Tag Archives: can

#436218 An AI Debated Its Own Potential for Good ...

Posted on November 27, 2019 by Android

Artificial intelligence is going to overhaul the way we live and work. But will the changes it brings be for the better? As the technology slowly develops (let’s remember that right now, we’re still very much in the narrow AI space and nowhere near an artificial general intelligence), whether it will end up doing us more harm than good is a question at the top of everyone’s mind.

What kind of response might we get if we posed this question to an AI itself?

Last week at the Cambridge Union in England, IBM did just that. Its Project Debater (an AI that narrowly lost a debate to human debating champion Harish Natarajan in February) gave the opening arguments in a debate about the promise and peril of artificial intelligence.

Critical thinking, linking different lines of thought, and anticipating counter-arguments are all valuable debating skills that humans can practice and refine. While these skills are tougher for an AI to get good at since they often require deeper contextual understanding, AI does have a major edge over humans in absorbing and analyzing information. In the February debate, Project Debater used IBM’s cloud computing infrastructure to read hundreds of millions of documents and extract relevant details to construct an argument.

This time around, Debater looked through 1,100 arguments for or against AI. The arguments were submitted to IBM by the public during the week prior to the debate, through a website set up for that purpose. Of the 1,100 submissions, the AI classified 570 as anti-AI, or of the opinion that the technology will bring more harm to humanity than good. 511 arguments were found to be pro-AI, and the rest were irrelevant to the topic at hand.

Debater grouped the arguments into five themes; the technology’s ability to take over dangerous or monotonous jobs was a pro-AI theme, and on the flip side was its potential to perpetuate the biases of its creators. “AI companies still have too little expertise on how to properly assess datasets and filter out bias,” the tall black box that houses Project Debater said. “AI will take human bias and will fixate it for generations.”
After Project Debater kicked off the debate by giving opening arguments for both sides, two teams of people took over, elaborating on its points and coming up with their own counter-arguments.

In the end, an audience poll voted in favor of the pro-AI side, but just barely; 51.2 percent of voters felt convinced that AI can help us more than it can hurt us.

The software’s natural language processing was able to identify racist, obscene, or otherwise inappropriate comments and weed them out as being irrelevant to the debate. But it also repeated the same arguments multiple times, and mixed up a statement about bias as being pro-AI rather than anti-AI.

IBM has been working on Project Debater for over six years, and though it aims to iron out small glitches like these, the system’s goal isn’t to ultimately outwit and defeat humans. On the contrary, the AI is meant to support our decision-making by taking in and processing huge amounts of information in a nuanced way, more quickly than we ever could.

IBM engineer Noam Slonim envisions Project Debater’s tech being used, for example, by a government seeking citizens’ feedback about a new policy. “This technology can help to establish an interesting and effective communication channel between the decision maker and the people that are going to be impacted by the decision,” he said.

As for the question of whether AI will do more good or harm, perhaps Sylvie Delacroix put it best. A professor of law and ethics at the University of Birmingham who argued on the pro-AI side of the debate, she pointed out that the impact AI will have depends on the way we design it, saying “AI is only as good as the data it has been fed.”

She’s right; rather than asking what sort of impact AI will have on humanity, we should start by asking what sort of impact we want it to have. The people working on AI—not AIs themselves—are ultimately responsible for how much good or harm will be done.

Image Credit: IBM Project Debater at Cambridge Union Society, photo courtesy of IBM Research Continue reading →

Posted in Human Robots

#436217 4 Ways Autonomous Technology Can ...

Posted on November 26, 2019 by Android

Photo by Matan Segev from Pexels Autonomous technologies are changing the way we interact with the world around us exponentially. Artificial intelligence (AI) and machine learning (ML) technology is responsible for automated shopping and smart homes, among many other consumers innovations. And, in the business world, autonomous tools are changing the workplace as we know it. While many …

The post 4 Ways Autonomous Technology Can Streamline Your Business appeared first on TFOT. Continue reading →

Posted in Human Robots

#436215 Help Rescuers Find Missing Persons With ...

Posted on November 25, 2019 by Android

There’s a definite sense that robots are destined to become a critical part of search and rescue missions and disaster relief efforts, working alongside humans to help first responders move faster and more efficiently. And we’ve seen all kinds of studies that include the claim “this robot could potentially help with disaster relief,” to varying degrees of plausibility.

But it takes a long time, and a lot of extra effort, for academic research to actually become anything useful—especially for first responders, where there isn’t a lot of financial incentive for further development.

It turns out that if you actually ask first responders what they most need for disaster relief, they’re not necessarily interested in the latest and greatest robotic platform or other futuristic technology. They’re using commercial off-the-shelf drones, often consumer-grade ones, because they’re simple and cheap and great at surveying large areas. The challenge is doing something useful with all of the imagery that these drones collect. Computer vision algorithms could help with that, as long as those algorithms are readily accessible and nearly effortless to use.

The IEEE Robotics and Automation Society and the Center for Robotic-Assisted Search and Rescue (CRASAR) at Texas A&M University have launched a contest to bridge this gap between the kinds of tools that roboticists and computer vision researchers might call “basic” and a system that’s useful to first responders in the field. It’s a simple and straightforward idea, and somewhat surprising that no one had thought of it before now. And if you can develop such a system, it’s worth some cash.

CRASAR does already have a Computer Vision Emergency Response Toolkit (created right after Hurricane Harvey), which includes a few pixel filters and some edge and corner detectors. Through this contest, you can get paid your share of a $3,000 prize pool for adding some other excessively basic tools, including:

Image enhancement through histogram equalization, which can be applied to electro-optical (visible light cameras) and thermal imagery

Color segmentation for a range

Grayscale segmentation for a range in a thermal image

If it seems like this contest is really not that hard, that’s because it isn’t. “The first thing to understand about this contest is that strictly speaking, it’s really not that hard,” says Robin Murphy, director of CRASAR. “This contest isn’t necessarily about coming up with algorithms that are brand new, or even state-of-the-art, but rather algorithms that are functional and reliable and implemented in a way that’s immediately [usable] by inexperienced users in the field.”

Murphy readily admits that some of what needs to be done is not particularly challenging at all, but that’s not the point—the point is to make these functionalities accessible to folks who have better things to do than solve these problems themselves, as Murphy explains.

“A lot of my research is driven by problems that I’ve seen in the field that you’d think somebody would have solved, but apparently not. More than half of this is available in OpenCV, but who’s going to find it, download it, learn Python, that kind of thing? We need to get these tools into an open framework. We’re happy if you take libraries that already exist (just don’t steal code)—not everything needs to be rewritten from scratch. Just use what’s already there. Some of it may seem too simple, because it IS that simple. It already exists and you just need to move some code around.”

If you want to get very slightly more complicated, there’s a second category that involves a little bit of math:

Coders must provide a system that does the following for each nadir image in a set:

Reads the geotag embedded in the .jpg
Overlays a USNG grid for a user-specified interval (e.g., every 50, 100, or 200 meters)
Gives the GPS coordinates of each pixel if a cursor is rolled over the image
Given a set of images with the GPS or USNG coordinate and a bounding box, finds all images in the set that have a pixel intersecting that location

The final category awards prizes to anyone who comes up with anything else that turns out to be useful. Or, more specifically, “entrants can submit any algorithm they believe will be of value.” Whether or not it’s actually of value will be up to a panel of judges that includes both first responders and computer vision experts. More detailed rules can be found here, along with sample datasets that you can use for testing.

The contest deadline is 16 December, so you’ve got about a month to submit an entry. Winners will be announced at the beginning of January. Continue reading →

Posted in Human Robots

#436209 Video Friday: Robotic Endoscope Travels ...

Posted on November 23, 2019 by Android

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

DARPA SubT Urban Circuit – February 18-27, 2020 – Olympia, WA, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

Kuka has just announced the results of its annual Innovation Award. From an initial batch of 30 applicants, five teams reached the finals (we were part of the judging committee). The five finalists worked for nearly a year on their applications, which they demonstrated this week at the Medica trade show in Düsseldorf, Germany. And the winner of the €20,000 prize is…Team RoboFORCE, led by the STORM Lab in the U.K., which developed a “robotic magnetic flexible endoscope for painless colorectal cancer screening, surveillance, and intervention.”

The system could improve colonoscopy procedures by reducing pain and discomfort as well as other risks such as bleeding and perforation, according to the STORM Lab researchers. It uses a magnetic field to control the endoscope, pulling rather than pushing it through the colon.

The other four finalists also presented some really interesting applications—you can see their videos below.

“Because we were so please with the high quality of the submissions, we will have next year’s finals again at the Medica fair, and the challenge will be named ‘Medical Robotics’,” says Rainer Bischoff, vice president for corporate research at Kuka. He adds that the selected teams will again use Kuka’s LBR Med robot arm, which is “already certified for integration into medical products and makes it particularly easy for startups to use a robot as the main component for a particular solution.”

Applications are now open for Kuka’s Innovation Award 2020. You can find more information on how to enter here. The deadline is 5 January 2020.

[ Kuka ]

Oh good, Aibo needs to be fed now.

You know what comes next, right?

[ Aibo ]

Your cat needs this robot.

It's about $200 on Kickstarter.

[ Kickstarter ]

Enjoy this tour of the Skydio offices courtesy Skydio 2, which runs into not even one single thing.

If any Skydio employees had important piles of papers on their desks, well, they don’t anymore.

[ Skydio ]

Artificial intelligence is everywhere nowadays, but what exactly does it mean? We asked a group MIT computer science grad students and post-docs how they personally define AI.

“When most people say AI, they actually mean machine learning, which is just pattern recognition.” Yup.

[ MIT ]

Using event-based cameras, this drone control system can track attitude at 1600 degrees per second (!).

[ UZH ]

Introduced at CES 2018, Walker is an intelligent humanoid service robot from UBTECH Robotics. Below are the latest features and technologies used during our latest round of development to make Walker even better.

[ Ubtech ]

Introducing the Alpha Prime by #VelodyneLidar, the most advanced lidar sensor on the market! Alpha Prime delivers an unrivaled combination of field-of-view, range, high-resolution, clarity and operational performance.

Performance looks good, but don’t expect it to be cheap.

[ Velodyne ]

Ghost Robotics’ Spirit 40 will start shipping to researchers in January of next year.

[ Ghost Robotics ]

Unitree is about to ship the first batch of their AlienGo quadrupeds as well:

[ Unitree ]

Mechanical engineering’s Sarah Bergbreiter discusses her work on micro robotics, how they draw inspiration from insects and animals, and how tiny robots can help humans in a variety of fields.

[ CMU ]

Learning contact-rich, robotic manipulation skills is a challenging problem due to the high-dimensionality of the state and action space as well as uncertainty from noisy sensors and inaccurate motor control. To combat these factors and achieve more robust manipulation, humans actively exploit contact constraints in the environment. By adopting a similar strategy, robots can also achieve more robust manipulation. In this paper, we enable a robot to autonomously modify its environment and thereby discover how to ease manipulation skill learning. Specifically, we provide the robot with fixtures that it can freely place within the environment. These fixtures provide hard constraints that limit the outcome of robot actions. Thereby, they funnel uncertainty from perception and motor control and scaffold manipulation skill learning.

[ Stanford ]

Since 2016, Verity's drones have completed more than 200,000 flights around the world. Completely autonomous, client-operated and designed for live events, Verity is making the magic real by turning drones into flying lights, characters, and props.

[ Verity ]

To monitor and stop the spread of wildfires, University of Michigan engineers developed UAVs that could find, map and report fires. One day UAVs like this could work with disaster response units, firefighters and other emergency teams to provide real-time accurate information to reduce damage and save lives. For their research, the University of Michigan graduate students won first place at a competition for using a swarm of UAVs to successfully map and report simulated wildfires.

[ University of Michigan ]

Here’s an important issue that I haven’t heard talked about all that much: How first responders should interact with self-driving cars.

“To put the car in manual mode, you must call Waymo.” Huh.

[ Waymo ]

Here’s what Gitai has been up to recently, from a Humanoids 2019 workshop talk.

[ Gitai ]

The latest CMU RI seminar comes from Girish Chowdhary at the University of Illinois at Urbana-Champaign on “Autonomous and Intelligent Robots in Unstructured Field Environments.”

What if a team of collaborative autonomous robots grew your food for you? In this talk, I will discuss some key advances in robotics, machine learning, and autonomy that will one day enable teams of small robots to grow food for you in your backyard in a fundamentally more sustainable way than modern mega-farms! Teams of small aerial and ground robots could be a potential solution to many of the serious problems that modern agriculture is facing. However, fully autonomous robots that operate without supervision for weeks, months, or entire growing season are not yet practical. I will discuss my group’s theoretical and practical work towards the underlying challenging problems in robotic systems, autonomy, sensing, and learning. I will begin with our lightweight, compact, and autonomous field robot TerraSentia and the recent successes of this type of undercanopy robots for high-throughput phenotyping with deep learning-based machine vision. I will also discuss how to make a team of autonomous robots learn to coordinate to weed large agricultural farms under partial observability. These direct applications will help me make the case for the type of reinforcement learning and adaptive control that are necessary to usher in the next generation of autonomous field robots that learn to solve complex problems in harsh, changing, and dynamic environments. I will then end with an overview of our new MURI, in which we are working towards developing AI and control that leverages neurodynamics inspired by the Octopus brain.

[ CMU RI ] Continue reading →

Posted in Human Robots

#436207 This Week’s Awesome Tech Stories From ...

Posted on November 23, 2019 by Android

COMPUTING
A Giant Superfast AI Chip Is Being Used to Find Better Cancer Drugs
Karen Hao | MIT Technology Review
“Thus far, Cerebras’s computer has checked all the boxes. Thanks to its chip size—it is larger than an iPad and has 1.2 trillion transistors for making calculations—it isn’t necessary to hook multiple smaller processors together, which can slow down model training. In testing, it has already shrunk the training time of models from weeks to hours.”

MEDICINE
Humans Put Into Suspended Animation for First Time
Ian Sample | The Guardian
“The process involves rapidly cooling the brain to less than 10C by replacing the patient’s blood with ice-cold saline solution. Typically the solution is pumped directly into the aorta, the main artery that carries blood away from the heart to the rest of the body.”

DRONES
This Transforming Drone Can Be Fired Straight Out of a Cannon
James Vincent | The Verge
“Drones are incredibly useful machines in the air, but getting them up and flying can be tricky, especially in crowded, windy, or emergency scenarios when speed is a factor. But a group of researchers from Caltech university and NASA’s Jet Propulsion Laboratory have come up with an elegant and oh-so-fun solution: fire the damn thing out of a cannon.”

ROBOTICS
Alphabet’s Dream of an ‘Everyday Robot’ Is Just Out of Reach
Tom Simonite | Wired
“Sorting trash was chosen as a convenient challenge to test the project’s approach to creating more capable robots. It’s using artificial intelligence software developed in collaboration with Google to make robots that learn complex tasks through on-the-job experience. The hope is to make robots less reliant on human coding for their skills, and capable of adapting quickly to complex new tasks and environments.”

ENVIRONMENT
The Electric Car Revolution May Take a Lot Longer Than Expected
James Temple | MIT Technology Review
“A new report from the MIT Energy Initiative warns that EVs may never reach the same sticker price so long as they rely on lithium-ion batteries, the energy storage technology that powers most of today’s consumer electronics. In fact, it’s likely to take another decade just to eliminate the difference in the lifetime costs between the vehicle categories, which factors in the higher fuel and maintenance expenses of standard cars and trucks.”

SPACE
How Two Intruders From Interstellar Space Are Upending Astronomy
Alexandra Witze | Nature
“From the tallest peak in Hawaii to a high plateau in the Andes, some of the biggest telescopes on Earth will point towards a faint smudge of light over the next few weeks. …What they’re looking for is a rare visitor that is about to make its closest approach to the Sun. After that, they have just months to grab as much information as they can from the object before it disappears forever into the blackness of space.”

Image Credit: Simone Hutsch / Unsplash Continue reading →

Posted in Human Robots