Crypto-trading becomes more and more popular. And it is natural, because the world has recently got to know about the cryptocurrency. And their rate jumps can be a good help to improve your financial well-being. But the cryptocurrency trading as well as other exchange trading instruments is a complex work that requires a self-control and covering a huge range of all sorts of factors. That's why exchange trades are more and more often intrusted to robot-advisers.

Japan is known for its cultural quirks. Be it the food, the growing gaming culture or the expanding robot arsenal, Japan never fails to set your imagination alight. Now, the country will be introducing multilingual robot concierges that would welcome visitors at a Tokyo Metropolitan Government's building to test their practical usage ahead of the 2020 Tokyo Olympic and Paralympic Games. The trial is part of the metropolitan government's efforts to help accelerate developments of such robots for use by foreign tourists visiting Japan, according to a news report published by NHK World. The government wants to slowly introduce these bots into Japan's everyday life to help commuters and people get information faster and more efficiently.

Call center agents wait for calls from their US clients as they work overnight in Manila's Makati financial district February 6, 2012.

Progress and innovation are critical for businesses to compete locally and internationally; it is essential for survival. Across many industries, there are tools and technologies specifically designed to make our lives easier and more productive. From marketing automation to the introduction of the computer and the fax machine, each was designed to support employees, teams, and businesses. They create opportunities and we use these types of tools as well as others, every day. The move from traditional robots to collaborative robots, or cobots, has made a big impact, giving manufacturers the opportunity to do things differently.

AI, which combs through large troves of raw data to predict outcomes and recognize patterns, is expected to replace 40,000 to 50,000 "low-skilled" or process-driven BPO jobs in the next five years, said Rey Untal, president and chief executive officer of the IT & Business Process Association of the Philippines (IBPAP).

Every week, we talk about important data and analytics topics with top data scientists. These data science chats are hosted by Mike Delgado. Please reach out if you have recommendations for topics or guests. Mike Delgado: Welcome to Experian's Weekly Data Talk, a show featuring some of the smartest people working in data science. Bill, thank you for being part of today's broadcast. Can you share a bit about your background and what got you started working in data science? In the '90s, I came out of industry and went into management consulting. I ran the consulting shop at JD Power and Associates. Then, I moved over into big four consulting at Ernst and Young and PricewaterhouseCoopers.

Just as electricity transformed the way industries functioned in the past century, artificial intelligence -- the science of programming cognitive abilities into machines -- has the power to substantially change society in the next 100 years. AI is being harnessed to enable such things as home robots, robo-taxis and mental health chatbots to make you feel better. A startup is developing robots with AI that brings them closer to human level intelligence. Already, AI has been embedding itself in daily life -- such as powering the brains of digital assistants Siri and Alexa. It lets consumers shop and search online more accurately and efficiently, among other tasks that people take for granted.

BENGALURU: Belong, an AI-driven outbound hiring solutions provider, has introduced a first of its kind algorithm that can assist companies in hiring quality professionals for sales and marketing roles across technology, hospitality, FMCG, pharma, insurance and finance. Often, when hiring for strategic roles in sales and marketing, companies continue to fall back on parameters like industry experience and education as a filter of relevance and quality. However, attempting to hire for strategic roles from within the same industry alone is not sustainable or scalable either. Traditionally, hiring for entry-level or field sales roles was a straightforward numbers game. Candidates were sourced primarily through inbound applications, career pages, job boards, advertisements, campus placements, etc.

We develop SHOPPER, a sequential probabilistic model of market baskets. SHOPPER uses interpretable components to model the forces that drive how a customer chooses products; in particular, we designed SHOPPER to capture how items interact with other items. We develop an efficient posterior inference algorithm to estimate these forces from large-scale data, and we analyze a large dataset from a major chain grocery store. We are interested in answering counterfactual queries about changes in prices. We found that SHOPPER provides accurate predictions even under price interventions, and that it helps identify complementary and substitutable pairs of products.

Speech recognition systems have achieved high recognition performance for several tasks. However, the performance of such systems is dependent on the tremendously costly development work of preparing vast amounts of task-matched transcribed speech data for supervised training. The key problem here is the cost of transcribing speech data. The cost is repeatedly required to support new languages and new tasks. Assuming broad network services for transcribing speech data for many users, a system would become more self-sufficient and more useful if it possessed the ability to learn from very light feedback from the users without annoying them. In this paper, we propose a general reinforcement learning framework for speech recognition systems based on the policy gradient method. As a particular instance of the framework, we also propose a hypothesis selection-based reinforcement learning method. The proposed framework provides a new view for several existing training and adaptation methods. The experimental results show that the proposed method improves the recognition performance compared to unsupervised adaptation.