, and new course on feature stores. He emphasizes the importance of writing for data scientists and shares insights on building real-time ML applications, developing AI companions, and investing in MLOps. The episode covers his use of tools like Databricks, Kinesis, and Swift programming for ML production.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9
Intro
00:00 • 2min
Understanding Machine Learning Architecture and Engineering
02:14 • 7min
Building Real-Time Machine Learning Applications and Working on Startups
09:44 • 3min
Virtualizing Personal Training Experience with Real-time Machine Learning
12:41 • 15min
Discussion on AWS Trainium and Inferentia Chips for AI Applications
27:59 • 2min
Challenges of Book Writing, Taking Risks, and Feature Stores in Machine Learning
30:13 • 12min
Exploring AI Companions, Timeless Skills, and Forward-Thinking AI Strategies
42:33 • 3min
Transition from Physics to Data Science, Investment in MLOps, and Writing for Data Scientists
46:02 • 17min
Exploring Tools and Technologies for Real-Time Machine Learning Applications
01:03:18 • 3min