Intel Starts R&D Effort in Probabilistic Computing for AI

Seeks ways to help self-driving cars and autonomous robots deal with the uncertainty of the real world Photo: iStockphoto Intel announced today that it is forming a strategic research alliance to take artificial intelligence to the next level. Autonomous systems don’t have good enough ways to respond to the uncertainties of the real world, and they don’t have a good enough way to understand how the uncertainties of their sensors should factor into the decisions they need to make. According to Intel CTO Mike Mayberry the answer is “probabilistic computing”, which he says could be AI’s next wave. IEEE Spectrum: What motivated this new research thrust? Mike Mayberry: We’re trying to figure out what the next wave of AI is. The original wave of AI is based on logic and it’s based on writing down rules; it’s closest to what you’d call classical reasoning. The current wave of AI is Continue reading Intel Starts R&D Effort in Probabilistic Computing for AI

Computers Match Accuracy of Radiologists in Screening for Breast Cancer Risk

Commercial software performs as well as doctors in measuring breast density and assessing breast cancer risk Photo: iStockphoto Women with dense breasts have a greater risk of undergoing mammogram screenings that miss signs of breast cancer. That’s why 30 U.S. states legally require that women receive some notification about their breast density. A new study suggests that commercial software for automatically classifying breast density can perform on par with human radiologists: a finding that could encourage wider use of automated breast density assessments. Increased breast density represents “one of the strongest risk factors for breast cancer,” because it makes it more difficult to detect the disease in its early stages, explained Karla Kerlikowske, a physician and breast cancer researcher at the University of California, San Francisco. Dense breast tissue may also carry a higher risk of developing breast cancer. Breast density refers to the proportion of “nondense” fatty tissue to other “dense” tissue, containing milk ducts and Continue reading Computers Match Accuracy of Radiologists in Screening for Breast Cancer Risk

“Dog Cam” Trains Computer Vision Software for Robot Dogs

Strapping some gear to an Alaskan Malamute produces data that can train deep learning algorithms to navigate the world like a dog Image: DECADE A dog’s purpose can take on new meaning when humans strap a GoPro camera to her head. Such “dog cam” video clips have helped train computer vision software that could someday give rise to robotic canine companions. The idea behind DECADE, described as “a dataset of ego-centric videos from a dog’s perspective,” is to directly model the behavior of intelligent beings based on how they see and move around within the real world. Vision and movement data from a single dog—an Alaskan Malamute named Kelp M. Redmon—proved capable of training off-the-shelf deep learning algorithms to predict how dogs might react to different situations, such as seeing the owner holding a bag of treats or throwing a ball. “The near-term application would be to model the behavior of the dog and try to make Continue reading “Dog Cam” Trains Computer Vision Software for Robot Dogs

How Not to Order Water from a Robot Waiter

When we ask robots to do things, should they do what we say, or what we mean? Image: IEEE Spectrum; Robot: TurtleBot; Glass: Jan/FlickrResearchers used a mobile robot similar to the one above as a waiter in a pretend restaurant where users had to place their orders by talking to the robot. Some entertaining conversations ensued. AI systems have gotten pretty good, by this point, at understanding us when we talk to it. That is, they’ve gotten pretty good at understanding what the words that we say mean. Unfortunately for AI, it’s often the case in conversations between humans that we say things that we don’t expect the other person to take literally, instead relying on them to infer our intentions, which may be significantly different than what the exact words that we use would suggest. For example, take the question, “Do you know what time it is?” Most of Continue reading How Not to Order Water from a Robot Waiter

AI Detects Papaya Ripeness

A machine learning algorithm for detecting ripeness levels in papaya fruit could help both shoppers and producers Photo: iStock Photo If you’re in the market to buy fresh papayas, it can be a challenge to figure out ripeness based on peel color without also squeezing the fruit to test for softness. A Brazilian research group could make life easier for both shoppers and producers in the near future with a computer vision algorithm that estimates ripeness based on images alone.  Last year, the United States alone imported more than US $107 million worth of fresh papayas as the world’s largest papaya import market. The computer vision software could enable papaya growers to maximize the value of their fruit by sending the ripest papayas to local markets and saving less ripe papayas for export, says Douglas Fernandes Barbin, a researcher in the department of food engineering at the University of Campinas in Continue reading AI Detects Papaya Ripeness

SXSW 2018: The Future of AI Assistants

Alexa, Google Home, Siri, and Cortana will learn to adjust to your changing life Photo: Stephen Barnes/Technology/Alamy In the years to come, what will be the biggest improvement in AI-powered digital assistants? It’s likely to be the ability to accommodate a fundamental aspect of being human: The fact that we all have different personas, we show different facets of ourselves depending on where we are and who we are with, and our personas change over time. And different personas want different things from their AI assistants. Assistants that can understand your personal circumstances are less likely to remind you to pick up your rash prescription as you drive by the pharmacy if there are other people in the car, bug you about work email at home, or keep suggesting fun nightclubs if you’ve just had a baby. That was the message from Sunday’s panel on “Designing the Next Wave of Natural Continue reading SXSW 2018: The Future of AI Assistants

Hacking the Brain With Adversarial Images

Researchers from Google Brain show that adversarial images can trick both humans and computers, and the implications are scary Image: Google Brain In the image above, there’s a picture of a cat on the left. On the right, can you tell whether it’s a picture of the same cat, or a picture of a similar looking dog? The difference between the two pictures is that the one on the right has been tweaked a bit by an algorithm to make it difficult for a type of computer model called a convolutional neural network (CNN) to be able to tell what it really is. In this case, the CNN think it’s looking at a dog rather than a cat, but what’s remarkable is that most people think the same thing. This is an example of what’s called an adversarial image: an image specifically designed to fool neural networks into making an Continue reading Hacking the Brain With Adversarial Images

AI Beats Dermatologists in Diagnosing Nail Fungus

Deep learning algorithms beat 42 dermatology experts at diagnosing nail fungus infections Photo: iStockphoto It’s still relatively rare for artificial intelligence to deliver a crushing victory over human physicians in a head-to-head test of medical expertise. But a deep neural network approach managed to beat 42 dermatology experts in diagnosing a common nail fungus that affects about 35 million Americans each year. The latest successful demonstration of AI’s capabilities in the medical field relied heavily upon a team of South Korean researchers putting together a huge dataset of almost 50,000 images of toenails and fingernails. That large amount of data used to train the deep neural networks on recognizing cases of onychomycosis—a common fungal infection that can make nails discolored and brittle—provided the crucial edge that enabled deep learning to outperform medical experts. “This study was the first to show that AI has overwhelmed the specialists,” says Seung Seog Han, a dermatologist and clinician at I Continue reading AI Beats Dermatologists in Diagnosing Nail Fungus

OpenAI Releases Algorithm That Helps Robots Learn from Hindsight

It’s not a failure if you just pretend that you meant to do it all along Image: OpenAI Being able to learn from mistakes is a powerful ability that humans (being mistake-prone) take advantage of all the time. Even if we screw something up that we’re trying to do, we probably got parts of it at least a little bit correct, and we can build off of the things that we did not to do better next time. Eventually, we succeed. Robots can use similar trial-and-error techniques to learn new tasks. With reinforcement learning, a robot tries different ways of doing a thing, and gets rewarded whenever an attempt helps it to get closer to the goal. Based on the reinforcement provided by that reward, the robot tries more of those same sorts of things until it succeeds. Where humans differ is in how we’re able to learn from our failures as Continue reading OpenAI Releases Algorithm That Helps Robots Learn from Hindsight

AI2-THOR Interactive Simulation Teaches AI About Real World

AI2-THOR, an interactive simulation based on home environments, can prepare AI for real-world challenges Image: Roozbeh Mottaghi, Eric Kolve / Allen Institute for Artificial Intelligence Training a robot butler to make the perfect omlette could require breaking a lot of eggs and throwing out many imperfect attempts in a real-life kitchen. That’s why researchers have been rolling out virtual training grounds as a more efficient alternative to putting AI agents through costly and time-consuming experiments in the real world. Virtual environments could prove especially useful in training the most popular AI based on machine learning algorithms that often require thousands of trial-and-error runs to learn new skills. Companies such as Waymo have already built their own internal simulators with virtual roads and traffic intersections to train their AI to safely take the wheel of self-driving cars. But a new, open-source virtual training ground called AI2-THOR enables AI agents to learn how to interact with objects in familiar home Continue reading AI2-THOR Interactive Simulation Teaches AI About Real World