(This blog post is part of a 5 part series, titled “How to launch IoT devices”. It will cover the key choices and concerns when turning bright IoT ideas into a product in the market. Sign up to the webinar on how to launch IoT devices to get the full story, all in one place.) First part: Why does IoT take so long? Second part: Select the right hardware and foundations Third part: IoT devices and infrastructure

Do you like gems? Perfectly cut diamonds? Crystal clear structures of superior beauty? You do? Then join me on a 10 minute read about a quest for hidden gems in your data: graphs! Be warned, it is going to be a mysterious journey into data philosophy. But you will be rewarded with artifacts that you can use to start your gemstone mining journey today.

Andreessen Horowitz recently published a blog about the Heavy Cloud Costs and Scaling Challenges of The New Business of AI, in which they describe how AI companies are facing cloud cost challenges, which are impacting their margins. As someone who used to manage a fully home-grown on-site distributed speech recognition platform for an industry leader, I know firsthand that ML can be expensive and challenging to maintain. However, it doesn’t have to be.

Maybe you’re interested in finding out more about deep learning? Maybe your current ML analytics are running too slowly or crushing your CPU and RAM? Or perhaps your boss has told you that they need an AI-based app so they can show off to their boss (who will then brag about it to their boss)?