The content below is taken from the original (Yamaha’s smart pianos work with Alexa and teach you how to play), to continue reading please visit the site. Remember to respect the Author & Copyright.

Of the many things we expected to see at IFA 2017, cutting-edge instruments weren’t one of them. But Yamaha is using its time in Berlin to showcase the Clavinova all-electric, smart pianos, which use an iOS device and LEDs above each key to teach you how to play. With the Smart Pianist application, which will also be available on Android next year, you can learn how to play tracks in real-time thanks to blue and red lights that will come on every time you’re supposed to hit a key. (Red LEDs are placed above white keys, blue above the black ones.) Not only that, but if you can read music, there’s a chord chart being displayed on the iPad in real-time for whatever song you’re playing.

In terms of Alexa compatibility, Amazon’s virtual assistant isn’t built into the Clavinova smart pianos. Instead, you’re able to trigger different commands by plugging something like an an Echo Dot to them. The only caveat is that you’ll need to route that through a MusicCast-powered hub, which is essentially Yamaha’s answer to Apple AirPlay and Google Cast. It’s not the most intuitive process, but it’s still fun to see in action — especially if it works quite smoothly, as was the case during our demo. For instance, you can tell Alexa to play you a song on your piano, in case you want rather save a few minutes and not browse your music library.

Here’s the other, and arguably main, caveat: Yamaha’s Clavinova CSP models start at $4,000, depending on your piano configuration And if you’re feeling adventurous, the company also has a Grand Piano that works with a similar iPad app and plays itself for $60,000. It just depends on how much you want to impress.

Follow all the latest news from IFA 2017 here!

The content below is taken from the original (Google’s Hollywood ‘interventions’ made on-screen coders cooler), to continue reading please visit the site. Remember to respect the Author & Copyright.

Google operates a “Computer Science in Media Team” that stages “interventions” in Hollywood to steer film-makers towards realistic and accurate depictions of what it’s like to work in IT.

The company announced the team in 2015 and gave it the job of “making CS more appealing to a wider audience, by dispelling stereotypes and showcasing positive portrayals of underrepresented minorities in tech.” Google felt the effort was worthy because typical depictions of techies on screen used geeky stereotypes and mostly featured men, “leading to particularly girls and underrepresented boys not seeing themselves in the field.” It also wants to have more people to hire: like just about every tech company it struggles to find good people to hire. But the company has noticed that “Five years after the premiere of the original CSI television series, forensic science majors in the U.S. increased by 50%, with an over index of women.”

The efforts of that team have now been detailed in a study [PDF], Cracking the Code: The Prevalence and Nature of Computer Science Depictions in Media.

The study says Google has worked “to intersect the decision-making process that ultimately leads to the on screen representation of computer science” and “Through engagements with show creators and corporate representatives … has attempted to integrate computer science portrayals into TV movies and ongoing series that deviate from stereotypes and showcase diversity.”

The study finds those efforts have mostly worked. While computer science rarely makes it into films and tellie, “The sample of Google influenced content (5.9%, n=61 of 1,039) had a higher percentage of characters engaging in computer science than a matched sample of programming (.5%, n=4 of 883).” While the study finds that a character involved in computer science is still overwhelmingly likely to be a white man, content that Google influenced featured more women than in shows it didn’t engage.

As it happens, El Reg may well already have reported on the Team’s work: back in 2015 we spotted an episode of made-for-kids cartoon The Amazing World of Gumball, a show the study says Google has “advised.” In the episode we reported, a character says the following:

I bypassed the storage controller, tapped directly in to the VNX array head, decrypted the nearline SAS disks, injected the flash drivers into the network’s FabricPath before disabling the IDF, routed incoming traffic through a bunch of offshore proxies, accessed the ESXi server cluster in the prime data center, and disabled the inter-VSAN routing on the layer-3.

The authors of the study think Google still has work to do, because the content it influenced resulted in shows depicting women as “praised for intelligence rather than attractiveness, and were more often rewarded for their CS activities than males”>. But both the stuff Google influenced and shows it didn’t touch “still primarily depict White, male characters engaging in CS, who are often stereotypically attired. The nature of these depictions also reflects CS stereotypes, namely that friendships are primarily with other CS individuals and a lack of children or romantic relationships.”

Overall, the study’s authors declare the effort worthwhile and say Google’s efforts have been well-received in Hollywood, even if stereotypes persist and CS remains something seldom depicted by the entertainment industry.

Shows Google influenced include Miles from Tomorrowland, The Fosters, Silicon Valley, Halt and Catch fire, The Amazing Gumball, The Powerpuff Girls and Ready, Jet, Go. ÂŽ

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The content below is taken from the original (UK.gov unveils six areas to pilot full-fat fibre, and London ain’t on the list), to continue reading please visit the site. Remember to respect the Author & Copyright.

Government has revealed the first six areas in Blighty to trial speeds of 1Gbps in a ÂŁ10m pilot, as previously revealed by The Register.

The areas include Aberdeen and Aberdeenshire, West Sussex, Coventry and Warwickshire, Bristol, Bath and North East Somerset, West Yorkshire and Greater Manchester.

In August, the Department for Digital, Culture Media and Sport had told industry it would trial a scheme to allow businesses to bid for vouchers worth up to ÂŁ3,000 for “gigabit-capable” connectivity, and will pay the ongoing line rental costs.

That will most likely to be delivered by fibre but not exclusively so, said the documents.

The model is similar to that of the ÂŁ100m broadband connection voucher scheme for speeds of more than 30Mbps in 2013-15, which was re-scoped after initially experiencing poor take-up from small businesses.

The latest scheme will be funded via the ÂŁ200m “full-fibre” investment pot announced in the Spring budget and intended to leverage private sector investment in full-fibre broadband. The remaining ÂŁ190m is due to be spent by 2020/21.

Exchequer Secretary to the Treasury Andrew Jones MP said: “Full-fibre connections are the gold standard and we are proud to announce today the next step to get Britain better connected.”

Minister of State for Digital Matt Hancock MP said: “We want to see more commercial investment in the gold-standard connectivity that full fibre provides, and these innovative pilots will help create the right environment for this to happen.

“To keep Britain as the digital world leader that it is, we need to have the right infrastructure in place to allow us to keep up with the rapid advances in technology now and in the future.” ÂŽ

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The content below is taken from the original (Samsung’s ‘AI-powered’ washer is just trying to save you time), to continue reading please visit the site. Remember to respect the Author & Copyright.

IFA 2017 isn’t all about smartphones, smartwatches and cute droids. The event is also a chance for companies to showcase their latest innovations for home appliances. Samsung did its part this year with the WW8800M washer, which sports technology called QuickDrive that promises to complete a full load of laundry in just 39 minutes –typically it’s about 70. The company says it’s able to do this without compromising washing performance, energy efficiency and fabric care, something that will matter deeply to people who are extra conscious of how they do their laundry. Oh and it says AI is involved.

Samsung is betting heavily on the "artificial intelligence" powers of its WW8800M to make laundry day less of a chore. The washing machine pairs with an app dubbed Q-rator, which offers modes including Laundry Planner, Laundry Recipe and HomeCard Wizard. The first two features let you do things like pick your desired cycle through the application and adjust the temperature and amount of spins. You can tell the virtual assistant what type of garments you plan to wash too, like if it’s a shirt or a sweater, and then it will suggest the best cycle for it based on the info you type in. HomeCare Wizard, meanwhile, monitors the WW8800M remotely and alerts you if it’s having any issues.

While Samsung’s main goal is to save you time washing your loads, these options could help you take better care of your clothes — all with just a couple of taps on an app. We don’t know if we’d agree with Samsung that the WW8800M is "AI-powered," as the press release suggests, but that doesn’t mean it isn’t smarter than its previous WiFI models.

Unfortunately, Samsung didn’t reveal any pricing or availability details here in Berlin, so we’ll have to wait to judge it by its price.

Follow all the latest news from IFA 2017 here!

The content below is taken from the original (Cummins unveils an electric big rig weeks before Tesla), to continue reading please visit the site. Remember to respect the Author & Copyright.

Sorry, Tesla, but someone just stole the thunder from the electric big rig you were planning to unveil this fall. The engine giant Cummins has unveiled a concept semi truck, the AEOS, that runs entirely on the power of an electric motor and a 140kWh battery pack. It’s roughly as powerful as a 12-liter fossil fuel engine and could haul 44,000 pounds of cargo, just without the emissions or rampant fuel costs of a conventional truck. There’s speedy 1-hour charging, and Cummins is even looking at solar panels on the trailer to extend range. It’s a promising offering, although Elon Musk and crew might not lose too much sleep knowing the limitations.

For one thing, range is a sore point. You’re looking at a modest 100-mile range with that 140kWh pack. That’s fine for inter-city deliveries, but it won’t cut the mustard for longer trips. And while there’s talk of extending that distance to 300 miles with extra packs, that would only make it competitive with Tesla’s anticipated 200- to 300-mile range.

And more importantly, this is a concept, not a production vehicle ready to roll off the manufacturing line. There should be a production model in a couple of years, according to CNET, but that gives Tesla plenty of time to get its own EV semi on the road. Not that we’re going to complain about both companies having a fighting chance — more electric big rigs means more competition and fewer polluting trucks.

Via: IndyStar, CNET

Source: Cummins (1), (2)

The content below is taken from the original (New – Amazon EC2 Elastic GPUs for Windows), to continue reading please visit the site. Remember to respect the Author & Copyright.

Today we’re excited to announce the general availability of Amazon EC2 Elastic GPUs for Windows. An Elastic GPU is a GPU resource that you can attach to your Amazon Elastic Compute Cloud (EC2) instance to accelerate the graphics performance of your applications. Elastic GPUs come in medium (1GB), large (2GB), xlarge (4GB), and 2xlarge (8GB) sizes and are lower cost alternatives to using GPU instance types like G3 or G2 (for OpenGL 3.3 applications). You can use Elastic GPUs with many instance types allowing you the flexibility to choose the right compute, memory, and storage balance for your application. Today you can provision elastic GPUs in us-east-1 and us-east-2.

Elastic GPUs start at just $0.05 per hour for an eg1.medium. A nickel an hour. If we attach that Elastic GPU to a t2.medium ($0.065/hour) we pay a total of less than 12 cents per hour for an instance with a GPU. Previously, the cheapest graphical workstation (G2/3 class) cost 76 cents per hour. That’s over an 80% reduction in the price for running certain graphical workloads.

When should I use Elastic GPUs?

Elastic GPUs are best suited for applications that require a small or intermittent amount of additional GPU power for graphics acceleration and support OpenGL. Elastic GPUs support up to and including the OpenGL 3.3 API standards with expanded API support coming soon.

Elastic GPUs are not part of the hardware of your instance. Instead they’re attached through an elastic GPU network interface in your subnet which is created when you launch an instance with an Elastic GPU. The image below shows how Elastic GPUs are attached.

Since Elastic GPUs are network attached it’s important to provision an instance with adequate network bandwidth to support your application. It’s also important to make sure your instance security group allows traffic on port 2007.

Any application that can use the OpenGL APIs can take advantage of Elastic GPUs so Blender, Google Earth, SIEMENS SolidEdge, and more could all run with Elastic GPUs. Even Kerbal Space Program!

Ok, now that we know when to use Elastic GPUs and how they work, let’s launch an instance and use one.

Using Elastic GPUs

First, we’ll navigate to the EC2 console and click Launch Instance. Next we’ll select a Windows AMI like: “Microsoft Windows Server 2016 Base”. Then we’ll select an instance type. Then we’ll make sure we select the “Elastic GPU” section and allocate an eg1.medium (1GB) Elastic GPU.

We’ll also include some userdata in the advanced details section. We’ll write a quick PowerShell script to download and install our Elastic GPU software.

<powershell>
Start-Transcript -Path "C:\egpu_install.log" -Append
(new-object net.webclient).DownloadFile('http://bit.ly/2wRAjuj', 'C:\egpu.msi')
Start-Process "msiexec.exe" -Wait -ArgumentList "/i C:\egpu.msi /qn /L*v C:\egpu_msi_install.log"
[Environment]::SetEnvironmentVariable("Path", $env:Path + ";C:\Program Files\Amazon\EC2ElasticGPUs\manager\", [EnvironmentVariableTarget]::Machine)
Restart-Computer -Force
</powershell>

This software sends all OpenGL API calls to the attached Elastic GPU.

Next, we’ll double check to make sure my security group has TCP port 2007 exposed to my VPC so my Elastic GPU can connect to my instance. Finally, we’ll click launch and wait for my instance and Elastic GPU to provision. The best way to do this is to create a separate SG that you can attach to the instance.

You can see an animation of the launch procedure below.

Alternatively we could have launched on the AWS CLI with a quick call like this:

$aws ec2 run-instances --elastic-gpu-specification Type=eg1.2xlarge \
--image-id ami-1a2b3c4d \
--subnet subnet-11223344 \
--instance-type r4.large \
--security-groups "default" "elasticgpu-sg"

then we could have followed the Elastic GPU software installation instructions here.

We can now see our Elastic GPU is humming along and attached by checking out the Elastic GPU status in the taskbar.

We welcome any feedback on the service and you can click on the Feedback link in the bottom left corner of the GPU Status Box to let us know about your experience with Elastic GPUs.

Elastic GPU Demonstration

Ok, so we have our instance provisioned and our Elastic GPU attached. My teammates here at AWS wanted me to talk about the amazingly wonderful 3D applications you can run, but when I learned about Elastic GPUs the first thing that came to mind was Kerbal Space Program (KSP), so I’m going to run a quick test with that. After all, if you can’t launch Jebediah Kerman into space then what was the point of all of that software? I’ve downloaded KSP and added the launch parameter of -force-opengl to make sure we’re using OpenGL to do our rendering. Below you can see my poor attempt at building a spaceship – I used to build better ones. It looks pretty smooth considering we’re going over a network with a lossy remote desktop protocol.

I’d show a picture of the rocket launch but I didn’t even make it off the ground before I experienced a rapid unscheduled disassembly of the rocket. Back to the drawing board for me.

In the mean time I can check my Amazon CloudWatch metrics and see how much GPU memory I used during my brief game.

Partners, Pricing, and Documentation

To continue to build out great experiences for our customers, our 3D software partners like ANSYS and Siemens are looking to take advantage of the OpenGL APIs on Elastic GPUs, and are currently certifying Elastic GPUs for their software. You can learn more about our partnerships here.

You can find information on Elastic GPU pricing here. You can find additional documentation here.

Now, if you’ll excuse me I have some virtual rockets to build.

– Randall

The content below is taken from the original (Automate.io is a free automation tool and IFTTT alternative), to continue reading please visit the site. Remember to respect the Author & Copyright.

The content below is taken from the original (Lost Alan Turing letters found in university filing cabinet), to continue reading please visit the site. Remember to respect the Author & Copyright.

A huge batch of letters penned by British cryptographer Alan Turing has been found at the University of Manchester. Professor Jim Miles was tidying a storeroom when he discovered the correspondence in an old filing cabinet. At first he assumed the orange folder, which had Turing’s name on the front, had been emptied and re-used by another member of staff. But a closer look revealed 148 documents, including a letter sent by GCHQ, a draft version of a BBC radio programme about artificial intelligence, and invitations to lecture at some top universities in America.

Turing worked at the University of Manchester from 1948, first as a Reader in the mathematics department and later as the Deputy Director of the Computing Laboratory. These jobs followed his pivotal work with the Government Code and Cypher School during the Second World War. At Bletchley park, he spearheaded a team of cryptographers that helped the Allies to unravel various Nazi messages, including those protected by the Enigma code. The newly discovered documents date from early 1949 until his death in June 1954. At this time, Turing’s work on Enigma was still a secret, which is why it’s rarely mentioned in the correspondence.

None of the letters contain previously unknown information about Turing. They do provide new detail, however, about his life at Manchester and how he worked at the University. They also shed light on his personality — responding to a conference invitation in the US, he said boldly: "I would not like the journey, and I detest America." The documents also reference his work on morphogenesis, the study of biological life and why it takes a particular form, AI, computing and mathematics. "I was astonished such a thing had remained hidden out of sight for so long," Miles said.

All of the letters have now been sorted, catalogued and stored by James Peters at the University’s library. "This is a truly unique find," Miles said. "Archive material relating to Turing is extremely scarce, so having some of his academic correspondence is a welcome and important addition to our collection." You can now search for and view all 148 documents online.

None of the correspondence references his personal life. Turing was arrested in 1952 for homosexual acts and chose chemical castration over time in prison. In 1954, he died through cyanide poisoning, which an inquest later determined as suicide. The British government officially apologised for his treatment in 2009, before a posthumous pardon was granted in 2013. Last October, the UK government introduced the "Alan Turing Law," awarding posthumous pardons to thousands of gay and bisexual men previously convicted for consensual same-sex relationships.

Via: International Business Times

Source: The University of Manchester

The content below is taken from the original (Drones will watch Australian beaches for sharks with AI help), to continue reading please visit the site. Remember to respect the Author & Copyright.

Humans aren’t particularly good at spotting sharks using aerial data. At best, they’ll accurately pinpoint sharks 30 percent of the time — not very helpful for swimmers worried about stepping into the water. Australia, however, is about to get a more reliable way of spotting these undersea predators. As of September, Little Ripper drones will monitor some Australian beaches for signs of sharks, and pass along their imagery to an AI system that can identify sharks in real-time with 90 percent accuracy. Humans will still run the software (someone has to verify the results), but this highly automated system could be quick and reliable enough to save lives.

The detection AI is a quintessential machine learning system. The team trains the system to both look for sharks based on aerial videos as well as distinguish them from other life on the water. That approach doesn’t just help it identify sharks, though. It can also flag dolphins, whales and other sea creatures of interest, which could give researchers an additional way to track populations.

Also, the use of drones doesn’t just save helicopters valuable flight time. The drones hold beacons and life rafts, so they can offer immediate help to anyone who’s in distress. Little Ripper is also developing an electronic ‘repellent’ that the drones could use to keep sharks at bay until rescuers arrive.

Australia isn’t relying solely on drones. The country has been deploying nets along its northeastern shores to prevent sharks from entering areas in the first place. However, drones could at least augment those methods, and would arguably be friendlier to the local ecosystem. Instead of fencing off areas and potentially blocking access to other species, authorities could use robotic fliers to deal with sharks only when they pose a genuine threat.

Source: Reuters