Imagine unleashing the power of artificial intelligence to automate a critical component of biomedical research, expediting life-saving research in the treatment of almost every disease from rare disorders to the common cold. This could soon be a reality, thanks to the fourth Data Science Bowl, a 90-day competition in which, for the very first time, participants trained deep learning models to examine images of cells and identify nuclei, regardless of the experimental setup--and without human intervention. Algorithms developed in this competition could save researchers hundreds of thousands of hours of effort per year. This year, the competition brought together nearly 18,000 global participants, the most ever for the Data Science Bowl. Collectively, they submitted more than 68,000 algorithms and worked an estimated 288,000 hours to automate the vital, but time-consuming, process of nuclei detection.

Microsoft's Surface Hub 2 is a beautiful bit of kit but it's a vision of the future that feels far removed. Speaking today at the Katapult Future Festival in Oslo on the subject of the future of work, Microsoft's vision feels removed from reality and a little bit farfetched. Put simply, if this puppy isn't about $1000 - and the Verge reports it'll be in line with competitor products so that's $4000 or so - you've just shelled out for a whiteboard that does pretty much what a$300 laptop can do. I'm not seeing anything other than office porn here..the rousing Westworld-esque music confirms it. The video shows a vision of the future for offices you wished you worked in but actually don't.

Helsinki University and tech strategy firm Reaktor say they want to make Finland the world's most educated country in the field of artificial intelligence. The academic and business partners say they want Finland to become forerunners in AI, and have developed an online course covering the quickly-growing technology open to anyone, free of charge. "The Elements of Artificial Intelligence" online course is entirely in English and offered to people who are interested in learning more about AI. User interface designer at Reaktor Janina Fagerlund says people might not know it, bu their lives are already affected - one way or another - by AI every single day. As a perhaps unexpected example, Fagerlund says that AI is used in industrial food production to sort produce and other items at food processing facilities.

Have you ever heard about Wikidata? If not, you might think of Wikipediafirst -- and that is not wrong. Wikidata is also a project of the Wikimedia Foundation. "Wikidata acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia (…)." Loosely, you could describe Wikidata as Wikipedias database with over 46million data items (April 2018). And in line with Wikimedia's mission, everyone can add and edit data, and use it for free.

When Google DeepMind researchers trained a neural network to tackle a virtual maze, it spontaneously developed digital equivalents to the specialized neurons called grid cells that mammals use to navigate. Not only did the resulting AI system have superhuman navigation capabilities, the research could provide insight into how our brains work. Grid cells were the subject of the 2014 Nobel Prize in Physiology or Medicine, alongside other navigation-related neurons. These cells are arranged in a lattice of hexagons, and the brain effectively overlays this pattern onto its environment. Whenever the animal crosses a point in space represented by one of the corners these hexagons, a neuron fires, allowing the animal to track its movement.

Darktrace has become a rarity in the British tech scene: a Unicorn. The cybersecurity company, which provides what it calls a network "immune system" powered by artificial intelligence, hit a $1.25 billion valuation last month, two sources close to the deal told Forbes. The new valuation came after a secondary round of financing in which former investors sold off their stakes. Vitruvian Partners, sources said, is the acquirer of the stock. How did Darktrace find itself at the vaunted Unicorn status?

DeepMind created an AI which spontaneously developed the machine learning equivalent of gut-based navigation. The UK-based Google sister-company seems to specialize in creating machine learning experiments designed to determine if AI can inform the field of neurology, and vice versa. DeepMind recently published a paper demonstrating a neural network that, upon trying to solve a navigational problem, developed a method of spatial awareness that imitates the creation of "Grid Cells" in mammals. Grid Cells, which were discovered in 2005, are a little-understood phenomena that occur within mammal brains to aid with navigation. Basically, our ability to generally understand where we are based on how far we've traveled and in what direction, is governed by these specialty cells that form in hexagon-shaped patterns that the brain sort of overlays into space, causing neurons to fire when we move through it.

Before reading the following dialogues, it can be guaranteed that although anonymised, every one of these small "scenes" have happened in the last three years. They have in fact happened many times, on a daily basis, with most of the brilliant people I come across as applicants, students and alumni! Me: "Why are you applying to a Data Science programme?" Random Applicant (Maths Graduate): "I am fascinated by artificial intelligence and its potentials" Me: "How are you with programming?" Random Applicant (Maths Graduate): "Mmm, IT is not really my thing."

Digital Curator Mia Ridge writes: in this guest post, Dr Giles Bergel describes some experiments with the Library's digitised images... The University of Oxford's Visual Geometry Group has been working with a number of British Library curators to apply computer vision technology to their collections. On April 5 of this year I was invited by BL Digital Curator Dr. Mia Ridge to St. Pancras to showcase some of this work and to give curators the opportunity to try the tools out for themselves. Computer vision - the extraction of meaning from images - has made considerable strides in recent years, particularly through the application of so-called'deep learning' to large datasets. Cultural collections provide some of the most interesting test-cases for computer vision researchers, due to their complexity; the intensity of interest that researchers bring to them; and to their importance for human well-being.

Regardless of how artificial intelligence (AI) is defined, there is little doubt that this resource can be of great value, especially in big data applications. Undoubtedly, AI is fast becoming a major technological tool for prescriptive analytics, the step beyond predictive analytics that helps us determine how to implement and/or optimize optimal decisions. In business applications, it can assess future risks, quantify probabilities and in so doing, give us insights how to improve market penetration, customer satisfaction, security analysis, trade execution, fraud detection and prevention, while proving indispensable in land and air traffic control, national security and defence. There are also a host of healthcare applications such as patient-specific treatments for diseases and illnesses. Recently, the popular concept of "Singularity" was perceived by computer scientists.