Researchers now believe that language might have developed from cave drawings. Specifically, they think the ancient artwork located in caves with good acoustics might have inspired humans to develop the vocal communication that exists today. A new report on the theory from the Massachusetts Institute of Technology hinges on the fact that caves allow for echoes. The researchers think that previously discovered cave drawings prove that the fundamental parts of speech were derived from artwork. The MIT team that worked on the new analysis said that taking a look in the depths of ancient caves can provide modern humans with answers about where languages stemmed from.

With a financial services industry increasingly reliant on technology, cyber-threats are a real, and for many organisations, persistent threat. There have been numerous examples of cyber-crime and internal fraud that have resulted in data leaks and/or financial losses. Firms are being required to be more vigilant when it comes to their technology, with greater pressure to improve both network resiliency and security. This is where firms like NetGuardians can assist, offering solutions to the industry to protect against fraud and cyber-crime. "We are helping to detect and reduce false positives and detect criminal activities via our innovative technology based on big data and machine learning" says Maio. Maio and his associate started the firm ten years ago in Switzerland and have now expanded overseas with offices in Kenya, Poland and Singapore.

IN its bid to adopt next generation technologies like AI, machine learning, big data and more in business and management practices while expanding collaborative efforts with other organizations, LG's has launched its CLOi Robot at CES 2018. The CLOi Robot made its debut appearance at the recently concluded LG MEA Innofest 2018, just as LG has announced the creation of ThinQ brand to identify all of its 2018 home appliances, consumer electronics and services that utilize artificial intelligence. Speaking on the smart products, Mr. Kevin Cha, President LG Electronics Middle East & Africa enthused; "LG ThinQ products and services will all have the ability to employ deep learning and communicate with one another, utilizing a variety of AI technologies from other partners as well as LG's own AI technology, DeepThinQ. "The advancements in AI and robotics are expected to transform lifestyles and industries around the world, ultimately improving humankind's experiences from reducing repetitive tasks at home or work to even eliminating age-old malignant practices. This is why significant investments will be made in this area.

Gone are the days of building just another boring website to have a digital presence. We have entered a new era where everything is connected to build next-generation digital experiences. The introduction of the iPhone in 2007 marked the mobile revolution which has entirely changed users' expectations of the web and the digital experiences it generates. This situation started a ripple effect and with the rise of the mobile Internet, we shifted away from installed software on our desktops to mobile apps at our fingertips. The explosion of mobile apps reached a tipping point in 2008, and just like every other technology trend, it settled in over time.

Meeshkan is an IoT service where people can convert almost any device into a client that executes distributed Machine Learning tasks. People are paid for the time their device is used. Meeshkan is currently in its public beta.

In October last year, fintech company NMRQL launched its first unit trust in South Africa. The NMRQL SCI Balanced Fund is the first local unit trust to exclusively use machine learning for managing its portfolio. Using computers in investment management is certainly not a new idea, as there are already a number of funds run using quantitative models and many active managers use these systems in their decision making. This is however the first fund giving South African investors the chance to see if machines on their own can make better investment decisions than humans. Proponents of artificial intelligence argue that this won't be much of a contest, given what has already been achieved.

Malawi is using drones to create maps of high risk areas to stem the spread of cholera, which has critically hit at least six districts following an outbreak in November.

Artificial Intelligence is a branch of Computer Science ( or Science) which deals with the creation of intelligent systems. Intelligent systems are those systems which posses intelligence just like humans. The science of Artificial intelligence is not new, The term Artificial intelligence has been mentioned in manuscripts of Ancient Greece and Egypt. Greeks believed in god Hephaestus, also known as God of Blacksmiths, according to a Greek mythology Hephaestus made intelligent weapons for all Gods, in their view, the goal of Artificial intelligence is to: be helpful for people to achieve a certain goal, be able to operate automatically and be programmed in advance to react in different ways depending on the situation. Well, The term Artificial Intelligence has become popular in the field of Entertainment, we can see lots of movies based on the concept of Super intelligence.

AI has taken some steps into banking, but it also poised to transform how banks learn from and interact with customers. Financial services will lead the charge in the implementation of AI. Africa's mobile phone market has expanded to become larger than either the EU or the United States with some 650 million subscribers (2016 data). At the same time, Internet bandwidth has grown 20-fold as hundreds of thousands of kilometres of new cables have been laid across the continent to serve an increasing number of its 1.2 billion Africans. Augmented experience on how to recommend how much to spend and on what.

A substantial progress in development of new and efficient tensor factorization techniques has led to an extensive research of their applicability in recommender systems field. Tensor-based recommender models push the boundaries of traditional collaborative filtering techniques by taking into account a multifaceted nature of real environments, which allows to produce more accurate, situational (e.g. context-aware, criteria-driven) recommendations. Despite the promising results, tensor-based methods are poorly covered in existing recommender systems surveys. This survey aims to complement previous works and provide a comprehensive overview on the subject. To the best of our knowledge, this is the first attempt to consolidate studies from various application domains in an easily readable, digestible format, which helps to get a notion of the current state of the field. We also provide a high level discussion of the future perspectives and directions for further improvement of tensor-based recommendation systems.