Fractals can help AI learn to see more clearly—or at least more fairly
The trouble is, assembling a data set like ImageNet by hand takes a lot of time and effort. The images are typically labeled by low-paid crowdworkers. Data sets might also contain sexist or racist labels that can bias a model in hidden ways, as well as images of people who have been included without their consent. There’s evidence these biases can creep in even in pretraining.
However, fractal patterns can be found in everything from trees and flowers to clouds and waves. This made the team at Japan’s National Institute of Advanced Industrial Science and Technology (AIST), the Tokyo Institute of Technology, and Tokyo Denki University wonder if these patterns could be used to teach an automated system the basics of image recognition, instead of using photos of real objects.
The researchers created FractalDB, an endless number of computer-generated fractals. Some look like leaves; others look like snowflakes or snail shells. Each group of similar patterns was automatically given a label. They then used FractalDB to pretrain a convolutional neural network, a type of deep-learning model commonly used in image-recognition systems, before completing its training with a set of actual images. They found that it performed almost as well as models trained on state-of-the-art data sets, including ImageNet and Places, which contains 2.5 million images of outdoor scenes.
Does it work? Anh Nguyen at Auburn University in Alabama, who wasn’t involved in the study, isn’t convinced that FractalDB is a match for the likes of ImageNet. He has studied how abstract patterns can confuse image recognition systems. “There is a connection between this work and examples that fool machines,” he says. He would like to explore how this new approach works in more detail. But the Japanese researchers think that with tweaks to their approach, computer-generated data sets like FractalDB could replace existing ones.
Why fractals: The researchers also tried training their AI using other abstract images, including ones produced using Perlin noise, which creates speckled patterns, and Bezier curves, a type of curve used in computer graphics. But fractals gave the best results. “Fractal geometry exists in the background knowledge of the world,” says lead author Hirokatsu Kataoka at AIST.
The Download: sleeping in VR, and promising clean energy projects
People are gathering in virtual spaces to relax, and even sleep, with their headsets on. VR sleep rooms are becoming popular among people who suffer from insomnia or loneliness, offering cozy enclaves where strangers can safely find relaxation and company—most of the time.
Each VR sleep room is created to induce calm. Some imitate beaches and campsites with bonfires, while others re-create hotel rooms or cabins. Soundtracks vary from relaxing beats to nature sounds to absolute silence, while lighting can range from neon disco balls to pitch-black darkness.
The opportunity to sleep in groups can be particularly appealing to isolated or lonely people who want to feel less alone, and safe enough to fall asleep. The trouble is, what if the experience doesn’t make you feel that way? Read the full story.
Inside the conference where researchers are solving the clean-energy puzzle
There are plenty of tried-and-true solutions that can begin to address climate change right now: wind and solar power are being deployed at massive scales, electric vehicles are coming to the mainstream, and new technologies are helping companies make even fossil-fuel production less polluting.
But as we knock out the easy climate wins, we’ll also need to get creative to tackle harder-to-solve sectors and reach net-zero emissions.
Inside the conference where researchers are solving the clean-energy puzzle
The Advanced Research Projects Agency for Energy (ARPA-E) funds high-risk, high-reward energy research projects, and each year the agency hosts a summit where funding recipients and other researchers and companies in energy can gather to talk about what’s new in the field.
As I listened to presentations, met with researchers, and—especially—wandered around the showcase, I often had a vague feeling of whiplash. Standing at one booth trying to wrap my head around how we might measure carbon stored by plants, I would look over and see another group focused on making nuclear fusion a more practical way to power the world.
There are plenty of tried-and-true solutions that can begin to address climate change right now: wind and solar power are being deployed at massive scales, electric vehicles are coming to the mainstream, and new technologies are helping companies make even fossil-fuel production less polluting. But as we knock out the easy wins, we’ll also need to get creative to tackle harder-to-solve sectors and reach net-zero emissions. Here are a few intriguing projects from the ARPA-E showcase that caught my eye.
“I heard you have rocks here!” I exclaimed as I approached the Quaise Energy station.
Quaise’s booth featured a screen flashing through some fast facts and demonstration videos. And sure enough, laid out on the table were two slabs of rock. They looked a bit worse for wear, each sporting a hole about the size of a quarter in the middle, singed around the edges.
These rocks earned their scorch marks in service of a big goal: making geothermal power possible anywhere. Today, the high temperatures needed to generate electricity using heat from the Earth are only accessible close to the surface in certain places on the planet, like Iceland or the western US.
Geothermal power could in theory be deployed anywhere, if we could drill deep enough. Getting there won’t be easy, though, and could require drilling 20 kilometers (12 miles) beneath the surface. That’s deeper than any oil and gas drilling done today.
Rather than grinding through layers of granite with conventional drilling technology, Quaise plans to get through the more obstinate parts of the Earth’s crust by using high-powered millimeter waves to vaporize rock. (It’s sort of like lasers, but not quite.)
The emergent industrial metaverse
Annika Hauptvogel, head of technology and innovation management at Siemens, describes the industrial metaverse as “immersive, making users feel as if they’re in a real environment; collaborative in real time; open enough for different applications to seamlessly interact; and trusted by the individuals and businesses that participate”—far more than simply a digital world.
The industrial metaverse will revolutionize the way work is done, but it will also unlock significant new value for business and societies. By allowing businesses to model, prototype, and test dozens, hundreds, or millions of design iterations in real time and in an immersive, physics-based environment before committing physical and human resources to a project, industrial metaverse tools will usher in a new era of solving real-world problems digitally.
“The real world is very messy, noisy, and sometimes hard to really understand,” says Danny Lange, senior vice president of artificial intelligence at Unity Technologies, a leading platform for creating and growing real-time 3-D content. “The idea of the industrial metaverse is to create a cleaner connection between the real world and the virtual world, because the virtual world is so much easier and cheaper to work with.”
While real-life applications of the consumer metaverse are still developing, industrial metaverse use cases are purpose-driven, well aligned with real-world problems and business imperatives. The resource efficiencies enabled by industrial metaverse solutions may increase business competitiveness while also continually driving progress toward the sustainability, resilience, decarbonization, and dematerialization goals that are essential to human flourishing.
This report explores what it will take to create the industrial metaverse, its potential impacts on business and society, the challenges ahead, and innovative use cases that will shape the future. Its key findings are as follows:
• The industrial metaverse will bring together the digital and real worlds. It will enable a constant exchange of information, data, and decisions and empower industries to solve extraordinarily complex real-world problems digitally, changing how organizations operate and unlocking significant societal benefits.
• The digital twin is a core metaverse building block. These virtual models simulate real-world objects in detail. The next generation of digital twins will be photorealistic, physics-based, AI-enabled, and linked in metaverse ecosystems.
• The industrial metaverse will transform every industry. Currently existing digital twins illustrate the power and potential of the industrial metaverse to revolutionize design and engineering, testing, operations, and training.