Meet the 13-year-old prodigy taking IBM and artificial intelligence by storm

Meet the 13-year-old prodigy taking @IBM and artificial intelligence by storm  @BreakfastNews

  • Tanmay Bakshi fell in love with computers at five, released his first iPhone app at nine, and now at just 13 years old is working with IBM on artificial intelligence.
  • He is currently in Australia for the IBM Watson Summit, which brings together experts in artificial intelligence to discuss how the technology can help people and businesses in the future.
  • “If you think about it, really anything would fascinate a five-year-old, especially a computer,” Tanmay told News Breakfast.
  • Tanmay names Apple co-founder Steve Jobs as an inspiration — “especially his passion and dedication towards his work” — and is now most excited by how artificial intelligence can be used in health care.
  • Tanmay has toured the world to spread the word on computer programming, including giving public lectures and joining forum discussions, which has meant he has left traditional school in lieu of home schooling.

Tanmay Bakshi isn’t your typical 13-year-old. Rather than playing video games he’s blazing new trails in AI and has become one of the youngest app developers in the world.
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The Startup Rushing to Usher in the Self-Driving Era Even Faster

The #Startup Rushing to Usher in the #SelfDriving Era Even Faster  @driveai_ #Cars #AI

  • Drive.ai never set out to build the best self-driving car.
  • Instead of striking early deals with car manufacturers to see who can roll out the most robust working product—though Drive.ai says it has some secret deals in place already—the company has focused on creating the best possible, fully autonomous self-driving AI “brain” in the world.
  • The company’s test vehicles have shown promising results driving in cloudy and rainy conditions that continue to stump other self-driving cars, bringing the world that much closer to the true prize in self-driving tech: the ability to eliminate the human altogether.
  • For now, drivers are expected to maintain awareness at all times, ready to take control of mostly self-driving cars if conditions make the automated system screw up.
  • And by lowering the price tag on self-driving from the cost of a new futuristic vehicle to that of a retrofit kit that can hook up with your old Toyota Tercel, Drive.ai could create a mass market overnight.

Using a simple kit users can make their cars self-driving if Drive.Ai is able to make these work for all car models on the road.
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This new AI can read your mind and predict your thoughts

This new AI can read your mind and predict your thoughts -   #ArtificialIntelligence  #AI

  • Today, various pieces of software can do everything from chat with us on Facebook Messenger to guiding the Mars rover Curiosity while its human engineers catch a nap.
  • The group’s new software takes a novel approach to guessing what is going on inside a human brain, using data gathered from brain scans via fMRI to predict human thoughts by seeing how the pattern of brain activity that produces them, then detecting it in reverse.
  • “One of the big advances of the human brain was the ability to combine individual concepts into complex thoughts,” lead researcher Marcel Just explains.
  • The discovery of this correspondence between thoughts and brain activation patterns tells us what the thoughts are built of.”
  • The algorithm was then trained using this data, and learned to detect the same patterns occurring again, accurately predicting what a person was about to say a stunning 90 percent of the time.

At one point in our history, the most impressive example of artificial intelligence was a computer that was really, really good at chess. Today, various pieces…
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YouTube Adds Machine Learning To Comments, Rebuilds Its Desktop Creator Studio

YouTube Adds Machine Learning To Comments #machinelearning #ML #datascience #youtube

  • Capping off the slew of updates it unveiled this year at VidCon, YouTube announced at a session on Saturday evening that it is rebuilding its Creator Studio on desktops and revamping comments with new machine learning technology.
  • The all-new YouTube Creator Studio — which the company is renaming YouTube Studio — will still feature a suite of channel management tools aimed to make creators’ lives easier.
  • YouTube says it’s rebuilding the Studio with creator input, and is inviting interested parties to sign up for a beta test right here.
  • YouTube said that updates to comments, including the ability for creators to bestow hearts and pin comments, are seeing great success.
  • The technology will also parse through comments to look for common themes and topics, giving creators a sense of what viewers are talking about at a glance.

YouTube announced it is rebuilding its Creator Studio on desktops and revamping comments with new machine learning technology.
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Get ready for 5G connectivity with your autonomous car

Get ready for #5G connectivity with your autonomous car   MT @UCStrategies #IoT #M2M #AI

  • Autonomous cars are going to need to send and receive mountains of data, and the current 4G wireless networks simply won’t cut it.
  • Super-fast transfer speeds will be required by self-driving cars to enable them to communicate with a wide range of systems such as navigation services, traffic signals as part of connecting to smart city infrastructure, car-to-car communication and even to close-proximity mobile phone users – all in the interest of pilotless vehicle safety.
  • Using 5G wireless networks will enable driverless cars to avoid hitting pedestrians by a direct connection between the car and the person’s handheld device as they approach an intersection.
  • While 5G standards are currently being worked out, expect to see everything up and running by 2020, when Volkswagen has promised to bring its first semi-autonomous electric car to market.
  • That said, electric car company Tesla will have fully-autonomous vehicles ready by 2018, Toyota, General Motors and Volkswagen by 2020, while Ford and BMW claim they will have autonomous cars on the road by 2021.

Autonomous cars are going to need to send and receive mountains of data, and the current 4G wireless networks simply won’t cut it….
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The Air Force and IBM are building an AI supercomputer

The Air Force and @IBM are building an #AI supercomputer #techradio

  • IBM and the USAF announced on Friday that the machine will run on an array of 64 TrueNorth Neurosynaptic chips.
  • The TrueNorth chips are wired together like, and operate in a similar fashion to, the synapses within a biological brain.
  • That is, these chips don’t require a clock, as conventional CPUs do, to function.VIDEOWhat’s more, because of the distributed nature of the system, even if one core fails, the rest of the array will continue to work.
  • This 64-chip array will contain the processing equivalent of 64 million neurons and 16 billion synapses, yet absolutely sips energy — each processor consumes just 10 watts of electricity.Like other neural networks, this system will be put to use in pattern recognition and sensory processing roles.
  • The Air Force wants to combine the TrueNorth’s ability to convert multiple data feeds — whether it’s audio, video or text — into machine readable symbols with a conventional supercomputer’s ability to crunch data.This isn’t the first time that IBM’s neural chip system has been integrated into cutting-edge technology.

Supercomputers today are capable of performing incredible feats, from accurately predicting the weather to uncovering insights into climate change, but they sti…
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How to Create Convolutional Neural Networks Using Java and DL4J

How to Create Convolutional Neural Networks Using #Java and @deeplearning4j

#deeplearning

  • Using Deeplearning4J, you can create convolutional neural networks, also referred to as CNNs or ConvNets, in just a few lines of code.
  • If you don’t know what a CNN is, for now, just think of it as a feed-forward neural network that is optimized for tasks such as image classification and natural language processing.
  • If you want to list all the labels present in the dataset, you can use the following code:

    At this point, if you compile and run your project, you should see the following output:

    It’s now time to start creating the individual layers of our neural network.

  • Another important thing to note in the above code is the call to the method, which specifies that our neural network’s input type is convolutional, with 32×32 images having 3 colors.
  • To start training the convolutional neural network you just created, just call its method and pass the iterator object to it.

In this tutorial, you’ll learn how to use Java and DeepLearning4J(DL4J) to create a convolutional neural network that can classify CIFAR-10 images.
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