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Quantization, Linear Regression, and Hardware for AI: Our Best Recent Deep Dives

Our weekly selection of must-read Editors' Picks and original features

Photo by K8 on Unsplash
Photo by K8 on Unsplash

There are times when brevity is a blessing; sometimes you just need to figure something out quickly to move ahead with your day. More often than not, though, if you’d like to truly learn about a new topic, there is no substitute for spending some time with it.

This is where our Deep Dives excel: these articles tend to be on the longer side (some of them could easily become a short book!), but they reward readers with top-notch writing, nuanced explanations, and a well-rounded approach to the question or problem at hand. We’ve published some excellent articles in this category recently, and wanted to make sure you don’t miss out.

Happy reading (and bookmarking)!

  • Quantizing the AI ColossiSure, Nate Cibik‘s comprehensive guide to quantization might be an 81-minute read, but we promise it’s worth the investment: it’s a one-stop resource to understand the mathematical underpinning of this ever-relevant approach, catch up with recent research, and learn about the practical aspects of implementation, too.
  • Linear Regressions for Causal ConclusionsFor a thorough and highly accessible intro to linear regression, especially in the context of business problems and decision-making scenarios, head right over to Mariya Mansurova‘s latest explainer, which shows how a relatively straightforward method can yield sophisticated insights.
  • Groq, and the Hardware of AI – Intuitively and Exhaustively ExplainedWe all know that recent advances in AI depend on major improvements to computing technology, but far fewer among us can explain in detail how this evolution unfolded. This is where Daniel Warfield‘s stellar overview kicks in, taking us through the entire recent history of hardware from CPUs and GPUs to TPUs and beyond.

Thank you for supporting the work of our authors! If you’re feeling inspired to join their ranks, why not write your first post? We’d love to read it.

Until the next Variable,

TDS Team


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