The AI that can make grainy images razor sharp: Experts hail sci-fi breakthrough that could revolutionise everything from holiday snaps to crime fighting

The #AI that can make grainy images razor sharp.  @_cheymac

  • Researchers have unveiled a Blade Runner-style AI that can enhance pixelated images.
  • Dubbed EnhanceNet, the system relies on neural networks to boost the image quality, creating high-resolution images from a low-resolution input.
  • Dubbed EnhanceNet, the system relies on neural networks to boost the image quality, creating high-resolution images from a low-resolution input – – The system uses adversarial training, which pits the networks against each other in competing goals so they ultimately learn together.
  • ‘By using feed-forward fully convolutional neural networks in an adversarial training setting, we achieve a significant boost in image quality at high magnification ratios,’ the researchers explain in the study.
  • Examples from the study show just how good the new AI is, far surpassing the quality of images enhanced using a method known as peak signal-to-noise ratio (PSNR).

Researchers from the Max Planck Institute for Intelligent Systems have unveiled a Blade Runner-style AI dubbed EnhanceNet, that can enhance pixelated images.
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Microsoft’s BrainWave is going to supercharge AI

Microsoft's #BrainWave is going to supercharge #AI - and it's coming to the cloud.

  • Microsoft is using custom hardware to realize a 50-100x speed up in how quickly it can run AI algorithms that power its Bing search engine — and will make the tech available to all from next year.
  • The acceleration is being powered by the BrainWave platform, a network of customizable chips known as Field-Programmable Gate Arrays (FPGAs), tailored to efficiently handle deep neural networks.
  • “The power of the BrainWave platform are FPGAs, field-programmable gate arrays, which are really executing these AI algorithms in hardware,” said Joseph Sirosh, corporate VP for artificial intelligence research at Microsoft.
  • A large amount of Bing search queries are served through BrainWave, with Sirosh saying the FPGAs are “especially good” for accelerating text-based applications.
  • So as AI evolves so rapidly, as new algorithms come in, it is possible for you to build the custom gate logic required to execute in hardware in that FPGA.

Microsoft’s AI chief talks about the speed up in AI performance being realized by its BrainWave platform.
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A.I. Researchers Leave Elon Musk Lab to Begin Robotics Start-Up

  • Mr. Abbeel and the other founders of Embodied Intelligence, including the former OpenAI researchers Peter Chen and Rocky Duan and the former Microsoft researcher Tianhao Zhang, specialize in an algorithmic method called reinforcement learning — a way for machines to learn tasks by extreme trial and error.
  • Researchers at DeepMind, the London-based A.I. lab owned by Google, used this method to build a machine that could play the ancient game of Go better than any human.
  • Much like Google and labs at Brown and Northeastern University, Embodied Intelligence is also augmenting these methods with a wide range of other machine learning techniques.
  • Some researchers question how much these machine learning techniques will ultimately improve robotics, believing they are overhyped among both researchers and the news media.
  • But Mr. Abbeel is among the world’s top researchers in his field, and his decision to start a own company is an indication that machine learning will continue to push robotics forward.

Pieter Abbeel, a Berkeley professor, is part of the team that has started Embodied Intelligence to make it possible for robots to learn on their own.
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Introducing Gluon — An Easy-to-Use Programming Interface for Flexible Deep Learning

Deep learning just got simpler & faster with the new Gluon API.

  • The first result of this collaboration is the new Gluon interface, an open source library in Apache MXNet that allows developers of all skill levels to prototype, build, and train deep learning models.
  • It brings together the training algorithm and neural network model, thus providing flexibility in the development process without sacrificing performance.
  • Then, when speed becomes more important than flexibility (e.g., when you’re ready to feed in all of your training data), the Gluon interface enables you to easily cache the neural network model to achieve high performance and a reduced memory footprint.
  • For each iteration, there are four steps: (1) pass in a batch of data; (2) calculate the difference between the output generated by the neural network model and the actual truth (i.e., the loss); (3) use to calculate the derivatives of the model’s parameters with respect to their impact on…
  • To learn more about the Gluon interface and deep learning, you can reference this comprehensive set of tutorials, which covers everything from an introduction to deep learning to how to implement cutting-edge neural network models.

Today, AWS and Microsoft announced a new specification that focuses on improving the speed, flexibility, and accessibility of machine learning technology for all developers, regardless of their deep learning framework of choice. The first result of this collaboration is the new Gluon interface, an open source library in Apache MXNet that allows developers of all skill levels to prototype, build, and train deep learning models. This interface greatly simplifies the process of creating deep learning models without sacrificing training speed.
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Salesforce: “Salesforce CEO @Benioff shows how the world is changing with artificial intelligence and the 4th Industrial Revolution.”

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Salesforce (@salesforce). Connect to your customers in a whole new way. Stay up-to-date on news, announcements, and innovation. On duty Mon – Fri 9am – 5pm PT.
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Artificial Intelligence ushers in the era of superhuman doctors

Artificial Intelligence ushers in the era of superhuman doctors

  • One in 10 medical diagnoses is wrong, according to the US Institute of Medicine.
  • In primary care, one in 20 patients will get a wrong diagnosis.
  • These are worrying figures, driven by the complex nature of diagnosis, which can encompass incomplete information from patients, missed hand-offs between care providers, biases that cloud doctors’ judgement, overworked staff, overbooked systems, and more.
  • This is why many want to use the constant and unflappable power of artificial intelligence to achieve more accurate diagnosis, prompt care and greater efficiency.
  • In the US and mainland Europe, health

Non-human intelligence will soon be a standard part of your medical care – if it isn’t already. Can you trust it?
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Machine Learning Quick Reference Card – Towards Data Science – Medium

#MachineLearning Quick Reference Card

  • Machine Learning Quick Reference CardSupervised and Unsupervised Machine LearningIn my last few posts, I had discussed few algorithms that I implement frequently at my work.
  • However, the most important question is when to use these algorithms.
  • You play with different algorithms and see which one works best in your case by doing model comparisons.However, having a quick reference card helps narrow down the options and in making the decision.
  • That also means that this reference card makes some but it points you towards the right direction.You can download this reference card here.Hope you enjoyed this post.
  • Stay tuned for next posts to learn more on Machine learning basics.Happy Learning!

In my last few posts, I had discussed few algorithms that I implement frequently at my work. However, the most important question is when to use these algorithms. There is no one right way of doing…
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18 Great Blogs Posted in the last 12 Months

18 Great Blogs Posted in the last 12 Months | #DataScience #MachineLearning #RT

  • This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published.
  • These articles are at least 6 month old but no more than 12 month old.
  • The previous digest in this series was posted here a while back.
  • 18 Great Blogs Posted in the last 12 Months

This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published. These articles are at l…
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Eric Schmidt says America needs to ‘get its act together’ in AI competition with China

#Google’s former #CEO says #US could fail in the #AI competition with #China ?

  • Alphabet chairman Eric Schmidt says the US is at risk of falling behind in the race to develop cutting-edge artificial intelligence.
  • “They are going to use this technology for both commercial and military objectives, with all sorts of implications,” said Schmidt, referencing a Chinese policy document outlining the country’s ambition to become the global leader in AI by 2030.
  • Schmidt reiterated several familiar talking points in this debate, primarily that the US is failing to invest in basic research, and that a restrictive immigration policy hobbles the country’s ability to attract AI talent from overseas.
  • In his talk, Schmidt also touched on the benefits that artificial intelligence could offer the US military, giving the example of vision systems.
  • Instead, research institutions like AI Now say companies need to employ more non-technical people in the development of artificial intelligence.

Alphabet chairman Eric Schmidt says the US is at risk of falling behind in the race to develop cutting-edge artificial intelligence.
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LEAK: Google Employees Defend Discrimination Against Conservatives

  • Internal discussions at Google, leaked exclusively to Breitbart News shine further light on the problem, revealing that conservative Googlers who voice concerns about political bias are often belittled and ignored by fellow employees.
  • A majority of Google employees have stated that the company culture has not improved since they joined the company, in an anonymous internal poll conducted shortly after the firing of viewpoint diversity advocate James Damore.
  • It was the employee’s comments about political correctness, however, that caused ire from his colleagues, one of whom suggested he simply leave the company.
  • Another employee entered the conversation to reject the call for viewpoint diversity, telling his fellow Googler that he thought the company would be better off without him.
  • The attitude appears to reflect that of other Google employees, including managers, who openly called for supporters of James Damore to be fired and blacklisted in the wake of the viewpoint diversity controversy.

Internal discussions at Google, leaked exclusively to Breitbart News reveal that conservative Googlers who voice concerns about political bias
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