Tag Archives: nature
#433785 DeepMind’s Eerie Reimagination of the ...
If a recent project using Google’s DeepMind were a recipe, you would take a pair of AI systems, images of animals, and a whole lot of computing power. Mix it all together, and you’d get a series of imagined animals dreamed up by one of the AIs. A look through the research paper about the project—or this open Google Folder of images it produced—will likely lead you to agree that the results are a mix of impressive and downright eerie.
But the eerie factor doesn’t mean the project shouldn’t be considered a success and a step forward for future uses of AI.
From GAN To BigGAN
The team behind the project consists of Andrew Brock, a PhD student at Edinburgh Center for Robotics, and DeepMind intern and researcher Jeff Donahue and Karen Simonyan.
They used a so-called Generative Adversarial Network (GAN) to generate the images. In a GAN, two AI systems collaborate in a game-like manner. One AI produces images of an object or creature. The human equivalent would be drawing pictures of, for example, a dog—without necessarily knowing what a dog exactly looks like. Those images are then shown to the second AI, which has already been fed images of dogs. The second AI then tells the first one how far off its efforts were. The first one uses this information to improve its images. The two go back and forth in an iterative process, and the goal is for the first AI to become so good at creating images of dogs that the second can’t tell the difference between its creations and actual pictures of dogs.
The team was able to draw on Google’s vast vaults of computational power to create images of a quality and life-like nature that were beyond almost anything seen before. In part, this was achieved by feeding the GAN with more images than is usually the case. According to IFLScience, the standard is to feed about 64 images per subject into the GAN. In this case, the research team fed about 2,000 images per subject into the system, leading to it being nicknamed BigGAN.
Their results showed that feeding the system with more images and using masses of raw computer power markedly increased the GAN’s precision and ability to create life-like renditions of the subjects it was trained to reproduce.
“The main thing these models need is not algorithmic improvements, but computational ones. […] When you increase model capacity and you increase the number of images you show at every step, you get this twofold combined effect,” Andrew Brock told Fast Company.
The Power Drain
The team used 512 of Google’s AI-focused Tensor Processing Units (TPU) to generate 512-pixel images. Each experiment took between 24 and 48 hours to run.
That kind of computing power needs a lot of electricity. As artist and Innovator-In-Residence at the Library of Congress Jer Thorp tongue-in-cheek put it on Twitter: “The good news is that AI can now give you a more believable image of a plate of spaghetti. The bad news is that it used roughly enough energy to power Cleveland for the afternoon.”
Thorp added that a back-of-the-envelope calculation showed that the computations to produce the images would require about 27,000 square feet of solar panels to have adequate power.
BigGAN’s images have been hailed by researchers, with Oriol Vinyals, research scientist at DeepMind, rhetorically asking if these were the ‘Best GAN samples yet?’
However, they are still not perfect. The number of legs on a given creature is one example of where the BigGAN seemed to struggle. The system was good at recognizing that something like a spider has a lot of legs, but seemed unable to settle on how many ‘a lot’ was supposed to be. The same applied to dogs, especially if the images were supposed to show said dogs in motion.
Those eerie images are contrasted by other renditions that show such lifelike qualities that a human mind has a hard time identifying them as fake. Spaniels with lolling tongues, ocean scenery, and butterflies were all rendered with what looks like perfection. The same goes for an image of a hamburger that was good enough to make me stop writing because I suddenly needed lunch.
The Future Use Cases
GAN networks were first introduced in 2014, and given their relative youth, researchers and companies are still busy trying out possible use cases.
One possible use is image correction—making pixillated images clearer. Not only does this help your future holiday snaps, but it could be applied in industries such as space exploration. A team from the University of Michigan and the Max Planck Institute have developed a method for GAN networks to create images from text descriptions. At Berkeley, a research group has used GAN to create an interface that lets users change the shape, size, and design of objects, including a handbag.
For anyone who has seen a film like Wag the Dog or read 1984, the possibilities are also starkly alarming. GANs could, in other words, make fake news look more real than ever before.
For now, it seems that while not all GANs require the computational and electrical power of the BigGAN, there is still some way to reach these potential use cases. However, if there’s one lesson from Moore’s Law and exponential technology, it is that today’s technical roadblock quickly becomes tomorrow’s minor issue as technology progresses.
Image Credit: Ondrej Prosicky/Shutterstock Continue reading
#433634 This Robotic Skin Makes Inanimate ...
In Goethe’s poem “The Sorcerer’s Apprentice,” made world-famous by its adaptation in Disney’s Fantasia, a lazy apprentice, left to fetch water, uses magic to bewitch a broom into performing his chores for him. Now, new research from Yale has opened up the possibility of being able to animate—and automate—household objects by fitting them with a robotic skin.
Yale’s Soft Robotics lab, the Faboratory, is led by Professor Rebecca Kramer-Bottiglio, and has long investigated the possibilities associated with new kinds of manufacturing. While the typical image of a robot is hard, cold steel and rigid movements, soft robotics aims to create something more flexible and versatile. After all, the human body is made up of soft, flexible surfaces, and the world is designed for us. Soft, deformable robots could change shape to adapt to different tasks.
When designing a robot, key components are the robot’s sensors, which allow it to perceive its environment, and its actuators, the electrical or pneumatic motors that allow the robot to move and interact with its environment.
Consider your hand, which has temperature and pressure sensors, but also muscles as actuators. The omni-skins, as the Science Robotics paper dubs them, combine sensors and actuators, embedding them into an elastic sheet. The robotic skins are moved by pneumatic actuators or memory alloy that can bounce back into shape. If this is then wrapped around a soft, deformable object, moving the skin with the actuators can allow the object to crawl along a surface.
The key to the design here is flexibility: rather than adding chips, sensors, and motors into every household object to turn them into individual automatons, the same skin can be used for many purposes. “We can take the skins and wrap them around one object to perform a task—locomotion, for example—and then take them off and put them on a different object to perform a different task, such as grasping and moving an object,” said Kramer-Bottiglio. “We can then take those same skins off that object and put them on a shirt to make an active wearable device.”
The task is then to dream up applications for the omni-skins. Initially, you might imagine demanding a stuffed toy to fetch the remote control for you, or animating a sponge to wipe down kitchen surfaces—but this is just the beginning. The scientists attached the skins to a soft tube and camera, creating a worm-like robot that could compress itself and crawl into small spaces for rescue missions. The same skins could then be worn by a person to sense their posture. One could easily imagine this being adapted into a soft exoskeleton for medical or industrial purposes: for example, helping with rehabilitation after an accident or injury.
The initial motivating factor for creating the robots was in an environment where space and weight are at a premium, and humans are forced to improvise with whatever’s at hand: outer space. Kramer-Bottoglio originally began the work after NASA called out for soft robotics systems for use by astronauts. Instead of wasting valuable rocket payload by sending up a heavy metal droid like ATLAS to fetch items or perform repairs, soft robotic skins with modular sensors could be adapted for a range of different uses spontaneously.
By reassembling components in the soft robotic skin, a crumpled ball of paper could provide the chassis for a robot that performs repairs on the spaceship, or explores the lunar surface. The dynamic compression provided by the robotic skin could be used for g-suits to protect astronauts when they rapidly accelerate or decelerate.
“One of the main things I considered was the importance of multi-functionality, especially for deep space exploration where the environment is unpredictable. The question is: How do you prepare for the unknown unknowns? … Given the design-on-the-fly nature of this approach, it’s unlikely that a robot created using robotic skins will perform any one task optimally,” Kramer-Bottiglio said. “However, the goal is not optimization, but rather diversity of applications.”
There are still problems to resolve. Many of the videos of the skins indicate that they can rely on an external power supply. Creating new, smaller batteries that can power wearable devices has been a focus of cutting-edge materials science research for some time. Much of the lab’s expertise is in creating flexible, stretchable electronics that can be deformed by the actuators without breaking the circuitry. In the future, the team hopes to work on streamlining the production process; if the components could be 3D printed, then the skins could be created when needed.
In addition, robotic hardware that’s capable of performing an impressive range of precise motions is quite an advanced technology. The software to control those robots, and enable them to perform a variety of tasks, is quite another challenge. With soft robots, it can become even more complex to design that control software, because the body itself can change shape and deform as the robot moves. The same set of programmed motions, then, can produce different results depending on the environment.
“Let’s say I have a soft robot with four legs that crawls along the ground, and I make it walk up a hard slope,” Dr. David Howard, who works on robotics at CSIRO in Australia, explained to ABC.
“If I make that slope out of gravel and I give it the same control commands, the actual body is going to deform in a different way, and I’m not necessarily going to know what that is.”
Despite these and other challenges, research like that at the Faboratory still hopes to redefine how we think of robots and robotics. Instead of a robot that imitates a human and manipulates objects, the objects themselves will become programmable matter, capable of moving autonomously and carrying out a range of tasks. Futurists speculate about a world where most objects are automated to some degree and can assemble and repair themselves, or are even built entirely of tiny robots.
The tale of the Sorcerer’s Apprentice was first written in 1797, at the dawn of the industrial revolution, over a century before the word “robot” was even coined. Yet more and more roboticists aim to prove Arthur C Clarke’s maxim: any sufficiently advanced technology is indistinguishable from magic.
Image Credit: Joran Booth, The Faboratory Continue reading
#433290 Inspired by Nature: Autonomous ...
Maryland Researchers Develop Robots With the Same Capabilities as Fish Continue reading
#432893 These 4 Tech Trends Are Driving Us ...
From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies.
Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference.
Today, the process of feeding humanity is extremely inefficient.
If we could radically reinvent what we eat, and how we create that food, what might you imagine that “future of food” would look like?
In this post we’ll cover:
Vertical farms
CRISPR engineered foods
The alt-protein revolution
Farmer 3.0
Let’s dive in.
Vertical Farming
Where we grow our food…
The average American meal travels over 1,500 miles from farm to table. Wine from France, beef from Texas, potatoes from Idaho.
Imagine instead growing all of your food in a 50-story tall vertical farm in downtown LA or off-shore on the Great Lakes where the travel distance is no longer 1,500 miles but 50 miles.
Delocalized farming will minimize travel costs at the same time that it maximizes freshness.
Perhaps more importantly, vertical farming also allows tomorrow’s farmer the ability to control the exact conditions of her plants year round.
Rather than allowing the vagaries of the weather and soil conditions to dictate crop quality and yield, we can now perfectly control the growing cycle.
LED lighting provides the crops with the maximum amount of light, at the perfect frequency, 24 hours a day, 7 days a week.
At the same time, sensors and robots provide the root system the exact pH and micronutrients required, while fine-tuning the temperature of the farm.
Such precision farming can generate yields that are 200% to 400% above normal.
Next let’s explore how we can precision-engineer the genetic properties of the plant itself.
CRISPR and Genetically Engineered Foods
What food do we grow?
A fundamental shift is occurring in our relationship with agriculture. We are going from evolution by natural selection (Darwinism) to evolution by human direction.
CRISPR (the cutting edge gene editing tool) is providing a pathway for plant breeding that is more predictable, faster and less expensive than traditional breeding methods.
Rather than our crops being subject to nature’s random, environmental whim, CRISPR unlocks our capability to modify our crops to match the available environment.
Further, using CRISPR we will be able to optimize the nutrient density of our crops, enhancing their value and volume.
CRISPR may also hold the key to eliminating common allergens from crops. As we identify the allergen gene in peanuts, for instance, we can use CRISPR to silence that gene, making the crops we raise safer for and more accessible to a rapidly growing population.
Yet another application is our ability to make plants resistant to infection or more resistant to drought or cold.
Helping to accelerate the impact of CRISPR, the USDA recently announced that genetically engineered crops will not be regulated—providing an opening for entrepreneurs to capitalize on the opportunities for optimization CRISPR enables.
CRISPR applications in agriculture are an opportunity to help a billion people and become a billionaire in the process.
Protecting crops against volatile environments, combating crop diseases and increasing nutrient values, CRISPR is a promising tool to help feed the world’s rising population.
The Alt-Protein/Lab-Grown Meat Revolution
Something like a third of the Earth’s arable land is used for raising livestock—a massive amount of land—and global demand for meat is predicted to double in the coming decade.
Today, we must grow an entire cow—all bones, skin, and internals included—to produce a steak.
Imagine if we could instead start with a single muscle stem cell and only grow the steak, without needing the rest of the cow? Think of it as cellular agriculture.
Imagine returning millions, perhaps billions, of acres of grazing land back to the wilderness? This is the promise of lab-grown meats.
Lab-grown meat can also be engineered (using technology like CRISPR) to be packed with nutrients and be the healthiest, most delicious protein possible.
We’re watching this technology develop in real time. Several startups across the globe are already working to bring artificial meats to the food industry.
JUST, Inc. (previously Hampton Creek) run by my friend Josh Tetrick, has been on a mission to build a food system where everyone can get and afford delicious, nutritious food. They started by exploring 300,000+ species of plants all around the world to see how they can make food better and now are investing heavily in stem-cell-grown meats.
Backed by Richard Branson and Bill Gates, Memphis Meats is working on ways to produce real meat from animal cells, rather than whole animals. So far, they have produced beef, chicken, and duck using cultured cells from living animals.
As with vertical farming, transitioning production of our majority protein source to a carefully cultivated environment allows for agriculture to optimize inputs (water, soil, energy, land footprint), nutrients and, importantly, taste.
Farmer 3.0
Vertical farming and cellular agriculture are reinventing how we think about our food supply chain and what food we produce.
The next question to answer is who will be producing the food?
Let’s look back at how farming evolved through history.
Farmers 0.0 (Neolithic Revolution, around 9000 BCE): The hunter-gatherer to agriculture transition gains momentum, and humans cultivated the ability to domesticate plants for food production.
Farmers 1.0 (until around the 19th century): Farmers spent all day in the field performing backbreaking labor, and agriculture accounted for most jobs.
Farmers 2.0 (mid-20th century, Green Revolution): From the invention of the first farm tractor in 1812 through today, transformative mechanical biochemical technologies (fertilizer) boosted yields and made the job of farming easier, driving the US farm job rate down to less than two percent today.
Farmers 3.0: In the near future, farmers will leverage exponential technologies (e.g., AI, networks, sensors, robotics, drones), CRISPR and genetic engineering, and new business models to solve the world’s greatest food challenges and efficiently feed the eight-billion-plus people on Earth.
An important driver of the Farmer 3.0 evolution is the delocalization of agriculture driven by vertical and urban farms. Vertical farms and urban agriculture are empowering a new breed of agriculture entrepreneurs.
Let’s take a look at an innovative incubator in Brooklyn, New York called Square Roots.
Ten farm-in-a-shipping-containers in a Brooklyn parking lot represent the first Square Roots campus. Each 8-foot x 8.5-foot x 20-foot shipping container contains an equivalent of 2 acres of produce and can yield more than 50 pounds of produce each week.
For 13 months, one cohort of next-generation food entrepreneurs takes part in a curriculum with foundations in farming, business, community and leadership.
The urban farming incubator raised a $5.4 million seed funding round in August 2017.
Training a new breed of entrepreneurs to apply exponential technology to growing food is essential to the future of farming.
One of our massive transformative purposes at the Abundance Group is to empower entrepreneurs to generate extraordinary wealth while creating a world of abundance. Vertical farms and cellular agriculture are key elements enabling the next generation of food and agriculture entrepreneurs.
Conclusion
Technology is driving food abundance.
We’re already seeing food become demonetized, as the graph below shows.
From 1960 to 2014, the percent of income spent on food in the U.S. fell from 19 percent to under 10 percent of total disposable income—a dramatic decrease over the 40 percent of household income spent on food in 1900.
The dropping percent of per-capita disposable income spent on food. Source: USDA, Economic Research Service, Food Expenditure Series
Ultimately, technology has enabled a massive variety of food at a significantly reduced cost and with fewer resources used for production.
We’re increasingly going to optimize and fortify the food supply chain to achieve more reliable, predictable, and nutritious ways to obtain basic sustenance.
And that means a world with abundant, nutritious, and inexpensive food for every man, woman, and child.
What an extraordinary time to be alive.
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