I'm Nathan Benaich -- welcome to issue #18 of my AI newsletter! I will synthesise a narrative that analyses and links important happenings, data, research and startup activity from the AI world. Grab your hot beverage of choice and enjoy the read! If you're looking to invest, research, build, or buy AI-driven companies, do hit reply and drop me a line. In a massive deal this quarter, Intel CEO agreed to purchase Mobileye for $15.3bn. The 18-year old NYSE-listed Israeli company holds a portfolio of camera-based computer vision, sensor fusion, mapping and driving policy products for advanced driver assistance features such as pedestrian, vehicle and sign detection as well as relationships with Tier 1 OEMs. Intel takes the view that "whoever has the best data can develop the best AI". Intel already has a strong position in silicon (in-house Nervana and Movidius), memory and communications.

Most fintech companies offer better interfaces for handling money (bank accounts, loans, payments, etc.), but quite a few startups are also offering a solution for a much older need than how to make money. Israel company I Know First, managed by CEO Yaron Golgher, is one of these. The company's main product is an algorithm that provides a forecast for three thousand different investment instruments, including shares, commodities, interest rates, foreign currency, exchange traded funds (ETFs), and global indices. "The algorithm rates all the investment instruments, and singles out investment opportunities in the capital market on a daily basis, according to the pricing anomaly it finds," Golgher says in a "Globes" interview. Golgher: "The algorithm is self-learning. It is based on purely quantitative values, not reading news or any kind of analysis. There is no human factor here. The algorithm uses artificial intelligence, an area in which huge companies like Apple Computers, Google, and Facebook have recently been making massive investments. The algorithm was developed by our development team, headed by cofounder and CTO Dr. Lipa Roitman. Roitman is a scientist from the Weizmann Institute of Science with over 20 years of experience in the specific field of artificial intelligence, machine learning, and algorithms. The forecast is given for a period of time. What is interesting is that for every forecast, the algorithm also assigns a probability that the forecast will be fulfilled. Every customer can receive a forecast according to his investment preferences. For example, a person investing in technology shares can receive the best opportunities in this segment, a customer investing in commodities will receive the best opportunities in the commodities market, etc." "We have expanded this year to 12 new countries, including the US and Europe, with an emphasis on Italy and France, and Russia, too. We work with Latin America, especially Brazil. The business model is based on access to the algorithm to a varying extent, according to the customer's size."

Databases are widespread, yet extracting relevant data can be difficult. Without substantial domain knowledge, multivariate search queries often return sparse or uninformative results. This paper introduces an approach for searching structured data based on probabilistic programming and nonparametric Bayes. Users specify queries in a probabilistic language that combines standard SQL database search operators with an information theoretic ranking function called predictive relevance. Predictive relevance can be calculated by a fast sparse matrix algorithm based on posterior samples from CrossCat, a nonparametric Bayesian model for high-dimensional, heterogeneously-typed data tables. The result is a flexible search technique that applies to a broad class of information retrieval problems, which we integrate into BayesDB, a probabilistic programming platform for probabilistic data analysis. This paper demonstrates applications to databases of US colleges, global macroeconomic indicators of public health, and classic cars. We found that human evaluators often prefer the results from probabilistic search to results from a standard baseline.

In sales, it's all about getting leads, and Lynkos, which today announced funding of $2.5 million, has a novel approach to finding them. The startup uses artificial intelligence to join CRM software with data on companies around the world. Using Lynkos, sales people can import their own leads or set criteria to find them using the online service. The leads can be prospected using the product's email marketing tools and tracked throughout the sales process. "We have a lot of automated bots crawling the web for business data, classifying them to improve business profiles, industries, and opportunities," wrote Federico Cella, founder and CEO of Lynkos, in an email to VentureBeat.

Google's April Fools' Day jokes have come to be expected over the years, and this year they haven't missed a step. Open up Google Maps today and you'll be greeted with a pleasant surprise: the option to play Ms. Pac-Man on any set of streets in the world. While Google also offered Pac-Man back in 2015, given that gameplay is only available for one day at a time, the novelty of exploring the world through such a hungry, two-dimensional lens has far from worn off. I spent a couple of hours playing early this morning, and chose five of my favorite locations around the world to play, included here with direct links to the maps so you can try them out yourself. How could I leave Lombard Street off of this list?

Google has marked April Fools' Day 2017 by bringing Ms Pac-Man to its Maps app. Opening Google Maps automatically launches the arcade classic, and a dedicated Pac-Man button sits above the'My Location' icon. Google Maps Ms Pac-Man is available on both Android and iOS, though some users are reporting slight differences between the two versions. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. 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.

Amazon just made news when its Prime Air delivery drone did its first public demo, landing on a lawn in California to drop off a few bottles of sunscreen for attendees of an Amazon conference on automation. But the cofounder and CTO of the drone delivery startup Zipline doesn't think much of Amazon's experiments in this area, or Google's either. Have you been near one of those quadrocopters when it sets down, Zipline's Keenan Wyrobek asks? "They're huge things with the power and blade size of four lawnmowers," he says. While Amazon dropped off sunscreen for Silicon Valley insiders, and Google has talked with Domino's about pizza delivery, Zipline is delivering life-saving blood to hospitals in Rwanda.

When you examine the lives of history's most creative figures, you are immediately confronted with a paradox: They organize their lives around their work, but not their days. Figures as different as Charles Dickens, Henri Poincaré, and Ingmar Bergman, working in disparate fields in different times, all shared a passion for their work, a terrific ambition to succeed, and an almost superhuman capacity to focus. Yet when you look closely at their daily lives, they only spent a few hours a day doing what we would recognize as their most important work. The rest of the time, they were hiking mountains, taking naps, going on walks with friends, or just sitting and thinking. Their creativity and productivity, in other words, were not the result of endless hours of toil. Their towering creative achievements result from modest "working" hours. How did they manage to be so accomplished? Can a generation raised to believe that 80-hour workweeks are necessary for success learn something from the lives of the people who laid the foundations of chaos theory and topology or wrote Great Expectations? If some of history's greatest figures didn't put in immensely long hours, maybe the key to unlocking the secret of their creativity lies in understanding not just how they labored but how they rested, and how the two relate. Let's start by looking at the lives of two figures. They were both very accomplished in their fields.

NEW YORK, LONDON & HONG KONG--(BUSINESS WIRE)--In the next stage of artificial intelligence adoption, banks will use AI to help understand the intentions and emotions of customers and enable better interactions, according to a new report from Accenture (NYSE:ACN). The report, Accenture Banking Technology Vision 2017, draws on the analysis of an advisory board of more than two dozen individuals, interviews with technology luminaries and industry experts, and results of a survey of more than 600 bankers. According to the report, more than three-quarters (78 percent) of bankers believe that AI will enable simpler user interfaces that will help banks create a more human-like customer experience. In addition, four out of five respondents (79 percent) believe that AI will revolutionize the way banks gather information and interact with customers, and three-quarters (76 percent) believe that within three years, banks will deploy AI as their primary method for interacting with customers. "Consumers' diverse needs and priorities are forcing financial services firms to redefine how they interact with them to determine the best products and services to meet individuals' needs," said Alan McIntyre, a senior managing director at Accenture and head of the company's Banking practice.

Games with large branching factors pose a significant challenge for game tree search algorithms. In this paper, we address this problem with a sampling strategy for Monte Carlo Tree Search (MCTS) algorithms called "naive sampling", based on a variant of the Multi-armed Bandit problem called "Combinatorial Multi-armed Bandits" (CMAB). We analyze the theoretical properties of several variants of naive sampling, and empirically compare it against the other existing strategies in the literature for CMABs. We then evaluate these strategies in the context of real-time strategy (RTS) games, a genre of computer games characterized by their very large branching factors. Our results show that as the branching factor grows, naive sampling outperforms the other sampling strategies.