Local firm Arc sees potential in 3D-printing tech

As the white, cube-shaped machine begins to whir at the front of the room, a metal arm can be seen jerking back and forth through the box’s transparent front-facing panel. The robotic mechanism whirs as it works, and onlookers watch as the 3D printer creates a small figurine of a dinosaur out of melted plastic.

“I want to know how to design and print something like this,” said one student, hoisting a different 3D-printed figure of a skeleton mask in the air.

At the first class offered by 3D-printing company Arc Hub Pnh in Phnom Penh on Tuesday, five students learned the basics of the technology and how to incorporate it into their own businesses.

Arch Hub founder KiHow Tran, who is also the director of operations at the co-working space Trybe which hosted the class, began the presentation by giving a brief overview of the software and mechanics involved in the 3D-printing process.

Arc Hub began operating in the Kingdom in 2013, originally setting up shop at a local university with the intention of catering to local businesses that required printed materials.

It soon became clear that 3D printing was not as prolific in Cambodia as Tran had originally hoped, however, and the business soon turned most of its efforts toward teaching young entrepreneurs and tech enthusiasts about the applications of 3D printing.

One of the students at Tuesday’s class, Chanpiseth Ly, said that he decided to attend because he was interested in using the technology to help him at his marketing job – although he admitted he wasn’t sure exactly how it could be used yet.

After the class, Ly said he would come back to talk more with Tran about how to best utilise the machine.

For others, like Lyhor Mom, there was a more obvious application. Mom’s sister is launching a new jewellery business, and he said the printer could help speed up the process of making models for new creations.

“For jewellery, we can sometimes use the 3D wax to [model] rings,” he said. “It would be good to learn how to use these machines to do that.”

Tran noted that 3D printing was often used in jewellery making, and could help speed the process of making wax models.

“3D printing is used a huge amount for jewellery making,” he said. “A jeweller used to have to chip away at these wax designs for over a week – but if you 3D print it, it takes just a few hours.”

Arc Hub Pnh’s 3D printer has already helped at least two startups create products in Cambodia so far.

Em Chanrithykol, the founder of Doy Doy, a toy company that uses 3D printing to create connectors to help make plastic straw models, attributed his success to a class taken at Trybe last year.

The firm also helped teach 3D-printing techniques to four young entrepreneurs who began 3D printing their award-winning rat traps following their victory in the Southeast Asia Makerthon in late 2016.

For Tran, the technology represents a chance to revolutionise a variety of businesses and sectors.

“Today, people are 3D-printing houses, 3D-printing gadgets and even trying to 3D-print jewellery straight onto people’s wrists,” he said. “We’ll all be dead by the time they make that happen, but it’s still cool.”

Google AI sees 3D printed turtle as a rifle, MIT researchers explain why

Nov 2, 2017 | By Benedict

Researchers at MIT have carried out an investigation into “adversarial examples,” objects that can fool AI vision into thinking an object is something completely different. The researchers made a 3D printed turtle that fooled Google’s Inception-v3 into thinking it was a gun, even from multiple angles.

Take a look at the 3D printed turtle above, and you’ll be hard pressed to find anything particularly threatening about it. Perhaps the 3D printing filament used to make it was slightly toxic, but ultimately, it’s just a plastic turtle.

That’s not how Google’s Inception-v3 AI image classifier sees it though. Through the eyes of the artificial intelligence system, that innocent-looking 3D printed sea creature looks just like a rifle.

The 3D printed prop is what is known as an adversarial example—something designed to trick an artificial intelligence system into thinking it’s something else entirely. In this instance, MIT researchers engineered the plastic turtle to make Google’s AI see it as a dangerous weapon.

It’s obviously quite funny on some level: who knows how many millions of dollars are being pumped into image classification systems, yet some still think a plastic toy is a rifle. It’s the same impressive yet amusing quality that made those nightmarish Google DeepDream pictures so mesmerizing.

But adversarial objects—or adversarial images in the 2D world—are actually highly significant, and potentially very troublesome.

AI neural network systems like Google’s Inception-v3 are, of course, incredibly smart. But they work on complex, human-made algorithms, not common sense. And if you’re familiar with the precise rules and logic behind an AI system, you can potentially exploit it.

Because Google’s Inception-v3 is open source, the MIT researchers—Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok, who are together known as “labsix”—were in the perfect position to exploit it, by looking at the exact criteria for “rifle” recognition and trying to somehow squeeze those characteristics into something not very rifle-like at all: a turtle.

The MIT researchers aren’t the first to create adversarial objects, of course. People can use certain tricks to fool facial recognition systems into misidentifying a person—something that border security services, for example, are currently trying to curtail.

For most adversarial objects or images, however, the “trick” only works from certain angles. You might fool a neural network into thinking a bag of chips is a face from a certain angle, but move it around slightly and the AI will likely correct its mistake.

But the 3D printed turtle, as well as the MIT researchers’ other 3D examples, are different. They actually fool the Google AI from multiple angles, rather than just one, making them far more devastating than your typical adversarial object.

In addition to the turtle that seems like a rifle, labsix also 3D printed a baseball that gets recognized as espresso. They also made digital models of a barrel that gets interpreted as a guillotine, a baseball that can appear like a green lizard, a dog that the AI thinks is a bittern, and several other examples.

The researchers were able to easily make more examples of these objects after creating an algorithm for “reliably producing physical 3D objects that are adversarial from every viewpoint,” working at almost 100 per cent accuracy. They call this algorithm “Expectation Over Transformation” (EOT).

In a sense, the team is pleased with its achievements, but it’s also worried by how easily it managed to pull it off.

“[EOT] shouldn’t be able to take an image, slightly tweak the pixels, and completely confuse the network,” Athalye told Quartz. “Neural networks blow all previous techniques out of the water in terms of performance, but given the existence of these adversarial examples, it shows we really don’t understand what’s going on.”

Of course, this isn’t just a bit of fun for the MIT researchers. They believe that their research proves beyond doubt that “adversarial examples are a practical concern for real-world systems.”

If, say, hackers were able to ascertain the complex algorithms behind a non-open AI system—the “eyes” of a self-driving car, for example—they might be able to cause real damage by manipulating real-world objects into making the car behave in erroneous ways.

This might all seem like a remote possibility—after all, Google’s open Inception-v3 isn’t used for any critical applications—but the MIT research certainly makes a strong point about the fallibility of visual AI systems.

The team even plans to look further into creating adversarial objects that challenge AI systems whose mechanics are hidden.

The MIT group’s research paper, “Synthesizing Robust Adversarial Examples,” will be presented at ICLR 2018, the sixth International Conference on Learning Representations. It can be read here.

Posted in 3D Printing Application

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