In honor of Orphan Black’s return next week I analyzed all 20 episodes. The result? After two seasons, there are 832 minutes of Orphan Black and 828 minutes of Tatiana Maslany.
The world’s girls are healthier than ever. They live longer and more of them are going to school than at any time in history.
But most of them face discrimination simply because they are girls. The discrimination happens at every point in their lives.
In some cases, it starts even before they’re born, when parents decide to abort a pregnancy if the fetus is female.
A good way to get a sense of the progress — and the remaining gaps — in worldwide gender equality is by looking at the data. Numbers can tell a compelling story. The story we’re going to tell focuses on girls ages 10 to 19, an age range used by the World Bank and other groups to track populations. Worldwide, about 600 million girls fall into this age range. Nearly half of them live in just seven countries. Those countries are the focus of our story.
You might expect that there would be an even number of boys and girls in this age group in these seven countries.
Make a list of 5 really critical pieces of information.
This can be information that’s critical to your team (or to your community).
What are the 5 most important things you know how to do that are game-changers?
It might be how you convert leads to clients, research and develop successful products, recruit highly talented staff members etc…
Now put someone in charge of keeping each of these 5 items updated. This means the knowledge is owned. This person is responsible for keeping the information at the best possible level.
They seek out feedback from people who use the knowledge and update accordingly. They seek out new ways to improve the knowledge. They ensure it’s properly tagged and easy to find. They make sure all newcomers acquire this knowledge.
This is what turns the information you already have into a powerful asset for everybody.
It’s crazy how rarely we do this. Most organisations have countless staff writing up important documents, publishing them, and watching them decay with each passing day. What a waste!
My colleague Todd is probably one of the foremost experts in community platforms today. He knows the capabilities and differences between each platform. He knows the costs of each platform. He knows exactly who to contact at each vendor for the best deal. He knows who can implement platforms and how to select a platform by any client’s need.
That’s a powerful piece of knowledge. The trick is to keep it updated as platforms rise and fall. As costs change. As staff move between different platforms. As new updates are released and we get more customer feedback on different vendors.
This works just as well in an online community as it does in an organisation. Determine the five critical pieces of information people need to know. Put someone in charge of keeping each updated and actually learnt by everyone else in the organisation.
Interestingly, the term 'surprisingly well' in the headline still means 'far from perfect'. The Yahoo tool uses keywords and word phrases to catch abusive emails, but finds it difficult to go deeper. “ The language of abuse is amorphous— changing frequently and often used in ways that do not connote abuse, such as when racially or sexually charged terms are appropriated by the groups they once denigrated. Given 10 tweets, a group of humans will rarely all agree on which ones should be classed as abusive, so you can imagine how difficult it would be for a computer.”
Not too long ago, when you were a BlackBerry fan, then Android was the enemy. A big pile of code, quickly hobbled together, with loads of security issues. Never in your life would you deploy this PoS in your enterprise.
Then BlackBerry launched an Android Phone.
I understand why BlackBerry needs a popular platform. But how do they make Android secure? The only thing I got to was "security is in our pedigree" b/s. I had to cut deeper. I tried to go through PR but they could not get anybody to meet with me. I asked a few people I know within the company, but they would not know enough.
All of this changed last week. I met with BlackBerry CISO David Kleidermacher, then with his direct report Alex Manea, who finally got me in touch with the Principal Architect. No, I will not reveal his name. But he was able to make me understand.
I worked this understanding into an article that will most likely be published next week in c't 17. Please bear with me while I wait until you bought this magazine. I promise I will explain things later.
The bottom line is: can you make Android as secure as BlackBerry 10? And the anwer is: yes, you can. You leave the user bits and pieces alone. The user only sees a familiar Android phone. But you change the fundamentals in a big way.
It's like vaccination. You expect to get sick and you deal with it before it happens. A vulnerability does not mean that you have an exploit. And when you were able to build this exploit, it might infect all Android devices, but not the one that has additional defenses.
There are Anti-Vaxxers out there. "If I cannot root this phone, I don't want it". Well, good luck, dummy. If you can root your phone, so can others. People who are way smarter than you will ever be. I am only waiting for this big malware that is going to wipe out most of Android. Not all of it though. Not all of it.
It’s been a decades-old commitment to add density along the major arterials of the city. (Residents of low-density and single-family neighbourhoods tend to support the initiative because it keeps higher density along the edges and provides a buffer from the busier routes – though most people would prefer to live on the quieter inside streets. See the West End and Kerrisdale on either side of 41st.)
Still, as examples emerge, the results are looking good. For example, along 41st across from Oakridge:
The S7 and S7 Edge were an act of refinement for Samsung, solving many of the S6’s most significant issues.
According to Samsung’s second quarter 2016 earnings, the S7 has been a resounding success for the South Korean company, with revenue up 50.94 trillion won ($45.2 billion), an increase of five percent over a year ago, and operating profit up 8.14 trillion won ($7.22 billion), an increase of 18 percent.
All in, Samsung mobile division accounted for over half of the company’s revenue and profit, with strong sales stemming form the well-received S7 and S7 edge pushing the company’s profits forward. Somewhat surprisingly, the larger and more expensive Edge made up more than half of the Galaxy S7’s total sales.
Samsung also mentioned in its earnings report that it expects its strong S7 sales to continue into the third quarter of 2016 with the launch of “a new large-screen flagship smartphone.” The Note 7 is expected to be announced on Tuesday and MobileSyrup will be on the ground covering the smartphone’s reveal.
Stickers are all the rage among tech companies in Silicon Valley — and even some Canadian firms.
Late last month, Twitter, lagging behind fast growing rivals like Facebook Messenger and Snapchat, added stickers to its first-party app. Today, the company announced that it has completed rolling out the feature to all of its 313 million monthly active users.
Users can add stickers to photos they’ve taken via the official app’s photo editing section. Once there, they can place multiple stickers on top of a photo, as well as resize and rotate them as they see fit. In a twist upon a the hashtag, users can find one another’s modified photos by searching for specific stickers.
While Twitter hasn’t announced specific plans to monetize the feature, it’s very likely the company will start selling sticker packs in the near future. Not only has the company’s revenue stopped growing, other apps, like Japanese messaging app Line and even BlackBerry with its BBM app, have managed to make a not insignificant amount of money selling stickers to frequent users.
In May, Microsoft announced it would shed 1,850 jobs from its phone division and also take a restructuring charge of approximately $950 million USD. Now, according to a report in Reuters, Microsoft has found a new round of cuts to make.
Microsoft noted in its annual report that the company would reduce its employee count by a stunning 2,850 over the next twelve months, which brings the total number of job losses in the phone department to 4,700. Microsoft has 114,000 employees worldwide and this represents approximately 4 percent of its workforce.
There are no details if Canadian jobs are impacted but most are layoffs are said to be located in Finland, which is where Nokia is situated. Microsoft purchased Nokia in 2014 for $7.2 billion.
Microsoft recently announced its Q4 results and reported revenues of $22.6 billion and a net income of $5.48 billion. Unfortunately, Microsoft’s smartphone division dramatically dipped as its revenue decreased by a staggering 70 percent over the last year.
Microsoft is still committed to smartphones, the company has shifted its focus to become mobile first by releasing its apps on iOS and Android, while also investing in cloud and software services. In addition, Microsoft recently purchased LinkedIn for $26.2 billion in cash.
Leak before failure is a fascinating engineering principle, used in the design of things like nuclear power plants. The idea, loosely stated, is that things should fail in easily recoverable non-critical ways (such as leaks) before they fail in catastrophic ways (such as explosions or meltdowns). This means that various components and subsystems are designed with varying margins of safety, so that they fail at different times, under different conditions, in ways that help you prevent bigger disasters using smaller ones.
So for example, if pressure in a pipe gets too high, a valve should fail, and alert you to the fact that something is making pressure rise above the normal range, allowing you to figure it out and fix it before it gets so high that a boiler explosion scenario is triggered. Unlike canary-in-the-coalmine systems or fault monitoring/recovery systems, leak-before-failure systems have failure robustnesses designed organically into operating components, rather than being bolted on in the form of failure management systems.
Leak-before-failure is more than just a clever idea restricted to safety issues. Understood in suitably general terms, it provides an illuminating perspective on how companiesscale.
Learning as Inefficiency
If you stop to think about it for a moment, leak-before-failure is a type of intrinsic inefficiency where monitoring and fault-detection systems are extrinsic overheads. A leak-before-failure design implies that some parts of the system are over-designed relative to others, with respect to the nominal operating envelope of the system. In a chain with a clear weakest link, the other links can be thought of as having been over-designed to varying degrees.
In the simplest case, leak-before-failure is like deliberately designing a chain with a calibrated amount of non-uniformity in the links, to control where the weakest link lies,. You can imagine, for instance, a chain with one link being structurally weaker than the rest, so it is the first to break under tensile stress (possibly in a way that decouples the two ends of the chain in a safe way as illustrated below).
You can imagine, in the same chain, another link that’s structurally strong, but made of a steel alloy that rusts the fastest, so if there’s a high humidity period, it breaks first. In the two cases, you can investigate the unusual load pattern, or possible failure in the HVAC (heating, ventilation and air conditioning) system.
Failure landscapes designed on the basis of leak-before-failure principles can sometimes do more than detect certain exceptional conditions. They might even prevent higher-risk scenarios by increasing the probability of lower-risk scenarios. One example is what is known as sacrificial protection: using a metal that oxidizes more easily to protect one that oxidizes less easily (magnesium is often used to protect steel pipes if I am remembering my undergrad metallurgy class right).
The opposite of leak-before-failure is another idea in engineering called design optimization, which is based on the exact opposite principle that all parts of a system should fail simultaneously. This is the equivalent of designing a chain with such extraordinarily high uniformity that at a certain stress level, all the links break at once (or what is roughly an equivalent thing, the probability distribution of link failure becomes a uniform distribution, with equal expectation that any link could be the first to break, based on invisible and unmodeled non-uniformities).
Slack and Learning
The inefficiency in a leak-before-failure design can be understood as controlled slack introduced for the purposes of learning and growing through non-catastrophic failure. A way to turn the sharp boundary of the operating regime of an optimized design into a fuzzy, graceful degradation boundary. So leak-before-failure is essentially a formalization and elaboration of the intuition that holding some slack in reserve is necessary for open-ended adaptation and learning. But this slack isn’t in the form of reserves of cash, ready for exogeneous “injection” into the right loci. Instead, it is in the form of variation in the levels of over-design in different parts of the system. It is a working reserve, not a waiting reserve.
For those of you who are fans of critical path/theory of constraints methods, you can think of an optimized design as one where the bottleneck is everywhere at once, and every path is a critical path. It is a degenerate state. In the idealized extreme case, the operating regime of the system is a single optimal operating point, with any deviation at all leading to a catastrophic failure of the whole thing.
Mathematically, you get this kind of degeneracy by getting rid of dimensions of design or configuration space you think you don’t need. This leads to a state of synchronization in time, and homogeneity in structure and behavior, where you can describe the system with fewer variables. A chain with a uniform type of link needs only one link design description. A chain with non-uniform types of link needs as many varieties as you decide you need. At the extreme end, you get a bunch of unique-snowflake link designs, each of which can fail in somewhat different ways, with each kind of failure teaching you something different.A prototype design thrown together via a process of bricolage in a junkyard is naturally that kind of design, primed for a whole lot of learning.
Leak-before-failure can be understood, in critical-path terms, as moving the bottleneck and critical path to a locus that allows a system to be primed for a particular type of high-value learning. Instead of putting it where you maximize output, utilization, productivity, or any of the other classic “lean” measures of performance.
Or to put it another way, leak-before-failure is about figuring out where to put the fat. Or to put it yet another way, it’s about figuring out how to allocate the antifragility budget. Or to put it a third way, it’s about designing systems with unique snowflake building blocks. Or to put it a fourth way, it is to swap the sacred and profane values of industrial mass manufacturing. Or to put it a fifth way, it’s about designing for a bigger envelope of known and unknown contingencies around the nominal operating regime.
Or to put it in a sixth way, and my favorite way, it’s about designing for economies of variety. Learning in open-ended ways gets cheaper with increasing (and nominally unnecessary) diversity, variability and uniqueness in system design.
Note that you sometimes don’t need to explicitly know what kind of failure scenario you’re designing for. Introducing even random variations in non-critical components that have identical nominal designs is a way to get there (one example of this is the practice, in data centers, of having multiple generations of hardware, especially hard disks, in the architecture)
The fact that you can think of the core idea in so many different ways should tell you that there is no formula for leak-before-failure thinking: it is a kind of creative-play design game which I call fat thinking. To get to economies of scale and scope, you have to think lean. To get to economies of variety on the other hand, you have to think fat.
The Essence of Fat Thinking
If you’re familiar with lean thinking in both manufacturing and software, let me pre-empt a potential confusion: setting up a system for leak-before-failure is not the same as agility, in the sense of recovering quickly from failures or learning the right lessons from failure in a time-bound way, or incorporating market signals quickly into business decisions.
Easy way to keep the two distinct: lean thinking is about smart maneuvering, fat thinking is about smart growth.
Leak-before-failure in the broadest sense, is a way to bias an entire system towards open-ended learning in a particular area, while managing the risk of that failure. It is a type of calibrated, directed chaos-monkeying, that actually sacrifices some leanness for growth learning and insurance purposes. If in addition you are able to distribute your slack to drive potentially high-leverage learning in chosen areas, it is also a way to uncover new strategic advantages.
How so? Lean is really defined by two imperatives, both of which fat thinking violates:
Minimizing the amount of invested capital required to do something (so you need less money locked up in capital assets and inventory)
Maximizing the rate of return on that invested capital (through, broadly, minimizing downtime, or equivalently, time to recover from failures).
When you’re running lean, with a highly optimized (and therefore fragile) design, with very high uptime, you’re basically in a regime of closed-world learning, where learning and adaptation loops are not only closed, they have a tight spread of recovery times, and every recovery potentially yields immediate efficiency gains.
This is why the “learning” by “leaning out” an operation serves as a way to cut costs (which often becomes the main purpose). This should strike you as bizarre, given that our archetypal examples of learning, young children learning through play, are costly money sinks who produce no immediate return on investment at all. Learning in a general sense should increase costs, not decrease them.
The kind of learning that intuitively strikes us as more natural, and closer to children playing, happens in fat regimes. This is where the term trial and error actually justifies itself. In strongly leaned-out systems, there is not actually much room for error.
When you get away from lean regimes, you’re running fat: you’ve deployed more capital than is necessary for what you’re doing, and you’re deriving a return from it at a lower rate than the maximum possible.
You’ve deliberately introduced slack into the system, to pay for two things: safety insurance, and open-world learning. The system is likely to fail (and drive learning) where there is the least slack. One way to choose where you learn is to put slack everywhere except where you want to learn.
You’ve sacrificed some productivity of capital assets to gain some control over the process we commonly know as what doesn’t kill you only makes you stronger.
Learn or Die Microeconomics
Here’s the thing that separates open-world learning from closed-world: there is no systematic way to control failure-recovery times. To use a brain analogy, closed-world learning is like the closed loops of the brain stem and cerebellum. Open-world learning bubbles up to the open-ended thinking processes of the cerebrum and neocortex. These processes may include completely open-ended research problems, problems you don’t know are NP-complete, poetic inspiration, and so forth.
To get killedin an open-world learning attempt is to experience an event or event cascade that causes such catastrophic damage that you don’t have the reserve resources to recover at all.
To grow stronger in an open-world learning attempt is to scale along some vector uncovered by the failure, like a hydra growing two heads where one has been cut off. The fruits of open-ended learning are unpredictable. They might range from radical redesign of your whole system, to a pivot that changes the basic idea of what you’re supposed to be doing. This is in contrast to the idea of kaizen in lean, where the learning occurs in predictably small steps near the local optimum, rather than in big leaps in directions that are potentially completely random.
(Caution: for a variety of reasons, it is best not to think of fat thinking/economies of variety as a kind of global optimization; that tempts you into one kind of model lock or another)
One way to understand this is to think of open-world learning as being waste-free: An error is just a trial you haven’t learned from yet, and there’s a good chance that you won’t be the one to learn from it at all.
This is a basic mechanism driving markets: one company’s unrecoverable error can serve as another company’s freebie lesson. In fact, this is the default. The bulk of the value of innovation accrues outside the boundaries of the innovator, through surplus and spillover effects: the locus of failure and the locus of learning are widely separated in effect, spanning multiple entities.
Tim O’Reilly’s advice to “create more value than you capture” isn’t a prescription for being a good economic citizen. It’s a description of operating conditions. If you can even capture enough to just barely survive, you’re doing better than most.
Which means fat and lean thinking have macroeconomic consequences beyond a single company.
Learn or Die Macroeconomics
The idea that you can’t be sure you’ll be the one to learn from your failure is what makes attempting to grow as big as possible, as fast as possible, a very wise idea if you have the stomach for it.
If you grow big, it means your system boundary is bigger, and if other things are set up right, you have a higher chance of being the beneficiary of your own open-ended learning. You can benefit from much wider separations between loci of failure and learning.
Of course, there are other factors that make large size a disadvantage, such as the comforts of monopoly status lowering the incentive to learn at all, so there is a sweet spot where you’re big enough to benefit sufficiently from your open-ended learning, but not so big that you have no reason to learn. A classic determinist error is to recognize the advantage of being bigger, while ignoring the cost. This is why I think Thiel’s notion of a creative monopoly is somewhere between incomplete and wrong, but I won’t go down that bunny-trail in this post.
So what doesn’t kill you makes you stronger, and what does kill you makes the broader economy, and society at large, stronger. With the probability of the two outcomes depending on your own size relative to the size of the economy you’re embedded in.
And of course, the system boundary for humanity is low earth orbit, so what doesn’t kill the planet will make it stronger. Like climate change. Some people think AI risk is also one of these kill-the-planet-or-make-it-stronger learning attempts. I am not so sure.
This means we can also talk about lean and fat thinking across entire economies. An entire economy full of lean-thinking, six-sigma-ing, customer-listening corporations is, as a whole, in a closed-world learning regime with very little spillover and surplus outside boundaries. In such an economy companies live long and prosper, as captives of a rentier, cronyist class. But they produce very little by way of truly novel products and services. So the stability comes at the cost of slow eroding economic dynamism and increasing fragility of the national and global economies they are part of.
An entire economy full of fat-thinking, unique-snowflaking, product-driven corporations is, as a whole, in an open-ended learning regime with very high spillover and surplus outside boundaries. In such an economy, companies live free or die hard, at very high rates, churning rapidly, and produce a great many new products and services, most of which fail. But in so failing, they add economic dynamism and antifragility to the national and global economies they are part of.
Most critically, lean economies have all their growth reflected in the numbers, but are zero-sum overall. Fat economies have trouble accounting for all the open-ended learning accruing in nooks and crannies, which nobody has exploited yet, but are non-zero-sum overall. Most of the world economy today, with the exception of Silicon Valley, is probably in a lean phase.
Visibly perfect bookkeeping implies invisible stagnation. Visibly imperfect bookkeeping implies invisible dynamism. This applies at both microeconomic and macroeconomic levels.
If I knew enough about high finance, I’d turn this idea into some clever commentary on bond yields, stock prices, secular stagnation, and Japan jokes, and make a lot of money by placing genius bets.
Learning through Repetition and Aggregation
Getting back to a single corporation, assuming your leak-before-failure setup has created an open-world learning “story” that hasn’t killed you, you will grow stronger in some indeterminate way that counts as a unit of scaling.
So scaling is really a series of weakly controlled (hence with indeterminate outcomes) attempts to create and redirect some slack in the system, sacrificing some productivity to learn a lesson somewhere between close-ended and open-ended, with some slight risk of killing yourself in the process. As you go more open, you’ll let the failure determine what you learn rather than some objective like lowering cost.
“Economies” of any sort, as I discussed in Economies of Scale, Economies of Scope, are basically types of learning. How you learn determines how you scale.
Classical economies of scale are the result of learning through repetition in engineering processes, with benefits realized as falling cost curves and increasing yields, once you go from early open-ended learning regimes to close-ended regimes. Assuming you survive the high infant-mortality rate in the early part of the bathtub curve that describes learning over a lifespan.
Economies of scope are the result of learning through aggregation in market coverage processes, with benefits realized as falling systemic transaction costs. Infant mortality on this bathtub curve is failing to learn enough about the market, quickly enough, to get to profitability and enough of a free cash flow to fuel operations.
Both these two kinds of learning through economies are intrinsically close-ended most of the time, outside of birth and death regimes. If you’re lucky enough to have had other companies make all the expensive mistakes before you, you can even start in the close-ended part of the curve, and skip the early, high-mortality part of the bathtub curve altogether. This is why “customer driven” companies and imitators survive better: the high-risk learning has already been done by another entity, may it rest in pieces. To the fast-follower the spoils.
These two together are what drive the business cycle. If everybody is making expensive mistakes early in the bathtub curve, you have an incentive to “defect” from the pioneering-innovation economy and start exploiting the learnings of the dead. This leads to a flood of defections, and now everybody is trying to exploit learnings through fast-follower strategies, with diminishing returns. So you can again defect, this time towards innovating by becoming more product-driven.
There is no simple relationship between the proportion of product-driven versus customer-driven activity in an economy and the booms and busts of the market, but I strongly suspect cycling on the one spectrum contributes strongly to the business cycle. Further, I suspect, the cycling will have a phenomenology similar to predator-prey population cycling as described by various models (with customer-driven companies being “predators” and product-driven ones being “prey”).
There is a missing piece here though. It is easy to see how you can turn into a fast follower if there are a lot of struggling pioneers around. But how do you turn into a pioneer, when everybody is trying to fast-follow? More importantly, how do you do so in a way that doesn’t make you the first lemming?
It is clear that we don’t have good answers to this question, which is why companies and entire nations find it easier to slip into a customer-driven regime than break out of it. So individual companies enjoy occasional bouts of inspiration that leads to some pioneering. Nations sometimes get inspired as a whole and get out in front, leading the global economy.
But sometimes, everybody is hanging back, waiting for somebody else to do the new learning.
Learning through Variation
As you might expect, what I call economies of variety involves learning that is closest to Darwinian: it is learning through artificial (or co-opted natural) variation. In the past few decades, a few companies seem to have demonstrated that it is possible to be consistently product-driven, pioneering one new category after another. Apple is of course, the textbook example, but there are several other candidates.
Others, like Twitter, have shown what happens when you fail to realize economies of variety, through what I call a too-big-to-nail pathology: they don’t get big enough, quickly enough, to retain enough of the value they create. This can happen through either weak management, or creating too much value.
Economies of variety are the result of learning through variation (in the sense of trying a variety of things looking for product-market fit for example), with benefits realized as creative innovation capacity distributed throughout the system.
If economies of scale and scope are about doing the thing right, economies of variety are about doing the right thing. Where the “right thing” is figuring out new product categories repeatedly, before old ones enter their harvest phases or are taken over by imitators, fast-followers, and traditional voice-of-customer driven competitors. Economies of variety are fundamentally what long-lived product-driven companies are good at creating and banking. They pioneer category after category in a predictable way, because they run fat rather than lean, using leak-before-failure creativity to survive their own learning risks.
These companies don’t seem to merely deal with Darwin, they appear to systematically beat Darwin. This beyond-Darwin survivability is variability selection. I didn’t make up that term; I borrowed it from a theory that offers an explanation for why humans, in a sense, beat Darwin at the selfish-gene level and moved the game to the memes-and-culture level. Hominids, effectively, were selected for having brains capable of generating and adapting to variety in software rather than hardware. We are not only more exploratory and curious than most species, we have hardware that can handle a lot more variety and survive.
So companies that figure out economies of variety are to industrial age companies as hominids are to other animals: they’ve grown an organ analogous to a brain through a process like variability selection.
Scaling Innovation
One way to understand what these companies is to think of them as having figured out how to scale innovation itself, something industrial age companies largely failed to do.
Innovation as a function, and the economies of variety it can deliver when scaled, has historically been something of a third wheel in industrial age corporations built around economies of scale and scope.
Xerox famously “fumbled” the future: the one bit of innovation from PARC it managed to hold on to, the laser printer, gave the company a fresh lease on life that sustained it for a couple of decades longer, but everything else that came out of the lab created wealth elsewhere in the economy. And Xerox was no exception. AT&T was not the primary beneficiary of the invention of the transistor at Bell Labs; Intel was. There are other examples.
These companies did capture some value, but they would have liked to capture more of the value than they did. Or better yet, gain control over the process of how much value they generated and retained.
The modern open innovation economy in the sense of Chesbrough (basically early-stage IP trading among corporate R&D outfits) is something of a market of consolation prizes for fumbling pioneers.
The classic industrial age corporation is a two-element chicken-egg loop of scaling and scoping. To expand on a thought in my earlier post, in an industrial style corporation, scoping decisions lead to scaling commitments, and scaling decisions lead to scoping commitments. There is no locus in this tight loop for innovation to enter in an endogeneous way. The best model we’ve had to date has been to have an R&D lab invent things and throw them over a wall into the loop (as an exogenous input), hoping for something good to happen.
Economies of variety offer an alternate model. You don’t think in terms of a bolted-on laboratory and a scale-and-scope operation separated by a wall, with “innovation” consisting of throwing “inventions” over the wall as exogenous inputs and hoping for the best.
Instead you think in terms of a fat operations that use leak-before-failure designs that introduce calibrated amounts of variety across nominally uniform operations, to catalyze endogenous growth.
Note #1: The term ‘fat thinking’ is derived from Ben Horowitz’s 2010 post The Case for the Fat Startup, which in turn is a response to the then-peak-of-fashion Lean Startup mode. The sense I’m using the term ‘fat’ here is related but not quite the same. Ben’s sense primarily has to do with finance, while mine here primarily has to do with the relationship between innovation and scaling.
Note #2: lately, I’ve moved much of my business-oriented writing over to the Breaking Smart newsletter, so I only rarely do business-themed posts here. Subscribe to the newsletter if you this sort of thing interests you more than my other writing. This particular idea will probably get fleshed out more carefully and digestibly in Season 2.
It looks like Nintendo is slowly beginning to modernize its business practices in some respects.
According to The Wall Street Journal, the NX, Nintendo’s upcoming gaming system that’s expected to be a handheld-console hybrid, will also “be compatible” with the company’s smartphone games. Nintendo has revealed plans to release two games based on the Animal Crossing and Fire Emblem series, as well as other mobile titles.
It’s unclear exactly how the NX will interact with smartphone titles or if Nintendo’s upcoming mobile games will be directly ported to the rumoured console.
Earlier this week information leaked that the NX will reportedly utilize cartridges, a storage format the Japanese gaming giant mistakenly stuck to in the mid to late 90s with the Nintendo 64.
Contrary to what many people thing, while Nintendo is a partner on Pokemon Go, the company only owns a portion of the Pocket Monster collecting property.
its ironic in many ways that so many people wanted to defend the hyperloop by claiming it was Elon Musks invention, and that hes a genius who invented rockets and electric cars. In reality, Elon Musk made it rich on software.
Have you ever wondered how Facebook decides what posts to show you? Here’s a hint: You’re not seeing everything your friends post. Not even close. Facebook’s computers try to decide which posts you’ll find most useful, based on your history of Liking and Sharing things. It also displays the most popular items at the top, so you’ll see them first—even if that’s not their chronological order. If you’d rather see them in the order they appeared, click Home and then Most Recent.
Jens von Bergmann at Mountain Math continues to astonish me with his ability to mash up different data sources into something more usable and bigger than any individual source.
Here’s Mobi station data superimposed on a Vancouver bike infrastructure map, updated in real time to show bikes and slots currently available. And yes, it looks fine on your phone (iPhone & Android). Ancient PC’s may balk.
Community made with passion, dedication and tons of Love and when we talk about our beloved community , we only think about its day by day progress . Since its a community with an essence of diversity and build by passionate people.
Recently I got to involved with Mozilla Community Mumbai with Few Awesome people who are maestro in there own path . Thanks to Mrinal, Kumaresan and Tejas for connecting the dots again.
It was a great meetup because of :
We get some passionate people who wanted to see an active community .
We shared our contributions and how passionately we handling our work-passion balance .
We discussed our future plans for community,with community and how to implement them.
Keeping to short and simple , with all goods , will come up with upcoming events from our Community .
Prisma, the viral photo-editing app that processes pictures into a variety of artwork-inspired styles, will soon offer video editing to its feature set.
In fact, co-founder Alexey Moiseenkov told Bloomberg that the much-anticipated feature is already developed, but the company has to update its computing infrastructure previous to releasing it. This will come as no surprise to fans of the app who have contended with long processing times for photos and occasional server crashes.
Moiseenkov is clearly expecting quick development on that front, however, as Bloomberg states the co-founder expects the feature to roll out “in the next several weeks.”
Moiseenkov spoke with Bloomberg on a recent trip to the U.S. from Russia, in which he promoted the app and took a meeting at Facebook, sparking acquisition rumours.
The app has been downloaded on about 16.5 million times on iOS devices since its June launch, and has been downloaded over a million times on Android only four days after its July 24th launch. It has recently begun experimenting with monetization, so far allowing companies, such as Colgate-Palmolive Co., to sponsor a certain filter.
Dan Dodge hasn’t worked at BlackBerry since December of 2015. Now however, he’s an Apple employee.
Apple recently hired QNX founder Dan Dodge, the software development company acquired by BlackBerry in 2010, to work with the Cupertino-company’s car team. Bloomberg reports that Dodge actually joined the team earlier this year, though the news is just surfacing now.
Dodge is reportedly part of a team led by Bob Mansfield, who’s taken a leadership role in the autonomous cars initiative. Furthermore, since Mansfield has taken over, he’s led the program through a strategy shift that now prioritizes tech.
Dodge stepped down from his role with BlackBerry’s subsidiary QNX in late 2015. There was no word at the time regarding any plans following this announcement. Currently, he’s part of a team working to develop an autonomous driving system, which has lately become the new focus of Apple’s car team.
This news comes months after Apple pledged to open a research and development facility in Kanata Ontario. Furthermore, Apple’s most recent earnings release for the second fiscal quarter revealed a waning demand for iPhones and a lower overall revenue year over year.
While the company’s revenue fell within its previous quarterly forecast, it’s yet another indicator that Apple may be searching for other forms of revenue. CEO Tim Cook confirmed in an earnings call Tuesday that the company is working on several initiatives beyond its current product line.
Dodge founded QNX back in 1980 while a student at the University of Waterloo. After being acquired by Harman International Industries in 2004 and then being acquired by BlackBerry again in 2010. At the time of his departure, he issued this quote to BlackBerry news site, Crackberry.com.
“My decision to leave was my own,” he said. “I threw my own party, invited everybody from QNX that I’ve known over the last 35 years and we had a grand time”.
In a quote obtained from BlackBerry at the time, the Waterloo company referred to Dodge’s departure as his “retirement.”
Using a circular loom, 1500 meters of thread, and a uniquely programed computer algorithm, Greek artist and engineer, Petros Vrellis has recently come up with a whole new way to knit. Unlike traditional knitting techniques, the thread used in Vrellis’ embroidery work isn’t actually woven but is instead knitted as straight lines contained within the circle—an assembly of intersecting and overlapping ‘chord’ lines, for those of us who remember geometry. The strings cross over from peg to peg 3000-4000 times, coming out to nearly a mile of string. When the string overlaps enough times, its density starts to black out the white wall behind the loom, allowing the artist to flesh out a portrait using the negative space within the circle.
A recent video Vrellis uploaded to Vimeo features a timelapse of the artist weaving together a portrait of Jesus himself. The 'weave' sequence is done completely by hand, however each step is mapped out by a computer through a specially designed algorithm that converts a digital photograph into a peg-by-peg knitting pattern. In order to translate the input from the photograph, Vrellis’ algorithm has to make over 2 billion calculations in order to produce the pattern.
Vrellis says his portraits are influenced by the works of 16th century Greek painter El Greco, whose dramatic and expressionistic style laid the groundwork for both the expressionist and cubist movements. Perhaps Vrellis' use of algorithms will start a movement all its own—a weaver’s revolution, enabled by technology.
Check out more work by Petros Vrellis on his website.
July’s almost over… but our updates are not, obviously :-) How have you been? Are you melting in the shade or freezing in the sun? Maybe both? ;-) Here are the hotte… no, wait, the coolest news on the web, for your eyes only!
If you want to add a discussion topic to the upcoming meeting agenda:
Start a thread in the Community Forums, so that everyone in the community can see what will be discussed and voice their opinion here before Wednesday (this will make it easier to have an efficient meeting).
Please do so as soon as you can before the meeting, so that people have time to read, think, and reply (and also add it to the agenda).
If you can, please attend the meeting in person (or via IRC), so we can follow up on your discussion topic during the meeting with your feedback.
UPDATE! We’re in the final stages of negotations and contracting details. More details as we have them (most likely in a special blog post dedicated to just the platform)
On a slightly less serious front… E10s is coming! (thank you, Jobava!)
Ongoing reminder #1: if you think you can benefit from getting a second-hand device to help you with contributing to SUMO, you know where to find us.
REMINDER: A social sprint for Firefox 48 is taking place soon, stay tuned for more news soon! Repeat after me – AUGUST THE SECOND! (almost a Polish king)
Thus, between a Firefox for iOS and a Firefox for Desktop and Android released into the wild wide web – that’s a lot of heat! Now I know why it’s so easy to sweat nowadays. Well, maybe there will be some relief in the weeks between releases ;-) Winter is coming! Slowly, but surely…
Lindsay Zoladz, writing for The Ringer, has a great story on the role of the iPod Classic in today's music streaming landscape. I understand where she's coming from, and I found this passage on the paradox of choice particularly accurate:
“When I’m searching for something to listen to on Spotify, I feel like I end up listening to the same albums and artists again and again,” my friend Becca wrote in an email, after I asked a handful of acquaintances about their post-iPod listening habits. “My brain by itself isn’t good at cataloguing everything I love.”
The psychologist Barry Schwartz has written (or, if you don’t have too much time on your hands, has TED-Talked) about a related phenomenon he calls “paradox of choice” — the notion that, although we tend to think of freedom of choice as an inherently good thing, too much choice can leave us feeling paralyzed and anxiety-ridden. “With so many options to choose from,” he says, “people find it very difficult to choose at all.” I personally have proven this theory many times over in the past few months, when I’ve stared for a few moments at the infinite void that is the Apple Music search bar and decided, “I guess I will just listen to Pablo or Lemonade again.” Another friend I emailed summed up the Paradox of Digital Music Listening succinctly: “With device-bound listening, I absolutely feel limited by [storage] space. With streaming, I feel limited by my own memory.”
This is why I often buy videogames from a small shop in my hometown. I could open the App Store, or the eShop, or the PlayStation Store, and buy anything I want. But there's just so much stuff. There's too many games and too many reviews and too many Let's Plays to choose from. Sometimes, it's nice to have fewer options.
I recently came across an old entry on Jonathan Blow's blog
called
John Carmack on Inlined Code.
The bulk of the entry consists an even older email message
that
Carmack,
lead programmer on video games such as Doom and Quake, sent
to a mailing list, encouraging developers to consider
inlining function calls
as a matter of style. This email message is the earliest
explanation I've seen of Carmack's drift toward functional
programming, seeking to as many of its benefits as possible
even in the harshly real-time environment of game programming.
The article is a great read, with much advice borne in the
trenches of writing and testing large programs whose run-time
performance is key to their success. Some of the ideas
involve programming language:
It would be kind of nice if C had a "functional" keyword to
enforce no global references.
... while others are more about design style:
The function that is least likely to cause a problem is one
that doesn't exist, which is the benefit of inlining it.
... and still others remind us to rely on good tools to help
avoid inevitable human error:
I now strongly encourage explicit loops for everything, and
hope the compiler unrolls it properly.
(This one may come in handy as I prepare to teach my compiler
course again this fall.)
This message-within-a-blog-entry itself quotes another email
message, by
Henry Spencer,
which contains the seeds of a programming challenge. Spencer
described a piece of flight software written in a particularly
limiting style:
It disallowed both subroutine calls and backward branches,
except for the one at the bottom of the main loop. Control
flow went forward only. Sometimes one piece of code had to
leave a note for a later piece telling it what to do, but
this worked out well for testing: all data was allocated
statically, and monitoring those variables gave a clear
picture of most everything the software was doing.
Wow: one big loop, within which all control flows forward.
To me, this sounds like a devilish challenge to take on when
writing even a moderately complex program like a scanner or
parser, which generally contain many loops within loops. In
this regard, it reminds me of
the Polymorphism Challenge's
prohibition of if-statements and other forms of
selection in code. The goal of that challenge was to help
programmers really grok how the use of substitutable objects
can lead to an entirely different style of program than we
tend to create with traditional procedural programming.
Even though Carmack knew that "a great deal of stuff that goes on
in the aerospace industry should not be emulated by anyone, and
is often self destructive", he thought that this idea might have
practical value, so he tried it out. The experience helped him
evolve his programming style in a promising direction. This is
a great example of the power of the pedagogical pattern known
as
Three Bears:
take an idea to its extreme in order to learn the boundaries of
its utility. Sometimes, you will find that those boundaries
lie beyond what you originally thought.
Carmack's whole article is worth a read. Thanks to Jonathan Blow
for preserving it for us.
~~~~
The image above is an example of the cover art for the "Commander
Keen" series of video games, courtesy of
Wikipedia.
John Carmack was also the lead programmer for this series. What
a remarkable oeuvre he has produced.
We know the Note 7 will be announced this coming Tuesday, August 2nd in New York City, and as with many phone releases, there is a slew of information already available about the device, with some of our information sourced directly from Samsung.
Here’s a quick look at all of the most significant rumours and speculation surrounding the note 7 so far.
It’s the Note 7, not the Note 6
In order to keep branding in line with the S7 and S7 edge, rumours indicate Samsung is set to pull a Microsoft with plans to release its latest Note device as the Note 7, not the Note 6.
The South Korean manufacturer has even gone so far as to publish a blog post essentially explaining why it’s opted to jump a digit with its latest phablet. In the post, Samsung describes the S7 as a “powerful instrument for achievement and self-expression, and is made for those who want to get the most from their phones — and their lives”
It will launch on August 13th (maybe)
Given the fact that the Galaxy Note 5 launched on August 13th 2016 alongside the Galaxy S6 edge+, it’s likely this year’s Note 7 will be released somewhere around the same date, though as usual, nothing has been confirmed yet.
Samsung Galaxy Note 6 US release scheduled for week of August 15th.
Popular leakster Evan Blass claims he has sources indicate the phone will be available the week of August 15th, just a couple of weeks after the phone’s August 2nd reveal.
Design and specs
In terms of design, it’s expected that the Note 7 will look very similar to the S7 edge, complete with double curved edges and the now standard S Pen. There have, however, been reports that a curved and flat version of the Note 7 could be released, just like the S7 and S7 edge, though some rumours indicate the flat version of the Note 7 might just be a prototype.
According to yet another leaker, this time @OnLeaks (Steve Hemmerstoffer), sourced from USwitch, the Note 7 will measure in at 153.5mm x 73.9mm x 7.9mm, which means it likely features the same 5.7-inch display as the Note 5. The phone is also rumoured to be IP68 water and dust resistant, a feature the S7 and S7 edge offers, and will reportedly be the first Samsung device to feature a built-in iris scanner, giving users another option when it comes to logging into their device.
In terms of other specs, the Note 7 is rumoured to feature a Quad HD Super AMOLED display, 12 megapixel “Super OIS Plus” shooter with “dual pixel” functionality, the same feature that made the the S7 and S7 edge’s camera so stellar. The phone’s sensor is rumoured to measure in at 1/2.3-inch with a f/1.4 aperture lens, allowing 17 percent more light, which in turn should result in better photographs.
Other rumours indicate the company is working on new technology called “Smart Glow” that creates a ring of light surrounding the Note 7’s rear camera, indicating missed calls and messages.
The Note 7 is also rumoured to feature a USB-C port, a first for Samsung. Hemmerstoffer tweeted out perhaps the most impressive leaked pics of the Note 7 earlier this month.
Final specs include a either a Qualcomm Snapdragon processor, possibly the unreleased Snapdragon 823, 821, or Samsung’s own propriety Exynos processor, which is featured in the Canadian version of Samsung’s S7 and S7 edge, but not in its U.S. counterpart.
The phone will also come equipped with either 6GB or 8GB of RAM and either 64GB or 128GB storage offerings, along with a battery somewhere between 3600mAh and 4000mAh. It’s unclear if the device will feature microSD support yet again, though it is quite possible given we saw the return of the feature with the S7.
I’ll be on the ground this coming Tuesday bringing you all the Note 7 news direction from Samsung’s event in New York.
The environmental review process for the $3.5 billion George Massey tunnel replacement project is now officially underway. The BC Environmental Assessment Office (EAO) has scheduled public open houses , starting in mid-August as part of a 60-day public comment period. The first open house takes place in Delta August 17, followed by one in Richmond September 13 and another open house in Delta September 14. …
The majority of Richmond city council is opposed to the project and wants to keep the tunnel. Most mayors with Metro Vancouver are also opposed to the project.
Delta Mayor Louise Jackson is among the only mayors on Metro Vancouver who supports the tunnel’s replacement. …
Vancouver’s business community is generally in favour of the project. The Greater Vancouver Board of Trade says the Highway 99 south corridor is “one of the most important highway corridors in British Columbia.” Highway 99 south connects the Lower Mainland to the U.S. border, BC Ferries’ Tsawwassen terminal and the Deltaport container terminal. …
According to the B.C. government, the new 10-lane bridge would shave 30 minutes off the commute of those who currently use the tunnel every day to get in and out of Vancouver.
.
Is there really any doubt that this review will approve the bridge with perhaps some cautionary notes?
More valuable would be a review of the bridge’s rationale, since it came basically from nowhere – certainly not in any plan, regional or provincial.
And then: what will be the impacts on regional transportation as a whole (not just the Highway 99 corridor) and the likely land-use impacts. (Bridges have region-shaping consequences: The Oak Street Bridge construction in 1957 led, two years later, to the rezoning of Richmond as a bedroom suburb of Vancouver. The first Port Mann Bridge in 1964 had even greater impacts on Surrey.)
Ultimately, the most important question is this: what is the Province’s vision for Metro Vancouver? Is the Fraser Delta to be industrialized? What energy projects will be facilitated? How is it expected that the Port will expand?
Is the transportation network for the region still to be car- and truck-dominated, with the minimum transit system the region can fund through referendum?
What are the next projects anticipated by the Ministry? Once Oak Street is further congested, will it be widened or replaced? Will there be another bridge at Boundary Road? Will tunnels be designed to handle the congestion on the arterials in Vancouver. (And if you think cross-city tunnels are unrealistic, check out Brisbane.)
Though the Massey will be one of the most gigantic bridges to be constructed in North America, is it only one piece of a more extensive road network for the region to handle the next million – one that will keep us car-dependent and cost many times more than the transit system that is one of the foundations of the regional plan?
The critical questions that must be addressed in any review of the Massey replacement are the ones that won’t even be asked.
“If you are not embarrassed by the first version of your product, you’ve launched too late.” – Reid Hoffman, Founder of LinkedIn Reid Hoffman, the founder of LinkedIn (recently acquired by Microsoft for $26.2 billion), famously said “If you are not embarrassed by the first version of your product, you’ve launched too late.” As a Product Manager, though, especially in enterprise, a...
Adrianna Tan @skinnylatte
You can imagine, in the same chain, another link that’s structurally strong, but made of a steel alloy that rusts the fastest, so if there’s a high humidity period, it breaks first. In the two cases, you can investigate the unusual load pattern, or possible failure in the HVAC (heating, ventilation and air conditioning) system.
Thunderf00t's YouTube Videos.
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