Notification centers and Apple Watches beg the question: what’s the best way to interrupt us properly?
We’ve been claiming information overload for decades, if not centuries. As a species, we’re pretty good at inventing new tools to deal with the problems of increasing information: language, libraries, broadcast, search, news feeds. A digital, always-on lifestyle certainly presents new challenges, but we’re quickly creating prosthetic filters to help us cope.
Now there’s a new generation of information management tools, in the form of wearables and watches. But notification centers and Apple Watches beg the question: what’s the best way to interrupt us properly? Already, tables of friends take periodic “phone breaks” to check in on their virtual worlds, something that might have been considered unthinkably gauche a few years ago.
Since the first phone let us ring a bell, uninvited, in a far-off house, we’ve been dealing with interruption. Smart interruption is useful: Stewart Brand said that the right information at the right time just changes your life; it follows, then, that the perfect interface is one that’s invisible until it’s needed, the way Google inserts hotel dates on a map, or flight times in your calendar, or reminders when you have to leave for your next meeting.
But all of this technology is interfering with reflection, introspection, and contemplation. In Alone Together, Sheri Turkle observes that it’s far easier to engage with tools like Facebook than it is to connect with actual humans because interactive technology’s availability makes it a junk-food substitute for actual interaction. My friend Hugh McGuire recently waxed rather poetically on the risks of constant interruption, and how he’d forgotten how to read because of it.
At work, modern productivity tools like Slack might do away with email conventions, encouraging better collaboration, but they do so at a cost because they work in a way that demands immediate attention, and that interrupts the natural rhythm we all need to write, to read, and to immerse ourselves in our surroundings. It’s hard to marinate when you’re being interrupted. Read more…
The success of Apple’s watch, and of wearables in general, may depend on brain plasticity.
Recently, to much fanfare, Apple launched a watch. Reviews were mixed. And the watch may thrive — after all, once upon a time, nobody knew they needed a tablet or an iPod. But at the same time, today’s tech consumer is markedly different from those at the dawn of the Web, and the watch faces a different market all together.
One of the more positive reviews came from tech columnist Farhad Manjoo. In it, he argued that we’ll eventually give in to wearables for a variety of reasons.
“It was only on Day 4 that I began appreciating the ways in which the elegant $650 computer on my wrist was more than just another screen,” he wrote. “By notifying me of digital events as soon as they happened, and letting me act on them instantly, without having to fumble for my phone, the Watch became something like a natural extension of my body — a direct link, in a way that I’ve never felt before, from the digital world to my brain.”
On-body messaging and brain plasticity
Manjoo uses the term “on-body messaging” to describe the variety of specific vibrations the watch emits, and how quickly he came to accept them as second nature. The success of Apple’s watch, and of wearables in general, may be due to this brain plasticity. Read more…
A look at the winners from a showcase of some of the most innovative big data startups.
At Strata + Hadoop World in London last week, we hosted a showcase of some of the most innovative big data startups. Our judges narrowed the field to 10 finalists, from whom they — and attendees — picked three winners and an audience choice.
Underscoring many of these companies was the move from software to services. As industries mature, we see a move from custom consulting to software and, ultimately, to utilities — something Simon Wardley underscored in his Data Driven Business Day talk, and which was reinforced by the announcement of tools like Google’s Bigtable service offering.
This trend was front and center at the showcase:
- Winner Modgen, for example, generates recommendations and predictions, offering machine learning as a cloud-based service.
- While second-place Brytlyt offers their high-performance database as an on-premise product, their horizontally scaled-out architecture really shines when the infrastructure is elastic and cloud based.
- Finally, third-place OpenSensors’ real-time IoT message platform scales to millions of messages a second, letting anyone spin up a network of connected devices.
Ultimately, big data gives clouds something to do. Distributed sensors need a widely available, connected repository into which to report; databases need to grow and shrink with demand; and predictive models can be tuned better when they learn from many data sets. Read more…
In the next decade, Year Zero will be how big data reaches everyone and will fundamentally change how we live.
Editor’s note: this post originally appeared on the author’s blog, Solve for Interesting. This lightly edited version is reprinted here with permission.
In 10 years, every human connected to the Internet will have a timeline. It will contain everything we’ve done since we started recording, and it will be the primary tool with which we administer our lives. This will fundamentally change how we live, love, work, and play. And we’ll look back at the time before our feed started — before Year Zero — as a huge, unknowable black hole.
This timeline — beginning for newborns at Year Zero — will be so intrinsic to life that it will quickly be taken for granted. Those without a timeline will be at a huge disadvantage. Those with a good one will have the tricks of a modern mentalist: perfect recall, suggestions for how to curry favor, ease maintaining friendships and influencing strangers, unthinkably higher Dunbar numbers — now, every interaction has a history.
This isn’t just about lifelogging health data, like your Fitbit or Jawbone. It isn’t about financial data, like Mint. It isn’t just your social graph or photo feed. It isn’t about commuting data like Waze or Maps. It’s about all of these, together, along with the tools and user interfaces and agents to make sense of it.
Every decade or so, something from military or enterprise technology finds its way, bent and twisted, into the mass market. The client-server computer gave us the PC; wide-area networks gave us the consumer web; pagers and cell phones gave us mobile devices. In the next decade, Year Zero will be how big data reaches everyone. Read more…
The Strata + Hadoop World 2015 Startup Showcase highlighted four important trends in the big data world.
At Strata + Hadoop World 2015 in San Jose last week, we ran an event for data-driven startups. This is the fourth year for the Startup Showcase, and it’s become a fixture of the conference. One of our early winners, MemSQL, has since raised $50 million in financing, and it’s a good way for companies to get visibility with investors, analysts, and attendees.
This year’s winners underscore several important trends in the big data space at the moment: the maturity of management tools; the deployment of machine learning in other verticals; an increased focus on privacy and permissions; and the convergence of enterprise languages like SQL with distributed, schema-less data stacks. Read more…
A Call for Proposals for Strata Conference + Hadoop World 2014
When we launched Strata a few years ago, our original focus was on how big data, ubiquitous computing, and new interfaces change the way we live, love, work and play. In fact, here’s a diagram we mocked up back then to describe the issues we wanted the new conference to tackle:
Such lists might mean we miss the truly great breakthroughs, inspirations, and leaps of faith necessary to evolve.
Editor’s note: this post originally appeared on Tilt the Windmill; it is republished here with permission.
First: it’s an excellent post. You should read it. I’ll wait.
Every enterprise decision-maker will soon be running their business according to the lists Barry envisions, as the power of big data and analytics finds its way into every boardroom and dashboard. Society will soon demand them, too. But while such analysis is tremendously valuable, it carries two dangers: the politics of setting criteria, and the trap of relying on data for inspiration.
The harsh light of data
Barry is right: rather than using our precious time and resources to make yet another linkbait list of the 50 cutest kittens, or the seven people I’ll try to avoid at SXSW, we should use abundant data and a connected world to build lists that matter: lying politicians, bad cars, lousy doctors. Then we can use these lists to change policy and behaviour because we’ll make things transparent. Shining the harsh light of data on something can improve it.
As society becomes increasingly data driven, it's critical to remember big data isn't a magical tool for predicting the future.
If you eat ice cream, you’re more likely to drown.
That’s not true, of course. It’s just that both ice cream and swimming happen in the summer. The two are correlated — and ice cream consumption is a good predictor of drowning fatalities — but ice cream hardly causes drowning.
These kinds of correlations are all around us, and big data makes them easy to find. We can correlate childhood trauma with obesity, nutrition with crime rates, and how toddlers play with future political affiliations.
Just as we wouldn’t ban ice cream in the hopes of preventing drowning, we wouldn’t preemptively arrest someone because their diet wasn’t healthy. But a quantified society, awash in data, might be tempted to do so because overwhelming correlation looks a lot like causality. And overwhelming correlation is what big data does best.
It’s getting easier than ever to find correlations. Parallel computing, advances in algorithms, and the inexorable crawl of Moore’s Law have dramatically reduced how much it costs to analyze a data set. Consider an activity we do dozens of times a day, without thinking: a Google search. The search is farmed out to thousands of machines, and often returns hundreds of answers in less than a second. Big data might seem esoteric, but it’s already here. Read more…
Eleven areas of focus for deeper investigation.
Conferences like Strata are planned a year in advance. The logistics and coordination required for an event of this magnitude takes a lot of planning, but it also takes a decent amount of prediction: Strata needs to skate to where the puck is going.
While Strata New York + Hadoop World 2013 is still a few months away, we’re already guessing at what next year’s Santa Clara event will hold. Recently, the team got together to identify some of the hot topics in big data, ubiquitous computing, and new interfaces. We selected eleven big topics for deeper investigation.
- Deep learning
- Time-series data
- The big data “app stack”
- Cultural barriers to change
- Design patterns
- Laggards and Luddites
- The convergence of two databases
- The other stacks
- Mobile data
- The analytic life-cycle
- Data anthropology
Here’s a bit more detail on each of them. Read more…