For background, Pete was a founder of jetpac which scraped millions of images from Instagram to use as content in their company which Google bought. [1] This e

For background, Pete was a founder of jetpac which scraped millions of images from Instagram to use as content in their company which Google bought. [1] This essay’s bold claims about nvidia are like jetpac: something shortsighted, flashy, and designed to make Pete money. Several flags in the essay: “Machine learning is focused on training, not inference” Nope! There are many start-ups that do large-scale inference in the cloud, and have been long before Transformers existed. Some of said companies are customers of e.g. Roboflow and Determined.ai etc. Sure it’s not Google-scale, as Pete has been in Tensorflow land for the past few years. “Researchers have the Purchasing Power.” False! Some can afford a 2-GPU machine, but Pete’s employer and many other large companies have shifted the attention of researchers to problems that require large clusters. It’s almost impossible to publish now (e.g. reproduce results and do something new) without Google’s network (hardware money and people) having a hand in it. The rest of the essay outlines a thesis that an inference-focused product (where Pete invests himself) will disrupt nvidia. Investors take note! Googler is almost done with his handcuffs! There are many risks to nvidia’s moat (they failed to get Arm after all) but this piece is about Pete trying to find investors, not about Nvidia. [1] e.g. https://petewarden.com/2018/05/28/why-you-need-to-improve-your-training-data-and-how-to-do-it/ https://petewarden.com/2018/05/28/why-you-need-to-improve-yo... Among others