Conferences, Refreshments, and What I Learn at the Networking Events

Organizational Structures
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One of the things I've missed are conferences and networking events.  When travel & expense budgets began getting ruthlessly cut, they cut their engineers off from the information exhange, from learning how the rest of the world communicates, what else is going on in the world.

Some of you might have seen me post that I attended a two day conference, Codess, a conference initiated by Microsoft (prior to the infamous 2014 Satya Nadella comment about women not needing to ask for a raise) for women coders.  Now, I write code even if I don't have a CS degree and the panels covered - yes - MACHINE LEARNING (via Facebook & Microsoft Applied Scientists & engineers), Facebook's distributed processing architecture to handle large data queries and caching, It was fun, but being around technical tecchies was like sitting in on two days of testing.  But a couple of things did get clarified for me.  Like, about machine learning.  Seems people finally have enough data about user experiences and data about humans to do more testing than sample sizes of 300.  We, in telecom, have been working with it much longer, we just never really called our ENGBHCA "machine learning," but that's what the machine is doing.  No idea what algorithms might be getting applied, but in our world we work primarily with Regression Analysis and Correlation in order to predict exhaust or customer impact.

But we have a hard time talking to people who work in the field of advertising and marketing data.  That's where things get sticky for us.  Also, we've been working for quite a while now with structured databases (i.e., we're not just using 'grep' to search for strings in files, etc.).  Facebook's Engineering Manager, Lianxiao Zhu gave a great topological view of the hardware systems used to support Facebook's data needs.  And answered that, yes, FB keeps all the data.  They don't throw data out with the dishwater.  I think I drooled a bit.  She also introduced some data structures I wasn't familiar with like the Tao Data Model.

In their eagerness to save a buck or two so they can buy, instead of grow customers, our company forgets that engineers need learn in the wild.  We are not hothouse plants, and the company greenhouses are actually more like industrial superfarms where familiar ideas are replicated ad nauseum with micro-scruitny by faceless workers walking around in white suits.

To grow, their technical leads need to be challenged by other industries, other ideas, other innovative thinkers.  A good engineer shouldn't ask to be led to the next interesting break-through, but should be fighting for a good seat in a packed conference room to hear the next application of ideas they've worked with their entire careers.

I'm headed to another all day conference for women in tech, tomorrow, held at Zulily. It's also a job fair.  There will be food and drink provided.  My ticket cost $25.  Sunday, I have my own Code Sisters Seattle Meetup.  Tuesday there is a mentoring event for entrepreneurs led by the City of Seattle's Start Up liaison.  Tuesday is a webinar with RStudio on how to start with Shiny and Friday another talk through Seattle's Incubator system on hardware development for startups.

I should have clamored for time off to attend these events, but I didn't.  I forgot how necessary being around fresh ideas were / are to my own technical development.  I finally feel like I'm beginning to get a grasp on the new languages being spoken out here in the wilds.  But there was one horrifying incident yesterday.  

One of the attendees spoke up at the panel talk, "fireside chats."  Basically, there was an executive panel talking about what companies & universities are trying to do to encourage women to remain in tech.  The attendee spoke up was a woman about 10 years older than I am (cringe), who was really just very angry that coding is now considered de rigeur for being a statistician, and how the "data scientist" job is displacing the work done by classical statisticians.  There was a lot of frustration she held, but when I talked to her later she was not interested in the availability of classes to learn how to use statistical languages, how this new term, "data scientist" is merging into the world.  Lord knows, I continually asked for a statistician in my Christmas stocking, but they still would have had to be interested in learning how to code.  Still, it was embarrassing to be an older woman with obviously grey hair and be associated with static ideas and a "world shouldn't change," attitude.  

Anyways, get yourselves out there, folks.  The world is large and it is grand.  Remember why you loved learning in the first place.  I don't know what the fuck I'm doing, but I'm learning lots these days and it is

glorious.