FaceApp and similar reality-warping applications are especially fun to use in ways their designers never intended. Along similar lines, Google’s DeepDream (designed for photo manipulation) creates fascinating results using photographs but is even more stunning when applied to representations of cityscapes.

While training DeepDream (a neural network that adapts like a brain to new inputs) to identify, differentiate and understand images, Google researchers discovered it could “over-interpret” results as well. In short: it could start to “read into” images from previous experience, resulting in an array of beautiful (if disturbing) hybrids.

Once it went public, mapmakers were among those intrigued by the possibilities of geo-visualization, turning flat maps into seemingly living landscapes. Tim Waters, a geospatial developer, began taking OpenStreetMap data and running it through the system, generating these strangely psychedelic urban environments.

He discovered that a short run could create fractal and quilting effects, while longer and reiterated processing started to introduce faces and creatures to the mix.

Above: monkeys and frogs seem to emerge from the grid, while a coastal region forms the head of a bear, making the landscape look like a giant bearskin rug. Overall, the effects are quite beautiful, creating a sense of depth and adding character to what would otherwise be fairly generic representations.

Jenny Odell collects and organizes all kinds of things, from meticulously sorting digital finds on Google Maps to tracing the origins of everything she used, wore, ate or bought on one particular day in 2013.

Her work often pulls objects out of context, aggregating and arranging something like a set of pools against a neutral backdrop (as seen above) or taking an entire industrial complex and carefully stripping it of its surroundings (like the facility below).

On June 26th, she will join an assortment of other unusual, curious and brilliant creatives — experts in the realms of art, design, interaction and information — as a speaker at the annual Eyeo Festival in Minneapolis, MN.

Designer, entrepreneur and artist Nicholas Felton, creator of the famously detailed and introspective data visualizations, will be back this year as well to talk about his recent work. His numerous personal annual reports condense the events of a year into a tapestry of maps, graphs and statistics.

Artist and programmer Gene Kogan will bring his interest in “generative systems, artificial intelligence, and software for creativity and self-expression.” He has collaborated on various open-source software projects, working at the “intersection of code, art, and technology activism.”

Others include: a smell researcher and artist with a collection of over 7,000 scents, a designer and software designer pursuing machine learning and news automation, and dozens of other fascinating folks from all over the world.

Eyeo asks: “What data is, where it comes from, and how we utilize it, looks different than ever before. What can we do with it all? What can’t we do? Artists, designers and coders build and bend technology to see what’s possible. What’s next with interaction, what’s revealed by the data. Eyeo brings together the most intriguing and exciting people in these arenas today.” If you haven’t been, this is as good a year as any to go for the first time — it is a wonderful and unique experience. Get tickets here.

A new geographical study of the United States reveals the functional boundaries of megapolises around the country, defining them by usage rather than arbitrary political borders. Unlike gerrymandered districts or state lines, these sprawling areas are rooted in deep data analytics versus historical accident.

Historical geographer Garrett Dash Nelson teamed up with urban analyst Alasdair Rae to publish a paper using commuting information and computational algorithms. Studying over 4,000,000 commutes, they traced interconnections between economically connected points and reported the results in An Economic Geography of the United States: From Commutes to Megaregions.

Taking it a step further, the authors also devised names for various megaregions extrapolated from the data – while semi-subjective, they start to give a sense of the real shape of metropolitan zones (and reveal areas where few residents and vast distances make it hard to define or confine regions).

Some cities at the heart of various sub-regions are not surprising — San Francisco and Los Angeles were givens — but others may be new to some people, like Fresno, California. Many cities trace influence across state borders, like Minneapolis into Wisconsin or New York City into effectively every adjacent state. Some overlap while others are isolated, especially in the west.

In the end, this is not a definitive way to look at geography within the Lower 48, but it does start to push the observer to rethink conventional regions of influence and defined borders. From the abstract: “The emergence in the United States of large-scale ‘megaregions’ centered on major metropolitan areas is a phenomenon often taken for granted in both scholarly studies and popular accounts of contemporary economic geography. We compare a method which uses a visual heuristic for understanding areal aggregation to a method which uses a computational partitioning algorithm, and we reflect upon the strengths and limitations of both. We discuss how choices about input parameters and scale of analysis can lead to different results, and stress the importance of comparing computational results with ‘common sense’ interpretations of geographic coherence.”

Online reviews indicate how popular your favorite place is in general, but cannot tell you whether now is a good time to drop by or if you may be stuck in a crowd or waiting in line – this is where the Density Sensor comes into play.

No need to resort to complex spatial mapping or real-time video sensors with this gadget, a people-counting device that simply tracks passages through doors (attached to the frame). Some more obvious applications include specific bars, restaurants, coffee shops and other businesses that have time-of-day and day-of-week cycles to contend with, but the same data can also help you pick the DMV or grocery store with the shortest line.

In turn, businesses can choose what data to share with customers and what to keep for optimization purposes, offering discounts during less busy times or adjusting when to open and close. Compared to non-networked break-beam technology or real-time surveillance cameras, there is no need to wait for data or face privacy concerns.

Of course, up-to-the-minute incoming and outgoing traffic are just a starting point – architecture firms, for instance, could use extended datasets to anonymously track customer or employee flows through a building and use that data to optimize going forward, shaping extensions or remodels. Ultimately, one could imagine this system being replaced by more detailed heat-mapped trackers keeping tabs on entire spaces, but for now this is a cheap solution to a long-standing problem.

With downtown densification usually comes a lack of light in surrounding spaces, leading one architecture firm to develop the world’s first algorithm-driven strategy to allow a tower to fully shed its shadow. Architects of NBBJ developed this set of adjacent skyscrapers that work in tandem to eliminate shade year-round in the spaces between them, proposing the pair for a prominent site in central London. As the simulation of No Shadow Tower illustrates below, considerations are made for all times of day, reflecting the passage of the sun through the sky from dawn until dusk.

The model inputs are complex, using real sun-tracking data tied to a specific location (though easily changed) but also taking into account everything from basic physics and structural engineering to public spaces and programmatic functions for building users. At the same time, considerations must be made for diffusing any reflected light to avoid creating obnoxious glare or even lighting adjacent spaces, vehicles or objects on fire. Fortunately, it is easier than ever to 3D model as well as implement a complex building shape with custom 3D-printed parts, as architects like Frank Gehry have increasingly demonstrated in recent years.

This proposal was inspired by the rapid growth of skyscrapers in areas like London, where 250 are currently planned or in progress, and New York City, where residents are resisting tall buildings that would cast long shadows over Central Park. Large-scale sunlight reflection can be found in built environments already, such as a mountain town in Norway found frequently or for long periods in shade during cold and dark winter months. Conversely, structures in hot climates could also be shaped to deflect sun from occupied spaces during warm summer months – shade and shadows, sunlight and heat can all be shaped, in short, for different environmental needs and conditions.

In this case, of course, the reflector is itself a building, which of course then casts a shadow of its own – arguably a limitation of the scheme applied in other places (in this instance the second structure’s shadow would fall over water). However, a series of structures could conceivably cancel shadows in sequence, creating multi-block solutions if designed in a coordinated fashion, the shape of each informed by the needs of the previous one in the series. Moreover, this is not just about elimination but control – the ability to redirect sun and shade dynamically through design rather than letting it be a byproduct of accidental shapes. Whether or not this particular pair of structures makes it past the conceptual phase, the idea behind them is powerful and the attitude could be applied more readily by (heat- and) light-sensitive architects down the line.