Automation Anywhere, a global leader in Robotic Process Automation (RPA), today announced the acqui-hire of product engineering start-up Cathyos Labs to support the company's expansion and product innovation. Cathyos Labs specializes in product development, automation, RPA and predictive analytics. Through the acqui-hire, Automation Anywhere will strengthen its engineering team to increase product development, support and delivery for customers in India and across the region. Cathyos Labs is the first talent led acquisition by Automation Anywhere. Throughout India, acqui-hires are becoming common as organizations purchase a company in order to acquire or gain access to its employees, but not necessarily the company's products and services.

Kenyan agri-tech startup Shamba Records has built a blockchain-based platform that uses artificial intelligence (AI) and big data to collect farmers' harvest records, process payments and issue credit. Founded in 2017 and already used by over 6,000 farmers, the Shamba Records platform provides users with features such as data collection and mapping, payment aggregation, smart contracts, and bulk SMS, making farms more efficient and collecting information that can allow them to access financial services. It was developed by a team with first-hand experience of farming in Africa. "Each founder has a story to tell of how inefficient the agriculture space in Africa is, for example, poor records, delayed payments, no credit alternatives, lack of communication tools, and so many other challenges," chief executive officer (CEO) George Maina told Disrupt Africa. These inefficiencies are major problems on a continent where over 600 million people depend on agriculture as their main source of income.

Increased market for cloud computing 3.5.1.2. Growth associated with artificial intelligence and cognitive computing 3.5.2.

Increased market for cloud computing 3.5.1.2. Growth associated with artificial intelligence and cognitive computing 3.5.2.

There is an analogy between machine learning systems and economic entities in that they are both adaptive, and their behaviour is specified in a more-or-less explicit way. It appears that the area of AI that is most analogous to the behaviour of economic entities is that of morally good decision-making, but it is an open question as to how precisely moral behaviour can be achieved in an AI system. This paper explores the analogy between these two complex systems, and we suggest that a clearer understanding of this apparent analogy may help us forward in both the socio-economic domain and the AI domain: known results in economics may help inform feasible solutions in AI safety, but also known results in AI may inform economic policy. If this claim is correct, then the recent successes of deep learning for AI suggest that more implicit specifications work better than explicit ones for solving such problems.

This paper develops a new approach for estimating the internal model of an autonomous agent that can plan and act, by interrogating it. In this approach, the user may ask an autonomous agent a series of questions, which the agent answers truthfully. Our main contribution is an algorithm that generates an interrogation policy in the form of a sequence of questions to be posed to the agent. Answers to these questions are used to derive a minimal, functionally indistinguishable class of agent models. While asking questions exhaustively for every aspect of the model can be infeasible even for small models, our approach generates questions in a hierarchical fashion to eliminate large classes of models that are inconsistent with the agent. Empirical evaluation of our approach shows that for a class of agents that may use arbitrary black-box transition systems for planning, our approach correctly and efficiently computes STRIPS-like agent models through this interrogation process.

The Royal Academy of Engineering's Africa prize, now in its sixth year, is the continent's biggest award for engineering innovation. Sixteen African inventors from six countries – including, for the first time, Malawi – have been shortlisted to receive funding, training and mentoring for projects intended to revolutionise sectors ranging from agriculture and banking to women's health. The winner will be awarded £25,000 and the three runners-up will receive £10,000 each. This year's inventions include facial recognition software to prevent financial fraud, a low-cost digital microscope to speed up cervical cancer diagnosis, and two separate innovations made from water hyacinth plants. Four inventors spoke to the Guardian about their innovations and their plans to change Africa for the better.

Over the last year, my focus has been diverted from exploring analytics, new packages and blogging, to completing my dissertation. With the dissertation now complete and only final edits remaining, I had some spare time to spend on projects that I have been curating throughout the year. One such project that has been in the back of my mind for the last couple of months concern itself with with faster, scalable machine learning. This is where h2o comes in. We have been using h2o in production over the last year with great results.

As of late, a number of hot topics have arisen in data policy, notably: how to ensure data privacy for individuals; the role of government in the regulation of technology; and how best to effectively and ethically leverage big data. At the forefront of these discussions is regulation of artificial intelligence (AI). As governments race to regulate AI, they should proceed with caution and seek to balance the needs of society and the private sector. Despite its recent prevalence in public discussion, AI is not a new topic. Industry leaders, such as Jonathan Zittrain, have commented on the generative Internet and how such systems are facilitating new kinds of control. Similarly, Timnit Gebru, cofounder of Black in AI, discussed the diversity crisis facing AI systems.

This Artificial Intelligence Market research report is framed by using integrated advancements and latest technology to give the most excellent results. A method of standard market research analysis is put forth while elaborating the studies and estimations that are involved in this Artificial Intelligence Market report. Such plentiful information accompanied with deep market insights supports the decision of increasing or decreasing the production of goods depending on the general conditions of market and demand. The Artificial Intelligence Market report has a lot to offer to both established and new players in the industry with which they can completely understand the Artificial Intelligence Market. Global Artificial Intelligence Market is accounted for $15.70 billion in 2017 and is expected to reach $300.26 billion by 2026 growing at a CAGR of 38.8% during the forecast period. Artificial intelligence is an intelligence established by machines, in contrast to the natural intelligence displayed by humans and other animals.