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.

Uber “exits” China, Growth and Developing Economies, Minecraft and the Future of Work + more

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This last week we learned that Uber, who invested heavily trying to win in the China market, has decided to sell that investment to its competitor in the market, Didi Chuxing.  Now, while Uber “lost” while Didi won, in the end Uber is ending up with a $1B cash infusion from Didi and an ~18% stake in Didi that is worth another $7B, what the Uber venture in China was valued.  Now, some might view this as a smart move on Uber’s part, as it allows Uber to shift its expansion efforts to other markets while maintaining a stake in China, but the Wall Street Journal notes that Uber, like many other Western tech companies before it, faced the same issues of favoritism for the local competitor and obstacles being thrown in their way by the Chinese government.  By selling to Didi, it allows Uber to remain competitive in China through this new partnership, but is also allowing Didi access to Uber’s algorithms.  That said, there are other threats out there to Uber than just unfavorable governments, from driver-owned apps to Uber itself.

Apple, by far, is one of the best marketing companies in the world today.  Yup, you heard me, not technology, but marketing.  They create their message in a way that creates an identity people want to be part of.  Yes, they make great technology to boot, but also encouraged all of us to think different in the process.  What about the world of public relations at Apple though?  Well, in this article from HBR, Cameron Craig talks about four key rules: keep it simple, value reporters’ time, be hands on, stay focused, and prioritize media influencers.  While we might not be dealing with the press on a day to day basis, these rules reinforce how we as leaders should interact with our people, perhaps worded like this: keep it simple, value our people’s time, be hands on (without micromanaging), stay focused, and prioritize people over all else.

Lithium ion batteries are something we use every day and are all well aware of their capacity issues,  Well, as odd as it is for me to be this excited about, lithium-air batteries might finally have reached a point where they are no longer theory.  What does that mean for us?  Lighter batteries that will have twice the charge capacity of the batteries of today and will last longer as well.

VB has a good follow up on chat bots this week – yes, they’re the most hyped tech add in this year, but this article gives an update on how bots are progressing as well as some of the challenges faced in the UX design.

Michael Spence may not be a name you’re familiar with, but he is a nobel laureate in Economics and wrote this week on the growth models of developing countries and how robotics and technology will again shift the way and where things are manufactured.  The slow growth were seeing in advanced countries is likely to persist, and that will tempt developing countries to pursue quick fixes, fixes that would burden those economies in the long run.  One of Spence’s points is that “entrepreneurial activity is vital to translate economic potential into reality.”  That’s my long set up for another two articles on tech in Africa, one about a day in the digital life on that continent, the other about how fintech is building the African financial market (not disrupting it).

Interesting things are going on in Dubai, where AstroLabs, a tech incubator, has set up a coworking space that allows companies to obtain free-zone company licenses, without which entering that market would be a huge hurdle.  It’s the first incubator of this sort to gain traction in that region, and it will be interesting to see how companies are able to leverage it to test out the Dubai market.

For those of us not paranoid enough, Motherboard has done a good job this week of capturing some of the things we should be scared of from a hacking standpoint thanks to the internet of things.  They posit that the IoT will soon see the first large scale disaster due to hacking.  For those of us that follow the infosec space, this isn’t a shock.  Motherboard goes on to have a collection of articles about the current state of hacking you can find here.

Microsoft’s Nokia purchase is leading to even more job cuts.  Yahoo is on a hiring frenzy despite layoffs.  Our brains are on a new drug and it’s called our phone.  A radical change to how kids learn everywhere might come from an online school.  This may be the smartest thing Facebook has ever done.

Last, Jim Fowler, the CIO at GE, has some interesting observations on how Minecraft predicts the future of collaborative work.  He posits this will happen in four ways: we will live inside our designs, we will work on platforms that attract skill and unleash creativity, through collaboration, no problem becomes too difficult to solve, and last, science and technology education will be more like games and less like school, making them both more engaging and exciting.  Also critical, though, is easy access to technology and data and the freedom to find the best way to use it.

I stumbled across a great TED talk this week by John Green titled “the nerd’s guide to learning everything online.”  To Green (who starts his talk with a story about a made up town), we all need to find out how learning works best for us.  He didn’t understand, when he was younger, why people would put nooses around their necks and then head off before it was daylight out to something that seemed to make them miserable.  As a child, if education led to that, why would he want education? Eventually he did, but it took a different kind of school for him to do so.  Check it out.

First Principles, Tackling Cybercrime, Cortana Awakens + more

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When you go about thinking through a problem, how do you typically do so?  If you’re like most people, you will tend to try to solve the problem through analogy.  By doing so, however, you end up basing “new” solutions on old ideas.  While that will work in many cases, there are times when we have to break that model of thinking in order to truly challenge how a task can be completed or a problem solved.  Hearkening back to the writings of Aristotle we’re led to the concept of first principle, searching for a basic, foundational, self-evident proposition or assumption that cannot be deduced from any other proposition or assumption.  This kind of thinking is how we can go about breaking a problem down into its base issues without letting other solutions get in the way of finding a new, novel solution.  James Clear has a good summary of this process, and captures how both Bill Thurston and Elon Musk have used it.

You may have heard the Verizon/Yahoo news and thought back to other internet and communications mergers of the past that failed and wondered as to why the “can you hear me now” network is buying an out of touch internet company.  Well, it comes down to Facebook and Google.  The question is, will Verizon be able to make some magic happen by adding another logo to its brand.

We’re heard a lot about Amazon’s drones and plans for filling our skies with scores and scores of them, but this week there was news of another sort of drone.  If you recall, both Google and Facebook have been working on how to bring the internet to people that don’t have the infrastructure in place to access it by standard means.  Well, this week Facebook’s solar-powered internet drone Aquila took off with great promise.

Part of the reason why there is such a push to bring the internet to the estimated 1.6 billion people in the world who don’t have it today is the belief that free and open access to the internet can change those people’s world for the better.  To that point, there’s a great article this week from The Guardian on whether the internet can reboot Africa and another about the top ten tech entrepreneurs on that continent.  Then there’s this article from HBR on what Africa’s banking industry needs to do to survive.

Today we’re more likely to have our money stolen not by someone in the street but by a hacker half way around the world from us – 20 times more likely, in fact.  While there are no easy solutions to this problem today, many times we simply ignore the issue, frankly because it is so complex and not top of mind until it happens to us.  Just as we need to be vigilant about our physical safety, we have to guard our online presence as well.  While it doesn’t offer discrete solutions, this article from The Conversation does start that dialogue, and awareness of trends and then there are both personal and professional steps one can take to start. Side note: the Internet of Things isn’t helping things.

Did you know that only 3% of venture backed companies have female CEOs?  Sarah Lacy recently spoke to one of them, Julia Hatrz of Eventbrite, in a wide-ranging conversation including her own journey to CEO and the confidence gap that is holding many women back.  Why do I bring this up?  Other than it the critical need to bring all voices to the table when it comes to innovation, there’s this recent article on how Facebook is still failing at hiring a diverse workforce (spoiler: Facebook then blamed those results on a lack of available talent).  Contrast that with this article on the growing number of women in technology.

It is a Facebook heavy week, but here’s an interesting look at what their plans are for Virtual Reality as a follow on to the VR post a few weeks back.

3D printing had been slow to live up to all that was promised when it debuted at SXSW a few years ago.  It was the darling, and there were so many theoretical applications that just haven’t seemed to materialize.  Well, now the head of the French fashion industry has called it “the new industrial revolution,” so perhaps change is finally coming.

If you have an hour to spare, there’s an excellent Google Talk available on the past, present, and future of Blockchains.

“If you want to guarantee your kids have a job when they grow up, teach them to code!”  How many times have we heard those words or uttered them ourselves?  Well, this week there’s a great article from Venture Beat that posits that learning to code isn’t what employers need, but instead we need people who can analyze data.  While it’s a similar set of skills, it doesn’t go as deep on the coding side and adds a focus of data analysis.

HBR has a great article this issue on how to create an exponential mindset for digital business models.  It focuses on what you need to launch, build, and grow to create the opportunity for innovation.

The last article I want to share this week is more for the title than the content.  It’s good to get an update on Microsoft’s virtual assistant, but really, who can resist a title like “Cortana Awakens?”  That can only be the title to a bad 90s tech blended horror film, however it’s still a good read to get insight into how the company that wanted to put a computer in every home in the world thinks about humanizing a digital assistant.

We often find ourselves with labels, labels that we accept as who we are, including the labels of introvert and extrovert.  In this TED talk, Brian Little explores the moment when we transcend those labels and the traits that go with them, the differences between introverts and extroverts, and the malleability of personality.

Innovation (revisited)

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Innovation is one of the ways by which we add value for our customers, however it is elusive to find at times.  When we look at the levers we can control when it comes to justifying our cost, we can improve quality, mitigate risk, reduce cost, or we can innovate.  You can’t reduce costs while improving quality and mitigating risk (typically), nor can we innovate while we’re in a cost cutting phase.  However, all three of those efforts can lead to a reduction in costs longer term.  Innovation usually has the most return for investment when successful and can lead to greater investment overall because of realized savings or increased revenue down the road.

There are many barriers to innovation that we have to overcome: Intrinsic (fear of failure, uncertainty, lack of talent), Managerial (maintaining status quo, risk aversion, rewards discourage innovation, limited resources), and Institutional (threat to career, territorialism, hard work).

Some ways to pursue innovation include out-operating for competitive advantage and executing in a totally different way.  Removing organizational barriers to innovation is key as well, but how do we do so?  From an operations standpoint, eliminate a business culture that undervalues operations, one in which operations is out of sight/out of mind.  Then you’ll be able to promote operational innovation by :

  • Benchmark outside of your organization
  • Identify, then defy constraining assumptions
  • Makes special cases into the norm
  • Rethink critical dimensions of work
  • Practice fast-cycle iteration with feedback

Critical to imbuing innovation throughout an organization is building the high performance team to go with it.  So how do we build high performance teams and take those teams from good to great?

First off, what are the characteristics of a high performance team?

  • Structured for results
  • Manage and improve group processes
    • Have a purposeful way to make the team better – stop and take a look at what’s working well and what isn’t so they can make improvements
    • Leverage start, stop, continue exercises where you discuss what needs to stop, what needs to start, what should be continued
  • Intentional about developing  a high performance team culture (culture describes the practices, traditions and values of the team – the environment in which we work)
  • Have results-oriented meetings
    • Have a purpose behind the meeting, an intent
    • Every once in a while need to do something with the team to have some fun
  • Achieve a high level of performance
    • Have goals and achieve goals
  • They have alignment between formal and informal group norms

Who are the people we look for on our teams?  People who are hungry, humble and smart.  Ok, but what does that mean?  People who are hungry are committed to results and willing to do whatever it takes to help realize success.  This isn’t about working eighty hour weeks and never having vacations, but more so about how when everyone needs to lean in, no one hesitates.  Humble people aren’t driven by ego.  It’s what behavioral questions like what’s your biggest career failure to date” or “Tell me about someone who is better than you in an area that really matters to you” are about.  Humble people share credit, emphasize team over self and define success collectively rather than individually.  Smart speaks to people smart, not book smart.  We have to have common sense about people. Smart people tend to know what is happening in a group situation and how to deal with others in the most effective way. They have good judgment and intuition around the subtleties of group dynamics and the impact of their words and actions. A lot of discord is created in organizations when

Once we have the right people in the right roles (or have coached our existing team to a state of hungry, humble, and smart), we’ve taken the first step in building a high performance team.  Here are some others:

  • Focus on different aspects which are observable and addressable
    • Structure, Processes, Culture, Meetings, and Results
    • Within that structure, dissect different areas where there are gaps and address
    • In order to have proper structure, have to be willing to work as team and not as group of individuals towards a common end.  Not feasible to have sustainable structure without clearly defined rallying cry
    • From a process standpoint, teams will frequently shut out those people that aren’t in favor or held in high regard.
    • Frequently radio station WIIFM gets in the way of a strong commitment to success of the team – we have to engage our teams at an individual level so that they:
    • Are aware of the need for change (and their own why)
    • Desire to participate and support the project
    • Have the knowledge of HOW to accomplish the unified vision (and how they fit in)
    • Have the ability to impact the project on a daily basis (through empowerment)
    • We reinforce the need for the broader change/project/program/rallying cry of our customers
  • Team norms need to be developed in the open, not in a vacuum
    • Once established, norms need to be maintained and nurtured; one has to establish a culture of “calling out” when people violate norms but needs to be in a compassionate way (i.e. when they aren’t being hungry, humble, or smart)

Clearly this is simply scratching the surface on innovation, and next week I’ll get back to more of a digest form.  In the interim, check out these articles from HBR on innovation and this talk from Jack Levis about the hardest step in innovation being looking like a fool in front of a crowd.

Brexit …

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I don’t think there’s a lot to add when it comes to the news this morning that Great Britain voted (by a 4% margin) to exit the EU.  Markets are being hit (although not as hard as might be expected), banks are roiling, xenophobia in the US has picked up a new pace, and David Cameron has resigned.  There are some balanced views on this out there, some of which include UK’s ‘Brexit’ results rattle the world, Britain Votes to Leave E.U.; Cameron Plans to Step Down, World wakes up to ‘Brexit’: 5 things to know,  The Brexit contagion: How France, Italy and the Netherlands now want their referendum too , Sterling Crash Just the Start of Brexit Market Fallout, Why Britain Left, and you can watch the live Sky News feed through the day to learn more.  I will note that US markets seem to be doing relatively well all things considered, rebounding quite a bit after a drop at the opening bell.

Living in small town America now and many cities in the past, I, like you, have observed the steady and sure decline of the shopping mall.  There are numerous drivers for that, from online shopping to population migration to consumer tastes.  Bandier is trying to change that with an approach that focuses on selling their product last and creating an experience first.

If you’ve not heard about the latest IPO this week, it boons well for the Startup world in Silicon Valley.  After a lackluster IPO for SecureWorks, the cybersecurity arm of Dell, Twilio’s IPO was a breath of fresh air with a 96% rise in value at the IPO.

Maybe you were scratching your head with some of the Facebook acquisitions over the past few years, from Snapchat to WhatsApp.  If you took the time to walk through Mary Meeker’s talk/slides that I shared a few weeks ago, you might have noticed a big disconnect in the growth in mobile computing and the spend on mobile advertising.  As we rely more on mobile, that gap will close and Facebook has positioned itself well to reap the rewards from it with its focus on Mobile.

I know there’s been a whole lot of press on chatbots, VR, AR, and machine learning this year, and I don’t want to keep adding to that pile, but I think the Wall Street Journal did a good job this week of exploring what current thinkers in the AI space think is next for machine learning.

If you’ve not read Eli Goldratt’s The Goal, you may be unfamiliar with his Theory of Constraints and how it applies to change management.  This week, strategy+business revisits our need to find the “Herbie” in our processes and focus on that – the part of the process that created the logjam similarly to how Herbie, a member of Goldratt’s scout troop, impacted the entire troop because of his pace.  It wasn’t until he led the group that the most efficient pace could be found.  From a change management standpoint, that means that companies can only operationalize real improvement at a certain pace.   strategy+business outlines five steps to accomplish this: identify the current constraints on your progress, set a pace that supports your “constraint resource,” sequence priorities over time, elevate the pace, and pay attention as your constraints shift.

Paired with that is an article this week from Harvard Business Review on how to navigate a digital transformation.  To not get left behind in the evolving consumer landscape, companies need to pivot to a digital strategy.  With that, they need to reallocate their asset portfolio to support new, digitally enabled business models. Speaking of pivot, HBR recommends a process they call PIVOT for those looking to make this transformation: pinpoint your starting place, make a complete inventory of all your organization’s assets, visualize a new future as a digital network where your firm partners and co-creates with one of your external networks, begin to operate a pilot of your network business by shifting small amounts of capital (including time, talent, and money) to the new initiative, and begin to track the progress of your network initiative.

I’ve had a number of friends tell me that I should watch Mr. Robot.  Well, given that I gave up cable more than eight years ago and don’t think much of Hulu, I was out of luck until Amazon started streaming season one through Prime.  Amazon’s GUI may be awful, but this content was worth getting into.  I’m only a few episodes in, but so far the hacks being used in the series are scarily accurate, and they are for a reason.  Part of that is because of Michael Bazzell, the technical advisor of the show.  After growing up building his own computers and having a deep interest in hacking.  He worked for a Midwestern police department and then the FBI before heading to Hollywood.  Now Tech Insider is claiming that Mr. Robot is the only show that has gotten hacking right, and you can get a quick overview of the top hacks used in Season One of the show from engadget, the backstory on Bazzell from Vulture, and some of the flaws with the show from Wired.

I start there this week as I continue to highlight some of the issues facing us today as hacking proliferates revealing more and more sensitive data.  A few weeks ago I spoke of Palantir, a data analysis company that has a reputation that drives legend in Silicon Valley.  Well, last year Palantir hired a set of hackers to try and take control of their network and information, which they were easily able to do.  The results of the hacking exercise — known as a “red team” test — show how a company widely thought to have superlative ability to safeguard data has struggled with its own data security.  Then there’s this in depth look by MIT Technology Review on an $80 million hack and the dangers of programmable money, another on the U.S. Cyber Command Chief on what threats to fear the most, and then interviews with Tessa88 and Guccifer 2.0, the former who was responsible for hacks that led to major password captures from MySpace and LinkedIn (note: change your passwords if haven’t already) and the latter for the dump of information from the DNC.  I need to do a deeper dive into this topic versus just throwing articles out there at you as I did with Artificial Intelligence, and I plan to in the next few weeks.  Stay tuned …

The logical place to leave off this week is this talk by Rodrigo Bijou on how governments don’t understand cyberwars – we need hackers.

The Curse of Culture, Trends Shaping the Future of Mobile Connectivity, Innovation for Hire + more

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As I sit here in the pre-dawn hour writing this week, it brought back to mind a conversation I had with a colleague where they made the comment that they were “burning the candle at both ends.”  It’s an idiom we often use, similar to “burning the midnight oil,” denoting living at a hectic pace.  But this idiom is interesting in that, while today we almost take a sense of pride at it, reality is that its origins implied a reckless waste.  So as we head into a holiday weekend here in the U.S. and embark on summer for the northern hemisphere, take a moment to reflect on the pace you’ve found yourself drawn into the past few months.

Ben Thompson has an excellent read this week about the curse of culture, drawing parallels between Apple and Microsoft and in particular Jobs and Ballmer, but more so because he delves into the multiple levels of culture, from surface artifacts all the way to assumptions that blind us and hobble our organizations.  Check it out over at Stratechery.  While we’re on the subject of culture, let’s skip over to strategic leadership, and take a moment to read strategy+business’s thoughts on the ten principles of strategic leadership.

While I’m on the subject of Microsoft, our friends over there laid off another 1850 people this week, all tied to Windows Phone.  That seems to indicate further retreat when it comes to the smartphone world; however there is a glimmer of hope in the news around a possible Surface Phone.  All in all, the failed Nokia acquisition that Ballmer pushed through cost the company over $16 billion.  At the same time, Walt Mossberg is posing the question of whether Apple can win the next tech war with a shift to AI.

Deloitte has an in depth report about the five trends shaping mobile connectivity.  You can access the report here, and it is definitely worth the read as a whole, but Deloitte has provided a handy infographic for us as well.  The five key trends shaping the future of mobile connectivity include (per Deloitte): mobility comes in all shapes and sizes, consumers can’t get enough mobile screen time, text and instant message are consumer favorites, mPayment usage is picking up speed, and network versus Wi-Fi is a regional preference.  Deloitte also just trashed a whole lot of hype around the “$180 billion” fintech market.

Just a quick thing to note: researchers now say that medical errors are now the third leading cause of death in America.

We’ve heard a lot of doomsayers talk about how tech is going to destroy any number of jobs, with much denial from various government entities and others.  Let’s face it, technology and advances in artificial intelligence will kill some jobs.  That’s a given.  But that doesn’t mean we should slow down tech advances to save jobs that are ending their life cycle naturally. One of those jobs?  Over-the-road hauling – which brings up the subject of the amorality of self-driving cars.

Dealing with a pessimist on your team or elsewhere?  Inc. has a few suggestions this week on how to interact with a pessimist, including such advice as not making too much eye contact.  It sounds funny, but it’s a good article that wraps some very practical methods around dealing with people who are low on the EQ spectrum or generally unpleasant.  Inc. also delves into seven habits you need to be an effective leader, and there will be no surprises there.   A companion piece to the pessimism one is this one from The Atlantic on why so many smart people are unhappy.  All I can say is that I must be an idiot.

There are a whole lot of incubators out there, from 500Startups to Stanford’s primarily alum-focused StartX and many more, so yet another wouldn’t seem like much news, except when this one is coming from Google.  The work 500Startups has accomplished is pretty amazing, and incubators are now even focused on specific verticals like solar.  Many incubators these days require their participants to have revenue and funding in place before they can join and are much less willing to take a shot over to the moon, all driven by competition.  It’ll be interesting to see how Google plays in this space with Area 120. At the same time, there is the looming question of why are so many startups failing.  At the same time, Snapchat just raised another $1.81 billion of funding.

Virgin, or all places, has a great article this week on innovation for hire, or how corporate giants are now injecting themselves with innovation.  It speaks of the need for companies to foster intrapreneurship through an incubator model, and we’ve seen some amazing things come out of such programs at places like Microsoft’s Research arm or Google and others.  To quote, “The notion that innovative working must become a staple of any 21st century organization is no longer in question. The question is whether or not more companies will embrace the change sooner rather than later.”

With Virtual Reality no longer being a part of a distant future, it’s time to start looking at how we can apply it beyond gaming and entertainment.  Michael Bodekaer explores what is possible for science education through virtual reality in this new TED talk.

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.

Ping Pong as a Tech Bubble Predictor, How Companies Are Using Machine Learning to Get Faster and More Efficient, When Innovating Stops Making Sense + more

This week, the Wall Street Journal had this piece about the sale of ping pong tables as a predictor of the woes of the tech industry as a whole and companies specifically.  Now whether ping pong sales are truly a leading indicator as to an industry bubble popping, or whether companies run out of space and don’t need more tables you’ll need to read the article to see for yourself, however there is an interesting correlation between the number of tables sold to the number of venture capital deals funded in any given quarter.  Along with that is this article about how disruptive tech is forcing investors to rethink their strategies.  There’s also an interesting opportunity out there for second-hand ping pong tables from struggling companies – perhaps someone will create an e-commerce startup for precisely that.

Autonomous cars are all in the news these days, but there’s an interesting point that hasn’t been addressed: most drivers don’t even want self-driving cars.  Bloomberg this week has an article about the billions that are being invested in a robot that no one even wants.  That’s not to say that there waon’t be a use for autonomous vehicles from a logistics standpoint, but with less than a quarter of boomers stating that they have any interest in a self-driving car and so many millennials opting out of car ownership as a whole, it does spark the question of why.  Then again, true innovation never answers the question around a need that is known, true innovation finds the unknown and provides a solution before we’re even aware of the need, like the internet or touch screen phones.

In part on the point of autonomous logistics, Medium has an interesting piece this week about the internet economy, how to view that economic loop, and about the era of bundling and how tech giants fit in and navigate those bundles.

I have some friends who ended up over at Uber through acquisition and I’ve yet to ask them about this one, but Tech Crunch has an article this week of how early employees over there feel handcuffed to the company.  It’s hard to cry about the why, but it still brings up some interesting points when a company won’t allow employees to trade or sell their pre-IPO shares, thus locking them in with not golden but rhodium handcuffs.

Digital processes can be overwhelmingly complex and create bottlenecks for companies that are difficult to overcome.  Harvard Business Review recently completed a study that shows how companies are using machine-reengineering to establish new forms of human-machine collaboration.  Some of the areas where this is having an impact include scanning images, voice, and text to sort through a huge volume of unstructured and varying format data and unburying buried insights for market monitoring, predictive modeling, root cause analysis, and predictive maintenance to start.   HBR also had a good piece this week about how the internet of things needs not just technology but design as well.

If you liked the machine-reengineering study, be sure to check out this from re/code on teaching machines to avoid our mistakes.

I had a laugh-out-loud moment this week reading about innovation in the South this week (my adopted home) when the author related the story of the first time he met Moses Ma.  Read the article yourself and see if you can hold back your own laughter, but read the article also for this: there’s an untapped spirit of innovation in the South that is slowly being released and while it may be a slow boil, there’s a litany of innovative geniuses that hail from the South to keep an eye on.

60 Minutes had an in depth look at Fintech and how it is shaking up the financial industry.  It points out that many of the innovations in financial services over the past ten years have not come from banks and includes Vikram Pandit, the former CEO of Citigroup and how while we’re in early days, it’s possible to see a future when banking is disrupted on par with how the travel industry has been and others.

Theranos has been in the headlines for a few years, at first for beyond-normal swooning for one of the many up and coming and since last fall many negative stories following this article in the Journal.  Vanity Fair followed up on that trying to find the secret culprit in the Theranos mess and it’s not what or who you may think.

Speaking of secrets, I had recommended to me this week to watch The Secret Rules of Modern Living: Algorithms.  I’m sure my almost nine and five-year-olds will be thrilled this week when we sit down for movie night to watch that.  Hint: if you don’t want to stream it on YouTube, it is also on Netflix.

Rovi bought Tivo for $1.1 billion this last week, which may surprise many, not from an acquisition standpoint, but from a valuation standpoint.  When it first premiered, Tivo provided a solution to something that was the bane to so many – a horrible set top unit with a cloodgy UI and no ability to easily record content that was the cable set top box.  The problem is, while Tivo may have been on the leading edge of innovation a decade ago, competitors were able to easily and quickly duplicate their model.  Tech Crunch dives into what happened to Tivo and how the innovation the company drove for in essence drove Tivo to a state of irrelevance.

We all face challenges in our lives, those that seem like a hiccup and then those that devastate us. Andrew Solomon talks about how those worst moments make us into the people we are in his TED Talk and the need to forge meaning from our biggest struggles.

How Big Data Creates False Confidence, A New Map for Business in Africa, How Giving Up Refined Sugar Changed My Brain + more

How big data creates false confidence.  That’s a doozy of a headline, especially with all the press about how magical and glorious and wonderful big data is.  Sure, we may have a hard time parsing any usable information out of that data sometimes because there is just so much of it, but still, the truth is out there buried in the data, no?  Nautilus has a great blog entry this week about the assumptions we make about big data, a term that can’t even really be defined.  We just know that the data sets are huge and they have patterns buried into them if we can just find them.  So if we do find them, they must be valuable, and right.  That can create a false sense of security, so always remember what Samuel Clemens said: “there’s lies, damn lies, and then there’s statistics.”  The same holds true for big data.

How do leaders create and use networks?  Back in 2007 Harvard Business Review answered that question and it’s a good one for a refresher.  The good meat in this article is around how to be successful at strategic networking, an area that consumes so much energy and the risk around getting bogged down in operational networking.

strategy+business gives a great overview of the current business climate in Africa, highlighting the need for companies to understand the local context in order to be successful.  Africa is home of seven of the world’s megacities and the World Bank expects consumer spending to be US $2.2 trillion by 2030, but the continent is made up of 54 separate sovereign states that cover a vast range of cultures, languages, and people.  Along with that is this article from Quartz about how megacities are the world’s dominant, enduring structures.

As well, strategy+business put together a compendium of twenty questions for business leaders and some hints at answer to those questions, ranging from “how do we win” to “what is honorable.”  My favorite?  “What the hell is leadership.”

Fortune has an article this week about the 21st century corporations and our new business model.  To quote “Imagine an economy without friction—a new world in which labor, information, and money move easily, cheaply, and almost instantly.”  Along with that is the concept that you might be aware of – that the assets of most corporations in today’s day and age are the employees themselves.  The 21st-century corporation will be based more and more on the work of knowledge workers and ideas-based business across all sectors.  That has and will continue to lead to barriers to entry coming down.

One of the top ten leadership stories Fast Company published last year was about how Michael Grothaus gave up refined sugar and how it affected his brain.  I’ve done this a number of times before but haven’t been able to maintain it yet, but I’ve noticed the same issues he highlighted in his article: when refined sugar is in my diet, I’m crankier, I’ll make rash decisions, and I just feel stupider when I do, or at least not as clear headed as when I’m not ingesting it.  The detox isn’t much fun, but it’s a good read and something to consider, especially once you experience the veil of refined sugar lifting.

How good are we at employee recognition?  No, really, how good are we?  Have you paid attention to your own employee recognition program?  Is it a passive part of culture or is it something you are actively engaged in?  Well, for your consideration are a couple of articles: first, one about the top ten reasons why companies fail at employee recognition and then another on why managers fail in this area.  While you are looking at that, take a moment to look at the 2012-2013 Towers Watson paper on balancing employer and employee priorities.

We all believe we know how a successful business must be run, what rules it must adhere to.  Even as we look at all the startups out there, all the corporate giants, even mom and pop shops, we all end up falling into the same rules, the same structure either from day one or when we hit certain milestones.  Semco Partners didn’t. When he founded it, Ricardo Semler asked the simple question of what happens when you take away all of what expect (“the rules”) and just let people work.  Watch his TED talk to learn what did.