Tag Archives: smile
#437935 Start the New Year Right: By Watching ...
I don’t need to tell you that 2020 was a tough year. There was almost nothing good about it, and we saw it off with a “good riddance” and hopes for a better 2021. But robotics company Boston Dynamics took a different approach to closing out the year: when all else fails, why not dance?
The company released a video last week that I dare you to watch without laughing—or at the very least, cracking a pretty big smile. Because, well, dancing robots are funny. And it’s not just one dancing robot, it’s four of them: two humanoid Atlas bots, one four-legged Spot, and one Handle, a bot-on-wheels built for materials handling.
The robots’ killer moves look almost too smooth and coordinated to be real, leading many to speculate that the video was computer-generated. But if you can trust Elon Musk, there’s no CGI here.
This is not CGI https://t.co/VOivE97vPR
— Elon Musk (@elonmusk) December 29, 2020
Boston Dynamics went through a lot of changes in the last ten years; it was acquired by Google in 2013, then sold to Japanese conglomerate SoftBank in 2017 before being acquired again by Hyundai just a few weeks ago for $1.1 billion. But this isn’t the first time they teach a robot to dance and make a video for all the world to enjoy; Spot tore up the floor to “Uptown Funk” back in 2018.
Four-legged Spot went commercial in June, with a hefty price tag of $74,500, and was put to some innovative pandemic-related uses, including remotely measuring patients’ vital signs and reminding people to social distance.
Hyundai plans to implement its newly-acquired robotics prowess for everything from service and logistics robots to autonomous driving and smart factories.
They’ll have their work cut out for them. Besides being hilarious, kind of heartwarming, and kind of creepy all at once, the robots’ new routine is pretty impressive from an engineering standpoint. Compare it to a 2016 video of Atlas trying to pick up a box (I know it’s a machine with no feelings, but it’s hard not to feel a little bit bad for it, isn’t it?), and it’s clear Boston Dynamics’ technology has made huge strides. It wouldn’t be surprising if, in two years’ time, we see a video of a flash mob of robots whose routine includes partner dancing and back flips (which, admittedly, Atlas can already do).
In the meantime, though, this one is pretty entertaining—and not a bad note on which to start the new year.
Image Credit: Boston Dynamics Continue reading
Posted in Human Robots
#437701 Robotics, AI, and Cloud Computing ...
IBM must be brimming with confidence about its new automated system for performing chemical synthesis because Big Blue just had twenty or so journalists demo the complex technology live in a virtual room.
IBM even had one of the journalists choose the molecule for the demo: a molecule in a potential Covid-19 treatment. And then we watched as the system synthesized and tested the molecule and provided its analysis in a PDF document that we all saw in the other journalist’s computer. It all worked; again, that’s confidence.
The complex system is based upon technology IBM started developing three years ago that uses artificial intelligence (AI) to predict chemical reactions. In August 2018, IBM made this service available via the Cloud and dubbed it RXN for Chemistry.
Now, the company has added a new wrinkle to its Cloud-based AI: robotics. This new and improved system is no longer named simply RXN for Chemistry, but RoboRXN for Chemistry.
All of the journalists assembled for this live demo of RoboRXN could watch as the robotic system executed various steps, such as moving the reactor to a small reagent and then moving the solvent to a small reagent. The robotic system carried out the entire set of procedures—completing the synthesis and analysis of the molecule—in eight steps.
Image: IBM Research
IBM RXN helps predict chemical reaction outcomes or design retrosynthesis in seconds.
In regular practice, a user will be able to suggest a combination of molecules they would like to test. The AI will pick up the order and task a robotic system to run the reactions necessary to produce and test the molecule. Users will be provided analyses of how well their molecules performed.
Back in March of this year, Silicon Valley-based startup Strateos demonstrated something similar that they had developed. That system also employed a robotic system to help researchers working from the Cloud create new chemical compounds. However, what distinguishes IBM’s system is its incorporation of a third element: the AI.
The backbone of IBM’s AI model is a machine learning translation method that treats chemistry like language translation. It translates the language of chemistry by converting reactants and reagents to products through the use of Statistical Machine Intelligence and Learning Engine (SMILE) representation to describe chemical entities.
IBM has also leveraged an automatic data driven strategy to ensure the quality of its data. Researchers there used millions of chemical reactions to teach the AI system chemistry, but contained within that data set were errors. So, how did IBM clean this so-called noisy data to eliminate the potential for bad models?
According to Alessandra Toniato, a researcher at IBM Zurichh, the team implemented what they dubbed the “forgetting experiment.”
Toniato explains that, in this approach, they asked the AI model how sure it was that the chemical examples it was given were examples of correct chemistry. When faced with this choice, the AI identified chemistry that it had “never learnt,” “forgotten six times,” or “never forgotten.” Those that were “never forgotten” were examples that were clean, and in this way they were able to clean the data that AI had been presented.
While the AI has always been part of the RXN for Chemistry, the robotics is the newest element. The main benefit that turning over the carrying out of the reactions to a robotic system is expected to yield is to free up chemists from doing the often tedious process of having to design a synthesis from scratch, says Matteo Manica, a research staff member in Cognitive Health Care and Life Sciences at IBM Research Zürich.
“In this demo, you could see how the system is synergistic between a human and AI,” said Manica. “Combine that with the fact that we can run all these processes with a robotic system 24/7 from anywhere in the world, and you can see how it will really help up to speed up the whole process.”
There appear to be two business models that IBM is pursuing with its latest technology. One is to deploy the entire system on the premises of a company. The other is to offer licenses to private Cloud installations.
Photo: Michael Buholzer
Teodoro Laino of IBM Research Europe.
“From a business perspective you can think of having a system like we demonstrated being replicated on the premise within companies or research groups that would like to have the technology available at their disposal,” says Teodoro Laino, distinguished RSM, manager at IBM Research Europe. “On the other hand, we are also pushing at bringing the entire system to a service level.”
Just as IBM is brimming with confidence about its new technology, the company also has grand aspirations for it.
Laino adds: “Our aim is to provide chemical services across the world, a sort of Amazon of chemistry, where instead of looking for chemistry already in stock, you are asking for chemistry on demand.”
< Back to IEEE COVID-19 Resources Continue reading
Posted in Human Robots
#437276 Cars Will Soon Be Able to Sense and ...
Imagine you’re on your daily commute to work, driving along a crowded highway while trying to resist looking at your phone. You’re already a little stressed out because you didn’t sleep well, woke up late, and have an important meeting in a couple hours, but you just don’t feel like your best self.
Suddenly another car cuts you off, coming way too close to your front bumper as it changes lanes. Your already-simmering emotions leap into overdrive, and you lay on the horn and shout curses no one can hear.
Except someone—or, rather, something—can hear: your car. Hearing your angry words, aggressive tone, and raised voice, and seeing your furrowed brow, the onboard computer goes into “soothe” mode, as it’s been programmed to do when it detects that you’re angry. It plays relaxing music at just the right volume, releases a puff of light lavender-scented essential oil, and maybe even says some meditative quotes to calm you down.
What do you think—creepy? Helpful? Awesome? Weird? Would you actually calm down, or get even more angry that a car is telling you what to do?
Scenarios like this (maybe without the lavender oil part) may not be imaginary for much longer, especially if companies working to integrate emotion-reading artificial intelligence into new cars have their way. And it wouldn’t just be a matter of your car soothing you when you’re upset—depending what sort of regulations are enacted, the car’s sensors, camera, and microphone could collect all kinds of data about you and sell it to third parties.
Computers and Feelings
Just as AI systems can be trained to tell the difference between a picture of a dog and one of a cat, they can learn to differentiate between an angry tone of voice or facial expression and a happy one. In fact, there’s a whole branch of machine intelligence devoted to creating systems that can recognize and react to human emotions; it’s called affective computing.
Emotion-reading AIs learn what different emotions look and sound like from large sets of labeled data; “smile = happy,” “tears = sad,” “shouting = angry,” and so on. The most sophisticated systems can likely even pick up on the micro-expressions that flash across our faces before we consciously have a chance to control them, as detailed by Daniel Goleman in his groundbreaking book Emotional Intelligence.
Affective computing company Affectiva, a spinoff from MIT Media Lab, says its algorithms are trained on 5,313,751 face videos (videos of people’s faces as they do an activity, have a conversation, or react to stimuli) representing about 2 billion facial frames. Fascinatingly, Affectiva claims its software can even account for cultural differences in emotional expression (for example, it’s more normalized in Western cultures to be very emotionally expressive, whereas Asian cultures tend to favor stoicism and politeness), as well as gender differences.
But Why?
As reported in Motherboard, companies like Affectiva, Cerence, Xperi, and Eyeris have plans in the works to partner with automakers and install emotion-reading AI systems in new cars. Regulations passed last year in Europe and a bill just introduced this month in the US senate are helping make the idea of “driver monitoring” less weird, mainly by emphasizing the safety benefits of preemptive warning systems for tired or distracted drivers (remember that part in the beginning about sneaking glances at your phone? Yeah, that).
Drowsiness and distraction can’t really be called emotions, though—so why are they being lumped under an umbrella that has a lot of other implications, including what many may consider an eerily Big Brother-esque violation of privacy?
Our emotions, in fact, are among the most private things about us, since we are the only ones who know their true nature. We’ve developed the ability to hide and disguise our emotions, and this can be a useful skill at work, in relationships, and in scenarios that require negotiation or putting on a game face.
And I don’t know about you, but I’ve had more than one good cry in my car. It’s kind of the perfect place for it; private, secluded, soundproof.
Putting systems into cars that can recognize and collect data about our emotions under the guise of preventing accidents due to the state of mind of being distracted or the physical state of being sleepy, then, seems a bit like a bait and switch.
A Highway to Privacy Invasion?
European regulations will help keep driver data from being used for any purpose other than ensuring a safer ride. But the US is lagging behind on the privacy front, with car companies largely free from any enforceable laws that would keep them from using driver data as they please.
Affectiva lists the following as use cases for occupant monitoring in cars: personalizing content recommendations, providing alternate route recommendations, adapting environmental conditions like lighting and heating, and understanding user frustration with virtual assistants and designing those assistants to be emotion-aware so that they’re less frustrating.
Our phones already do the first two (though, granted, we’re not supposed to look at them while we drive—but most cars now let you use bluetooth to display your phone’s content on the dashboard), and the third is simply a matter of reaching a hand out to turn a dial or press a button. The last seems like a solution for a problem that wouldn’t exist without said… solution.
Despite how unnecessary and unsettling it may seem, though, emotion-reading AI isn’t going away, in cars or other products and services where it might provide value.
Besides automotive AI, Affectiva also makes software for clients in the advertising space. With consent, the built-in camera on users’ laptops records them while they watch ads, gauging their emotional response, what kind of marketing is most likely to engage them, and how likely they are to buy a given product. Emotion-recognition tech is also being used or considered for use in mental health applications, call centers, fraud monitoring, and education, among others.
In a 2015 TED talk, Affectiva co-founder Rana El-Kaliouby told her audience that we’re living in a world increasingly devoid of emotion, and her goal was to bring emotions back into our digital experiences. Soon they’ll be in our cars, too; whether the benefits will outweigh the costs remains to be seen.
Image Credit: Free-Photos from Pixabay Continue reading
Posted in Human Robots