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Google Blew It August 12, 2017

Posted by Peter Varhol in Technology and Culture, Uncategorized.
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I don’t think that statement surprises anyone.  Google had the opportunity to make a definitive statement about the technology industry, competence, inclusion, ability, and teamwork, and instead blew it as only a big, bureaucratic company could.  Here is why I think so.

First, Google enabled and apparently supported a culture in which views colored by politics are freely promoted.  That was simply stupid.  No one wins at the politics game (and mostly everyone loses).  We believe what we believe.  If we are thoughtful human beings with a growth mindset, our beliefs are likely to change, but over a period of years, not overnight.

Second, Google let the debate be framed as a liberal versus conservative one.  It is most emphatically not.  I hate those labels.  I am sure I have significant elements of each in my psyche, along with perhaps a touch of libertarianism.  To throw about such labels is insulting and ludicrous, and Google as a company and a culture enabled it.

Okay, then what is it, you may ask.  It is about mutual respect, across jobs, roles, product lines, and level of responsibility.  It is working with the person, regardless of gender, race, age, orientation, or whatever.  You don’t know their circumstances, you may not even know what they have been assigned to do.  Your goal is to achieve a robust and fruitful working relationship.  If you can’t, at least some of that may well be on you.

The fact that you work together at Google gives you more in common with each other than almost anyone else in the world.  There are so many shared values there that have nothing to do with political beliefs, reflexive or well-considered.  Share those common goals; all else can be discussed and bridged.  It’s only where you work, after all.

You may think poorly of a colleague.  God knows I have in the past, whether it be for perceived competence, poor work habits, skimpy hours, or seeming uninspired output (to be fair, over the years a few of my colleagues may have thought something similar about me).  They are there for a reason.  Someone thought they had business value.  Let’s expend a little more effort trying to find it.  Please.

So what would I have done, if I were Sundar Pichai?  Um, first, how about removing politics from the situation?  Get politics out of office discussions in general, and out of this topic in particular.  All too often, doctrinaire people (on both sides of the aisle) simply assume that everyone thinks their ideas are inevitably right.  Try listening more and assuming less.  If you can’t, Sundar, it is time to move aside and let an adult take over.

Second, Google needs everyone to understand what it stands for.  And I hope it does not stand for liberal or conservative.  I hope it wants everyone to grow, professionally, emotionally, and in their mindsets.  We can have an honest exchange of ideas without everyone going ballistic.

Get a grip, folks!  There is not a war on, despite Google’s ham-handed attempts to make it one.  We have more in common than we are different, and let’s work on that for a while.

I can’t fix Google’s monumental screw-up.  But I really hope I can move the dial ever so slightly toward respect and rational discourse.

The Incorrect Assumptions Surrounding Diversity in Tech August 7, 2017

Posted by Peter Varhol in Uncategorized.
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There was a time in my life when I believed that the tech industry was a strict meritocracy, that the best would out.  At this stage of my life, I now realize that is a pipe dream.

Can we define the best software engineers?  We can perhaps define good ones, and perhaps also define poor ones, in a general sense.  “I know it when I see it,” said former Supreme Court Justice Potter Stewart, speaking of pornography.  Which may not be that different from speaking of code.

The problem is that those are very subjective and biased measures.  The person who writes fast code may not write the best code.  The person who write the best code may be slow as molasses.  Which is better?  There are certainly people who write the best code fast, but are they writing code that will make the company and product successful?

There are a thousand tech startups born every year.  They think they have a great idea, but all ideas are flawed.  A few are flawed technically, but most are flawed in terms of understanding the need or the market.  Those ideas have blind spots that others outside of that creative process can also certainly readily recognize.

The ultimate question for companies is what do you want to be when you grow up.  Companies build applications that reflect its market focus.  But they also build applications that reflect its teams.  When we build products, we do so for people like us.

In tech companies, we are building a product.  I have built products before.  Software engineers make hundreds of tactical decisions on how to implement product every day.  Product managers make dozens of strategic decisions on what products to build, what it runs on, and what features to include.

I have made those decisions.  I am painfully aware that every single decision I make has an accompanying bias.  I dislike that, because I know that decisions I have made can foil the larger goals of being successful and profitable.

I want a diverse team participating in those decisions.  Because I don’t trust that my own biases will let me make decisions that will build the best product, for widest customer base.  I mean gender, race, economic status, orientation, age, everything I can include.  Many tech companies use the term “cultural fit” to eliminate any diversity from their teams.  Diverse teams may have more tension, because you have different experiences and think differently, but you end up making better decisions in the end.  I’m pretty sure that’s demonstrable in practice.

You may believe that you know everything, and are the best at any endeavor you pursue.  Let me let you in on something: you are not.  We would all be amazed at what everyone around us can contribute.  If we just let them.

The Internet is After Me August 4, 2017

Posted by Peter Varhol in Uncategorized.
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The Internet is after me.  It’s trying to grab my attention, for a few seconds, so I can dote on cute little kittens scurrying across my dinner, in exchange for my unconscious watching an ad for Tidy Bowl for half a minute.

Hey, I’m old.  Did I tell you that?  I must have forgotten.  Kittens are the only thing I recognize on the Internet, but boy, are they cute.  I have cats, and they sure are cute, but the ones on the Internet are so highly trained in the art and science of cuteness that I simply can’t stop looking at them.  But there is a problem.

I walk down the street, looking at my kittens on a screen that my eyes can barely discern, and I see random ads popping up on the screen.  In fact, the ads are covering up the kittens!  I stop abruptly, causing a little boy to crash right into my backside, and look around me.

Yes!  There is the Hamburger Haven, right across the street.  I look back down and my screen, and yes, the kittens were chasing hamburgers!  And when a kitten caught one, it polished it off with a lick of its lips and a smirk on its face.  What a cute kitten!

It made me hungry just watching.  I looked up again at the Hamburger Haven, then started crossing the street.  I didn’t get far before I got clipped by a car.  I spun around and fell, but was still focused on getting to that hamburger.  Double meat, double cheese, bacon, oh yes bacon, lettuce, and ketchup.  A tomato would not be overkill, would it?

I wasn’t hurt, more startled, but the car screeched to a stop, and a young guy got out.  He was looking at his phone as he rushed to my side, but I don’t think he was calling 9-1-1.  No, he showed me the screen, and said, “Let’s go get a hamburger.”  Damn.

So we had a hamburger.  And super fries.  And a drink.  But as I licked my lips, I realized an essential truth.

They not only know who I am, they know where I am.  And they want to sell me hamburgers.  Maybe panty hose, though I hope not.  But kittens?  Oh yes, show me more kittens.

What Brought About our AI Revolution? July 22, 2017

Posted by Peter Varhol in Algorithms, Software development, Software platforms.
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Circa 1990, I was a computer science graduate student, writing forward-chaining rules in Lisp for AI applications.  We had Symbolics Lisp workstations, but I did most of my coding on my Mac, using ExperList or the wonderful XLisp written by friend and colleague David Betz.

Lisp was convoluted to work with, and in general rules-based systems required that there was an expert available to develop the rules.  It turns out that it’s very difficult for any human expert to described in rules how they got a particular answer.  And those rules generally couldn’t take into account any data that might help it learn and refine over time.

As a result, most rules-based systems fell by the wayside.  While they could work for discrete problems where the steps to a conclusion were clearly defined, they weren’t very useful when the problem domain was ambiguous or there was no clear yes or no answer.

A couple of years later I moved on to working with neural networks.  Neural networks require data for training purposes.  These systems are made up of layered networks of equations (I used mostly fairly simple polynomial expressions, but sometimes the algorithms can get pretty sophisticated) that adapt based on known inputs and outputs.

Neural networks have the advantage of obtaining their expertise through the application of actual data.  However, due to the multiple layers of algorithms, it is usually impossible to determine how the system arrives at the answers it does.

Recently I presented on machine learning at the QUEST Conference in Chicago and at Expo:QA in Spain.  In interacting with the attendees, I realized something.  While some data scientists tend to use more complex algorithms today, the techniques involved in neural networks for machine learning are pretty much the same as they were when I was doing it, now 25 years ago.

So why are we having the explosion in machine learning, AI, and intelligent systems today?  When I was asked that question recently, I realized that there was only one possible answer.

Computing processing speeds continue to follow Moore’s Law (more or less), especially when we’re talking floating point SIMD/parallel processing operations.  Moore’s Law doesn’t directly relate to speed or performance, but there is a strong correlation.  And processors today are now fast enough to execute complex algorithms with data applied in parallel.  Some, like Nvidia, have wonderful GPUs that turn out to work very well with this type of problem.  Others, like Intel, have released an entire processor line dedicated to AI algorithms.

In other words, what has happened is that the hardware caught up to the software.  The software (and mathematical) techniques are fundamentally the same, but now the machine learning systems can run fast enough to actually be useful.

The Final Frontier July 6, 2017

Posted by Peter Varhol in Education, Technology and Culture.
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Yes, these are the voyages of the Starship Enterprise.  Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before.

To someone of my age, this defined the possibilities of space, perhaps even more so than the Apollo 11 landing on the moon.

We failed at this, in my lifetime, to my dying (hopefully not soon) regret.  We failed, not because of a lack of technology, but because of a lack of will.  Since the 1980s, America has been looking inward, rather than reaching for the next brass ring in the universe.

Today, we have no ability to launch astronauts into orbit.  No, we don’t.  Our astronauts go into orbit courtesy of the ESA or the Russians (not sure that ESA is doing all that much any more).  I am sure many of you are pleased at this, but you miss the larger picture.

May I quote Robert Browning: “Ah, but a man’s reach should exceed his grasp, Or what’s a heaven for?”

Seriously.  Life is bigger, much bigger, than our individual petty concerns.  We may think our concerns are larger than life, but until we reach beyond them, we are petty, we are small.  Until we give ourselves to larger and more grandiose goals, we are achieving nothing as human beings.

Look at the people, throughout history, who have given their lives, willingly, in favor of a larger goal.  Not just the astronauts, but soldiers, sailors, explorers, yes, even a few politicians.

Today, my only hope is with the private companies, SpaceX, Blue Origin, Virgin Galactic, and their ilk.  They are our future.  Not NASA, or the government in any way, shape or form.  I hope with all of my heart and soul they can reach where the collective citizenry has declined to.

Set controls for the heart of the sun.

Why I Have to Keep Task Manager Running in Windows July 2, 2017

Posted by Peter Varhol in Software platforms.
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Over the last year or so, my daily personal laptop has been running slower and slower.  For a variety of reasons, Windows performance and reliability tends to degrade over time.  Memory especially, but also disk and CPU have been pegging at 100 percent all too frequently.  I suppose I could wipe the system and start again from scratch, but that’s also a good indication that it’s time to get a new laptop.

I’ve upgraded to a new laptop, a midrange Core i5 quad-core system with 8 GB of RAM, running Windows 10.  That will fix my memory, CPU and disk problems, I thought.

Wrong.  My system still hung regularly.  So I started investigating in more detail.

Chrome, for one very big reason.  I will typically keep four or five tabs open, and it doesn’t take long for one or two of them to take up well over 2GB of memory.  And I’m talking about very commonly used sites, like weather.com, fitbit.com, or cnn.com.

While I’ve read several reasons (some of which are contradictory or don’t reflect my situation) why Chrome consumes memory like a drunken sailor, there doesn’t seem to be a whole lot to do about it.  Some talk about disabling add-ins; the only add-in I have running is Flash, and that is still required by many commercial websites (and crashes just as frequently).

Chrome has also been known to consume huge amounts of CPU and disk bandwidth.  I haven’t really read anything actionable about what to do here.

So I keep Task Manager open.  When a Chrome tab starts to misbehave, there is no alternative but to kill the process.

But wait!  It’s not just Chrome!  In Windows 10, there’s also this process called Microsoft Telemetry Service (and yes, it is a Windows Service).  I found this service using 99 percent of my CPU on more than one occasion.  What does Microsoft Telemetry Service do?  It sends use information from your computer to Microsoft.  Not just error information; use information.

It is enabled by default.  If you disable it, some of the Windows updates will re-enable it without telling you.

My very strong recommendation is to disable it and the horse it rode in on.  I guess this is what we deserve in the Facebook era, where we have no privacy.

About Uber, Friction, and Life June 28, 2017

Posted by Peter Varhol in Technology and Culture.
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No matter where you are in most major or even minor cities around the world (yes, there are significant exceptions), you can pull out your smartphone, press a couple of buttons, and have an Uber taxi meet you at your location in a few minutes.  You compare the driver with the photo you received, and you have a measure of security.  The driver already knows your destination, and you know that you don’t have to pass him (or her) some cash at the end of the process.

And that’s the way it should be, in this day and age.  The technology has been there, and Uber, Lyft, and their ilk are bringing it together.

But let’s take an honest look about what we are trading off, because there are always tradeoffs.  In this case, we are trading off friction.  By friction, I mean the hassle of hailing a commercial taxi, finding the phone number and calling a taxi company, or getting to a location where taxis tend to congregate.

(And as I was told in Stockholm last month, all taxis are not created equal.  “Don’t take that one,” the bell captain at a hotel said.  “They will gouge you.”)

All of this sounds like a good thing.  But it turns out it is part of the life learning process as a person.  For the first twenty-three years of my life, I never saw a taxi, or a train, or a subway.  I grew up in rural America.  Today I am comfortable finding and navigating all of the above, in any city in the US or Europe.  Why?  Because I had to.

(And incidentally, no matter the payment method, I always tip in cash.  These folks work for a living, and deserve the discretion of how and where to report their tips.)

I have grown as a person.  That’s difficult to quantify, and certainly given a more frictionless path in the past I might well have chosen it.  But the learning process has built my confidence and yes, my worldliness.  I am more comfortable navigating cities I have never been to before.  I don’t stay in a bubble.

If you are using Uber (and Lyft) as an excuse for not interacting with others, especially others who are different from you, then you are not learning about the world, and how to interact with it.  And as your life winds down, you may come to regret that.

The Future is Now June 23, 2017

Posted by Peter Varhol in Algorithms, Technology and Culture.
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And it is messy.  This article notes that it has been 15 years since the release of Minority Report, and today we are using predictive analytics to determine who might commit a crime, and where.

Perhaps it is the sign of the times.  Despite being safer than ever, we are also more afraid than ever.  We may not let our electronics onto commercial planes (though they are presumably okay in cargo).  We want to flag and restrict contact with people deemed high-risk.  We want to stay home.  We want the police to have more powers.

In a way it’s understandable.  This is a bias described aptly by Daniel Kahneman.  We can extrapolate from the general to the particular, but not from the particular to the general.  And there is also the primacy bias.  When we see a mass attack, was are likely to instinctively interpret that as an increase in attacks in general, rather than looking at the trends over time.

I’m reminded of the Buffalo Springfield song: “Paranoia strikes deep, into your lives it will creep.”

But there is a problem using predictive analytics in this fashion, as Tom Cruise discovered.  And this gets back to Nicholas Carr’s point – we can’t effectively automate what we can’t do ourselves.  If a human cannot draw the same or more accurate conclusions, we have no right to rely blindly on analytics.

I suspect that we are going to see increased misuses of analytics in the future, and that is regrettable.  We have to have data scientists, economists, and computer professionals step up and say that a particular application is inappropriate.

I will do so when I can.  I hope others will, too.