I am a transitional research fellow in the Digital Creativity Hub at the University of York working on Artificial Intelligence (AI), data mining and machine learning for digital games and interactive media. I am also a member of the Artificial Intelligence and Games groups, in the Department of Computer Science. My research is focussed on using games to push boundaries in the capabilities of modern AI and making state of the art methods accessible to the industry to encourage a new generation of intelligent games.

The "photonic time stretch" was invented by Professor Barham Jalali, who holds a patent for this technology, and its use in microscopes is just one of many possible applications. It works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly – in nanoseconds, or billionths of a second – that the images would be too weak to be detected and too fast to be digitised by normal instrumentation. The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitised at a rate of 36 million images per second. It then uses deep learning to distinguish the cancer cells from healthy white blood cells. Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data, with the goal of achieving accurate decision making.

For both humans and machines, understanding the visual world requires relating new percepts with past experience. We argue that a good visual representation for an image should encode what makes it similar to other images, enabling the recall of associated experiences. Current machine implementations of visual representations can capture some aspects of similarity, but fall far short of human ability overall. Even if one explicitly labels objects in millions of images to tell the computer what should be considered similar--a very expensive procedure--the labels still do not capture everything that might be relevant. This thesis shows that one can often train a representation which captures similarity beyond what is labeled in a given dataset.

A recent acquisition looks to bring artificial intelligence and deep learning capabilities to the CRM powerhouse. Marketers using Salesforce products may soon find artificial intelligence–enabled features rolling out across the CRM platform due to the company's acquisition of AI and deep learning technology service MetaMind. MetaMind CEO Richard Socher announced the merger through a company blog post. The acquisition will ostensibly infuse Salesforce's existing services with MetaMind's natural language and deep machine learning software, which can reportedly analyze images, as well as text and sentiment. "At MetaMind, we've always been excited to bring breakthrough AI to high impact use cases. I can't think of a better place to have impact with AI than Salesforce and its many existing and future products," Socher said in a separate statement.

Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov, and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can. Go is played on a far larger board (19 by 19 squares, compared to 8x8 for chess) and has more possible moves than there are atoms in the universe, so raw computing power was unlikely to beat a human with a strong intuitive sense of the best moves. Instead, AlphaGo was designed to win by playing a huge number of games against other programs and adopting the strategies that proved successful. You could say that AlphaGo evolved to be the best Go player in the world, achieving in only two years what natural selection took millions of years to accomplish.

GE's electronic work instructions with the Google Glass by Novotek: Novotek combined GE's electronic work instructions with the Google Glass wearable computing device, and was demonstrated to Summit attendees in the Technology Fair. Novotek, is the largest European distributor for GE's Intelligent Platforms business and it has been awarded the Scanautomatic Prize for Innovation at Scanautomatic 2014 in Gothenburg, Sweden in October. Novotek has since 1986 worked with integration of IT and automation systems in the process and production industry. Novotek mainly supplies world-leading products and solutions from GE in the Nordics and Benelux. A work process management solution, GE's Proficy Workflow software provides users with interactive, step-by-step task instructions and captures process, traceability and quality data across systems to reduce errors, waste and delays.

Businesses and developers will be able to make their services available inside Messenger by way of Chat SDK. Powered by artificial intelligence, chatbots are computer software programs that mimic human conversations. Facebook says three times as many messages are sent on its platforms than SMS, with 60 billion messages a day sent and received on Facebook Messenger and WhatsApp. The news comes just weeks after Microsoft devoted a large chunk of its Build developer conference keynote to what its executives called "conversations as a platform". AI is already used in Messenger, and can do things like recognise faces in pictures to suggest potential recipients.

In keeping with its vision of an era of cognitive computing enabled by acceleration technology, IBM Research (NYSE: IBM) today announced plans for a multi-year collaboration with the University of Illinois Urbana-Champaign to create the Center for Cognitive Computing Systems Research (C3SR) which will be housed within the College of Engineering on the Urbana campus. IBM has big ambitions for the center: "C3SR will build and optimize integrated systems such as state-of-the-art cognitive computing systems modeled on IBM's Watson technology that can master a subject area by learning from multimedia and multi-modal educational content. Such systems will efficiently ingest vast amounts of data including videos, lecture notes, homework, and textbooks, and reason through this knowledge effectively enough to be able to eventually pass a college level exam." Many details are yet to be worked out. The level of funding and size of installation will be announced this summer when the new center formally opens, said Hillery Hunter, a project driver and the director for systems acceleration and memory at IBM Research.

One of these target audiences is university students(undergraduate or graduate) learning about machine learning, including those who are beginning a career in deep learning and artificial intelligence research. The other target audience is software engineers who do not have a machine learning or statistics background, but want to rapidly acquire one and begin using deep learning in their product or platform. Basically, if you are interested in reading this book and haven't been turned off by the content of this post, the book is likely for you. The book starts off covering the required background for understanding later material, along with historical context and elementary explanations of the technical concepts. In fact, the entire first part of the book is dedicated to building the technical foundation required to study deep learning.

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification.