I actually watched a couple of videos by Yannic Kilcher in the recent days, but that is a completely different format. There is probably a reason he does videos and not audio only, why he is not interviewing (and interviewing a different person with different expertise each episode).
What I value in Lex's content is that it is not complete pop-science level, that he is very neutral and especially that he leads his guest to make opinionated statements. The last point is usually the single value nugget I can extract from the episodes. It is basically a shortcut for me watching Yannic Kilcher like videos and getting deep into a topic through the proxy of a person who is not rarely one of the best in his field. I do not have the time / energy to get deeply into compilers and programming language design I just want to get a feeling in broad strokes where the field is heading, what are the key developments and bottlenecks that have shaped the past and especially future of certain technologies and applications.
I will probably dig a (tiny) bit deeper into MLIR after listening to the podcast because it seems to me to be the 80/20 kind of way to get a better feeling for the developments happening in compilers and how ML workloads are mapped to accelerators.
What I value in Lex's content is that it is not complete pop-science level, that he is very neutral and especially that he leads his guest to make opinionated statements. The last point is usually the single value nugget I can extract from the episodes. It is basically a shortcut for me watching Yannic Kilcher like videos and getting deep into a topic through the proxy of a person who is not rarely one of the best in his field. I do not have the time / energy to get deeply into compilers and programming language design I just want to get a feeling in broad strokes where the field is heading, what are the key developments and bottlenecks that have shaped the past and especially future of certain technologies and applications.
I will probably dig a (tiny) bit deeper into MLIR after listening to the podcast because it seems to me to be the 80/20 kind of way to get a better feeling for the developments happening in compilers and how ML workloads are mapped to accelerators.