"Really, we're building collision avoidance for industrial drones," said Alexander Harmsen, CEO and co-founder of Iris Automation. "We see this huge need for industrial drones for mining exploration, pipeline inspection, agricultural surveying, forestry, or even package delivery." Without a way to avoid mid-air collisions, drones risk crashing into a Cessna, a flock of geese or a 747. Worst case scenario: a drone gets sucked into a jet engine causing catastrophic engine failure as high-velocity bits of metal penetrate fuel tanks, hydraulic lines and the cabin. Iris Automation's solution is an AI computer that blends real-time images and 3D maps to track incoming objects.

First, it is important for procurement organisations and their leaders to embrace the reality and potential for AI and cognitive procurement. Understand that, like most technologies, AI may bring changes, but it also presents significant opportunities. Next, based on the capabilities outlined above, think about what projects or processes in your organisation could most benefit from cognitive procurement. As you apply AI to certain procurement tasks and processes, you'll begin developing internal capability and expertise. It will also change the profile and enhance the skill set of your procurement professionals.

Google has announced that it had acquired a visual recognition machine learning technology start-up, Moodstocks for an undisclosed amount. Incorporated in 2009, the French start-up originally introduced on-device image recognition in 2012, which enables smartphones to automatically recognize the content their camera detects. With the recent acquisition, Google had made a substantial investment in the machine learning technologies since accurate object recognition is one of the difficult problems for machine learning. For the past 3 years, the small team of researchers and engineers based in Google has taken advantage of deep learning to extend the reach of their object recognition algorithms, licensing machine-readable executable object code including the launch of a software development kit for OEMs to enable them to embed the code into their products. The Moodstocks API, meanwhile, enable users to integrate visual search into their applications in addition to analyzing the images related to color, shape, and texture.

Introduction This is the first in a series of posts exploring artificial neural network (ANN) implementations. The purpose of the article is to help the reader to gain an intuition of the basic concepts prior to moving on to the algorithmic implementations that will follow.

Christopher Crosbie is a Healthcare and Life Science Solutions Architect with Amazon Web Services. This post is co-authored by Gopal Wunnava, a Senior Consultant with AWS Professional Services. SparkR is an R package that allows you to integrate complex statistical analysis with large datasets. In this blog post, we introduce you running R with the Apache SparkR project on Amazon EMR. The diagram of SparkR below is provided as a reference, but this video provides an overview of what is depicted.

A new release out of Evans Data reports, "Over a third (36%) of all developers who are actively working on Big Data or advanced analytics projects now use elements of machine learning according to Evans Data's recently released Big Data and Advanced Analytics survey report. While the market for machine learning is still fragmented, those developers actively working with machine learning are most likely to be targeting financial sectors, Internet of Things, or manufacturing. The survey of over 500 developers actively working with Big Data also showed that decision trees are the most used analytical model which links in closely with artificial intelligence and machine learning development. Linear regression and logistics regression were the next most cited analytical models. Logistics, distribution, or operations were the company departments most likely to be using advanced data analytics or Big Data solutions."

People on the streets of London, Düsseldorf, Bern, and other European cities will soon see robots rolling along the sidewalk to deliver prepared food, parcels, and retail goods to nearby customers. Starship Technologies, a robotics company launched two years ago by Skype cofounders Ahti Heinla and Janus Friis, says it plans to announce on Wednesday four industry partners that will be testing its delivery robots: Just Eat, a European food delivery company; Hermes, a German parcel delivery company (not to be confused with the similarly named French luxury goods maker); Metro Group, a major German retailer; and Pronto.co.uk, a food delivery service based in London. The four companies later this month will begin tests with real customers to assess the viability of automated product deliveries. A similar program is being developed for cities in the US. Starship has been conducting proof-of-concept tests without real customers for the past nine months.

Artificial intelligence that can understand and answer any work-related question it is asked has been made available in the UK for the first time. The computer software, called Starmind, uses machine learning to understand queries, then source answers from previous staff conversations on a subject or track down experts within the company who are able to help. Its creators refer to it as'brain technology', adding its aim is to become a central knowledge bank within any company, an instant database of information that can be accessed by anyone. AI software which understands and answers work-related questions has been made available in the UK. Starmind is an artificial intelligence software for the workplace, designed in Switzerland.

For more than a decade the company formerly known as Google, latterly rebranded Alphabet to illustrate the full breadth of its A to Z business ambitions, has engineered an annually increasing revenue generating empire which last year pulled in 75 billion. And it's done this mostly by mining user data for ad targeting intel. Slice it and dice it how you like but Google's business engine needs data like the human body needs oxygen. Most of its products are thus designed to remove friction to accessing more user data; whether it's free search, free email, free cloud storage, free document editing tools, free messaging apps, a fuzzy social network that no one loves but which is somehow still hanging around, free maps, a mobile OS platform that OEMs can load onto smartphone hardware without paying a license fee… Most of what Google builds it opens to all comers to keep the data pouring in. The bits and bytes must flow.

Drowsy driving is notoriously tough to detect. There's no test to prove it, the way a breathalyzer can prove someone was driving drunk. But technology to detect drowsy driving is in the works. In commercial transport, one industry is leading the way: mining. The stakes are particularly high in this field since the enormous haul trucks used in mining are several times the height of a person.