Back in 2010, when the term "cloud computing" was still laden with peril and mystery for many users in enterprise and high performance computing, HPC cloud startup, Nimbix, stepped out to tackle that perceived risk for some of the most challenging, latency-sensitive applications. At the time, there were only a handful of small companies catering to the needs of high performance computing applications and those that existed were developing clever middleware to hook into AWS infrastructure. There were a few companies offering true "HPC as a service" (distinct datacenters designed to fit such workloads that could be accessed via a web interface or APIs) but many of those have gone relatively quiet over the last couple of years. When Nimbix got its start, the possibilities of running HPC workloads in the cloud was the subject of great debate in the academic-dominated scientific computing realm. As mentioned above, concerns about latency in the performance-conscious realm of these applications loomed large, as did the more general concerns about the cost of moving data, the remote hardware capability for running demanding jobs, and the availability of notoriously expensive licenses from HPC ISVs.

What are you doing yourself? We work for the Chief Data Officer of a CAC40 company who even decided to make his 2017 tagline as "Zero POC!". Machine Learning and Artificial Intelligence are not anymore reserved to Amazon, Facebook or Google. However, very few initiatives (less than 1/3rd) deliver some measurable ROI. To overcome this hurdle, it is however somewhat rather simple. For a change, do not start only investing hundred thousands or millions euros building a data lake… We quite often see that a couple of hundreds megabytes already offer very rich insights to train predictive models. And plugging a simple but well designed bot with powerful NLP (Natural Language Processing) to your legacy BI datawarehouses free up tremendous hidden value.

The new prototype drone from Amazon takes off vertically like a helicopter but flies from place to place horizontally, like an airplane. Flying machines are hard secrets to keep. By their very nature, they soar into the heavens, above the heads of those below. America's military tends to keep its secret planes secret by only flying them in vast swathes of empty desert, until they're ready for public debut. But that's not really an option for Amazon, which is testing delivery drones in the United Kingdom (while it attempts to weave its way through U.S. regulations).

Incremental clustering approaches have been proposed for handling large data when given data set is too large to be stored. The key idea of these approaches is to find representatives to represent each cluster in each data chunk and final data analysis is carried out based on those identified representatives from all the chunks. However, most of the incremental approaches are used for single view data. As large multi-view data generated from multiple sources becomes prevalent nowadays, there is a need for incremental clustering approaches to handle both large and multi-view data. In this paper we propose a new incremental clustering approach called incremental minimax optimization based fuzzy clustering (IminimaxFCM) to handle large multi-view data. In IminimaxFCM, representatives with multiple views are identified to represent each cluster by integrating multiple complementary views using minimax optimization. The detailed problem formulation, updating rules derivation, and the in-depth analysis of the proposed IminimaxFCM are provided. Experimental studies on several real world multi-view data sets have been conducted. We observed that IminimaxFCM outperforms related incremental fuzzy clustering in terms of clustering accuracy, demonstrating the great potential of IminimaxFCM for large multi-view data analysis.

A brain computer interface (BCI) is a system that measures brain activity and converts it into an artificial output which is able to replace, restore or improve any normal output (neuromuscular or hormonal) used by a person to communicate and control his/her external or internal environment. Thus, BCI can significantly improve the quality of life of people with severe neuromuscular disabilities [35]. Communication between the brain of a person and the outside world can be appropriately established by means of a BCI system based on eventrelated potentials (ERPs), which are manifestations of neural activity as a consequence of certain infrequent or relevant stimuli. The main reason for using ERP-based BCI are: it is noninvasive, it requires minimal user training and it is quite robust (in the sense that it can be use by more than 90 % of people) [34]. One of the main components of such ERPs is the P300 wave, which is a positive deflection occurring in the scalp-recorded EEG approximately 300 ms after the stimulus has been applied. The P300 wave is unconsciously generated and its latency and amplitude vary between different EEG records of the same person, and even more, between EEG records of different persons [18].

Multi-view data clustering refers to categorizing a data set by making good use of related information from multiple representations of the data. It becomes important nowadays because more and more data can be collected in a variety of ways, in different settings and from different sources, so each data set can be represented by different sets of features to form different views of it. Many approaches have been proposed to improve clustering performance by exploring and integrating heterogeneous information underlying different views. In this paper, we propose a new multi-view fuzzy clustering approach called MinimaxFCM by using minimax optimization based on well-known Fuzzy c means. In MinimaxFCM the consensus clustering results are generated based on minimax optimization in which the maximum disagreements of different weighted views are minimized. Moreover, the weight of each view can be learned automatically in the clustering process. In addition, there is only one parameter to be set besides the fuzzifier. The detailed problem formulation, updating rules derivation, and the in-depth analysis of the proposed MinimaxFCM are provided here. Experimental studies on nine multi-view data sets including real world image and document data sets have been conducted. We observed that MinimaxFCM outperforms related multi-view clustering approaches in terms of clustering accuracy, demonstrating the great potential of MinimaxFCM for multi-view data analysis.

While many large technology and car manufacturers are building self-driving cars from the ground up, an increasing number of off-the-shelf systems will allow plenty of other models to take to the road without a driver. The latest such project is a newly announced partnership between the GM tech spinoff Delphi Automotive and Israeli machine vision company Mobileye. Both companies are no stranger to self-driving car technology: they both supply sensors and software to big-name automakers, including the technology behind Volvo's vehicle detection systems and, until recently, Tesla's Autopilot. But while both companies work closely with car manufacturers--Mobileye is working with BMW to put an autonomous car on the road by 2021, for instance--other large automakers, such as Ford, are building systems in-house. Now, according to the Wall Street Journal, the pair plans to invest "several hundred million dollars" in developing an off-the-shelf autonomous driving system, presumably for use by automakers who don't have the capacity or inclination for such research and development. The collaboration promises to demonstrate a system that will allow cars to autonomously navigate challenging road conditions--such as roundabouts or turns across multiple traffic lanes--as soon as January.

VCs are getting serious about space-related startups, and there are some truly exponential growth opportunities in the SpaceTech ecosystem. But the majority of money that went into SpaceTech last year was in just two deals -- a 1 billion fundraise for SpaceX and a 500 million raise for OneWeb. If you ignore those as outliers, SpaceTech funding in 2015 was only around 300 million. The segment of startups seeing the most VC attention is the earth observation (EO) segment. Companies building earth observation (EO) satellite constellations (basically, cameras put into orbit and photographing the Earth on a regular basis) pulled in more than half the SpaceTech funding from 2012 to 2015 and 72% in 2015.

A spin-out company from the University of Oxford called Oxbotica has developed a new software system for making regular cars into driverless vehicles. The system, called Selenium, can ingest data from visual cameras, laser scanners, or radar systems. It then uses a series of algorithms to establish where the "it" is, what surrounds it, and how to move. "It takes any vehicle and makes it into an autonomous vehicle," explains Paul Newman, a professor at the University of Oxford and cofounder of Oxbotica. That sounds ambitious, but he's being serious: the team plans for the software to be used to control not just autonomous cars, but warehouse robots, forklifts, and self-driving public transport vehicles. Most systems being developed by other manufacturers rely on building a system that is robust enough to handle driving from the moment they are first switched on.

Originally published by Sramana Mitra on LinkedIn: Future Of Artificial Intelligence - Triumph Of Communism? I have written several pieces already on my deep concerns about the kind of society we're moving towards in the next 30-50 years as technology-induced changes sweep through society, rendering hundreds of millions of people unemployable. It seems to me that the end game in this thought experiment is the triumph of communism. A Universal Basic Income provides for the basic needs of human beings - food, shelter, clothing - and keeps society from imploding through crime and revolution. I am sure there will be interesting mechanisms to facilitate this process of vegetating - immersive computer games, ever-addictive social media, etc. Note, however, no one can afford anything beyond the basics, so don't think the entertainment industry will be thriving either.