Machine Learning & AI

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AI’s Potential in Changing the Workforce

Talking about the future without artificial intelligence is impossible.

After the paradigm-shift in our work culture due to Big Data and the Internet of Things (IoT) transforming everyday devices into smarter ones, AI is now making analytics even more efficient and productive.

Data volumes are exploding and there is more data created in the past two years than in the entire history of the human race. By 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.

The Emergence of Voice Search

The growth of voice search has been exponential in recent years. There is no doubt about the fact that technology is changing and our interaction with the internet is also transforming.

From small-tail keywords to long-tail ones, we are now moving towards ‘voice’. You can now pick up an iPhone and ask “Siri” to play a song of your choice or even shout, “Hey Alexa” to find Italian recipes for your next feast. There’s a growing tendency among users to rely on voice command or digital assistants to find answers.

WHY ARE DATA SCIENTISTS CRUCIAL FOR AI?

Today, we are talking about the impact of artificial intelligence (AI) – positive or negative – and how it will surpass the human workforce.

The possibilities of AI are numerous but everything depends on big data. Big data is still as relevant as it was 10 years ago as it is still underutilized.

In the world of science fiction, AI systems often overpower human civilization. Similarly, artificial intelligence is already predominant in the real-world around us. Think about Google, Facebook, and Amazon who are changing the game with AI discoveries.

Why is AI powered Customer Engagement a must now?

In 2017, Aeromexico launched a customized AI system, a neural network that was built on the foundation of machine learning.

At the Facebook’s F8 Global Conference, the company announced that it went from zero to 96% automation of its customer service function and that its AI-powered platform, which learns as it goes by scanning and analyzing previous customer service transcripts, reduced the average customer service resolution time from an average of 16 minutes to just 2 minutes.

THE THIRD WAVE OF AI – BE MORE HUMAN

When the British mathematician Alan Turing designed the Turing test in 1950 as a means of measuring whether a computer was capable of demonstrating intelligent behavior equivalent to or indistinguishable from that of a human, he unleashed what was perhaps the first known benchmark for the performance of Artificial Intelligence systems.

How AI makes data more “Intelligent"

In the fast-paced world of today, there is a constant urge for companies to grow, and this has led to stiff competition among them.

This is where Data comes in and now more than ever, data quality is the primary determinant of one staying above the competition.

With tons of raw data available and the many advances in technology, data segregation and analysis have become more accessible for marketers and growth hackers alike. However, decision makers do not have a high level of confidence in their systems with providing them conclusive information on operational data.

Impact of Artificial Intelligence in Pharma: An overview

Today, AI is being implemented in every industry that we can think of. Some use it as a buzzword to generate hype while others truly understand the full potential of the value it brings.

To keep up with the 21st century, the pharmaceutical industry is constantly on research mode and AI is drawing plenty of attention in the industry. The widespread success of AI in several industries has led many big pharma companies to invest in it.

How leading brands are using AI

Analytics is changing the way brands conduct business, and now with the introduction of AI, it is easier than ever to get hold of this information. By delving deeper into their data, brands can increase efficiency, gain a better competitive advantage, boost sales, and much more. This has resulted in many brands investing in AI in many different ways, notable examples being Google, Nordstrom and even Sephora.

NLG- The Automated Future of Insight

Insight delivery from market research is a very complex process, which is why adding insight equates to adding value for market researchers and marketers. Insights are hardly an automatic result of research and often, it needs human expertise to determine the proper goals, interpret results, or provide common sense checks for solutions. However, with the entry of technologies like AI, ML, NLP and NLG in the insights and research industry, the very process of insight generation is rapidly changing.

How can AI powered CX solve the Data Silo problem?

Your organization has gathered tons of data about your customers— from surveys, social channels and on the ground data. And it’s all over the place siloed with different teams. Without a systematic approach to aggregating and analyzing feedback in one place, it will be difficult for any company to showcase a unified Customer Experience (CX) or even provide additional perspectives that can enhance it.

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