Obviously, today’s newsletter is publishing much later than normal, so I am going to keep this brief and just highlight a couple of things worth reading.:
This macro-analysis of the Intel-Mobileye deal from Stratechery. It’s a great look into the economics of chips to begin with, and also self-driving or otherwise-smart cars. The only thing it’s missing, if you ask me, is a reference to the data center, where Intel getting inside cars might also be a way to ensure Intel remains the chipmaker of choice on the backend of the connected car workflow, as well.
Basically, how does Google balance CIOs and software developers in its go-to-market strategy? This is the biggest question for pretty much everybody, but which AWS was able to largely avoid early on by just creating its own market.
It’s the guy who co-founded Geometric Intelligence, the company Uber acquired in December and that catalyzed Uber AI Labs. The former chief scientist, Gary Marcus, was the other co-founder, but he resigned last week.
This is a smart, existential take from SwiftKey’s Ben Medlock on the question of whether AI can really be smart like humans. Basically, he argues, millions of years of evolution connecting our brains with our bodies will be hard to replicate in machines.
The Cloudera Data Science Workbench is one of the company’s first steps toward an actual application, targeting the folks who actually try to make us of systems like Hadoop and Spark. Hard to tell if there’s a SaaS option, though—which would be a good idea.
No one every accused MapR of not pushing the envelope in terms of product offerings. It’s new “mini-cluster” is a really smart idea and potentially a foot in the door to winning industrial IoT workloads.
Last week, Google announced a cloud data-preparation service built using Trifacta’s software. Data prep is arguably one of the most important, and most overlooked, aspects of actually doing big data (and AI, for that matter) right.
Basically, Rheos provides lifecycle management and monitoring across eBay’s streaming pipeline and across data centers. The effort that goes into building something like this is why people think most companies will just adopt cloud services.
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