Recap of the 2017 Interop ITX Conference

I spoke at 2017 Interop ITX Conference which ran from May 15 – 19 in Las Vegas. See http://www.interop.com/. I estimate there were about 3,000 attendees. Most of the attendees I spoke to were fairly senior managers at all kinds of companies, small to large, in all kinds of businesses.

My talk was titled “Understanding Deep Neural Networks”. I explained in some detail what regular NNs are, then described some variations of DNNs including convolutional NNs, recurrent NNs, LSTM NNs, and generative adversarial networks. I also mentioned a bit about some of the work Microsoft Research is doing in the area of deep learning. My talk was hosted by Sam Charrington, who is very knowledgeable, and who gave a great intro to the current state of ML. See https://twimlai.com.

I’ve spoken at many Interop events over the years and each one was different from all the others. My overall impression is that most of the nuts-and-bolts challenges of enterprise networks seem to have been solved and that the two dominant issues are security and evolving infrastructure to give a competitive business advantage (such as predictive systems that use deep neural networks).

Other talks at the event that I particularly liked were “Machine, Platform, Crowd” (Andrew McAfee, MIT), “Machine Learning” (Josh Bloom, General Electric), and “AI for Wireless Networking” (Ajay Malik, Google).

Anyway, I met a lot of interesting people and picked up a lot of useful information, mostly about the current state of machine learning in enterprises. Every company I talked to is trying to find some way to get expertise in how to create advanced predictive systems.

The bottom line is that the 2017 Interop ITX conference was a good experience. I intend to speak there next year and if you work in IT management I recommend you consider attending too.

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