Financial markets, throughout their evolution, have always been susceptible to manipulations and various unscrupulous activities. The history can be traced back as far as 600 BC when a Greek merchant borrowed money from public to grow corn. The lenders were assured of repayment along with interest when the product was sold. In case of failure to repay on time, the lenders could acquire merchant's cargo along with the boat. The fraud designed by the borrower was to sink the empty boat and keep both the money and corn.

Artificial intelligence (AI) made the leap from science fiction to the corporate world some time ago. Amazon and Netflix use it routinely to make purchasing recommendations, iPhone users speak to Siri every day, and banks give investment advice or calculate risks thanks to these technologies. But these are only the first hesitant steps of AI, which is due to have a major impact on the financial sector, as revealed in this report in the magazine Euromoney, and featuring an interview with Marco Bressan, Chief Data Scientist at BBVA. Artificial Intelligence has been present in the financial industry for many years now, Marco Bressan, Chief Data Scientist at BBVA, tells Euromoney: "Currently it denotes a vision of the future; an aspect of the sci-fi imagination; something that you still can't do. But the truth is senior financial executives have been doing AI-related work, research and deployment of products for years", he notes. When we talk about Artificial Intelligence we refer to a set of technologies –many created decades ago– rather than one single product or system.

How many robots does it take to open a door? If the robots are trying to figure out how to do the task from scratch, then it helps to have as many as possible involved. In three separate research papers posted online Monday, researchers at Google and other Alphabet subsidiaries showed several ways in which robots can learn to perform simple tasks more quickly by sharing different types of learning experiences. The researchers are training teams of industrial robots to perform simple tasks using a technique called reinforcement learning, which combines trial and error with positive feedback. For the moment, these tasks are extremely simple, like opening doors or nudging objects around.

The world's first laundry sorting and folding robot will go on sale in 2017, its manufacturer said on Tuesday at the Ceatec electronics show just outside of Tokyo. Laundroid is the size of a large refrigerator and has a pull-out drawer near its base where unsorted clothes can be thrown in. A robot inside the device picks up each item of clothing and uses image analysis with artificial intelligence to figure out what kind of clothing it is so it knows the correct way to fold it. For humans, identifying and folding laundry is an easy albeit mundane task, but for a machine it's very difficult. That's reflected in the size of the device and its speed. During a demonstration on Tuesday it took about 10 minutes to pick out one garment, identify it and fold it.

In the summer of 2008, I noticed a mole on my arm that seemed to be getting bigger. It was hard to tell, though. I wasn't sure if it had actually grown -- or if I was just freaking out and being a hypochondriac for no good reason -- so I decided to have it checked out. Doing so required me to call a clinic, set up an appointment, wait for a few days, and then drive to the doctor's office. Once I was there, a woman with more than eight years of specialized medical education look a long, hard look at the mole and asked me a series of questions about it -- but when it was all said and done, she didn't have a definitive answer for me. Instead, she just referred me to different doctor who had more experience with melanoma, and the whole process started over again. It ended up being nothing, but the second doctor told me to keep an eye on it just to be safe. Fast-forward eight years, and I'm still keeping an eye on it -- but my methods have become a bit more sophisticated. Now, every few months, I pull a smartphone out of my pocket, fire up an application called SkinVision, and snap a picture of the mole.

Artificial intelligence is, of course, all the rage in tech circles, and the press is awash in tales of AI entrepreneurs striking it rich after being acquired by one of the giants, often early in the life of their startups. As always, the reality of building a startup is different, especially when one aims to build a self-standing company for the long term. The path to success in AI requires not just technical prowess but also careful thinking and execution through a range of strategic and tactical questions that are specific to this domain and market. One possible framework to think through these topics is this "5P"list: Positioning (finding blue ocean), Product, Petabytes (data), Process (social engineering) and People. This week at the excellent O'Reilly Artificial Intelligence Conference, I covered those topics (as much as a 40 minute presentation allows), with the help of Peter Brodsky, CEO of HyperScience.

In this blog post, we welcome ex-NGDATA collaborator and now university professor Willem Waegeman who reports on a scientific research project he worked on part-time while working with us. NGDATA takes pride in supporting research to advance the field of machine learning. If you want to learn more about our offerings in this area, take a look at our Lab and do not hesitate to contact us. While 2012 has been the year of Big Data technologies, 2013 is becoming the year of Big Data analytics. Gathering and maintaining large collections of data is one thing, but extracting useful information from these collections is even more challenging.

Remember that endangered anteater-esque ball of scales from Favreau's recent film, The Jungle Book? Over one million pangolins have likely been poached and illegally traded in the last decade, especially because of their importance in Chinese medicine and food. And the internet hasn't exactly helped its plight. As wildlife trade monitoring network TRAFFIC reports, their researchers investigated 39 Chinese e-commerce websites over June and July 2016; a single survey in the first month alone detected 153 ads for pangolin scales and meat and live specimen from 94 traders across six sites. Virtual wildlife trafficking poses a serious threat to not just the pangolin.

Five major technology companies said Wednesday that they had created an organization to set the ground rules for protecting humans -- and their jobs -- in the face of rapid advances in artificial intelligence. The Partnership on AI, unites Amazon, Facebook, Google, IBM and Microsoft in an effort to ease public fears of machines that are learning to think for themselves and perhaps ease corporate anxiety over the prospect of government regulation of this new technology. The organization has been created at a time of significant public debate about artificial intelligence technologies that are built into a variety of robots and other intelligent systems, including self-driving cars and workplace automation. The industry group introduced a set of basic ethical standards for engineering development and scientific research that its five members have agreed upon. In a conference call on Wednesday, five artificial intelligence researchers representing the companies said they thought the technology would be a major force in the world for social and economic benefits, but they acknowledged the potential for misuse in a wide variety of ways.

Put on your QUIZ hats, cyborgs, robots, and natural humans!! This episode we're rejoined by futurist Alexandra Whittington, to quiz us on AI (Artificial Intelligence) and BlockChain (most commonly known as the technology underlying BITCOIN). Play along while you listen, see if you are up on these exciting new technologies. Oh, and also we complain about old people, selfies and Facebook too… c'mon along for some futurist-y goodness.