The receptionist at the Institute of Media Innovation, at Singapore's Nanyang Technological University, is a smiling brunette called Nadine. From a distance, nothing about her appearance seems unusual. It's only on closer inspection that doubts set in. Nadine is an "intelligent" robot capable of autonomous behaviour. For a machine, her looks and behaviour are remarkably natural.

Armando Gonzalez has got a problem. The CEO of Ravenpack, a company which uses artificial intelligence to turn news and social media into usable indicators for financial services firms, is struggling to hire one particular species of coder: Lisp (formerly known as LISP) specialists. There just aren't enough of them to go around. "We're very actively hiring in data science," says Gonzalez. "Our team is going to grow by 20% to 30% this year and we're looking for data science specialists and developers who work across everything from Python to Lisp, but Lisp professionals are very hard to find."

As we discussed in a previous article, "Analytics in The Stock Market: Made for Each Other," the financial services industry would seem to be a particularly good fit for current advances in artificial intelligence (AI) and machine learning. After all, financial services are based on understanding risk and balancing a wide range of numeric factors as well as predicting trends. However, uptake of machine learning and AI has been relatively slow in this industry. The chief reason is the need to maintain a conservative outlook and to accommodate a wide range of processes and systems based around legacy information technology. Despite this, we will likely see some change soon.

British adults feel more stressed about the prospect of losing their smartphone than they do about Brexit, according to a new study conducted by the Physiological Society. The Stress in modern Britain survey asked people to rate how stressful they find – or imagine they would find – 18 different life events, with the Physiological Society using the results to assign an average score to each one from a scale of zero to ten, with zero meaning'Not at all stressful' and ten'Very stressful'. Smartphone loss came 14th on the list, with a score of 5.79, making it more stressful than Brexit (4.23), but slightly less stressful than terrorist threats (5.84). The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar. Japan's On-Art Corp's CEO Kazuya Kanemaru poses with his company's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' and other robots during a demonstration in Tokyo, Japan Japan's On-Art Corp's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' performs during its unveiling in Tokyo, Japan Singulato Motors co-founder and CEO Shen Haiyin poses in his company's concept car Tigercar P0 at a workshop in Beijing, China A picture shows Singulato Motors' concept car Tigercar P0 at a workshop in Beijing, China Connected company president Shigeki Tomoyama addresses a press briefing as he elaborates on Toyota's "connected strategy" in Tokyo.

Authors: Lili Jiang, Shuo Chang, and Nikhil Dandekar In order to build a high-quality knowledge base, it's important that we ensure each unique question exists on Quora only once. Writers shouldn't have to write the same answer to multiple versions of the same question, and readers should be able to find a single canonical page with the question they're looking for. For example, we'd consider questions like "What are the best ways to lose weight?", "How can a person reduce weight?", and "What are effective weight loss plans?" to be duplicate questions because they all have the same intent. To prevent duplicate questions from existing on Quora, we've developed machine learning and natural language processing systems to automatically identify when questions with the same intent have been asked multiple times.

A key area of AI intervention in logistical operations involves adaptive scheduling of deliveries and routing of vehicles. Advanced logistics and supply chains are being created using expert decision systems. Products can be transported more efficiently through vision-based driver assist and automated/robotic systems. This has made transportation less susceptible to disruptions caused by weather, traffic and unnatural events. Some of the major areas of application of AI in the banking and financial services sector include early detection of financial risk and systemic failures, and automation to reduce malicious intent in financial systems, such as market manipulation, fraud, anomalous trading and reduction in market volatility and trading costs.

"Machine learning is really not dark magic, it's just another tool." As the leading professor involved in the development of Google Brain, and Google's Director of Augmented Intelligence Research, he worked on their release of their open-source library for machine learning, Tensorflow. "Our main hurdle is to get people educated on how this works in practice." He shared that practical advice last week at TQ in Amsterdam (disclaimer: TQ is part of TNW), alongside three startups that each have their own hands-on experience with machine learning as well. For years now, the decreasing costs of computation power and data storage have gone hand in hand with the explosive birth of tech startups.

Machine learning is creating a foothold in the business world, especially when it comes to innovative digital experience, and Web Content Management (WCM) players are diving headfirst into machine learning in the aim of supporting a smart experience across industries. As Forrester's recent industry overview said, "The web CMS market is changing because more organizations recognize the necessity of contextual digital experiences. Every vendor in this landscape is tracking toward this goal."¹ As contextual experiences increasingly become brand differentiators, the ability of machine learning to provide these experiences at scale is massively advantageous. The broad statement that machine learning and other AI technologies are going to infiltrate all corners of our lives, while likely true, paints an often dystopian picture that can be a bit overwhelming.

In the beginning (1966), there was ELIZA – she was the first bot of her kind, had roughly 200 lines of code and was extremely smart. But you probably don't know her. Later, came PARRY who was smarter than ELIZA (and could imitate a paranoid schizophrenic patient). But you probably don't know PARRY either. But you do know Siri!

"I, Robot", a movie from 2004 set in the year 2035 where humans and robots coexist, but the humanoid robots are really just assistants and labor workers for humans. These robots run on an AI supercomputer called V.I.K.I, but all it took is for V.I.K.I to become self aware and turn the robots on the humans, much like "Terminator" with SkyNet, but with a bit less violence. The year is 2017 and we are not yet at the point where we have AI mastered enough to create robots like those in "I, Robot" and "Terminator", but we are getting very close. The point is, we'll more than likely see robots like those in "I, Robot" before the year of the movie, 2035. The way the technology is going in AI and robotics, we could see mass produced AI equipped robot assistants as early as 2025.