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[] Takeaways
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Systems Engineering in Machine Learning - Navigating Low-Level Challenges
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- 1 [] Andrew's preferred coffee
- 2 [] Introduction to Andrew Dye
- 3 [] Takeaways
- 4 [] Huge shoutout to our sponsors UnionML and UnionAI!
- 5 [] Andrew's background
- 6 [] Andrew's learning curve
- 7 [] Bridging the gap between firmware space and MLOps
- 8 [] In connection with Pytorch team
- 9 [] Things that should have learned sooner
- 10 [] Type of scale Andrew works on
- 11 [] Distributed training at Meta
- 12 [] Managing the huge search space
- 13 [] Execution patterns programs
- 14 [] Non-ML engineers dealing with ML engineers having the same skill set
- 15 [] Pace rapid change adoptation
- 16 [] Consensus challenges
- 17 [] Abstractions making sense now
- 18 [] Comparing to others
- 19 [] General principles in UnionAI tooling
- 20 [] Seeing the future
- 21 [] Inter-task checkpointing
- 22 [] Combining functionality with use cases
- 23 [] Wrap up
