The relationship between the human mind and body is something that has occupied philosophers at least since the father of modern philosophy, René Descartes, bequeathed his notorious "dualism" to his successors. Low-power machine vision company Movidius has teamed up with thermal imaging company FLIR Systems, bringing Artificial Intelligence capabilities to Boson, FLIR's latest thermal-imaging camera core. FLIR will now integrate the Myriad 2 Vision Processing Unit into its thermal core to create the most intelligent thermal imaging solution to date. When artificial intelligence technology intersects with abundant oil and gas seismic data, the outcome could yield a more accurate depiction of what lies beneath the surface, enabling cash-strapped drillers to better target sweet spots and maximize returns.It's all based on algorithms that essentially teach computers how to solve complex problems-in this instance, how to quickly and accurately find subsurface faults that lead to lucrative hydrocarbon discoveries. In previous articles, we've talked about the merits of artificial intelligence and big data and how these technologies can enable a multitude of industries to begin learning how to do things more effectively.

When British mathematician Sir Andrew J. Wiles was awarded the Abel Prize Laureate in math on 15 March for cracking a centuries-old hypothesis, a friend asked me, "Why did he get the prize, and will this solve any real-world problem?" Quoting from the statement that the Norwegian Academy of Science and Letters gave to the press, I told him that 63-year-old Wiles had been given the annual award "for his stunning proof of (French mathematician Pierre de) Fermat's last theorem by way of the modularity conjecture for semi-stable elliptic curves, opening a new era in number theory". So let me try to simplify it a bit. Number theory--also sometimes referred to as the "queen of mathematics" or "higher arithmetic"--is a branch of pure math, devoted primarily to the study of the properties of whole numbers. Fermat--a prominent mathematician of the 17th century--contributed significantly to number theory, probability theory, analytic geometry and the early development of infinitesimal calculus. Fermat's last theorem states that no three positive integers a, b, and c satisfy the equation an bn cn for any integer value of n that is greater than two.

The secret to big data is of course the ability to do work in parallel. Modern Big Data engines like Hadoop don't rely on the invention of clever new algorithms or artificial intelligence to produce impressive results; instead, they are based on the idea of taking lots of inputs, working on little pieces of it in lots of places at the same time, then bringing the results together. Usually, the results are much smaller than the inputs, small enough that human beings can look at them directly. In order to work on lots of small pieces at the same time, whatever task we're performing has to be structured to be run in parallel. Many algorithms we're used to seeing work well sequentially have to be tweaked at least a little to work in parallel, and some have to be discarded as unusable in parallel.

Intelligent Machines and the Future of Recruitment is the conference, organised by Textkernel in honour of its 15th anniversary, that explores the impact of rapidly evolving machine intelligence on the future of people and jobs. Among the speakers are Glen Cathey (Kforce), Behshad Behzadi(Google), Federico Pistono (author), Maarten de Rijke (University of Amsterdam),Martin le Vrang (ESCO), Perry Timms (Media Zoo), Ton Sluiter (USG People),Balazs Paroczay (Randstad Sourceright) and Prof. Dr. Armin Trost (Furtwangen University). "The rise of machine learning, search engines, semantic technologies and the large amounts of available information are changing the labour market," says Jakub Zavrel, CEO of Textkernel. "When I started the company 15 years ago, the use of AI in recruiting was still in its infancy. Companies like us have been making AI and semantic search technology part of the mainstream. What better way to celebrate Textkernel's anniversary than to organise a conference to spark the discussion on how artificial intelligence will evolve and change the way we hire and work."

The future of food looks a lot like advanced animal product substitutes; we've already gone beyond tofurkey to plant-based burgers that "bleed." Down in Santiago, Chile, a five-person startup is using machine learning to figure out how to create its own versions of vegetarian substitutes for animal products. Called the Not Company (or NotCo), the one-year-old company is rolling out its first products -- NotMilk, NotMayo. "All I can tell you is that there are some star ingredients ranging from legumes to flowers," NotCo cofounder Matias Muchnick tells Tech Insider. Machine learning, the programming technique where algorithms learn from data sets, has become the hot new thing in Silicon Valley.

CommerzVentures, the fintech venture capital fund of Commerzbank, has released a white paper highlighting the key technologies which it believes will transform the insurance industry. Aimed at providing insights into their potential uses in the insurance sector, CommerzVentures' 'Emerging Technologies Transforming the 4tn Insurance Industry' paper explores how the insurance chain value will be transformed by technological innovations. Innovations such as artificial intelligence, connected devices, drones, blockchain tech, among others, are enabling new value propositions and distribution methods, the firm says. Effectively cooperating with startups may be the only way for incumbent insurers to fend off potential competitors such as Google, Amazon, Facebook and other non-traditional players, it argues. Generating over US 4 billion in global revenue, insurance is one of the two major sectors within fintech and the largest long-term opportunity, and yet insurtech companies have received 12 times less funding than bankingtech.

Persado is a computerized system that writes natural language to obtain direct marketing goals: to consistently inspire action in any given audience. Our automated machine-learning platform tests millions of words, phrases, and images; collects data; and understands, at scale, consumer reactions to targeted language in calls to action. The engine of the commercial internet is propelled by short, digital marketing messages. Persado is its first qualified driver.

They tell a story, which gives the photos context and additional emotional meaning. A paper published by Microsoft Research describes an image captioning system that mimics humans' unique style of visual storytelling. Companies like Microsoft, Google, and Facebook have spent years teaching computers to label the contents of images, but this new research takes it a step further by teaching a neural-network-based system to infer a story from several images. Someday it could be used to automatically generate descriptions for sets of images, or to bring humanlike language to other applications for artificial intelligence. "Rather than giving bland or vanilla descriptions of what's happening in the images, we put those into a larger narrative context," says Frank Ferraro, a Johns Hopkins University PhD student who coauthored the paper.

Andrew Moore was a professor of computer science and robotics at Carnegie Mellon University for a dozen years when Google hired him away in 2006 to lead some of its efforts around ad targeting and fraud prevention. CMU lured Moore back in 2014, making him the dean of its computer science school. But he still understands well what goes through his colleagues' minds when industry comes calling, and he says the battle to keep them in academia grows fiercer by the year. Earlier today, we talked with Moore about Uber, which famously raided the school's robotics department a year ago, poaching 40 of its researchers and scientists. We also talked about how Moore entices people to stay, and the newest new thing his 2,000-student school is focused on right now.

I recently read an article on robotics by a fellow intern. He cited an example of a flying bird robot developed by Festo Industries' Bionic Learning Network. It is an autonomous ornithopter. While this is certainly an impressive achievement, because they have deciphered the flight of birds, something even more interesting has been going on in the field of machine learning. What is difficult is making them learn how to do things on their own and improve their performance independently.