Smartphone chipmaker Nvidia has partnered with automotive safety company Autoliv and automotive company Volvo to develop self-driving software and hardware. "This cooperation with NVIDIA places Volvo, Autoliv, and Zenuity at the forefront of the fast-moving market to develop next generation autonomous driving capabilities and will speed up the development of Volvo's own commercially available autonomous drive cars," Håkan Samuelsson, President and Chief Executive of Volvo Cars, stated in the press release Tuesday. The press release further stated the companies will work together to create artificial intelligence-based deep learning solutions for object detection, recognition the anticipation of threats and safe navigation. The self-driven car developed by Nvidia, Volvo, Autoliv, and Zenuity, will use the Nvidia Drive PX2 artificial intelligence based self-driving system which was first showcased at Consumer's Electronic Show (CES) 2016.

While there's concerning hype about artificial intelligence in the market today, Salesforce's chief scientist says researchers don't have to fear that interest in the field will disappear again. "At the same time, I don't think there will be an'AI winter' again, where hype cycles happen and there's no more funding, and so on, because AI is now running in production," Richard Socher said during an onstage interview at a Bloomberg event today. "Google search and social media, and now enterprises, are using AI on an ongoing basis -- they're seeing great returns on those investments." Socher was referencing a set of historical periods when funding in artificial intelligence research cratered after a particularly significant hype cycle. As we see increasing interest in machine learning, experts have warned that over-hyping the field could lead to another period of disillusionment and reduced investment. At the same time, he said that the hype around superintelligent AI has reached a fever pitch that goes well beyond what the technology is capable of.

Proactive insights and personalized guidance are becoming a differentiator in the financial services marketplace, Artificial intelligence (AI), machine learning and eventually the Internet of Things will all play a role in improving a consumer's financial health and well-being. At the same time, as many as three in five consumers say banks are failing to keep up with their need. To win in banking, financial institutions must take steps to serve these customers by helping them improve their financial well being. "Cognitive" Banking – a combination of Artificial Intelligence (AI), predictive analytics and conversational capabilities tailored to financial institutions – provides a huge opportunity for banks to improve their relationships with customers and support them in leading healthy financial lifestyles. Here are a few ways how.

'Hostbot' is a text message bot from Burner that has been introduced to save Airbnb hosts the trouble of answering frequently asked questions over and over again. When an Airbnb guest arrives in a new city or country, they are bound to have tons of questions like: "What's the Wi-Fi password?" Hostbot makes it possible for an Airbnb host to fill in some of the questions that they are asked often and link the chatbot to their Burner phone number. This way, when a guest has a question, the bot auto-responds with the appropriate answer. This way, a host is able to focus on parts of the hosting experience that a bot can't assist with.

When Apple announced plans earlier this year to expand its engineering operation in Seattle, the company said it would be looking for "the best people who are excited about AI and machine learning." Job listings on the tech giant's website reveal just who Apple hopes to attract on its Siri Advanced Development team. Business Insider pointed at the listings on Monday, saying that Apple was making a move on Amazon's home turf to go after Siri talent in the land of Alexa -- the voice-activated assistant on devices such as the Echo and Dot. One job, posted back in January, is for a software engineer, and the other, posted on May 23, is for a speech scientist/engineer. A description at the bottom of both doesn't pull any punches when it comes to regarding the work as groundbreaking and Siri as the original AI.

Austin-based SparkCognition, a startup focused on artificial intelligence, announced Monday that it has closed on $32.5 million in funding. Verizon Ventures led the Series B funding round with participating from The Boeing Company, through its Boeing HorizonX unit. "SparkCognition has pioneered the use of artificial intelligence to bring unparalleled advancements to many of the world's Fortune 1000 companies," Vijay Doradla, Director at Verizon Ventures, said in a news release. "We are thrilled to invest in SparkCognition again, and look forward to supporting the company as it continues to transform markets and the businesses of tomorrow." SparkCognition has created a data-driven analytics platform for Internet of Things applications with customers in energy, oil and gas, manufacturing, finance, aerospace, defense, telecommunications, and security.

D. Fox Harrell (fox@csail.mit.edu) is Professor of Digital Media in both the Comparative Media Studies Program and the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, Cambridge MA, and the founder and director of the Imagination, Computation, and Expression Laboratory. Chong-U Lim (culim@csail.mit.edu) recently completed his Ph.D. in electrical engineering and computer science from the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, Cambridge MA, where he was a member of the Imagination, Computation, and Expression Laboratory.

Since the 1920's, some researchers and studies have suggested that chimps are'super strong' compared to humans. These past studies implied that chimps' muscle fibers - the cells that make up muscles - are superior to humans'. But a new study has found that contrary to this belief, a chimp muscles' power output is just about 1.35 times higher than human muscle of similar size - a difference the researchers call'modest' compared with historical, popular accounts of chimp'super strength' being many times stronger than humans. When all factors were integrated in a computer model, chimp muscle produces about 1.35 times more dynamics force and power than human muscle Dr Brian Umberger, a researcher at the University of Massachusetts Amherst and a co-author of the study, said that the researchers found that this modest performance advantage wasn't actually due to strong muscle fibers found in chimpanzees compared to humans - but due to the different mix of muscle fibers found in chimpanzees compared to humans. According to the authors of the research, if the long-standing, untested assumption about chimpanzee's exceptional strength was true, it'would indicate a significant and previously unappreciated evolutionary shift in the force and/or power-producing capabilities of skeletal muscle' in either chimps or humans, whose lines diverged about 7 or 8 million years ago.

Increasing technological sophistication and widespread use of smartphones and wearable devices provide opportunities for innovative and highly personalized health interventions. A Just-In-Time Adaptive Intervention (JITAI) uses real-time data collection and communication capabilities of modern mobile devices to deliver interventions in real-time that are adapted to the in-the-moment needs of the user. The lack of methodological guidance in constructing data-based JITAIs remains a hurdle in advancing JITAI research despite the increasing popularity of JITAIs among clinical scientists. In this article, we make a first attempt to bridge this methodological gap by formulating the task of tailoring interventions in real-time as a contextual bandit problem. Interpretability requirements in the domain of mobile health lead us to formulate the problem differently from existing formulations intended for web applications such as ad or news article placement. Under the assumption of linear reward function, we choose the reward function (the "critic") parameterization separately from a lower dimensional parameterization of stochastic policies (the "actor"). We provide an online actor-critic algorithm that guides the construction and refinement of a JITAI. Asymptotic properties of the actor-critic algorithm are developed and backed up by numerical experiments. Additional numerical experiments are conducted to test the robustness of the algorithm when idealized assumptions used in the analysis of contextual bandit algorithm are breached.

Learning by children and animals occurs effortlessly and largely without obvious supervision. Successes in automating supervised learning have not translated to the more ambiguous realm of unsupervised learning where goals and labels are not provided. Barlow (1961) suggested that the signal that brains leverage for unsupervised learning is dependence, or redundancy, in the sensory environment. Dependence can be characterized using the information-theoretic multivariate mutual information measure called total correlation. The principle of Total Cor-relation Ex-planation (CorEx) is to learn representations of data that "explain" as much dependence in the data as possible. We review some manifestations of this principle along with successes in unsupervised learning problems across diverse domains including human behavior, biology, and language.