Category Archives: FWIW

Five for Friday: Machine Learning, Cybersecurity Skill Gap, Snap Maps + more

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First this week is an excellent look “under the hood” of machine learning from OReilly.  While I’ve written on this topic before, OReilly does well exploring some options around reference architecture.  Oh, and there’s this article about AI taking over transcription.  I’m unusually excited about that future.

There’s a trend out there I’ve mentioned before around “the death of staffing agencies” that hasn’t seen the traction/evolution that was predicted in 2016, however there is another trend that might actually help speed that up – the gig economy, in that as entrepreneurs/digitally innovative firms latch on to that notion, we’ll see more companies like Konsus come about.  Buying by work product created has been around for a little bit, but how Konsus does it is what’s interesting.

Speaking of digital firms and a topic from last week, Venture Beat has a good read this week on how digital organizations are facing a severe cybersecurity skill gap.

I think it’s expected that there’d be a follow on article about Amazon this week after last week’s Whole Foods announcement.  This one is a little different though, looking at the monopoly that is Amazon.  Oh, and fun fact, the Whole Foods purchase in effect paid for itself with the surge in Amazon’s stock price after it was announced.  I wonder how many people on Wall Street are longing for the days when PE ratios made sense.

Just to comment in passing, Snap launched Snap Maps this week.  Not a lot of detail that I want to dig into, just to note it and the fact that yet another company that doesn’t do mapping is getting into mapping and all the metadata that comes with … geolocation/geofencing seems to still be a thing.  There’s also this mega road trip across Europe if you’re open to some travel this summer/fall.  Oh, and Kalanicky resigned, which shouldn’t shock anyone given Holder’s report.

For your longer read this week, check out this from McKinsey about how cities can benefit from the future of mobility.

Last this week, check out this TED talk from Stanley McChrystal about how to build sense of purpose across people of many ages and skill sets.

Musk’s Plan for Mars, Computer Chips that can Reprogram Themselves, How Goldman Sachs lost $1.2B of Libya’s Money + more

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There’s quite a bit that’s reported on in a week, and when one misses a week because of a stomach bug, well, it leads to an even longer list for all of you.  I do hope to shift to more evergreen material in the future as time allows, but that said, here’s the round up for the last few weeks:

First, Elon Musk is at it again, this time with travel to Mars.  For the low-low price of $200k (later to be reduced to $100k), you can travel to the Red Planet.  Musk hopes to have the space program up and running in the next ten years “if things go super-well.”  Key to the success of this program?  Reusable rockets.  Ars technical notes that this is either a moment of audacity, madness, or brilliance, or perhaps all three for Musk.  CNET looks at the ethical questions around building a city on Mars – and they do make a reference to Space Jam in the process.

If you recently updated your phone OS, you likely had thirty-six pages of terms of service to read through, and it’s likely you didn’t bother.  Heck, I didn’t either.  There are some funny stories out there of companies and developers hiding jokes into their terms of service to highlight that no one ever reads them, but Quartz this week digs into how terms of service are actually changing ownership rights in a way that many of us don’t realize.  A good example of that is how John Deere owners can’t legally fix their own equipment, they are required to take it to a John Deere certified mechanic (at quite the price difference over a local shop).

Ever wondered how equity compensation works at a startup?  Fortune covers that here.

The Federal Reserve has failed, despite its best efforts over the past twenty year and three administrations, to stabilize inflation at the targeted 2%.  In the past four years it has stayed well below that, which those of you who studied economics at some point will realize speaks to a major issue in our economy: wage stagnation.  Don’t take my word for it, though, check out what Time said on the issue in 2015 and how New Constructs thinks the root of it is the Internet Economy.

As we’re on the topic of the internet, it seems that the police are raiding houses based on IP addresses … but the only issue is that sometimes those addresses can be spoofed or point to the wrong place.  Fusion had a piece a while back on a farm in Kansas that has the unfortunate fate of being the default address for MaxMind, an IP address tracker, for any IP address they couldn’t map.  MaxMind says its IP geolocation is inaccurate in the United States 12% of the time. That’s a bit more than a standard deviation, but there are extra steps the police can take, like seeking out additional information about who actually owns an IP address from an Internet Service Provider.

As a tag along to that, Venture Beat has a great article this week on how machine learning can help the security industry.  ML has been used successfully for implicit authentication, and if it lives up to the hype, it should be an excellent tool for addressing authentication-based hacks in the future.

Did you know that women launch more than half of all internet companies in China?  I certainly didn’t, and this article from Bloomberg explores the how.

Brexit hasn’t been as much of a headline of late, but The Guardian had a great article on the orchestrator of the movement and the long road he slogged.

Well, it seems the whole E-Waste recycling thing may be a sham (I don’t think this is really a shock to anyone), and Motherboard does a great job of digging deep into how the current system works and what the actual net value of many of those recyclable parts is.  That said, some good news to follow on: a UC Irvine Doctoral student accidentally invented a battery that lasts 400 years.  Seriously.  Four hundred years.

One of my oldest friends works for Illumina and so I’ve been hearing about their tech for a long while.  Fast Company has a good long read about the company this week – if you’ve ever looked at finding out who your ancestors were via genetic testing, they’re the ones who sell the machines that do the analysis.

Speaking of machine learning, one of the issues we face is the implicit gender bias that is created by our language and society and then can impact the results of even a simple search.  A group of researchers trained a machine learning system using Google news stories and then asked the question “Man is to Computer Programmer as Woman is to X.”  The answer the system came back with was homemaker.  This study revealed the bias that can be programmed into a newly created machine learning system based on the inputted data.  The team of researchers ended up having to (and were successful at) explicitly remove gender stereotypes from the embedding the machine learning algorithm was using.  This also speaks to why the AI that Microsoft unleashed on the world months ago went so hilariously awry.

Microsoft had a couple of interesting articles come out about it this week, including one about how Nadella thinks AI will transform Microsoft and another about computer chips that can reprogram themselves on the fly.  There’s a lot of hype around AI this year, so the latter article is more interesting to me for a few reasons: for one, it captures some of the culture that existed in Ballmer’s day at the reigns of the company and highlights the stark contrast under Nadella’s leadership.  Another is that the chips in question, FPGAs, let engineers build chips that are faster and less energy-hungry than an assembly-line, general-purpose CPUs, but customizable so they handle the new problems of ever-shifting technologies and business models.  Oh, and Microsoft also just announced yesterday that they are merging the Research, Bing, and Cortana divisions to create a 5000 person strong AI division.

Five thirty eight has a good piece this week on AI and bots, and it’s worth looking at just for the opening paragraph … you’ll see why.

Did you know that over 50 million people under the age of 21 are on the app musical.ly and the app has over 11 million uploads a day with a user base of 120 million worldwide?  The New York Times had a good piece on the app recently, but Vice has a better one out this week, explaining both the popularity of the app and its potential impacts in the 13 – 24 demographic.

Remember Google Glass?  It’s likely that they were simply ahead of their time as I think we’ll see the how we use computers change drastically over the next ten years (especially with VR), but they failed nonetheless.  Now Snapchat is getting into the eyewear business, and there are varying opinions on whether they’ll see success.   Techcrunch spoke to the hopes and headaches of Snap, Inc.’s new frames, and Stratechery had a good piece this week on the future of wearables as a while.

Speaking of Google, they who shall “do no evil” have a plan to try and take down Amazon’s Echo that will be unveiled next week called Google Home.  It’ll be interesting to see if they can catch up where Amazon is so clearly in the lead.

HBR has a good overview of the platforms that are effectively disrupting businesses today.  Many of them won’t be a surprise to any of us, but what’s interesting is that the authors posit that it’s not traditional business being disrupted by platforms, but businesses which already play on a platform (albeit antiquated in some cases).  This leads to the conclusion that even platforms that are seeing success today can be disrupted and changed even further.

There’s a trio of articles to do with bandwidth and data speeds this week worth a read: Who Cares About 5G Wireless?  You Will, Why is America’s Internet So Slow?, and Teleportation across Calgary marks ‘major step’ toward creation of ‘quantum internet’.  That’s right … teleportation.  What’s most interesting is that in order for us to realize the full potential of the Internet of Things and Virtual Reality, how devices connect online we’re going to need a completely different way for those devices to do so, and with how the world is still going more and more mobile (even with odd claims that the mobile phone is dead out this week), that change is likely going to have to be on the order of the creation of the internet at Darpa or the iPhone by Apple for us to realize that potential.

Moving on to culture and values, there’s a great piece from GeekWire about how Zillow created a culture around six core values that empower employees and then another on how Warby Parker is getting better results by reducing managers’ control over their workers.  It seems that WP is taking some advice from GitHub.  Oh, and another one about Tower Paddle Boats, where the CEO made a commitment to five hour work days for his employees, and his employees have made up for that change by a marked increase in productivity.

There was also a bit of news in the past few weeks after the Federal Government released its thoughts on autonomous cars, leading to The Atlantic to remark that we’re entering a new era for the automobile, strategy+business to comment on the auto industry’s real challenge, the New York Times to state that in backing autonomous cars, the Fed has told automakers to figure it out, and last from O’Reilly their thoughts on how AI is propelling autonomous cars and what that means for the future of transport.

Bloomberg has a phenomenal, in-depth article into how Goldman Sachs lost $1.2 Billion of Libya’s money, but it’s interesting not just for the details of the deals that went awry, but also for how the article sets the stage and presents the history leading up to the deals as well.  All in all, well worth the long read.

No Ted talk this week, instead take seven minutes and watch Musk’s presentation on how we build out a space exploration program that will take us to Mars.

 

 

Uber’s Driverless Cars go live, Apples, Apples everywhere, Revisiting Gartner’s Top Ten for 2016 + more

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As we get close to Q4 in 2016 and the release of Gartner’s Top Ten Tech Trends for 2017, I thought it’d be good to take a look back at what they predicted for 2016  to refresh our memories plus share a few articles from the world this week.  First, the news:

Uber is now letting riders experience their autonomous cars in Pittsburg.  This article highlights what the experience is like – while the writer felt safe for most of his drive, he was glad he could override the technology a couple of times as well.  It’s pretty cool to see the technology being leveraged, including LiDar on every vehicle.

The income and poverty report for 2015 came out this week, and good news: we’re as rich as we were in 1998.  Aside from the cheeky and insightful analysis from the New Yorker, there is good news in the report, although tempered.  I’ve not had a chance to finish it yet, but you can find the entire thing here if you’d like to dig in.

I, apparently, need to get a job with Wells Fargo … well, no, I don’t because I missed the window to cash in on a $124M bonus package for defrauding customers, costing the company a nearly $200m fine.

Microsoft beat Facebook in, of all places, Github with open source code submissions.  Why is that a big deal?  Well, this is the company that, under Gates and Ballmer, tried their hardest convince CIOs that open source was rife with issues.  Well, under Nadella that has changed.

There are two articles worth a look this week from HBR: to succeed in tech, women need more visibility and how cybersecurity is every executive’s job.  Definitely take the time to read the first article, as it points to an ongoing epidemic of sorts for tech companies: the highest-profile losses in tech are those at the senior level. Women at these levels “often are less satisfied with their careers, perceive that they are unlikely to advance at their current organizations, or believe they must change jobs in order to reach the next level.”

A round up of some Apple articles for the week: first, I’ve downloaded iOS 10 and between the price of the 7 for lack of innovation and some of the “features” of that new OS, it might be enough to push me off the platform, but at least I was able to get it to install.  Next, apparently the “boys” of 1 Infinite Loop are rethinking autonomous cars.  I used quotes there because then there’s this piece on leaked emails that shows how Apple is still a sexist and toxic workplace for women.  There are a few others, including how Apple will leverage ear buds to make Siri smarter, that the age of Apple is over, and what’s next for Apple now that smartphone sales continue to decline, much less stratechery’s look at beyond the iPhone.  But I feel like I buried the lead there – Cook may be much admired, but there’s critical work to be done at Apple to get rid of the “bro” culture that we thought was only an epidemic as Unicorns.

There’s a good piece this week about the state of computer science education in the United States.  While it’s important to look at how primary education is filling the pipeline of secondary education in computer science (and, thereby, industry), we also need to face the reality that we’re moving towards a degree-less future in development in part and figure out how to enable future success without straddling another generation with unnecessary debt.

Tesla and Elon Musk have been in the news of late (what with the acquisition of Solar City).  Curious about the future of the company?  Check it out here.  Hint: we’re back to autonomous cars.

For those afraid of AI, Venture Beat has an opinion piece this week about how it can actually save us from future stock market failures.

Now for Gartner:

Gartner defines a strategic technology trend as one with the potential for significant impact on the organization. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization’s long-term plans, programs and initiatives.

The top 10 strategic technology trends for 2016 are the device mesh, ambient user experience, 3D printing materials (hmmm), information of everything, advanced machine learning, autonomous agents and things, adaptive security architecture, advances system architecture, mesh app and service architecture, and IoT platforms

 The Device Mesh

The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses. The device mesh includes mobile devices, wearable, consumer and home electronic devices, automotive devices and environmental devices — such as sensors in the Internet of Things (IoT).

While devices are increasingly connected to back-end systems through various networks, they have often operated in isolation from one another. As the device mesh evolves, we expect connection models to expand and greater cooperative interaction between devices to emerge.

 Ambient User Experience

The device mesh creates the foundation for a new continuous and ambient user experience. Immersive environments delivering augmented and virtual reality hold significant potential but are only one aspect of the experience. The ambient user experience preserves continuity across boundaries of device mesh, time and space. The experience seamlessly flows across a shifting set of devices and interaction channels blending physical, virtual and electronic environment as the user moves from one place to another.

 3D Printing Materials

Advances in 3D printing have already enabled 3D printing to use a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceuticals and biological materials. These innovations are driving user demand, as the practical applications for 3D printers expand to more sectors, including aerospace, medical, automotive, energy and the military. The growing range of 3D-printable materials will drive a compound annual growth rate of 64.1 percent for enterprise 3D-printer shipments through 2019. These advances will necessitate a rethinking of assembly line and supply chain processes to exploit 3D printing.

 Information of Everything

Everything in the digital mesh produces, uses and transmits information. This information goes beyond textual, audio and video information to include sensory and contextual information. Information of everything addresses this influx with strategies and technologies to link data from all these different data sources. Information has always existed everywhere but has often been isolated, incomplete, unavailable or unintelligible. Advances in semantic tools such as graph databases as well as other emerging data classification and information analysis techniques will bring meaning to the often chaotic deluge of information.

 Advanced Machine Learning

In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend.

DNNs (an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear “intelligent.” DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.

 Autonomous Agents and Things

Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. While advances in physical smart machines such as robots get a great deal of attention, the software-based smart machines have a more near-term and broader impact. VPAs such as Google Now, Microsoft’s Cortana and Apple’s Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.

 Adaptive Security Architecture

The complexities of digital business and the algorithmic economy combined with an emerging “hacker industry” significantly increase the threat surface for an organization. Relying on perimeter defense and rule-based security is inadequate, especially as organizations exploit more cloud-based services and open APIs for customers and partners to integrate with their systems. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfill the adaptive security architecture.

 Advanced System Architecture

The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. Providing this required boost are high-powered and ultraefficient neuromorphic architectures. Fueled by field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic architectures, there are significant gains to this architecture, such as being able to run at speeds of greater than a teraflop with high-energy efficiency.

 Mesh App and Service Architecture

Monolithic, linear application designs (e.g., the three-tier architecture) are giving way to a more loosely coupled integrative approach: the apps and services architecture. Enabled by software-defined application services, this new approach enables Web-scale performance, flexibility and agility. Microservice architecture is an emerging pattern for building distributed applications that support agile delivery and scalable deployment, both on-premises and in the cloud. Containers are emerging as a critical technology for enabling agile development and microservice architectures. Bringing mobile and IoT elements into the app and service architecture creates a comprehensive model to address back-end cloud scalability and front-end device mesh experiences. Application teams must create new modern architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible and dynamic user experiences that span the digital mesh.

 Internet of Things Platforms

IoT platforms complement the mesh app and service architecture. The management, security, integration and other technologies and standards of the IoT platform are the base set of capabilities for building, managing and securing elements in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital mesh and ambient user experience and the emerging and dynamic world of IoT platforms is what makes them possible.

I was in the midst of a conversation with a colleague yesterday when we both noticed an ant on the wall next to us.  We both watched it for a few moments before I “helped” it to the ground so it could get where it was going faster.  It reminded me of this TED talk by Deborah Gordon where she explores how ant life provides a useful model for learning about many other topics, including disease, technology, and the human brain.

Transportation as a Service, Apple vs. the EU, Delta gets smart about luggage + more

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Last week there was a bit a news around Uber losing a bit of money in the first half of 2016.  This week, news came out about Google’s own efforts to undercut Uber in San Francisco in the ride-sharing game leveraging its Waze app.  That goes a ways to explain why David Drummond exited from Uber’s board, and this week Stratechery has a great article on the evolution of transportation as a service.  Mind you, Google would be wise to focus on first/last mile issues like Uber and Lyft, and at the same time might not avoid “doing evil” in that pursuit.

Speaking of cars, did you know that earlier this year for the first time the net adds of connected cars surpassed that of smartphones in the US.  This all points to how connected cars are going to become revenue machines, or so says TechCrunch, and I think they’re on to something.

If you haven’t guessed yet, I’m a bit of a geek and I like learning about obscure or trivial things.  I like it when writers connect disparate concepts in new and insightful ways.  While these aren’t obscure, this article from Business Insider that walks through the seventeen equations that changed the world was right up my alley.

If you hadn’t heard, there’s a strike today in India which has shut down most of the country.  The strikes were driven by the belief that Narendra Modi, India’s Prime Minister, is pursuing anti-labor policies.  Entire cities have been shut down, with transportation and banks hit hardest.  On top of that, add this article about how Tata and Infosys are starting to feel the Brexit heat and you start to see the potential storm that could hit India’s economy.

There was a great interview this week from recode with Quip CEO Bret Taylor, not just because it explores his belief that companies die when they are afraid to fail, but also for his statement that you have to aggressively recruit a diverse workforce from the start or you will fail at employee diversity.  Popular Science has a piece this week that speaks to hiring diversity in Silicon Valley as well.

I gave an overview a while back on artificial intelligence and the difference between narrow and general intelligence.  The reality is we just don’t know how far we are out from having AGI, which is likely the next internet or iPhone level innovation.  The New Yorker’s Om Malik explores the hope and hype of AI this week, and the thing that struck home for me most was this “computers do the best they can (that is being consistent, objective, precise), and humans do our best (creative, imprecise but adaptive).”  That’s the best description I’ve heard of the disconnect, and the reason why even when we achieve AGI the human race is so interesting – because we’re imprecise but adaptive.

Along with that is this article on how Facebook is trying to catch up with Google in open-sourcing AI code and then an inside look at how artificial intelligence and machine learning work at Apple.

The first software startup was founded in 1892.  Well, not really, but that kind of hyperbole catches the eye, doesn’t it?  Well, GE is that software startup, and while they just started their push to be competitive with Google and Microsoft a few years ago, they’re serious about it, to the tune of billions of dollars and thousands of people.

Speaking of click bait and hyperbole, ever wondered how government agencies can hack into your smartphone?  Well, here’s a story of how hackers from the NSA got caught doing exactly that.

You may have heard the news this week that the EU has levied a 13 Billion Euro tax on Apple for back taxes.  Apple’s response?  That the EU can either have their back taxes or jobs, but not both.  Robert Reich explores why it is so difficult for governments to stand up to Apple (and others), while The New Yorker walks through how Apple created Ireland’s economies, “real and fantastical.”  If you are wondering how Apple and others avoid paying taxes, Wired has you covered, while 9to5 Mac discusses how tone deaf Tim Cook’s response to the findings are.

There’s an interesting question that keeps popping up: why is consumer tech ignoring baby boomers?  While millennials are an important market share, the people with the money are their parents, and yes, millennials may end up inheriting a gob smacking amount of wealth, it seems short sighted to keep ignoring a generation with money to spend today for the generation that will spend money tomorrow.

Mark Zuckerberg is not a happy man this week.  You’ve likely heard about the latest SpaceX rocket explosion, and that that rocket had a Facebook satellite as its payload.  Apparently, Zuck is “deeply disappointed” that the satellite was lost, although likely not because of the $195M price tag.  Nope, it’s more to do with his mission to bring internet access to Africa, and his belief in Nigeria’s tech industry.

Did you hear the one about Amazon leasing its own fleet of airplanes?  What about the drones (even pizza delivery!)?  To date Amazon has been great business for UPS and FedEx, but the times they may be changing.

Here’s an interesting fact for you this week: 90% of software developers live outside of Silicon Valley.  It only makes sense when you think about it, but often we don’t.  What about this: in five years, the Midwest will have more startups than Silicon Valley.

So, oddly, airlines are finally catching up with warehouses and supply chain management in that Delta is using RFID tags to track baggage.  The eventual hope is that RFID tags will be incorporated into luggage at manufacture so that we, the consumer, can register our bags ourselves to take that burden off the airlines, but we’re a bit away from that.  It’s nice to see that at least one airline is finally catching on.

We all have biases, conscious or sub, and when we do become aware of them, then we face the challenge of overcoming them.  In this TED talk, Vernā Myers looks closely at our attitudes towards out-groups and how we can move towards the groups that make us uncomfortable.

VLC, interscatter communication, and Wi-Fi: what’s next?, Vehicle-to-Vehicle Communication, How (and why) to Set Up a VPN + more

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That may be one of the nerdiest post titles yet, but here we go …

As Google Fiber rethinks its approach to rolling out ubiquitous, high-speed internet access, it seems a good time to take a look at what technology options are out there aside from Wi-Fi given the current limitations of that technology.  Visible light and interscatter communications are both new technologies that are showing promise for a variety of reasons, although when I first read about VLC I have to admit I had a second of “but the lasers will melt my eyes.”  Perhaps I shouldn’t have watched all of Stranger Things this last week.

The Boston Globe (Go Red Sox!) had a great article this week on staying ahead of technologies curves; the article is more about who is keeping us on track when it comes to staying on the right side of technology versus the nefarious side and the Office of Technology Assessment.

Have you ever thought about how trust affects economic prosperity?  I mean, there has to be a belief in the strength of the dollar to keep us away from hyper-inflation as we moved away from the gold standard decades ago.  It makes sense that part of the reason why the developed world has been sustainable is because we trust the strength of those economies, while the failure of Brazil, Russia, India, and even China to take off to the extreme expected in that famous Goldman Sachs BRICs report might be because we, as a world, don’t trust those countries governments.  Tim Hartford explores trust in the Airbnb age and what it means with regards to prosperity.

One would expect that given Amazon’s dominance of eCommerce over the past fifteen years that the data collected from all those transactions would fuel an AI beast never before seen.  True, but their newest AI, DSSTNE, has only been in use since 2014 and holds much more promise given how successful Alexa has been and while the drones are coming, it appears they might be delivering pizza first.

Did you know that Uber lost $1.27 billion dollars globally in the first half of 2016?  And while Uber had a profitable first quarter in North America, in its quest to corner the ridesharing market, it lost $100 million domestically in the second quarter.  This is driven by steep price discounts and promotional fares for consumers that are subsidized by Uber’s investors as it tries to dominate the market (and drive Lyft out of it) while it figures out a business model.  What’s clear is that the current ride-sharing model isn’t sustainable, the question is can we get to autonomous vehicles fast enough for either company to survive.

Speaking of autonomous cars, there’s two articles this week of interest: one about how the co-opting of dedicated radio airwaves that would enable vehicle-to-vehicle communications, technology that has the potential to greatly reduce the number of accidents and deaths caused by them on an annual basis and another on how automakers are approaching a “fork in the road” when it comes to autonomous car design.   Curious about how the radio spectrum is auctioned off and how economists saved it from anarchy when it first become an open market?  Read about it here.

Curious on “what’s next” from an innovation standpoint? MIT Technology Review profiles 35 of the top innovators under 35 in this article.  It runs the gamut from robotics to sweatbands that monitor your health.  Oh, and there’s also their ranking of the 50 smartest companies for 2016.

Just as we learn more about how AI is being used at Apple, the Wall Street Journal walks us through how China is ramping up and investing in AI.

I posted a couple of articles by Alex Danco last week; here are the follow up articles on the paradigm shift machine (driver culture to car culture and in a world of energy mainframes).  Oh, and along those lines, there is no tech industry.

Ever heard of Fordlandia?  If so, you can explore other lost cities here.  If like me you hadn’t, check out the story behind it here.

I’ve posted a few articles about how individuals can use social engineering to both hack into your home system or steal your identity, but the reality is there are completely legal ways for someone to find out who you are and exploit that information that don’t involve breaking the law to that point.  There’s a series of videos on YouTube where a user does exactly that, and this interview discusses where those holes are.  One of the first things you can do is set up a virtual private network (VPN), which is a method used to add security and privacy to private and public networks, like WiFi Hotspots and the Internet.  PC World has a good step-by-step guide to help you set one up or you can use a site like hide.me.

I feel like a broken record on blockchain, but this week’s TED talk from Don Tapscott does an excellent job of breaking down the technology and clarifying how it works.  Tapscott has authored or co-authored 15 books about various aspects of the reshaping of our society and economy.  Give it a watch.

A Dive into Artificial Intelligence + more

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Today’s is a bit of a different read as after I listened to This Week In Startups and a podcast on Artificial Intelligence I got curious as to what’s developed in the past couple of years and what the future looks like.  More on that later, though, first your weekly digest of what’s interesting (at least to me):

First, if you’ve not heard of it, the President of Brazil was impeached last week by her congress.  While it may seem trivial or inconsequential to some (we think back to Bill Clinton’s impeachment in the 90s), for the world it has serious implication, some of which are explored by Marketwatch.

Speaking of leadership and issues around it, HBR has a good article this week that asks the question “why do so many incompetent men become leaders?”  It’s interesting to note that the mythical image of a leader aligns with narcissism, psychopathy, histrionics, and Machiavellianism and how many male leaders that have embodied those traits.  Strategy+business also had two interesting articles this week, one on how to design a team to deliver powerful capabilities and another on the obsolescence of traditional organizational structures.

Last week I had a few articles about how Facebook has supposedly been squelching conservative news from people’s feeds. This week, the New York Times has an interesting take on the topic, including that there was a whole bunch of hub bub over nothing, for even if the editor’s at Facebook were biased against conservative news sources, the “Trending Topics” section was so small that it was inconsequential (it’s practically invisible in the mobile UI).  The issue more lies in the algorithms that determine what users see in their feeds.

Also on Facebook, here’s a look the Book’s attempt to bring millions of Indians to the internet and how it failed.  Oh, and I’d be remiss if I didn’t include a good summary of everything Google discussed at its i/o conference.

Since last year’s market peak, Apple has lost on quarter of a billion dollars of market capitalization, and even with the recent influx from Warren Buffet’s Berkshire Hathaway, the stock is still hovering at $94 per share, versus the market high of $132.  The Conversation this week posits that Apple has gone from being a disruptor to being the disrupted, with Apple losing momentum and direction on what the next “one more thing” may be.

If there’s one trend we’ve been seeing, it’s that personalized medicine is the next big thing when it comes to mobile health.  There’s an estimated $42 billion market waiting to be opened up and a mad dash to do so.  Techcrunch this week has a good read on how that blue ocean is going to be regulated and monitored by a partnership between the FDA and the FTC.   That said, there is and has been a flurry of activity when it comes to personal health apps.  In talking to friends of mine in the startup space, they say that all those regulations from the government get in the way.  It appears like the partnership between the FDA and the FTC is intended to make that ocean more accessible.  Speaking of startups, though, here’s an interesting article from someone I know from my days in Boulder that poses the question “do startups have a drinking problem?”

In a bit of a turn of events, it appears that emerging economies are turning out to be early tech adopters.  The World Economic Forum terms this as the Fourth Industrial Revolution and MIT Technology Review has a good overview of the how and the why.  The technology most driving this change?  The mobile phone, which shouldn’t be a shock to anyone.  Also from MIT is an article on how wireless, super-fast internet access is coming to our homes.

For those of you who have paid attention to Zappos and the organizational structure there, you’ll know a little something about Holocracy.  For those that don’t, Holocracy is a system of organizational governance in which authority and decision-making are distributed throughout a holarchy of self-organizing teams rather than being vested in a management hierarchy.  Well, it seems that system may not be living up to its hype.  In fact, it may be time to put a nail in that coffin.

As a bit of a segue into the world of Artificial Intelligence, there’s an interesting article this week about how companies are trying to be more human.  In a similar vein to our introduction to Viv last week, Google, Amazon, Microsoft, and even Facebook are augmenting their personal assistant efforts. While there may be some question around privacy, AI, and Personal assistants, bots are pushing ahead in this area as well.  Brands attempt to act like people as well, engaging with and talking to consumers on social media.  We see that extended in the TV show Community where, in order to open a franchise on campus, Subway enrolls as a student in the school. The next step, according to the author, is for Google to install an always-on device that listens and analyzes everything you say, allowing Google to become even more attached to your life.  And if that turns your stomach, you’ve not seen anything yet.

Artificial Intelligence.  I’ve shared a few articles about this space over the months but was listening to a podcast earlier this week about Vicarious and I thought it would be good to explore a bit the different types of AI together and end with a question:  what happens when we finally achieve artificial general intelligence and have massive computational power behind it.

So what is AI?  Many of us think of the Hollywood-ized version of AI when we think of it: everything from Teminator to Star Wars and a whole lot in between.  The reality is that AI is already everywhere, although not in those fanciful ways.  It ranges from your phone’s calculator to self-driving cars to something in the future that might change the world dramatically. AI refers to all of these things, which is confusing.  We use it all the time in our everyday lives but we likely don’t even realize it.  John McCarthy coined the term AI in 1956, and as he did he complained that once it works, it’s how things have always worked and we don’t acknowledge it as AI anymore.  Because of this, AI often sounds like a mythical future prediction more than a reality. At the same time, it makes it sound like a pop concept from the past that never came to fruition.

To clear it up a bit, I’m going to talk about Artificial Narrow Intelligence (what we have today) and Artificial General Intelligence (what companies like Vicarious are trying to achieve), and Artificial Super Intelligence.  Along the lines of clearing things up, it is good to note that AI doesn’t mean robots.  Robots are the shell that holds the AI, the ocntainer – think the latest Avengers movie with Ultron occupying Ironman armor. AI is the brain, and the robot is its body—if it even has a body. For example, the software and data behind Siri is AI, the woman’s voice we hear is a personification of that AI, and there’s no robot involved at all.

Secondly, you’ve probably heard the term “singularity” or “technological singularity.” This term has been used in math to describe an asymptote-like situation where normal rules no longer apply. It’s been used in physics to describe a phenomenon like an infinitely small, dense black hole or the point we were all squished into right before the Big Bang. Again, situations where the usual rules don’t apply. In 1993, Vernor Vinge wrote a famous essay in which he applied the term to the moment in the future when our technology’s intelligence exceeds our own—a moment for him when life as we know it will be forever changed and normal rules will no longer apply.

So back to those catergories of AI: Narrow, General, and Super:

Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.

Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board—a machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it. Professor Linda Gottfredson describes intelligence as “a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.” AGI would be able to do all of those things as easily as you can.

Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board. ASI is the reason the topic of AI is such a spicy meatball and why the words “immortality” and “extinction” will both appear in these posts multiple times.  It also may be able provide the answer to the ultimate question of life, the universe, and everything.

Currently we are in a world of Artificial Narrow Intelligence.  Artificial Narrow Intelligence is machine intelligence that equals or exceeds human intelligence or efficiency at a specific thing. A few examples:

  • Cars are full of ANI systems, from the computer that figures out when the anti-lock brakes should kick in to the computer that tunes the parameters of the fuel injection systems. Google’s self-driving car, which is being tested now, will contain robust ANI systems that allow it to perceive and react to the world around it.
  • Your phone is a little ANI factory. When you navigate using your map app, receive tailored music recommendations from Pandora, check tomorrow’s weather, talk to Siri, or dozens of other everyday activities, you’re using ANI.
  • Your email spam filter is a classic type of ANI—it starts off loaded with intelligence about how to figure out what’s spam and what’s not, and then it learns and tailors its intelligence to you as it gets experience with your particular preferences. The Nest Thermostat does the same thing as it starts to figure out your typical routine and act accordingly.
  • You know the whole creepy thing that goes on when you search for a product on Amazon and then you see that as a “recommended for you” product on a different site, or when Facebook somehow knows who it makes sense for you to add as a friend? That’s a network of ANI systems, working together to inform each other about who you are and what you like and then using that information to decide what to show you. Same goes for Amazon’s “People who bought this also bought…” thing—that’s an ANI system whose job it is to gather info from the behavior of millions of customers and synthesize that info to cleverly upsell you so you’ll buy more things.
  • Google Translate is another classic ANI system—impressively good at one narrow task. Voice recognition is another, and there are a bunch of apps that use those two ANIs as a tag team, allowing you to speak a sentence in one language and have the phone spit out the same sentence in another.
  • When your plane lands, it’s not a human that decides which gate it should go to. Just like it’s not a human that determined the price of your ticket.
  • The world’s best Checkers, Chess, Scrabble, Backgammon, and Othello players are now all ANI systems.
  • Google search is one large ANI brain with incredibly sophisticated methods for ranking pages and figuring out what to show you in particular. Same goes for Facebook’s Newsfeed.

ANI systems as they are now aren’t especially scary. At worst, a glitchy or badly-programmed ANI can cause an isolated catastrophe like knocking out a power grid, causing a harmful nuclear power plant malfunction, or triggering a financial markets disaster (like the 2010 Flash Crash when an ANI program reacted the wrong way to an unexpected situation and caused the stock market to briefly plummet, taking $1 trillion of market value with it, only part of which was recovered when the mistake was corrected).

So what will it take to get us from ANI to AGI?  Well, that’s a tough one.  Nothing will make you appreciate human intelligence like learning about how unbelievably challenging it is to try to create a computer as smart as we are. Building skyscrapers, putting humans in space, figuring out the details of how the Big Bang went down—all far easier than understanding our own brain or how to make something as cool as it. As of now, the human brain is the most complex object in the known universe.

What’s interesting is that the hard parts of trying to build AGI (a computer as smart as humans in general, not just at one narrow specialty) are not intuitively what you’d think they are. Build a computer that can multiply two ten-digit numbers in a split second—incredibly easy. Build one that can look at a dog and answer whether it’s a dog or a cat—spectacularly difficult. Make AI that can beat any human in chess? Done. Make one that can read a paragraph from a six-year-old’s picture book and not just recognize the words but understand the meaning of them? Google is currently spending billions of dollars trying to do it. Hard things—like calculus, financial market strategy, and language translation—are mind-numbingly easy for a computer, while easy things—like vision, motion, movement, and perception—are insanely hard for it.

What you quickly realize when you think about this is that those things that seem easy to us are actually unbelievably complicated, and they only seem easy because those skills have been optimized in us (and most animals) by hundreds of millions of years of animal evolution. When you reach your hand up toward an object, the muscles, tendons, and bones in your shoulder, elbow, and wrist instantly perform a long series of physics operations, in conjunction with your eyes, to allow you to move your hand in a straight line through three dimensions. It seems effortless to you because you have perfected software in your brain for doing it. Same idea goes for why it’s not that malware is dumb for not being able to figure out the slanty word recognition test when you sign up for a new account on a site—it’s that your brain is super impressive for being able to.

One thing that definitely needs to happen for AGI to be a possibility is an increase in the power of computer hardware. If an AI system is going to be as intelligent as the brain, it’ll need to equal the brain’s raw computing capacity. The second key to creating AGI is to make it smart.  There pretty much are three ways to do this: plagiarize the human brain, leverage evolution through simulation, or to make the whole thing a computer’s problem, not ours.  For the middle one, we’d leverage a method called “genetic algorithms” which would work something like this: there would be a performance-and-evaluation process that would happen again and again (the same way biological creatures “perform” by living life and are “evaluated” by whether they manage to reproduce or not). A group of computers would try to do tasks, and the most successful ones would be bred with each other by having half of each of their programming merged together into a new computer. The less successful ones would be eliminated. Over many, many iterations, this natural selection process would produce better and better computers. The challenge would be creating an automated evaluation and breeding cycle so this evolution process could run on its own.

The downside of copying evolution is that evolution likes to take a billion years to do things and we want to do this in a few decades.

But we have a lot of advantages over evolution. First, evolution has no foresight and works randomly—it produces more unhelpful mutations than helpful ones, but we would control the process so it would only be driven by beneficial glitches and targeted tweaks. Secondly, evolution doesn’t aim for anything, including intelligence—sometimes an environment might even select against higher intelligence (since it uses a lot of energy). We, on the other hand, could specifically direct this evolutionary process toward increasing intelligence. Third, to select for intelligence, evolution has to innovate in a bunch of other ways to facilitate intelligence—like revamping the ways cells produce energy—when we can remove those extra burdens and use things like electricity. It’s no doubt we’d be much, much faster than evolution—but it’s still not clear whether we’ll be able to improve upon evolution enough to make this a viable strategy.

The thing is, all of this could happen now.  Rapid advancements in hardware and innovative experimentation with software are happening simultaneously, and AGI could creep up on us quickly and unexpectedly.

I’ll leave the question of ASI out there simply because we don’t know enough yet to even really conceptualize it – we need to get to AGI before we can truly understand what is possible with ASI.  Perhaps Roddenberry will have been right all along with his vision from the 60’s.  If you want to get up to speed on how to converse in AI, check out this resource from of all places the BBC, or check out this article from The Verge for more. Also, check out that podcast I mentioned to get some answers to what might be instore for us from AGI.

To end this week there are two TED talks on the AI: one from Nick Bostrom on what happens when our computers get smarter than we are and another from Jeremy Howard on the wonderful and terrifying implications of computers that can learn.

Meet Viv, The Flaws of Machine Vision, Facebook vs. Conservative News + more

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Google Now, Cortana, and Siri.  Those are the three “main” players that we use when it comes to a virtual assistant on our phones.  Microsoft has made a play to bring Cortana to all Windows devices, but what’s more interesting to me is what’s coming next from the creators of Siri: a platform-ambivalent, smarter version of Siri.  Viv is different than our current assistants because “she” writes her own programs to answer the queries you ask and take action on them.  Viv is, as the article notes, scary smart.

Speaking of Cortana, earlier this year Microsoft offered $55 billion to acquire Salesforce, only to be turned down.  Now, however, it appears that Microsoft is becoming Salesforce’s hottest competitor.  Oh, and Microsoft’s new work sharing app is not only entering an invitation-only phase of using GigJam, but according to Business Insider, might be crazy enough to work.

If you hadn’t heard, there’s been a bit of cost cutting at Silicon Valley startups.  Dropbox is the latest to cut a number of perks, all aimed at bringing them closer to profitability as a weaker Venture Capital funding environment and a stalled tech-IPO market have forced startups of all sizes to cut back or lose early investor confidence.  Perhaps that explains the down turn in ping pong table sales.  While you’re pondering that, take a moment to read about why Pinterest is a sleeping giant.  Or read about how this Silicon Valley billionaire wants to give us all robot bodies.

There’s a good article this week from Forbes on the five signs you are working for a truly great manager – it’s a good, quick read and a great one for us to invert and do some self-reflecting on when looking at how we are managing our people.  Remember, our people not only need to know how they are being measured, but also how their work is relevant and how they fit into the bigger picture.

All the way back in 2010 Niciola Marzari set his smart phone to the task of calculating the electronic structure of silicon in real time.  The task took 40 seconds, a task that used to take many hours on a supercomputer to carry out quantum-mechanical calculations.  Now, just six years later, artificial intelligence is being used to create the next “wonder material,” with researchers believing that machine-learning techniques can revolutionize how materials science is done.

We’ve been discussing machine vision and computer learning quite a bit of late, and with good reason.  MIT this week looks at the flaws in machine vision, in that new evidence has emerged that the neural networks used by machines to recognize objects and faces may be flawed.  Along with that is an interview with Gary Marcus on whether Big Data is taking us closer to the deeper questions in AI, another on learning about deep learning, and last one on how as Moore’s Law is running out of room, its successor is being desperately sought.

A bit of a story in the last week was Uber and Lyft’s campaign to change how ridesharing works in Austin.  Both companies worked together and spent around $8 million in support of Proposition 1, just to see it fail.  Both companies have pulled out of the city since, and it’ll be interesting to see if and when they come back.  What was the issue at hand? Finger-print based background checks on their drivers and placards on driver vehicles noting they “worked” for the companies.  Mind you, Uber pretty much has monopoly status at this point in spite of Lyft’s best efforts.

The top 2016 Cybersecurity Reports are out from a number of companies – take a moment to read more about those trends here.

Ever heard of Palantir Technologies?  I’d not be surprised if you, like me, hadn’t.  Palantir supposedly has proprietary software that allows for its customers to mine for data about consumers that results in much more lucrative results.  It has certainly been lucrative for Palantir, with some customers paying more than $1 million per month for the data.  Of all the odd sources, Buzzfeed did a deep look into who and what Palantir is, how it started, and where it is headed.

There’s been a slew of stories this week about how Facebook has been manipulating the news, so much so that the U.S. Senate wants Mark Zuckerberg to testify on the matter.  Now, I think we all need to recall that Facebook is a social media platform, the “social network.”  It has never purported to be a news organization or a news source.  That said, it’s interesting to think about how much we now rely on it for our daily news, for keeping up on what’s happening across the world.  Now, Facebook denies censoring the news, but more interesting is how we’ve shifted to using alternative media.

Plans to visit one of the Disney properties this summer?  Redef has a great, deep look at how Disney as a Service is bringing the company closer to Walt’s vision than ever.

Alphabet was briefly valued more than Apple the other day and looks to be on its way to be the most valuable company in the world.  I’d say that’s due to Alphabet’s desire to make big bets on future technology without knowing the return.  Astro Teller is the head of X (formerly Google X), Alphabet’s “moonshot factory,” and in his TED talk he explores the importance of celebrating failure and why the team’s at X feel comfortable working on “impossible” projects.

The Actuated Internet, Good Bosses Create More Wellness than Wellness Plans Do, the Global Power Shift + more

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It was an oddly light offering with regards to tech news this week, even with Facebook’s F8 conference, although one man did accidentally erase his entire company with one line of bad code.  That said, here’s a rundown on a few items from the week:

This article from Medium this week speaks of how we might in twenty years’ time look back at 2016 as the year the Internet broke free from its current constraints and “became one with the physical world.”  The author spent time with Andy Rubin, creator of Android, at his lab in Palo Alto, California and from that believes that this is the year we’ll see an AI-actuated version of the internet come to life and with people like Rubin involved, it will be an open source one.

Given how much press they are getting right now, I’d be remiss if I didn’t share some of the most recent press on Bots for the week: Life on the Human/Bot Continuum, Inside Microsoft’s build-a-bot strategy, and Facebook Messenger introducing ‘chat bot’ artificial intelligence.

Last week in HBR was a thought piece on how it’s good bosses, not wellness programs, that bring about wellness in employees.  Time and time again, we see that employees prefer a happier workplace to more money.  But what leads to employee happiness?  A humane workplace.  An organization that is built on trust and respect, as well as kindness, forgiveness, and inspiration.  The best way for us, as leaders, to improve our employee’s well-being is through what we do day-to-day, not through wellness programs.  Also from HBR was an article on how we’re making the wrong case for diversity in Silicon Valley.  Instead of just focusing on the social case, let’s look at the business case as well.

Along with that, there’s a terrific post from Kim Scott, a former Google and Apple executive, on the need for radical candor, regardless of gender, in the workplace.  As leaders, we need to get our teams to overcome their fear of conflict, starting with a foundation of trust, and not shy away from sharing what they really think of an idea.  Along with that, we have to get over a fear of offending, and we certainly need to retrain ourselves from decades of coddling some individuals due to gender and also viewing women who are direct in a negative light.

For those of you who’ve heard quite a bit of rumblings about cable being dead, Wired has a good article about Layer3 and their plan to take on Comcast to reinvent cable.  While I think we’re going to see content providers going away from the standard cable package for delivering their content (and already have), the intent behind Layer3 is to re-vitalize the cable market by making the cable experience better.

Sean Parker, co-founder of Napster, has invested $250 million dollars in his Parker Institute to develop cancer immunotherapies.  This is the largest donation to the field of immunotherapy ever, and is meant to fund something of a cancer cure moonshot.  Broadly speaking, cancer immunotherapy researchers seek to understand the mechanisms by which cancer cells evade detection. They are bringing new therapies to market, notably immune checkpoint inhibitors, which help the immune system recognize and target cancer cells as foreign. Parker is approaching cancer research with a startup mindset, funding the ideas that are too complicated or too ambitious for the status quo.

strategy+business has a long missive around the winners, losers, and strategies in the new world economic order.  It’s a longer piece, but a good one to read for an overview on where we’ll see the world economy as a whole trend over the next few decades.  They also give six key areas businesses should be focused on: developing a cyber-focused center of excellence, mastering the RMB, recognizing relations as a key competency, effectively managing in a multipolar world, cultivating talent wherever you do business, and nurturing innovation everywhere.

One of the more noticeable schisms between younger consumers of technology and everyone else is the tendency for younger people to simply opt in when it comes to sharing sensitive data with the world.  One might point to snapchat and say that this isn’t true, that younger users are concerned with privacy.  To me it seems they are more interested in limited privacy, and have little concern for what information they share overall with the world, in particular when it comes to location based or demographically based services.  This TED talk from 2014 goes into why privacy matters, both in the services we use and with regards to what others (and our government) can discover about us.

The Coming $1.5 Trillion Shift in Healthcare, How AI Is Feeding China’s Internet Dragon, Why You Should Try That Crazy Virtual Reality Headset + more

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For those of us who spend time in the world of Healthcare, with the consolidation of payers, the promulgation of wearables consumers long to have interface with systems, and ongoing government reforms (with potentially massive ones in the pipes), it is hard for anyone in the vertical to sort out a strategy for the next few months, much less the next few years.  strategy+business digs deep into this arena this week, and their work is definitely worth the read.

Things are looking rocky at at least one of the many companies that roll up under Alphabet (nee Google) as this article details the conflict between Tony Fadell, the executive in charge of (and founder who sold) Nest.  Strife has broken out between Fadell and Dropcam’s Greg Duffy and Fadell might not jus tbe a bad boss – Nest is looking like a one hit wonder with software glitches that are plaguing their hardware.  While Fadell may have designed good products at Apple, he seems to have lost sight of Steve Jobs’ drive beauty not only on the outside of a product, but within and in the software that drives it.

I’ve been bringing up the effects and change being stoked by Artificial Intelligence of late and with good reason – it’s been heavy in the news cycles and it’s important for us all to be abreast of what’s coming next both for business and as consumers.  To that point, AI is being strongly leveraged in China to drive not only fun app uses but is also making existing products smarter and driving developers in their ideation.  Deep learning is being used in a variety of apps and platforms to identify and give meaning to abstract patterns that exist in the vast quantities of data being inputted.  It’s one of the ways we can expect to see data analytics evolve over the next few years, and a lot of that evolution is being driven in China.

Our friends at Goldman Sachs this week in their “What We’re Thinking” series share a few thoughts on the state of Tech financing and Innovation – check out the video if you have a chance.

Many of us spend a good portion of our time in airports and we can expect our experiences there streamlined through wayfinding and other tools soon.

There is a great article from late February about what’s next in computing by Chris Dixon that I just stumbled upon.  Dixon does a great job of talking about the product cycle of progress in the computing industry, and lays out what’s impacting the future today: small, cheap, and ubiquitous hardware, software and the golden age of AI, and the new generation of computers being created by that combination.

If I’m going to spend this much time on Artificial Intelligence, I guess I should give Virtual Reality its due.  The Wall Street Journal has a nice look at VR and how it can be leveraged in a slew of applications, not just for gaming.  Along with that, The Medium digs into how Oculus Rift cracked the impossible design of VR.  Along with that is the current state of Augmented Reality as seen at Build this week.

As a follow up to last week, I had shared a few articles about Tay, Microsoft’s venture into an AI bot that went a bit … awry.  Business Week has a great article on what drove Microsoft to create Tay, how bots, Satya Nadella’s first unique idea since taking over as CEO, can change how we interact with technology, and what those experiences might look and feel (conversations as a platform), built in deep learning.  Nadella event went on to demo bots at this week’s Build 2016 conference with solid results.

Last is a futuristic vision of the age of holograms brought to us by TED.  It involves holographic teleportation at around the eleven minute mark, which is a practical application of all that VR/AR tech discussed above that is here today.

Rocket Ships, Transforming how retail banking works,How Does In-Flight Wi-Fi Really Work? + more

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Many of us have heard much of Elon Musk’s aspirations around commercializing space flight with his company SpaceX, little has been known about Jeff Bezos’ own passion and aspirations around rocket ships.  This week, the New York Times gave us a look into his company,  Blue Origin, and while it is just a start, it seems like exciting things are to come from Bezos and the commercial space race should amp up a few notches in the near term.

Slack has gotten a lot of press of late, with its irreverent CEO and how it is extending its reach and new users at a rapid pace – over 2.3 million daily users at this point.  Arstechnica looks at how Slack got started (modifying IRC so non-technical people wouldn’t find it to be “a pain in the ass”), the desire to change how we work so we can all be virtual, what the transition to Slack was like for the author, the myth of increased productivity, and many other topics.

ZDNet takes a look at the rise of IoT hacking and the implication for security and solutions being pursued.  It’s a good look at how cyberattackers are exploiting any weakness or vulnerability they can find in the enterprise and as we see the growth of BYOD across companies as well as the numerous devices that can and do connect to enterprise networks, those attackers are using anything and everything they can get to to access and exploit networks.  The author suggests asking three key questions when evaluating existing and new assets that have access into your company’s network: what is connected, where is it, and what is it transmitting. That start to fill in the gaps when deciding what the proper protocols are and hopefully uncovering the unknown unknowns that exist in a firm’s network.

Retail banking has gone through a few bumps in the past decade and has struggled to keep up with changes in technology and the market.  TechCrunch puts some thought into what that will take to transform how retail banking works, from going all-in on mobile, the need to cross-sell and up-sell, act as a virtual financial advisor, and focusing on letting the data drive the business.  One thing is true: unless banks start shifting and adapting to accommodate the digitalization of consumer’s lifestyles, they won’t last in the long run.  Along with that, they have another article around the broken world of mobile payments and how to fix it.

I’ve posted several times about Unicorns and how they are and aren’t flaming out, what may or may not be happening from a bubble standpoint, and Bloomberg this week has some more insight into what’s happening from a mutual fund standpoint and how different mutual funds who have invested in various Unicorns are now viewing those investments.

If you’ve not heard of it, Google’s A.I. program AlphaGo has beaten another ‘Go’ champion, and it looks like it is on the way to claim the overall victory in the humans vs. A.I. tournament.  Rolling Stone has a two-part special report on the artificial intelligence revolution that is long but worth the time to digest – Part One is here, Part Two here.  Then there’s how augmented and virtual reality are being used to change how doctors treat patients and the potential there.

Facebook is eating the world.  Or so the Columbia Journalism Review states.  I’ll just leave that there.

Many startup companies make light of how easy it is to sell to big companies, and many of those start ups are here and gone before the ink is dry on those quotes because what sales they do make don’t necessarily have longevity.  Marc Benioff, CEO of Salesforce (that little company that no one thought would last in the late 90s) thinks the opposite is true: selling to Enterprise isn’t something that should be taken lightly and is something that takes time and focused effort, not just word-of-mouth.  In this article from strategy+business, Benioff explains why.   The contrast to it is Dropbox, which isn’t going anywhere anytime soon, but it seems like an incongruent comparison, as Salesforce is strictly Enterprise based, whereas Dropbox is heavily focused in the consumer space as well (and finds a lot of its traction resulting from that).

Last, we’ve all suffered the woes of lackluster in-flight Wi-Fi from the likes of GoGo.  I’ve always been a bit curious as to how in-flight Wi-Fi really works, and this week The Points Guy posted an article answering exactly that, making it so I didn’t have to go and do any pesky research myself.