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episode 50: Sam Ritchie on Portal Abstractions


Buckle up, on today’s episode Adam interviews Sam about how the abstract algebra and probabilistic data structures helped solve fast versus big data issues that many are struggling with. Sam Ritchie is a machine learning researcher and a mechanical engineer by training.

Stop in to hear Adam and Sam’s conversation about portal abstractions that let you leverage work from other fields. You cannot miss this episode!

"And that's really all we want to do. Like, we want things where you can pause and wait a while and then load it back out and keep going." - Sam Ritchie

"I'm aiming to implement these interfaces and pass these tests and then being able to immediately turn around and have like an approximate sliding window counter that would just work with stripes, like entire machine learning feature generation interface." - Sam Ritchie

"I'm really passionate about and the reason this stuff's important is. You want to go mine the literature of what other people have done. You know you want to go be able to plug these things into your work and really just benefit from this incredible community that's been cranking for, you know, again, maybe hundreds of years." - Sam Ritchie

Episode Page

Episode Transcript

Links:

Sam's Blog

Summing Bird

Algebird

Reinforcement Learning


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 April 17, 2020  35m