Amazing real-time character control animation generated by neural net

Amazing real-time character control animation generated by neural net

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Modern day video games have come a long way from Mario the plumber hopping across the screen. Incredibly intricate environments of games today are part of the lure for new gamers and this experience is brought to life by the characters interacting with the scene. However the illusion of the virtual world is disrupted by unnatural movements of the figures in performing actions such as turning around suddenly or climbing a hill.

To remedy the abrupt movements, [Daniel Holden et. al] recently published a paper (PDF) and a video showing a method to greatly improve the real-time character control mechanism. The proposed system uses a neural network that has been trained using a large data set of walking, jumping and other sequences on various terrains. The key is breaking down the process of bipedal movement and its cyclic behaviour into a series of sub-steps or phases. Each phase translates to a natural posture for the character while moving. The system precomputes the next-phases offline to conserve computational resources at runtime. Then considering user control, previous pose of the character(including joint positions) and terrain geometry, the consequent frame of the animation is computed. The computation is done by a regression network that calculates future position of the joints and a blending function is used for Motion Matching as described in a presentation (PDF) and video by [Simon Clavet].

Point Break Live!

Point Break Live!

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This is crazy. These guys tour around the US and live re-enact the classic 80’s Keanu Reeves’ movie “Point Break”. But even better, they come with no lead actor. They grab a few willing fans out of the audience who quickly do 3 different audition quotes, the audience votes for the best one, and that person becomes agent Johnny Utah for the next hour and a half.

It’s a pretty hilarious time – totally recommend it.

Model wooden roller coaster

Model wooden roller coaster

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Model maker Adam Throgmorton shows off an incredible build – a fully functioning, massively intricate HO-scale replica of an old-school wooden rollercoaster. He reports he worked on it over the course of 6 years.

I’m also going to bet he’s not married since it seems to have its own table in the house. 🙂

Saltscapes

Saltscapes

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Australian photographer Murray Fredericks journeys to the center of Lake Eyre, a desert salt lake. Fredericks drags all of his equipment out into the barren landscape, capturing the dramatic sky reflected in both the inch-deep water and his rectangular mirror. The images are breathtaking color-based works.

The failure of Coin and why gadget ventures often fail

The failure of Coin and why gadget ventures often fail

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Ben Einstein does an excellent analysis of the failure of many smart gadget companies.

His analysis breaks down like this:

First generation products are always plagued with bugs, fail whales, and even the occasional mass-recall – most companies can bounce back from these setbacks. But other companies do not. It boils down to risk.

Technical Risk and Product Risk

When it comes to hardware startups, there are two types of risk. They are manageable on their own, but together often spell failure. These risks are: technical risk and product risk.

Technical risk is the chance you can’t deliver a product due to an engineering or manufacturing constraint. Examples from Coin: getting an e-Ink screen, Bluetooth antenna, battery, and microprocessor all working in a 0.76mm thick PVC card.

Product risk, however, is the risk that many overlook. Most products have low product risk. They routinely fail in small ways, but those failures are viewed as mere annoyances. A pop top that breaks off once every 1000 cans of Coke, the Roomba that occasionally misses a spot, an Alexa that mistranslates your command and you try again. Not big deals. But an automated door lock that fails might leave one stranded outside at 2am in a bad part of town or opens the door to robbers, a website that exposes your address and bank accounts for emptying, or your sole payment method that fails you at a fancy dinner are another matter.

You likely have high product risk if any of these are true:

  1. If a small number (one or two) of failures over the lifetime of your product create a negative interaction (like door locks or sole payment methods).
  2. If users would pay significantly more for a product that is guaranteed to work 100% of the time (like wireless routers).
  3. If users rely on your product for critical business operations (like point-of-sale systems).
  4. If failure could wreak massive havoc on personal security or safety (like home security systems or cars).

The Goal:

Your goal then is to only have high risk in one of the two risk classifications. Very few companies that have both kinds of risk survive. Tesla and SpaceX are notable exceptions, which should give you an idea of the efforts you will need to go to in order to overcome these risks. The other method is to reduce your feature set to minimize technical complexity or lower user expectations in case of product failure.

Long haul overnight pilot from Europe to South America sets up 10+ hour time lapse…

Long haul overnight pilot from Europe to South America sets up 10+ hour time lapse…

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Sales Wick is a long haul pilot and photographer. He was piloting a massive 10+ hour overnight flight from Switzerland to Rio de Janeiro. The route takes them across the Sahara and the Atlantic Ocean. While most people will be settling in for a night of sleep, he sets up his camera and captures this transcendent video. I won’t do it justice, so just read his words:

“(We go) …past the bright city light of the capital of Algeria towards the Sahara. Tonight will be a special night, since its one of the few nights every August where countless shooting stars will be seen all over the night sky. Deriving from the constellation of Perseus, these meteor showers will guide us through the night.

 Just as the bright city lights are vanishing behind us, the Milky way starts to become clearly visible up ahead. It’s now pacing us, at almost the speed of sound, along the invisible highway and the pitch-black night sky above this surreal landscape. Ahead of us are another eight hours flight time, but we already stopped counting the shooting stars. And we got already to a few hundred.”

If you ever doubt there is beauty in the world – watch this.