The Builder

Wearable Tech – Testing Out the Myo Armband


I pre-ordered the Myo Armband well over a year ago. After multiple iterations and a period of time for developers, Thalmic Labs finally started shipping their first customer beta versions of the Myo Armband. The Myo allows you to control (soon to be any) Bluetooth devices via arm-gestures. As the marketplace/ecosystem grows (think the iTunes store), you’ll be able to control more devices with more gestures.

Initial Reaction: It’s pretty mind-blowing to control the devices around you without having to physically interact with each and every single one. I personally prefer to gesture control devices around me, as opposed to voice control devices. Gesture and voice control I believe will be the future of interacting with tech, but they each will have their places. For example, I’d rather voice control devices in a car, but would rather control a home entertainment system in my house with gestures. Though I do believe much further down the road, they will exist together, but for the foreseeable future, each will be relegated to their own applications.

Thoughts Going Forward: If you look up reviews on Myo so far, they are fairly mixed. But I feel the poor reviews are by people who have never worked at a hardware/software company before and don’t understand/appreciate how hard this stuff is to build. My take on the Myo is this a great step in the right direction and knowing that it will get better with time is promising. I compare it to the Rio PMP3000, one of the first MP3 players in the late 90’s. I bought this 32MB device and have the same feeling, the technology itself is extremely innovative, but there are glaring holes in the technology that you would assume be solved over time. I think we all know what happened with MP3 players in the few years after the PMP3000, with a little device called the iPod and a company called Apple.

How It Works: Out of the box, the Myo Armband recognizes 5 gestures: wave right, wave left, spread fingers, fist (with rotation left/right), and tapping of fingers to thumb. Once you’ve connected it to the Bluetooth device of your choice (Mac, iOS, PC, Android, with more to come), you make a gesture to activate the Myo Armband. From there, it’s best to let the Myo Armband adjust to your arm for about 2 minutes. After it has adjusted to control the device you’re connected to, you must “unlock” the Myo Armband before executing an action. For example, say I have it connected to my Spotify on my phone. To turn up the volume, I must “unlock” by double tapping finger to thumb. The Myo is then unlocked for roughly 2 seconds for me to begin performing a recognized gesture. Once unlocked, I make a fist and rotate it clockwise to turn the volume up. Once I’m done adjusting the volume, I return my hand to a “resting position” and the Myo locks again.

My Use/Thoughts So Far: In the first few days, I’ve been doing chores around the house while controlling the music on my Sonos system. It’s pretty awesome. The downfall of the Armband at this point are that at times it identifies other actions as the “unlocking” and/or one of the five recognized gestures, thereby doing unintended actions. My current workaround for this is if I know I’ll be active in the near future, I’ll move the armband to deactivate the connection. Then, next time I want to change a song, I do the syncing action, then can immediately perform the 5 gestures, as the Myo recognizes it hasn’t left my arm, so therefore doesn’t need the 2 minutes to sync.

Napster, Uber, AirBnB, and Bitcoin VERSUS Regulation


If you have Netflix and are a 90’s kid, watch the documentary Downloaded. The Napster documentary takes an interesting look into how a technology (peer-to-peer file sharing) single handedly brought the music industry to its knees. While watching it, I couldn’t help but think of two things: 1.) Shawn Fanning is the man (founder of Napster) 2.) several other industries are experiencing the same level of disruption today (taxi industry – Uber, hotel industry – AirBnB, and I would argue the financial payment industry – Bitcoin).

To give some quick background, when Napster came around, it was the music industry and its constituents that refused to understand and embrace the technology, and instead decided to sue the technology to high-heaven. This ultimately led to the downfall of Napster within two years of its humble beginnings, where its community reached as many as 60 million users (ridiculous). The music industry was colluding, i.e. all major labels were price-fixing the price of CDs at $15. It was the failure of an industry to innovate and diversify their business models that caused this technology to hurt revenues so much.

Now to today, all of the recent legislation and legal battles that this new wave of startups is facing, is similar to what Napster went through. Granted, technically, people were stealing music through Napster, but, the technology itself (peer-to-peer file sharing, decentralized file systems) was able to scale and could have been repurposed for a more legal use. The taxi industry, in one municipality or another, is fighting to keep Uber out. They are always finding these laws that have been setup over time that in some way shape or form make taxi-like services that aren’t sanctioned cab companies illegal. (Side rant: two reasons I despise our government. Too many laws; solution: for every law that we add, we get rid of another. Laws that are too protective of industries that disincentivize innovation. Technology is our friend, not our enemy). I feel like Uber has fought its way through a fair amount of regulation, legally, and will thrive.

The others AirBnB and Bitcoin are still in their infancy and possibly their first iteration of their service. The documentary brings this fact to light, where, although Napster failed, many copy-cats and enhanced legal versions of the technology popped up. Despite Napster failing, the technology and service survived, and ultimately thrived over the next decade (i.e. Spotify, Pandora, etc.). Despite the diminished success of AirBnB and Bitcoin, relative to Uber, don’t think that the technology will go away. Other startups will iterate and learn what worked and didn’t work for AirBnB and Bitcoin, and create a product that works. (Side note: I feel AirBnB will be successful, but it has much more legal mumbo jumbo to fight through, and ultimately change. Bitcoin is the wave of the future, yup.)

 

Today’s Unemployment/Underemployment Is Not Driving the Growth of “Uber for X” Companies


I ran across an interesting article on Bloomberg where the columnist argues that if it wasn’t for today’s “unusual” unemployment/underemployment (underemployment is where people are over-qualified for their current jobs), startups like Uber, Lyft, Instacart, Postmates, etc. would NOT have the large network of drivers that allow them to deliver quality on-demand services, thus driving their growth and valuations.

It’s absolutely insane to me that anyone can make this argument with any type of credibility. If the logic of her argument were to hold true in other recessions, she is saying that if these contract jobs were to have popped up then, these startups wouldn’t have survived. It’s ludicrous to think that if Uber would have existed in the 60’s, 70’s, or 80’s, that no one would have signed up to work for the company. I’m a firm believer that the American workforce will gladly do these “side-jobs”, especially when there is little to no qualifications barring them from making the extra side-cash. What makes these types of jobs extremely attractive for the long-term, and this isn’t just a fad as she concludes, is that workers get to utilize an asset (their car) that would otherwise be idle and costing them money. Irregardless of whether this is a historic time for underemployment or not, Americans will always be looking to make more money to pay for that extra something, fill a void of unemployment, or make ends meet more reasonably.

Coming from a tech startup, I may have my own biases, but ignorance shouldn’t be allowed in mainstream media. When non-tech people claim that an idea/company won’t work, it makes us tech people work that much harder, and more times than not, that same naysayer is singing that company’s praises years later.

Finding The Answers in Big Data


Ah, BIG DATA. In the last few years there haven’t been bigger buzz words than those. If you haven’t heard of it, then I hate to break it to you, but everyone and their mother have been talking about it, look at the Google searches over last ten years.

2014-08-26 21_31_01-Google Trends - Web Search interest_ Big data - Worldwide, 2004 - present

Working at an artificial intelligence startup, we’ve seen our fair share of clients/prospects looking for an alternative to all of the dashboards out there (Tableau, Domo, etc.). With these dashboards (just a fancy word for all of the data and charts about your business on one screen), they don’t scream at the user what they should know, or what business decisions need to be made next based on all of their current data. It takes interpretation and people are afraid to get the answers wrong.

As we continue on this path of “sensor-ized everything”, people and businesses will be able to collect more data on themselves and about others, to possibly influence decisions. Regular consumers with their FitBits and businesses with rewards cards and cookies in their websites; all of that data is now at their fingertips, but the question is, how do we turn all of that into actionable items? But more importantly, the correct actionable items?

Today companies are working to figure out how to interpret all of this new found data and how to act correctly upon it. Sure, you can throw all of the correlations, relationships, and other fancy stats at these new data sets and find which one leads more directly to increased sales. But the funny thing is, there is rarely one answer to this question. What people need are instantaneous perspectives and explanations as to what all of this means to their business without having to interpret the correct answer, and to have those explanations change as the data changes, to better help businesses understand the current state of their business.

The way I see it, there are a couple of answers to the “big data” problem:

1.) Businesses need tools to not only aggregate all of their old and “new” data, but a way to communicate that data, and its every changing properties. The only way to do that is through hiring people to dig into and communicate all of this data. But that is hardly feasible, given the capital needed to hire the necessary talent. That’s where artificial intelligence comes in.

Now, let me rant a little bit. Artificial intelligence can mean numerous things, and it means something different to everyone. “Deep learning” is one practice of AI, “machine learning” is another. People associate “algorithms” with AI. Heck, you could even classify the first chess program that beat a person as AI.

What’s different about today’s AI, however you want to classify it, is it can begin to understand the outcomes of it’s analysis and communicate it. That’s where Narrative Science comes in. When the world starts collecting more data, businesses should have systems/applications in place that allows the data to speak to us, instead of employing more resources to look at dashboards to give us the same insight.

Oh, and the second answer to “big data”, in my opinion, is good ol’ common sense.

Why We’re Not in a Tech Bubble – “The Tech-Only Argument”


There has been a lot of talk over the last year or so over one simple question, are we in another tech bubble? There are pundits on both sides making their cases, both tend to have valid arguments.

Coming from a tech enterprise startup, I tend to lean on the side of “No. We aren’t in a tech bubble.” For a handful of reasons; I could write a dissertation on this, but for now I’ll solely focus on technology, as opposed to including my views around valuations, exits, and funding levels (i.e. the investment environment around startups).

1.) When I was 10 years old (late 1998), I bought an MP3 player, one of the first of its kind. This was back in the day when I had to Google (back then it was Yahoo! or Lycos) for Mp3’s. Guess what the storage size on this thing was (pictured below), and how many songs it held? 32 megabytes, that would hold roughly 12 songs (depending on the compression/bit rates). I paid $200 to be  the first of many to have the songs I wanted to listen to on a portable device, and most importantly, a device that doesn’t skip. That was right around the first tech bubble, which was made up of Geocities websites, 32MB MP3 players, and Lycos was the top search engine. I think we all can argue that the landscape has changed for all tech products/services since then. Which leads me to my next points.

done-rio-pmp300

2.) This is a mind-blowing stat, “In 1995, the average cost per gigabyte was $1,120. Last year it was $.05. 22,000X+ improvement in 2 decades will change a lot of things.”

3.) We didn’t have PCs in our pockets back in the late 1990’s/early 2000’s. Sure cell phones might have been on a meteoric rise, but smart phones were not existent. Just think of all of  the industries, companies, and jobs focused solely on fighting for ad space on your phone’s screen; or way that you interact with your friends that a PC never could (Snapchat, FaceTime, Uber). I remember I used to dread trying to stream a video online and would usually go eat dinner, then by the time I was done, it would be loaded so I didn’t have to wait for it to buffer.

4.) I also firmly believe that the general public and investment community’s understanding of technology’s power greatly lags where it currently stands. Back in the tech bubble, there was  a great focus on technology hardware, as opposed to software. At the time, people were able to get their hands on technology, and now the advancements in power is being burdened by software companies in the cloud, and are intangible to the end user. For example, you don’t need a new device for each app on your iPhone. These companies are taking on the computing power and distilling the information down to something consumable, in one ecosystem (Apple/Android). My point is further validated by the illustration below which shows the amount of business investment in hardware vs. software since the tech bubble.

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5.) I bet we can call come up with our “back in my day” moments with technology. But in efforts to keep these posts a fairly short read, I’ll keep it at five reasons, and will leave you with this (from PandoDaily). Each generation is shaped by defining moments, like the tech bubble. But we can’t let those past events cloud our judgement in the future.

Here are some facts about our incoming 9th graders… the class of 2018!

  • Incoming high school freshman were born in the year 2000 or 2001.
  • They were newborns when Wikipedia was formally launched.
  • They have lived [entirely] in a world in which monthly texting limits do not exist.
  • They were toddlers when MySpace was launched. They were about to enter Kindergarten when it was acquired by News Corporation for $580 million, and were rising 5th graders when it was sold again for mere $35 million.
  • They were in preschool when Facebook moved to Palo Alto, CA.
  • Some of them were born the same year the first Apple store opened.
  • They have been alive for 3 (maybe 4) Harry Potter books.
  • They do not know that “Blockbuster” was a video-rental place.
  • If they pay attention to the news, all they know about Clay Aiken is that he is running for Congress.
  • Paris Hilton was never popular.
  • The Spice Girls are middle-aged British singers.

 

 

The Singularity (Robots Take Over) and Artificial Intelligence


The Wikipedia definition of “The Singularity”:  “is a hypothetical moment in time when artificial intelligence will have progressed to the point of a greater-than-human intelligence, radically changing civilization, and perhaps human nature.[1] Because the capabilities of such an intelligence may be difficult for a human to comprehend, the technological singularity is often seen as an occurrence (akin to agravitational singularity) beyond which the future course of human history is unpredictable or even unfathomable.”

What most people think of when they think of situations like The Singularity, many people think of movies or fiction books (Skynet, The Matrix, 1984, etc.). Each envision a world where “the machines” are smarter than us and think on their own, without regard for the human condition, well-being. Famous entrepreneur and investor Peter Thiel, has  a particularly interesting take on all of this, much of which I agree with. To save you the time of watching the link, he says “all we [humanity] needs is The Singularity.” The reason I agree with the fundamental point of his message is that technology “usually” makes our lives easier, more efficient. More importantly, a new advancement in artificial intelligence would create new jobs where humans control the “smart machines”. Think of it as when machinery was first introduced to factories during the Industrial Revolution. The advent of machines in factories lowered the barrier to entry to the industry and encouraged new competition. For example, it took less “man-power” to produce thousands of garments in a day. Curating and maintaining a machine’s artificial intelligence will be the “factory job” of the future. This may sound odd, but that may be because artificial intelligence is commonly misunderstood.

By working at a startup that gets looped into the “artificial intelligence” realm/discussions, I’m well aware of its recent resurgence, popularity. And what’s comical/frustrating is the public’s view of what artificial intelligence is. We’ve made it a point in sales meetings to explain the different “flavors” of artificial intelligence. So let me set the record straight, artificial intelligence by and large can be: 1.) self-learning (machine-learning), 2.) mimick current human behavior, or 3.)  deep-learning. [Head over to the Narrative Science blog for more interesting pieces on this discussion.]

My larger point about point about all three types of AI is that, despite what you may think, all of these take human interaction and intervention. A computer has no sense of what is right and what is wrong, unless verified by a human. Computers can find interesting things in data (machine-learning), but only a human can verify that correlation equals causation. For example, a computer might find that the number of kiwis harvested increases fairly linearly with the number of deer killed each season in Wisconsin. This is useless, spurious correlation that we wouldn’t want computers to identify as significant.

Sure, there are ways to program and help a computer dictate with metadata what could be true/false. But don’t believe that these machines are learning all on their own, they need validation, which usually happens “off-line”, aka by humans (including Watson and every other piece of AI). That’s where jobs are created by artificial intelligence, as opposed to consuming the very jobs that people are concerned they’d be replacing.

Revolution in Batteries and Wireless Charging


If you didn’t know that the ‘battery revolution’ was upon us, then let Tesla’s announcement of its plan to build a multi-billion dollar battery factory be your wake up call.  The lithium-ion batteries that are in our always-on  phones are now moving to cars, as movement away from non-renewable resources grows.

Although this push for longer-lasting, more efficient batteries is the next logical step in the world’s dependency on energy everywhere, 24/7. But  I think the inevitable next step after “super” batteries would be no batteries at all, via wireless charging. Let me explain a little more.

There is a company that is keeping its technology close to the vest about wireless charging, a company called uBeam (there’s not much to the site). They’re aiming to build new infrastructure and networks that work much like cell towers and cell signals work today. Except they’d be emitting a certain frequency that a special sensor in your device can detect and initiates a charging-like actions. So batteries wouldn’t necessarily go away, but you’d be less tied to your power cord and a wall.

It makes sense that they may roll out an “in-house” product first, so you can wirelessly charge items in your house (and keep them charged, even with a weaker battery). At that point, a high-end battery would be rather useless if you could essentially be “plugged into the wall” 100% of the time.

How the Tech World Turns


With Facebook buying Oculus Rift (a virtual reality startup that produces virtual reality “goggles”), it’s apparent that Zuckerberg is trying to stay ahead of the tech curve. What FB will do with Oculus remains slightly unknown, but the Oculus team has up to $300 million in incentives to hit certain milestones. I’m imagining that FB will attempt to capitalize on virtual reality as the new platform and its social and advertising revenue opportunities, while still keeping users active on PCs and on mobile.

This seems outlandish and slightly far-fetched, but after working at a tech startup for over the last year, you start to understand how quickly tech evolves. From the creation to testing to market acceptance or denial of a new technology can be a relatively short time. We at Narrative Science have been working to perfect artificial intelligence for years. The advances we’ve made have been astounding, all while getting a fair amount of press. But if people can’t use your product everyday, they assume you’ve failed. Until one day your product ends up in the hands of consumers who finally understand how they leverage your technology. My point, because people haven’t been able to use the Oculus Rift or Narrative Science for that matter, it’s easy to scrutinize the technology.

The second industrial age in upon and the rate that software is progressing is astonishing, rates we’ve never seen before. At the beginning of this second machine age, FB realizes how important it is to have a hand in the latest, possibly game-changing tech. Although people can’t see it now, FB will help bring this technology to the masses, while putting a few dollars in its pocket.

Understanding Innovation……From the History Channel


This weekend I caught an episode of “The Men Who Built America” on the History Channel. The particular episode was about Andrew Carnegie, who began the “Age of Steel”, who started the Carnegie Steel Company; ultimately minimizing production time for building-grade steel from two weeks to 15 minutes.

Certainly a better process as well as a better understanding of the chemical properties of steel helped them mass produce it, and inevitably build out of America at rates never seen before. But it wasn’t smooth sailing to convince people that steel was the next material to build better, stronger, and bigger buildings, leading to the invention of the skyscraper.

His three main hurdles:

1.) Finding a better process to manufacture high-grade steel

Lesson learned: Research and development are the keys to the next innovative breakthrough. Easy problems to answer don’t make anyone money (besider the pet rock and Flappy Bird). Hard problems to solve have the biggest payoff.

2.) Convincing railroads, construction companies, and consumers that steel was the next precedent in buildings

Lesson learned: Marketing your new idea and trying to sell it sometimes makes you feel like a mad man talking to yourself in the corner of an insane asylum. It takes much longer than you think to persuade consumers, even the early adopters, of this new view/idea. Patience and persistence prevail when you’ve done adequate research and development.

3.) Going in all in when you feel the market is “turning”

Lesson learned: Once you begin getting traction in the market, don’t be afraid to be aggressive with your spend, because it will be “now or never” to make your vision a reality.

Mind-F**k Friday – “Quantum Computing”


Computers as we know them today, ones that use processors, were being developed and slowly enhanced since the early 1900’s. Slowly, companies started commercializing machines, including the IBM’s first accounting systems, which were all punch-card based. All they could do was add, subtract, and print the results. From the ’30s to the late ’50s, this was by and large how computers were used. It was a means of doing work, but it never replaced workers. These computers were the size of rooms and required multiple workers to use the machine correctly and efficiently. Nowadays, all of that (and a little bit more), is in our pocket.

Early_SSA_accounting_operations

So what’s next after what we use today (machines driven by processors and how powerful they are)? The next level is “quantum computing”. I would recommend Googling it because it’s mind-blowing and hard to explain in a few paragraphs. So I’ll keep the explanation short to give some background, but will focus on how game-changing it will be.

Today, computers think in binary, either 1’s or 0’s (think of the Matrix). What a quantum computer can do is think  in 1’s, 0’s, or 1’s AND 0’s at any length. So instead of making one decision at a time (1 or 0), it can make potentially millions at a time. Making computers a million times faster than they are today. Kind of a mind-fuck, huh? To continue, in today’s computers, processors (think Intel) create the 1’s and 0’s via electrical impulse (think motherboards, wires, etc.). Quantum computing will send impulses through particles in the air.

Now, just like the computer that we know today took a good 50 years to develop, the quantum computer will take the same amount of time to get to the consumer. But businesses are doing initial testing (particularly Google). What they’re using it for today is machine-learning. For example, Google is trying to build a self-driving car; within in this car are programs that need to be taught the rules of the road, what a red-light looks like, etc. etc. For a computer program to get the answer correct 100% of the time takes a lot of computing power to identify unique situations, environments, etc. A quantum computer could figure it out in seconds, then Google can put that more accurate algorithm/program in your self-driving car’s arsenal.

P.S. – A company producing these today are D-Wave Systems if you’re interested.