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."

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?

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.

Tinder has always lived on your phone. The dating app, which seduced tens of millions of users with its delightfully simple right-swipe, didn't just have a mobile experience, it was a mobile experience. That changes today, with the release of a browser-based applet the company calls Tinder Online. When it arrives in the US later this year (the company is now testing it in countries like Argentina, Brazil, Colombia, and Indonesia, where users with weak cellular connections will finally be able to use Tinder from a desktop), Tinder Online will look a lot like the mobile version. But the company's designers made some changes to the interaction, starting with the swipe.

Tinder is joining the earliest electronic dating services and adding support for web. The app is designed to virtually introduce users to others in a set radius around them via photos and a short biography. Based on that limited information users swipe right if they're intrigued or left if they're not. If both users swipe right, they're matched and can begin a conversation. Tinder originated as an app, but soon it will be available in web browsers on any device.

The company is beginning to test a new web-based version of its service that allows people to access Tinder from a browser, rather than its mobile app. Called Tinder Online, the service is being tested in a handful of countries outside the U.S. but the company plans to make it available to everyone in the future. That may sound like a minor change but it's a significant shift for the company, which has been mobile-only up until now. With Tinder Online, which is being tested in Argentina, Brazil, Colombia, Indonesia, Italy, Mexico, the Philippines, Italy, and Sweden, users can browse profiles, check out matches and send messages all from within a browser. Tinder says the change is meant to help the dating service expand its presence in international markets, especially those where LTE and unlimited data plans aren't readily available.

This article presents a logical formalization of the emotional appraisal theory, i.e., it formalizes the cognitive process of evaluation that elicits an emotion. This formalization is psychologically grounded on the OCC cognitive model of emotions. More specifically, we are interested in event-based emotions, i.e., emotions that are elicited by the evaluation of the consequences of an event that either happened or will happen. The formal modelling presented here is based on the AfPL Probabilistic Logic, a BDI-like probabilistic modal logic, which allows our model to verify whether the variables that determine the elicitation of emotions achieved the necessary threshold or not. The proposed logical formalization aims at addressing how the emotions are elicited by the agent cognitive mental states (desires, beliefs and intentions), and how to represent the intensity of the emotions. These are important initial points in the investigation of the dynamic interaction among emotions and other mental states.

NHGRI medical geneticist Paul Kruszka explains that "Human malformation syndromes appear different in different parts of the world. Even experienced clinicians have difficulty diagnosing genetic syndromes in non-European populations." That's where facial recognition comes in. The NHGRI team studied the photographs of 101 participants with the rare disease from Africa, Asia and Latin America. They then developed a facial recognition tech that was able to correctly diagnose the condition 96.6 percent of the time during their trial runs.

Disrupting the streaming music market is extremely difficult to do, given the entrenched positions of Pandora and Spotify in the world market. But Brazilian company SuperPlayer is doing just that, with its streaming music service that is simple, curated, and effectively halves the price of Spotify's Premium service in Brazil. With the ability to listen to music offline without consuming data, Spotify should be worried. But the most impressive disruption that SuperPlayer has pulled off is using chatbots in their influencer marketing schemes. It's no secret that chatbots are essential to customer service, but SuperPlayer is the first to integrate music into chatbots, and effectively.