Day: April 24, 2019

3D Printering: The Quest For Printable Food

April 24, 2019 by 44 Comments

A video has been making the rounds on social media recently that shows a 3D printed “steak” developed by a company called NovaMeat. In the short clip, a machine can be seen extruding a paste made of ingredients such as peas and seaweed into a shape not entirely unlike that of a boot sole, which gets briefly fried in a pan. Slices of this futuristic foodstuff are then fed to passerby in an effort to prove it’s actually edible. Nobody spits it out while the cameras are rolling, but the look on their faces could perhaps best be interpreted as resigned politeness. Yes, you can eat it. But you could eat a real boot sole too if you cooked it long enough.

To be fair, the goals of NovaMeat are certainly noble. Founder and CEO Giuseppe Scionti says that we need to develop new sustainable food sources to combat the environmental cost of our current livestock system, and he believes meat alternatives like his 3D printed steak could be the answer. Indeed, finding ways to reduce the consumption of meat would be a net positive for the environment, but it seems his team has a long way to go before the average meat-eater would be tempted by the objects extruded from his machine.

But the NovaMeat team aren’t the first to attempt coaxing food out of a modified 3D printer, not by a long shot. They’re simply the most recent addition to a surprisingly long list of individuals and entities, not least of which the United States military, that have looked into the concept. Ultimately, they’ve been after the same thing that convinced many hackers and makers to buy their own desktop 3D printer: the ability to produce something to the maker’s exacting specifications. A machine that could produce food with the precise flavors and textures specified would in essence be the ultimate chef, but of course, it’s far easier said than done.

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Stealing DNA By Phone

April 24, 2019 by 8 Comments

Data exfiltration via side channel attacks can be a fascinating topic. It is easy to forget that there are so many different ways that electronic devices affect the physical world other than their intended purpose. And creative security researchers like to play around with these side-effects for ‘fun and profit’.

Engineers at the University of California have devised a way to analyse exactly what a DNA synthesizer is doing by recording the sound that the machine makes with a relatively low-budget microphone, such as the one on a smart phone. The recorded sound is then processed using algorithms trained to discern the different noises that a particular machine makes and translates the audio into the combination of DNA building blocks the synthesizer is generating.

Although they focused on a particular brand of DNA Synthesizers, in which the acoustics allowed them to spy on the building process, others might be vulnerable also.

In the case of the DNA synthesizer, acoustics revealed everything. Noises made by the machine differed depending on which DNA building block—the nucleotides Adenine (A), Guanine (G), Cytosine (C), or Thymine (T)—it was synthesizing. That made it easy for algorithms trained on that machine’s sound signatures to identify which nucleotides were being printed and in what order.

Acoustic snooping is not something new, several interesting techniques have been shown in the past that raise, arguably, more serious security concerns. Back in 2004, a neural network was used to analyse the sound produced by computer keyboards and keypads used on telephones and automated teller machines (ATMs) to recognize the keys being pressed.

You don’t have to rush and sound proof your DIY DNA Synthesizer room just yet as there are probably more practical ways to steal the genome of your alien-cat hybrid, but for multi-million dollar biotech companies with a equally well funded adversaries and a healthy paranoia about industrial espionage, this is an ear-opener.

We written about other data exfiltration methods and side channels and this one, realistic scenario or not, it’s another cool audio snooping proof of concept.

Self-aware Robotic Arm

April 24, 2019 by 16 Comments

If you ever tried to program a robotic arm or almost any robotic mechanism that has more than 3 degrees of freedom, you know that a big part of the programming goes to the programming of the movements themselves. What if you built a robot, regardless of how you connect the motors and joints and, with no knowledge of itself, the robot becomes aware of the way it is physically built?

That is what Columbia Engineering researchers have made by creating a robot arm that learns how it is connected, with zero prior knowledge of physics, geometry, or motor dynamics. At first, the robot has no idea what its shape is, how its motors work and how they affect its movement. After one day of trying out its own outputs in a pretty much random fashion and getting feedback of its actions, the robot creates an accurate internal self-simulation of itself using deep-learning techniques.

The robotic arm used in this study by Lipson and his PhD student Robert Kwiatkowski is a four-degree-of-freedom articulated robotic arm. The first self-models were inaccurate as the robot did not know how its joints were connected. After about 35 hours of training, the self-model became consistent with the physical robot to within four centimeters. The self-model then performed a pick-and-place task that enabled the robot to recalibrate its original position between each step along the trajectory based entirely on the internal self-model.

To test whether the self-model could detect damage to itself, the researchers 3D-printed a deformed part to simulate damage and the robot was able to detect the change and re-train its self-model. The new self-model enabled the robot to resume its pick-and-place tasks with little loss of performance.

Since the internal representation is not static, not only this helps the robot to improve its performance over time but also allows it to adapt to damage and changes in its own structure. This could help robots to continue to function more reliably when there its part start to wear off or, for example, when replacement parts are not exactly the same format or shape.

Of course, it will be long before this arm can get a precision anywhere near Dexter, the 2018 Hackaday Prize winner, but it is still pretty cool to see the video of this research: