Posts Tagged ‘learns’
Honeywell has had WiFi-capable thermostats on the market for some time, but few of them would be a great match for home interiors that have escaped 1980s beige chic. The company’s new Wi-Fi Smart Thermostat is going a long way toward bringing that design fully into the present century. Owners can color match the touchscreen interface with the paint on their walls, down to very exact shades. Of course, the thermostat wouldn’t be much of a competitor in the Nest era if it didn’t have some of that namesake intelligence underneath. As with its main rival, the Honeywell system has (already existing) Android and iOS apps, and can tell how long it takes to change the temperature; it’s also aware of when filters need a change based on furnace behavior. If you’re on the cusp of a home renovation and don’t want anything so gauche as a differently-colored screen, home improvement shops should have the Wi-Fi Smart Thermostat this May for $ 249.
Filed under: Household
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Vicki Lombardi’s students do a great job of learning how to build a Spider robot.
Video Rating: 5 / 5
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With Americans voting today in the most hotly-contested poll since 2000, it & rsquo; s no surprise that politicians are using complex mathematics styles to hypothesize about voter behavior. But exactly what is unusual is that styles exist for each of the nation & rsquo; s 170 million registered voters– styles that make use of factors like age, wide range level, and geographic place to identify just what individual voters are most likely to do on election day, and with astonishingly high accuracy.
On Monday evening & rsquo; s Colbert Report, Slate factor and writer of The Victory Laboratory, Sasha Issenberg visited to explain exactly how this kind of analytical analysis is carried out and exactly how the data can be utilized to obtain people to the polls. While the idea might seem benign (who cares if …
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We such as to inform ourselves that finding out by doing is the finest technique for enhancing our abilities, but we rarely apply that philosophy to our robots; with certain exceptions, they’re simply expected to understand exactly what to do from the beginning. Specialists at the Technical University of Darmstadt disagree and have actually established formulas proving that robotic arms simply need practice, practice, practice to find out complicated activities. After some literal hand-holding with a human to comprehend the basics of a ping-pong swing, a TUD robot can slowly abstract those motions and return the ball in circumstances beyond the initial instance. The strategy is effective enough that the test arm took a mere hour of practice to effectively bounce back 88 percent of gos and compete with a human. That’s definitely better than many of us fared after our very first game. If all works out, the science might result in robotics of all kinds that need only a small foundation of code to accomplish a whole lot. Simply wish that the inescapable struggle in between people and robots isn’t settled with a ping-pong match … it might end badly.
Filed under: Robotics, AltGerman robot arm learns ping-pong as it plays humans, may rival its masters originally appeared on Engadget on Sun, 28 Oct 2012 07:57:00 EDT. Please see our terms for use of feeds. Permalink New Scientist|University of Texas (PDF)|E-mail this|Comments
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This video demonstrates an architecture allowing an humanoid robot iCub to learn new objects presented to it. This is done by adding the concept of object to an existent low-level attention system of the robot. When the robot first encounters an unknown object, found to be within a certain (small) distance from its eyes, it stores a cluster of the SIFT visual features present within an interval about that distance, using depth perception. Whenever a previously stored object crosses the robot’s field of view again, it is recognized and mapped into an egocentrical frame of reference and gazed at. This mapping is persistent, in the sense that its identification and position are kept even if not visible by the robot. More info at mediawiki.isr.ist.utl.pt
Video Rating: 4 / 5
On the list of dangerous humanoid bots DARwIn is easily topped by the bow-happy iCub. Still — we don’t trust this thing one iota. While we haven’t seen it pick up any weaponry just yet, our friends to the north are teaching it one of man’s most notoriously violent sports: hockey. Researchers at the University of Manitoba have managed to train the former RoboCup star to stay upright while shuffling about on skates. Smacking a puck into a goal, on the other hand, has proven somewhat trickier. Eventually Jennifer, as the autonomous hockey-bot has been dubbed, managed to get the hang of it, but we don’t think the Flyers or Rangers will be offering her the big bucks just yet. And, honestly, before this little guy gets too good and turns into a bully on the ice, we’d get it to switch games — curling suddenly seems like a perfectly acceptable past time. Check out the video after the break.
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Still having a blast adding people into circles? Well hold on tight, because Mountain View just introduced some worthy upgrades to its social network. First up is a new feature dubbed “What’s Hot” which, much like trending topics on Twitter, highlights popular content being shared on the social network. Photography aficionados in the audience can gussy up snaps with more photo editing features dubbed “Creative Kit”, including a multitude of filters — some of which (for a limited time) pertain to Halloween. And finally, those of you who use Google Apps within an organization can now partake in all the Google+ fun — provided your IT admin isn’t a social networking-hating luddite. Links explaining all that and more await you below, but before you go, why not hop past the break for some vampiric renditions of Larry and Sergey, and a few other celebs.
There are few technology products less inspiring than the thermostat. Yet for the past week, I’ve been more captivated by a thermostat than I ever thought possible.
It’s a thermostat called Nest from iPod inventor Tony Fadell’s new start-up, Nest Labs. And like Apple, Nest Labs has taken something you use every day and made it simple and delightful to use.
Nest operates with the same genius wheel user interface as the original iPod, with a digital screen in its center. It connects to your Wi-Fi network, allowing you to control it remotely via an iPhone app or the Web. And its stylish design made of brushed stainless steel is a showpiece.
What makes Nest stand out from other programmable thermostats is that it learns your behavioral patterns and creates a temperature-setting schedule from them. Nest has six sensors that can determine things like when you’re away from home.
Suddenly, I can’t imagine my house without a Nest.
Up front, it’ll cost you. Nest will be $ 249 when it’s available the week of Nov. 14. Installation costs $ 119 for the first unit and $ 25 for each additional unit. You can opt to install it yourself, but I strongly suggest ponying up for a professional installation unless you or someone you know has electrical expertise.
Installation took me an hour and a half, including removing my old unit and unplugging six wires, pushing anchors and screws into my wall, attaching the Nest base, clipping and stripping six wires to fit the new system, and using all manner of tools to fit the wires into the base. (Nest comes with four screwdrivers but no needle nose pliers, which are a big help.) After all this, my Nest didn’t run properly. The company sent someone to fix it, who discovered that only three of my system’s wires were attached, mimicking a working system without a fan.
The Nest thermostat.
Setting up Nest’s software was a breeze. Elegantly animated menus and instructions walked me through each step, including setting up my Wi-Fi network, setting my highest and lowest overall temperatures and entering my ZIP Code.
I entered data on my Nest by turning its outer ring left or right to skim through letters, numbers and symbols, and pushing in the center of the device to select each one. A gentle clicking sound — like the old iPod wheel — can be heard as you turn this ring and pass over each character.
At first, Nest doesn’t do much because it’s waiting for you to use it so it can learn your preferences. Turning the outer ring right or left adjusts the temperature. Cranking up the heat several degrees turned the Nest screen red; turning down the heat made the screen blue.
A little green leaf appears on the screen if an adjustment you make sets your system into energy-conserving mode relative to your normal behavior. This tiny symbol made me feel like I earned a gold star at school for good behavior.
Another way Nest teaches people is with on-screen messages that say how long it will take to get to a desired temperature. For example, if I turn my heat up two degrees from 72 degrees, a message on the screen may say, “In 30 minutes,” with a 74 below this message. This data is meant to deter people from making drastic temperature changes.
After two days of use, a message appeared on my Nest saying, “Initial heating schedule learning complete.” If the device’s sensors detect that no one has walked by the Nest in the past two hours, it goes into Away mode, automatically adjusting to the most energy-conserving temperature, set ahead of time.
Nest operates with the same genius wheel user interface as the original iPod, with a digital screen in its center.
If I didn’t agree with any of these learned behaviors, I could tweak the temperatures to my liking, and Nest adjusted to these corrections. After I adjusted the temperature two nights in a row so the house would be cooler when we were sleeping, Nest learned this and automatically adjusted temperatures around 11:30 p.m. We like heat in the morning, so Nest had the heat going when I hopped out of bed.
Nest.com, the website where people can control their device and review schedules and behavior, wasn’t yet live when I tested. The site shows a summary page of your Nest account, which reflects how much time your heat or air conditioning was used per day. A green leaf is awarded to the days on which the least energy was consumed.
To use the Nest app, you need only hold your iPhone in landscape view, and as long as it’s running on the same Wi-Fi network, the thermostat’s account is automatically set up on the iPhone. The iPhone app let me adjust temperatures from afar. One chilly day at work, I opened the Nest app and turned up my heat just before I went home.
People with more than one thermostat in one home can use more than one Nest, and they’ll all communicate with one another, though each can be adjusted to different temperatures. People with multiple homes can put all of their Nests on the same account.
Nest can get automatic software updates that the company says will let it do things in the future like adjusting temperatures according to current local weather and showing how much money temperature adjustments will save on utility bills.
Apple’s iPhone 4 may not have the fancy dual core CPU of its successor, but thanks to the efforts of developer Steven Troughton-Smith and the folks at 9to5 Mac, it may soon have Siri. The port of the sultry voice assistant was accomplished by using the 4S Siri and Springboard files, and some serious elbow grease, no doubt. As you can see in the video below, it’s far from perfect, but it can recognize spoken commands without issue. Currently, the hack is missing an iPhone 4 GPU driver that keeps things running buttery smooth on the elder phone, and Cupertino won’t authenticate Siri’s commands coming from it either. So, it isn’t quite ready for primetime, but it should only be a matter of time before all you iPhone 4 owners can tell Siri what to do, too.
Pancake day special! The video shows a Barrett WAM robot learning to flip pancakes by reinforcement learning. The motion is encoded in a mixture of basis force fields through an extension of Dynamic Movement Primitives (DMP) that represents the synergies across the different variables through stiffness matrices. An Inverse Dynamics controller with variable stiffness is used for reproduction. For pancake day special, the skill is first demonstrated via kinesthetic teaching, and then refined by Policy learning by Weighting Exploration with the Returns (PoWER) algorithm. After 50 trials, the robot learns that the first part of the task requires a stiff behavior to throw the pancake in the air, while the second part requires the hand to be compliant in order to catch the pancake without having it bounced off the pan. Video credits for pancake day special: ————————– Dr. Petar Kormushev kormushev.com Dr. Sylvain Calinon http Affiliation: ———————- Advanced Robotics dept. Italian Institute of Technology (IIT) Link to publication about pancake day special: programming-by-demonstration.org Link to publication on PoWER algorithm by Jens Kober and Jan Peters: books.nips.cc Pancake day special
Video Rating: 4 / 5