All items by Alistair Croll

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Google introduces AI-as-a-service

Google’s recently launched learning engine tries to predict the future. The prediction engine takes data and tries to guess at outcomes. It’s not quite that simple: you have to supply the engine with a set of training data, and it will then try to predict new data based on what it’s learned, using a supervised learning algorithm.

By offering this as a cloud service, Google has removed an obstacle for many startups. Learning engines can predict everything from future purchases to suspicious behavior, but growing them as the data set expands can be difficult. The prediction engine can be built into applications running in Google’s App Engine, for example, making it easy to experiment with machine learning at scale. While the data is anonymous, Google does benefit from improved algorithms as it learns what works and what doesn’t.

Following on the heels of Google’s investment in Recorded Future, it’s clear the company’s mission goes far beyond putting the world’s information at our disposal. But even if Google can show the world the future, will we change what we do?

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In The Shockwave Rider, his 1970s vision of a future that’s arriving faster than we can deal with it, John Brunner talks about Delphi Pools. These public, crowdsourced lotteries let citizens bet on predictions. The government uses this data to decide what’s most important to the population.

Break out your tinfoil hats: now Google and the CIA may be up to the same thing, having invested in a “temporal analytics” startup called Recorded Future last year.

According to Wired:

The CIA and Google are both backing a company that monitors the web in real time — and says it uses that information to predict the future.

The company is called Recorded Future, and it scours tens of thousands of websites, blogs and Twitter accounts to find the relationships between people, organizations, actions and incidents — both present and still-to-come. In a white paper, the company says its temporal analytics engine “goes beyond search” by “looking at the ‘invisible links’ between documents that talk about the same, or related, entities and events.”

Sentiment analysis is nothing new; what’s different here seems to be the visualization and extrapolation of past trends into the future.

Like Brunner’s Delphi, this helps guess what might happen, but rather than soliciting our input directly the way prediction markets do, this uses the trails we leave online — links, comments, retweets, and so on. The predictions can include competitive intelligence, brand monitoring, and personal investigation.

Incidentally, in Brunner’s novel, the government uses the Delphi pools to placate an otherwise implacable citizenry, and often alters the results before publishing them to sway public opinion.

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Mapping the human brain

GigaOm has a great piece on IBM’s efforts to map the brain. It’s a long way from downloading ourselves into a computer, but this interview shows just how far we’ve come — and how much more there is to do.

Go visit GigaOm for Stacey’s take on the discussion. Mapping the brain has tremendous potential for both good and bad. We can tackle diseases and cure trauma; but we can also understand when someone is lying, or manipulate them below their conscious defenses. IBM’s efforts center around simulating the way brains work within computer systems, and mapping real brains is key to that effort.

(Hat tip to Duncan Hill for the pointer)

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Via @lennysan, this is a great piece on how public, prosthetic memories will change us forever. Humans forget things with good reason: forgetting lets us discard old ideas in favor of new ones, and pain recedes so we can try things like childbirth again. Not so digital memory.

There’s a growing movement to put a statute of limitations on public digital data, even as Google reveals that it’s stored every search since its launch and the Library of Congress is archiving every Tweet.

As this Ars Technica piece points out, “in an age of ever-cheaper storage, the data committed to machine memory requires an act of will to delete.”

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It’s one of the great philosophical debates of all time. Given enough computing horsepower, would we know the difference between the real world and a simulated one? With the cost of bandwidth, computing, and storage dropping precipitously, it’s harder and harder to tell the real from the simulated.

Check out the Lagoa Multiphysics plugin for Softimage. It’s pretty impressive. Tools like this do for interactive visualization what still-image tools like Photofuse do for traditional photographs.

You might argue that to really trick us into believing the world around us was a simulation, each particle the software represented could only consume one particle of computing infrastructure. But isn’t that what the universe looks like? And did I just blow your mind?

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Visualizing big data

Making sense of the huge reams of data around us isn’t easy. Sometimes it takes new visualizations and dimensions, like the ones in this photo set on Flickr, prepared as part of Wired UK‘s latest issue. The image at right shows how we can track human mobility from cellphone data.

As we drink from the firehose, we’ll get informational obesity — there’s a reason they call it a feed. New interfaces — from the immersive to the augmented — will be key to coping with it. This set has some tantalizing suggestions of what that might look like.

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AR meets 3D modeling

Techi has a piece on Leonar3Do, a new take on 3D modeling. It looks as far from traditional modeling tools as they were from pen and paper.

Years ago, I played around with 3D modeling (and narrowly avoided a career at Matrox and Softimage in the process.) Building models was tedious: manipulating 3D space with two-dimensional tools like a mouse and a screen is tough. Software relies on all sorts of controllers, UI conceits, and tricks: rotating the onscreen image; holding down shift to move along the third dimension, and so on.

Google acquired Sketchup to help crowdsource 3D content for Google Earth largely because it was comparatively easy to use. But so far, we can’t work with 3D content in three dimensions.

That’s about to change: using modeling tools and AR visualization, designers can actually manipulate in three dimensions. Which will go a long way to making 3D models mainstream, unlocking all kinds of use cases.

Who knows, maybe soon, we’ll have opt-in vandalism, where taggers add 3D objects to the real world for those who want to see them.

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Visualization at two extremes

I’ve been spending a lot of time on interfaces and visualization lately, as part of a new conference that melds Big Data, Ubiquitous Computing, and New Interfaces. Along the way, I was struck by these two extremes of visualization.

At one extreme, there’s the Canadian filmmaker who’s implanted a camera in his eye socket. It’s a great example of embedded, ubiquitous data collection — something we’ll likely all take for granted very soon. This is visualization in the truest sense.

At the other end of the spectrum is the Allosphere, an immersive, three-storey-tall sphere used for visualizing and interacting with data.

These two spheres are very different. One collects a single person’s perspective; the other reveals huge amounts of data. One shows things at an intimate, human scale; the other zooms out to galazies or in to neurons.

Posts

Is Zynga’s break with Facebook a sign that software developers, feeling trapped by the platforms on which they grew, want to down the garden wall?

The biggest app maker on Facebook may want to break up with the social network site. Flash and Apple have divorced, citing irreconcilable differences. We’re moving past the days of net neutrality, into those of app neutrality. Are the garden walls of social networks and mobile devices ready to crumble, just as rigidly controlled online services gave way to the Web fifteen years ago?

Read more »

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Mashable has a look at how social networks are the tool of choice for divorce lawyers.

The American Academy of Matrimonial Lawyers says 81 percent of its members have used or faced evidence plucked from Facebook, MySpace, Twitter and other social networking sites, including YouTube and LinkedIn, over the last five years.

It’s not just compromising pictures that are being used: sometimes, the evidence is nasty–parents tugging at their children’s social graphs to try and pull children away from their alienated spouse. With Overshare the word of the year in 2008, it’s no surprise that all that disclosure is catching up with us.

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