Light reading day today, but still read, listened to, and watched some good things. Check out a handful of AI pieces, guidance on data processing, and clarification on what SRE is all about.
[blog] Data-centric ML benchmarking: Announcing DataPerf’s 2023 challenges. All these snazzy AI/ML models are useless without decent data that’s been sourced and prepped. Here’s a new effort to identify, improve, and incentivize good data-centric models.
[article] Debunking Myths About Reliability. How much reliability is too much? What’s more important, innovation or reliability? Kit explores those questions here.
[blog] Where does a data center go to retire? Wayfair’s 2,000 servers are going off to colleges. Server have a long life, so what do you do with the ones you have after moving all your workloads to the cloud. I like this story.
[podcast] Jennifer Mace on How Google Does SRE. If you kinda sorta understand what Site Reliability Engineering is about, but freeze up when someone asks you to explain it, take 30 minutes and listen to this podcast. It’s the best explanation I’ve heard.
[blog] How to use ChatGPT for product marketing. This post has some useful ideas for generative AI. I’ve started doing a few of these this week.
[article] Batch Processing vs. Stream Processing: Why Batch Is Dying and Streaming Takes Over. Batch isn’t dying, but maybe it’s not growing as quickly as more real-time data processing solutions. Good overview here, though.
[youtube-video] Which AI/ML solution on Vertex AI is right for me? Good, short video that explains the types of AI/ML solutions you may build.
[blog] Got your eye on AI? Try these 6 interactive tutorials. I’ve done one of these, but it was good to get a link to other tutorials for learning about AI/ML.
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Richard Seroter's Architecture Musings 
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