SILICON has been making our computers work for almost half a century. Whether designed for graphics or number crunching, all information processing is done using a million-strong horde of tiny logic gates made from element number 14. But silicon's time may soon be up. Moore's law – the prophecy which dictates that the number of silicon transistors on microprocessors doubles every two years – is grinding to a halt because there is a limit to how many can be squeezed on a chip. The machine-learning boom is another problem. The amount of energy silicon-based computers use is set to soar as they crunch more of the massive data sets that algorithms in this field require.

Just what is meant by artificial intelligence? It has only been in recent years that we ve come to see artificial intelligence as a reality and not something out of a science fiction story. Even now, we re still struggling to come up with an adequate definition of the term artificial intelligence which isn t surprising when you consider that after thousands of years, humans can t even decide on a definition for intelligence. Put one way, artificial intelligence is a term given to computer systems that attempt to simulate human intelligence and learning. But even that definition is too big to wrap your head around.

BARCELONA, SPAIN – Newfound enthusiasm for the latest technologies, such as drones and smartphones, to improve the way aid is provided to people in disasters may be overblown, experts warn. The annual World Risk Report from the United Nations University (UNU) highlights the growing interest in new technologies to improve emergency response -- from drones that can survey crisis-hit areas to social media networks that allow survivors to communicate with the wider world. These can provide important information to the logisticians who organize aid delivery or health workers trying to track deadly diseases like Ebola in no-go areas, the report said. But Matthiasƒ Garschagen, a risk management expert with the UNU Institute for Environment and Human Security (UNU-EHS), said it could not substitute for the basic infrastructure some countries have lacked for decades. "Too many people see technology as the main panacea for solving all the problems you have after disasters strike," he told the Thomson Reuters Foundation.

Fintech reloaded maps out a strategy showing how traditional banks should become a digital platform.

Machine and statistical learning wizards are becoming more eager to perform analysis with Spark ML library if this is only possible. It's trendy, posh, spicy and gives the feeling of doing state of the art machine learning and being up to date with the newest computational trends. It is even more sexy and powerful when computations can be performed on the extraordinarily enormous computation cluster - let's say 100 machines on YARN hadoop cluster makes you the real data cruncher! In this post I present sparklyr package (by RStudio), the connector that will transform you from a regular R user, to the supa! Moreover, I present how I have extended the interface to K-means procedure, so that now it is also possible to compute cost for that model, which might be beneficial in determining the number of clusters in segmentation problems.

In the last few years, you cannot have a discussion around technology without those terms entering the conversation. They have been major technology disruptors impacting all aspects of the business. Change seems to occur at breakneck speeds and shows no sign of slowing. Today, it appears the one constant in technology is change. Constant change requires constant innovation which thereby introduces more new technologies.

As more cyber-security threats arise every day, extensive research into prevention and detection schemes is being conducted globally. One of the issues faced is keeping up with the sheer mass of new emerging threats online. Traditional detection schemes are rule or signature based. The creation of a rule or signature relies on prior knowledge of the threats structure, source and operation, making it impossible to stop new threats without prior knowledge. Manually identifying all new and disguised threats is too time-consuming to be humanly possible.

Private conversations and moments might not be so private anymore following CIA's latest plan. A CIA-linked firm is reportedly joining forces with Amazon. This is to spy on earth in an unprecedented detail. The firm known to be closely associated with the US Intelligence agency, CosmiQ Works, is working with Amazon and DigitalGlobe, a satellite mapping firm. The trio will be training artificial intelligence with an algorithm to find out what exactly is happening on the surface of the earth.

Elias G. Bekele, PhD, Hydrologist with the Institute of NaturalResources Sustainability at UIUC, has published several articlesin peer-reviewed journals and conference proceedings. Dr. Bekeleis Honorable Mention Recipient in the 2007 UCOWR BestDissertation Award and is the Runner-up winner in the 2008 SIUCOutstanding Dissertation Award.

We recently had the opportunity to sit down with Kris Hammond, the Chief Scientist for Narrative Science. Narrative Science focuses around automating text generated from data, turning raw data into insightful accounts. Hammond has spent over 20 years working in and developing the AI labs at the University of Chicago and Northwestern University, making him uniquely placed to offer perspectives on the past, present and future of AI. In the first part of our discussion, we discussed the technologies which will shape the future of machine learning; in this installment, Hammond discusses the future of AI, and whether or not robots could actually wipe out humanity and steal our jobs. When we talk about AI, almost anyone you talk with will say that they think that AI image- the genuine artificial intelligence that is building a system as intelligent, if not more intelligent than a human being- is simply not feasible or possible.