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Why You Should (or Shouldn't) be Using Google's JAX in 2023

assemblyai.com · 5,273 words · saved by 1 readers

Should you be using JAX in 2023? Check out our recommendations on using JAX for Deep Learning and more! Developer Educator at AssemblyAI Since Google's JAX hit the scene in late 2018, it has been steadily growing in popularity, and for good reason. DeepMind announced in 2020 that it is using JAX to accelerate its research, and a growing number of publications and projects from Google Brain and others are using JAX. With all of this buzz, it seems like JAX is the next big Deep Learning framework, right? Wrong. In this article we’ll clarify what JAX is (and isn’t), why you should care (or shouldn't, but you probably should), and whether you should (or shouldn’t) use it. Let’s dive in! Recommendations Note If you're already familiar with JAX and want to skip the benchmarks, you can jump ahead to our recommendations on when to use it here It may be best to start off with what JAX is not. JAX is not a Deep Learning framework or library, and it is not designed to ever be a Deep Learning fram

Why You Should (or Shouldn't) be Using Google's JAX in 2023 Introducing our Voice Agent API: The fastest path to a working voice agent Learn more Customers Developers Resources Playground Pricing Enterprise Contact us Log in Get started Insights & Use Cases February 15, 2022 Why You Should (or Shouldn't) be Using Google's JAX in 2023 Should you be using JAX in 2023? Check out our recommendations on using JAX for Deep Learning and more! Ryan O'Connor , Senior Developer Educator JAX Reviewed by No items found. Table of contents [Visible on live site] Since Google's JAX hit the scene in late 2018

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