A short while ago a recent article in Wired described how physicists are about to rule Silicon Valley. The opening of the article resonated strongly with me when I also used to tackle difficult research questions at the world's most renown laboratories for particle physics: CERN in Geneva, Switzerland and the Fermi National Laboratory in Chicago, IL. For more than 10 years I've tried to uncover the origins of our Universe before transitioning to the private sector and joining Blue Yonder, a cloudbased company that delivers automated, machine learning solutions in the Retail space. Why did I make this move? The LHC has yet to discover anything new – even the Higgs boson discovered in 2012 was about the same mass it was previously expected to be.

There's been a lot of hand-wringing about artificial intelligence and robots taking away jobs--by one recent estimate, AI could replace up to six percent of jobs in the U.S. by 2021. While most of those will be in customer service and transportation, a recent study suggests that at least one job requiring highly skilled labor could also be getting some help from AI: dermatologist. Susan Scutti at CNN reports that researchers at Stanford used a deep learning algorithm developed by Google to diagnose skin cancer. The team taught the algorithm to sort images and recognize patterns by feeding it images of everyday objects over the course of a week. "We taught it with cats and dogs and tables and chairs and all sorts of normal everyday objects," Andre Esteva, lead author on the article published this week in the journal Nature, tells Scutti. "We used a massive data set of well over a million images."

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As the EMR "space race" peaks, clinical and health leaders are coming to understand that digitising data does not, on its own, drive innovation or transformation. Many are wondering what's next. Looking ahead, the next wave in our journey towards digital transformation is Artificial Intelligence (AI). Simply put, Artificial Intelligence is a collection of systems that sense, comprehend, act and learn. The goal of AI in health is to drive greater "data dividends" than what we are getting from investments already made in EMRs and other systems.

DAVOS: Open markets and global trade have been blamed for job losses over the last decade, but global CEOs say the real culprits are increasingly machines. And while business leaders gathered at the annual World Economic Forum (WEF) in Davos relish the productivity gains technology can bring, they warned this week that the collateral damage to jobs needs to be addressed more seriously. From taxi drivers to healthcare professionals, technologies such as robotics, driverless cars, artificial intelligence and 3D printing mean more and more types of jobs are at risk. Adidas, for example, aims to use 3D printing in the manufacture of some running shoes. "Jobs will be lost, jobs will evolve and this revolution is going to be ageless, it's going to be classless and it's going to affect everyone," said Meg Whitman, chief executive of Hewlett Packard Enterprise.

Deep neural networks have evolved to be the state-of-the-art technique for machine learning tasks ranging from computer vision and speech recognition to natural language processing. However, deep learning algorithms are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. To address this limitation, deep compression significantly reduces the computation and storage required by neural networks. For example, for a convolutional neural network with fully connected layers, such as Alexnet and VGGnet, it can reduce the model size by 35x-49x. Even for fully convolutional neural networks such as GoogleNet and SqueezeNet, deep compression can still reduce the model size by 10x.

A team from the Stanford Artificial Intelligence Laboratory set up a machine-learning AI to teach itself to diagnose cancer by looking at skin lesions just as a doctor would during an exam. The team tested the algorithm against 21 board-certified dermatologists, and it performed just as well as its human counterparts. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," Sebastian Thrun, an adjunct professor in the Stanford Artificial Intelligence Laboratory, said in a statement. "That's when our thinking changed. That's when we said, 'Look, this is not just a class project for students, this is an opportunity to do something great for humanity.'"

The researchers tested the AI against 130,000 images, comparing the results to diagnoses of 21 clinicians. They say the result showed the software could detect the cancer with a high degree of accuracy. The findings were published in the academic journal Nature. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," said Sebastian Thrun from the Stanford Artificial Intelligence Laboratory, in a statement published by the university's website. "That's when our thinking changed. That's when we said, 'Look, this is not just a class project for students, this is an opportunity to do something great for humanity.'"

Google is intending to expand the dev tools available to makers using the Raspberry Pi microprocessor to power their projects this year -- potentially offering software tools for face- and emotion-recognition, speech-to-text translation, natural language processing, sentiment analysis, predictive analytics and more. The company is currently running a survey for Pi makers asking about the sorts of tools they would like it to develop. You can access the survey via the Raspberry Pi Foundation's website. "We at Google are interested in creating smart tools for Makers, and want to hear from you about what would be most helpful," it says in this survey. Tech areas that can be selected during the survey include home automation, drones, IoT, robotics, 3D printing, wearables and machine learning -- so the company is casting a pretty wide net here. We've reached out to Google and the Pi Foundation with questions and will update this post with any response.

Microsoft will increase its use of artificial intelligence (AI) in order to improve the company's products, chief executive Satya Nadella said when revealing the tech giant's latest financial results. The company behind the Windows PC software reported revenue of 24.1 billion US dollars (£19.1bn) in the three months to December 31, up on the 23.8 billion dollars (£18.9bn) it generated in the same period last year, an increase driven by the firm's cloud-based products, Nadella said. Since taking over as chief executive in 2014, Nadella has shifted Microsoft's focus to its cloud business and software and away from hardware including smartphones. "Our customers are seeing greater value and opportunity as we partner with them through their digital transformation," he said of the latest figures, which also included 5.2 billion dollars (£4.1bn) in net income. "Accelerating advancements in AI across our platforms and services will provide further opportunity to drive growth in the Microsoft Cloud."