Tag Archives: appliances

#432181 Putting AI in Your Pocket: MIT Chip Cuts ...

Neural networks are powerful things, but they need a lot of juice. Engineers at MIT have now developed a new chip that cuts neural nets’ power consumption by up to 95 percent, potentially allowing them to run on battery-powered mobile devices.

Smartphones these days are getting truly smart, with ever more AI-powered services like digital assistants and real-time translation. But typically the neural nets crunching the data for these services are in the cloud, with data from smartphones ferried back and forth.

That’s not ideal, as it requires a lot of communication bandwidth and means potentially sensitive data is being transmitted and stored on servers outside the user’s control. But the huge amounts of energy needed to power the GPUs neural networks run on make it impractical to implement them in devices that run on limited battery power.

Engineers at MIT have now designed a chip that cuts that power consumption by up to 95 percent by dramatically reducing the need to shuttle data back and forth between a chip’s memory and processors.

Neural nets consist of thousands of interconnected artificial neurons arranged in layers. Each neuron receives input from multiple neurons in the layer below it, and if the combined input passes a certain threshold it then transmits an output to multiple neurons above it. The strength of the connection between neurons is governed by a weight, which is set during training.

This means that for every neuron, the chip has to retrieve the input data for a particular connection and the connection weight from memory, multiply them, store the result, and then repeat the process for every input. That requires a lot of data to be moved around, expending a lot of energy.

The new MIT chip does away with that, instead computing all the inputs in parallel within the memory using analog circuits. That significantly reduces the amount of data that needs to be shoved around and results in major energy savings.

The approach requires the weights of the connections to be binary rather than a range of values, but previous theoretical work had suggested this wouldn’t dramatically impact accuracy, and the researchers found the chip’s results were generally within two to three percent of the conventional non-binary neural net running on a standard computer.

This isn’t the first time researchers have created chips that carry out processing in memory to reduce the power consumption of neural nets, but it’s the first time the approach has been used to run powerful convolutional neural networks popular for image-based AI applications.

“The results show impressive specifications for the energy-efficient implementation of convolution operations with memory arrays,” Dario Gil, vice president of artificial intelligence at IBM, said in a statement.

“It certainly will open the possibility to employ more complex convolutional neural networks for image and video classifications in IoT [the internet of things] in the future.”

It’s not just research groups working on this, though. The desire to get AI smarts into devices like smartphones, household appliances, and all kinds of IoT devices is driving the who’s who of Silicon Valley to pile into low-power AI chips.

Apple has already integrated its Neural Engine into the iPhone X to power things like its facial recognition technology, and Amazon is rumored to be developing its own custom AI chips for the next generation of its Echo digital assistant.

The big chip companies are also increasingly pivoting towards supporting advanced capabilities like machine learning, which has forced them to make their devices ever more energy-efficient. Earlier this year ARM unveiled two new chips: the Arm Machine Learning processor, aimed at general AI tasks from translation to facial recognition, and the Arm Object Detection processor for detecting things like faces in images.

Qualcomm’s latest mobile chip, the Snapdragon 845, features a GPU and is heavily focused on AI. The company has also released the Snapdragon 820E, which is aimed at drones, robots, and industrial devices.

Going a step further, IBM and Intel are developing neuromorphic chips whose architectures are inspired by the human brain and its incredible energy efficiency. That could theoretically allow IBM’s TrueNorth and Intel’s Loihi to run powerful machine learning on a fraction of the power of conventional chips, though they are both still highly experimental at this stage.

Getting these chips to run neural nets as powerful as those found in cloud services without burning through batteries too quickly will be a big challenge. But at the current pace of innovation, it doesn’t look like it will be too long before you’ll be packing some serious AI power in your pocket.

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Posted in Human Robots

#431081 How the Intelligent Home of the Future ...

As Dorothy famously said in The Wizard of Oz, there’s no place like home. Home is where we go to rest and recharge. It’s familiar, comfortable, and our own. We take care of our homes by cleaning and maintaining them, and fixing things that break or go wrong.
What if our homes, on top of giving us shelter, could also take care of us in return?
According to Chris Arkenberg, this could be the case in the not-so-distant future. As part of Singularity University’s Experts On Air series, Arkenberg gave a talk called “How the Intelligent Home of The Future Will Care For You.”
Arkenberg is a research and strategy lead at Orange Silicon Valley, and was previously a research fellow at the Deloitte Center for the Edge and a visiting researcher at the Institute for the Future.
Arkenberg told the audience that there’s an evolution going on: homes are going from being smart to being connected, and will ultimately become intelligent.
Market Trends
Intelligent home technologies are just now budding, but broader trends point to huge potential for their growth. We as consumers already expect continuous connectivity wherever we go—what do you mean my phone won’t get reception in the middle of Yosemite? What do you mean the smart TV is down and I can’t stream Game of Thrones?
As connectivity has evolved from a privilege to a basic expectation, Arkenberg said, we’re also starting to have a better sense of what it means to give up our data in exchange for services and conveniences. It’s so easy to click a few buttons on Amazon and have stuff show up at your front door a few days later—never mind that data about your purchases gets recorded and aggregated.
“Right now we have single devices that are connected,” Arkenberg said. “Companies are still trying to show what the true value is and how durable it is beyond the hype.”

Connectivity is the basis of an intelligent home. To take a dumb object and make it smart, you get it online. Belkin’s Wemo, for example, lets users control lights and appliances wirelessly and remotely, and can be paired with Amazon Echo or Google Home for voice-activated control.
Speaking of voice-activated control, Arkenberg pointed out that physical interfaces are evolving, too, to the point that we’re actually getting rid of interfaces entirely, or transitioning to ‘soft’ interfaces like voice or gesture.
Drivers of change
Consumers are open to smart home tech and companies are working to provide it. But what are the drivers making this tech practical and affordable? Arkenberg said there are three big ones:
Computation: Computers have gotten exponentially more powerful over the past few decades. If it wasn’t for processors that could handle massive quantities of information, nothing resembling an Echo or Alexa would even be possible. Artificial intelligence and machine learning are powering these devices, and they hinge on computing power too.
Sensors: “There are more things connected now than there are people on the planet,” Arkenberg said. Market research firm Gartner estimates there are 8.4 billion connected things currently in use. Wherever digital can replace hardware, it’s doing so. Cheaper sensors mean we can connect more things, which can then connect to each other.
Data: “Data is the new oil,” Arkenberg said. “The top companies on the planet are all data-driven giants. If data is your business, though, then you need to keep finding new ways to get more and more data.” Home assistants are essentially data collection systems that sit in your living room and collect data about your life. That data in turn sets up the potential of machine learning.
Colonizing the Living Room
Alexa and Echo can turn lights on and off, and Nest can help you be energy-efficient. But beyond these, what does an intelligent home really look like?
Arkenberg’s vision of an intelligent home uses sensing, data, connectivity, and modeling to manage resource efficiency, security, productivity, and wellness.
Autonomous vehicles provide an interesting comparison: they’re surrounded by sensors that are constantly mapping the world to build dynamic models to understand the change around itself, and thereby predict things. Might we want this to become a model for our homes, too? By making them smart and connecting them, Arkenberg said, they’d become “more biological.”
There are already several products on the market that fit this description. RainMachine uses weather forecasts to adjust home landscape watering schedules. Neurio monitors energy usage, identifies areas where waste is happening, and makes recommendations for improvement.
These are small steps in connecting our homes with knowledge systems and giving them the ability to understand and act on that knowledge.
He sees the homes of the future being equipped with digital ears (in the form of home assistants, sensors, and monitoring devices) and digital eyes (in the form of facial recognition technology and machine vision to recognize who’s in the home). “These systems are increasingly able to interrogate emotions and understand how people are feeling,” he said. “When you push more of this active intelligence into things, the need for us to directly interface with them becomes less relevant.”
Could our homes use these same tools to benefit our health and wellness? FREDsense uses bacteria to create electrochemical sensors that can be applied to home water systems to detect contaminants. If that’s not personal enough for you, get a load of this: ClinicAI can be installed in your toilet bowl to monitor and evaluate your biowaste. What’s the point, you ask? Early detection of colon cancer and other diseases.
What if one day, your toilet’s biowaste analysis system could link up with your fridge, so that when you opened it it would tell you what to eat, and how much, and at what time of day?
Roadblocks to intelligence
“The connected and intelligent home is still a young category trying to establish value, but the technological requirements are now in place,” Arkenberg said. We’re already used to living in a world of ubiquitous computation and connectivity, and we have entrained expectations about things being connected. For the intelligent home to become a widespread reality, its value needs to be established and its challenges overcome.
One of the biggest challenges will be getting used to the idea of continuous surveillance. We’ll get convenience and functionality if we give up our data, but how far are we willing to go? Establishing security and trust is going to be a big challenge moving forward,” Arkenberg said.
There’s also cost and reliability, interoperability and fragmentation of devices, or conversely, what Arkenberg called ‘platform lock-on,’ where you’d end up relying on only one provider’s system and be unable to integrate devices from other brands.
Ultimately, Arkenberg sees homes being able to learn about us, manage our scheduling and transit, watch our moods and our preferences, and optimize our resource footprint while predicting and anticipating change.
“This is the really fascinating provocation of the intelligent home,” Arkenberg said. “And I think we’re going to start to see this play out over the next few years.”
Sounds like a home Dorothy wouldn’t recognize, in Kansas or anywhere else.
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Posted in Human Robots

#430630 CORE2 consumer robot controller by ...

Hardware, software and cloud for fast robot prototyping and development
Kraków, Poland, June 27th, 2017 – Robotic development platform creator Husarion has launched its next-generation dedicated robot controller CORE2. Available now at the Crowd Supply crowdfunding platform, CORE2 enables the rapid prototyping and development of consumer and service robots. It’s especially suitable for engineers designing commercial appliances and robotics students or hobbyists. Whether the next robotic idea is a tiny rover that penetrates tunnels, a surveillance drone, or a room-sized 3D printer, the CORE2 can serve as the brains behind it.
Photo Credit: Husarionwww.husarion.com
Husarion’s platform greatly simplifies robot development, making it as easy as creating a website. It provides engineers with embedded hardware, preconfigured software and easy online management. From the simple, proof-of-concept prototypes made with LEGO® Mindstorms to complex designs ready for mass manufacturing, the core technology stays the same throughout the process, shortening the time to market significantly. It’s designed as an innovation for the consumer robotics industry similar to what Arduino or Raspberry PI were to the Maker Movement.

“We are on the verge of a consumer robotics revolution”, says Dominik Nowak, CEO of Husarion. “Big industrial businesses have long been utilizing robots, but until very recently the consumer side hasn’t seen that many of them. This is starting to change now with the democratization of tools, the Maker Movement and technology maturing. We believe Husarion is uniquely positioned for the upcoming boom, offering robot developers a holistic solution and lowering the barrier of entry to the market.”

The hardware part of the platform is the Husarion CORE2 board, a computer that interfaces directly with motors, servos, encoders or sensors. It’s powered by an ARM® CORTEX-M4 CPU, features 42x I/O ports and can support up to 4x DC motors and 6x servomechanisms. Wireless connectivity is provided by a built-in Wi-Fi module.
Photo Credit: Husarion – www.husarion.com
The Husarion CORE2-ROS is an alternative configuration with a Raspberry Pi 3 ARMv8-powered board layered on top, with a preinstalled Robot Operating System (ROS) custom Linux distribution. It allows users to tap into the rich sets of modules and building tools already available for ROS. Real-time capabilities and high computing power enable advanced use cases, such as fully autonomous devices.

Developing software for CORE2-powered robots is easy. Husarion provides Web IDE, allowing engineers to program their connected robots directly from within the browser. There’s also an offline SDK and a convenient extension for Visual Studio Code. The open-source library hFramework based on Real Time Operating System masks the complexity of interface communication behind an elegant, easy-to-use API.

CORE2 also works with Arduino libraries, which can be used with no modifications at all through the compatibility layer of the hFramework API.
Photo Credit: Husarion – www.husarion.com
For online access, programming and control, Husarion provides its dedicated Cloud. By registering the CORE2-powerd robot at https://cloud.husarion.com, developers can update firmware online, build a custom Web control UI and share controls of their device with anyone.

Starting at $89, Husarion CORE2 and CORE2-ROS controllers are now on sale through Crowd Supply.

Husarion also offers complete development kits, extra servo controllers and additional modules for compatibility with LEGO® Mindstorms or Makeblock® mechanics. For more information, please visit: https://www.crowdsupply.com/husarion/core2.

Key points:
A dedicated robot hardware controller, with built-in interfaces for sensors, servos, DC motors and encoders

Programming with free tools: online (via Husarion Cloud Web IDE) or offline (Visual Studio Code extension)
Compatible with ROS, provides C++ 11 open-source programming framework based on RTOS
Husarion Cloud: control, program and share robots, with customizable control UI
Allows faster development and more advanced robotics than general maker boards like Arduino or Raspberry Pi

About Husarion
Husarion was founded in 2013 in Kraków, Poland. In 2015, Husarion successfully financed a Kickstarter campaign for RoboCORE, the company’s first-generation controller. The company delivers a fast prototyping platform for consumer robots. Thanks to Husarion’s hardware modules, efficient programming tools and cloud management, engineers can rapidly develop and iterate on their robot ideas. Husarion simplifies the development of connected, commercial robots ready for mass production and provides kits for academic education.

For more information, visit: https://husarion.com/.
Photo Credit: Husarion – www.husarion.com

Photo Credit: Husarion – www.husarion.com

Media contact:

Piotr Sarotapublic relations consultant
SAROTA PR – public relations agencyphone: +48 12 684 12 68mobile: +48 606 895 326email: piotr(at)sarota.pl
http://www.sarota.pl/
Jakub Misiurapublic relations specialist
phone: +48 12 349 03 52mobile: +48 696 778 568email: jakub.misiura(at)sarota.pl

Photo Credit: Husarion – www.husarion.com
Photo Credit: Husarion – www.husarion.com
Photo Credit: Husarion – www.husarion.com

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Posted in Human Robots