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Artificial Intelligence is the Most Revolutionary Technology Seen in Decades | Analytics Insight

Artificial Intelligence (AI) is arguably the most revolutionary technology that is seen in several decades having the potential to completely turn the world upside down and then re-shape it with new contours.

In the coming years, we will continue to witness the disruption what deep learning and AI-related technologies can bring to create an impact not only to the software and the internet industry but also to other verticals such as manufacturing, automobile, agriculture, and healthcare and so on.

Over the next three to five years, augmented analytics, continuous intelligence and explainable AI will be the toast of data and analytics technology having significant disruptive potential.  Augmented analytics deploying machine learning and AI techniques will transform how analytics content is developed, consumed and shared.

The need to analyse complex data combinations and to make analytics accessible to everyone in the organization will drive organisations towards broader adoption, allowing analytics tools to be easily accessible as a search interface or a conversation with a virtual assistant.

Artificial Intelligence Creates a New Generation of Machine Learning

Originally a chemist, Yiwen Huang, PhD, ended up working in Artificial Intelligence (AI) and Machine Learning (ML) 23 years ago when doing research using AI to identify molecular structures in chemicals.

'I found the world of machine learning and computing so fascinating that I decided to switch into computer science.

Since then, I've worked for 20 years in this space with data and data management, machine learning, and enterprise software development,' he tells Interesting Engineering.

'The reason why I started R2aiis that when I was at Teradata, we actually developed the world's first machine learning platform based on distributed parallel computing architecture, which can train a machine learning model of terabytes of data in just minutes, unlike the traditional ways of doing it that takes weeks.

Despite constant feedback from almost all of R2ai's customers saying how fast and fascinating the technology was, they couldn't find enough machine learning experts to operate the tool.

According to a Gartner's survey of over 3,000 CIOs, Artificial intelligence (AI) was by far the most mentioned technology and takes the spot as the top game-changer technology away from data and analytics, which is now occupying a second place.

Indeed, responding to this and the feedback given by R2's customers, Yiwen Huangfigured he now had a new mission: To work on a new machine learning development in an operation platform that not only should be fast but also it should be easy to use;

'So, I had this idea of why can't we use AI technology to develop a new generation of machine learning development and operation platform that can compute models automatically without giving problems in the data set,' says Huang.

R2 Learn is the new generation AutoML tool that turns big data into high-quality, sophisticated Machine Learning models in a fast, easy, and affordable way. is a pioneer in the market with these combined technologies that tackle key AI development pain points: The technology is actually industry agnostic.

For Huang, the industries that are currently most ready for machine learning are life insurance, healthcare, finance, manufacturing, and also telecommunications.

'The SaaS offering can be very useful for those who are actively doing machine learning but having a hard time acquiring machine learning developers or anyone who wants to speed up their projects or anyone who wants to have a piece of mind that they are fully leveraging the value of the data,' he explains.

The second group of customers include 'the ones who want to get into Machine Learning but are intimidated today by the investment and also the lack of machine learning expertise.

Businesses and individuals interested in developing their own AI solutions or accelerating slow-moving AI projects are invited to sign up for a free trial.Huang is also happy to offer a free initial consultation to customers who want help on evaluating AI possibilities.

Even though industry experts and futurists have said that automation is going to create new jobs for those who have prepared acquiring or developing new skills, especially soft skills.

So, engineering used to develop that tool to make people's job really easy and really fast, more efficient, and boost their productivity.

There are cost savings aspects but I think the most important area is how I can leverage the tool with my existing resources,' says Huang.

Huang believes that there is going to be a short term of change for some people in terms that they will have to shift into a different domain, career, or industry.

It's also about constantly learning new skills in order to remain current to the times we live and the technology that is coliving with us.

There’s a Power Struggle Inside Google to Control Superhuman AI

DeepMind, the artificial intelligence startup purchased by Google in 2014, is on a mission to build the world’s first artificial general intelligence (AGI) — the sort of all-encompassing, superhuman AI we see in science fiction.

To make sure that AGI is used responsibly, DeepMind founder Demis Hassabis protected his company’s independence from Google and parent company Alphabet by building internal safeguards, according to a new story by The Economist‘s cultural publication, 1843 Magazine — including an ethics board controlled by Hassabis and his original team, rather than Google.

Some of those same anonymous sources also shared doubts with 1843 that DeepMind would ever crack the code of artificial general intelligence, pointing to little-known weaknesses and caveats to the company’s highly-publicized AI success stories.