This is an excellent write-up on the practical aspects of standing up a predictive model. Useful for both practitioners and managers, because it’s not a matter of code or specific training routines but rather conceptual focus. Couldn’t agree more with the fundamental premise: too many teams spent too long iterating on incremental model performance, and don’t move quickly enough to test it in the field and solve all the challenges of predicting things in context that have nothing to do with the model itself.

As a visual and interactive piece of storytelling, this piece is AMAZING. All caps, really, the presentation alone is an achievement. Deeply technical, it will walk you through how neural networks recognize images and use really novel interpretability techniques in combination to illustrate the underlying mechanics. You will feel really smart after reading this and the interpretability concepts explored here are very powerful. Hopefully, as the conclusion states, with ongoing development they will be a powerful tool in enabling meaningful human oversight and in building fair, safe, and aligned AI systems.

Viya is SAS’ fifth attempt to deliver a scalable platform. It’s possible that SAS has finally nailed it; I know of at least one customer that uses the software, and they seem happy with it. But customers don’t seem to be voting with their pocketbooks. SAS launched Viya in 2016, and it was generally available for all of 2017. In a market growing at double digits, SAS barely managed 1% revenue growth in 2017. If customers bought Viya, they pulled the plug on legacy SAS rather than expanding the footprint.

If you’ve been in the data/analytics space for any significant amount of time, you’ve come across SAS which engenders a love/hate relationship like few platforms. Hate is probably a strong word, to be fair, but we certainly don’t fall on the love side of that equation. There’s just a monolithic ivory-tower-ness that the entire platform exudes, from its pricing to integration. Personally, the best thing I’ve learned in SAS is “PROC SQL. This is a great no-bs analysis of recent happenings at SAS that highlights the fundamental issues with their path in real concrete terms.