Machine Learning & AI

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Automated Machine Learning: A new Paradigm

Automated Machine Learning or AutoML has emerged as an exciting new branch of AI/ Machine Learning. Existing Machine Learning algorithms require a certain amount of pre-processing of the dataset to make it suitable for machine learning and this requires considerable expertise and knowledge of ML. AutoML helps automate this process. In essence, AutoML is the process of automating automation. Not only does AutoML help expedite the process of creating AI solutions, it also helps create superior solutions.

What is Machine Learning bias and how to overcome it?

Machine learning (ML) has emerged as a popular and effective AI learning technique. This isn’t surprising, given its remarkable ability to sift through humongous volumes of data and find patterns that are simply not obvious to humans. What is even more remarkable is its ability to learn from data over time and to deliver extremely accurate insights and predictions.

Accelerate Your Sales Results with Machine Intelligence

Ever bought a product or a vacation, and it seemed to suddenly pop up on your search page or in your email inbox? If you said yes, then that’s an ML algorithm at work, monitoring your online activity and making relevant recommendations. With AI becoming an everyday reality, the role of sales teams is constantly changing. A Harvard Business Review study found that sales teams that adopted AI saw more than 50% increase in leads and appointments, cost reductions of 40%–60%, and call time reductions of 60%–70%.

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.

Meet the Power Duo: Big Data and AI

Data without insights is useless and we all know how, getting meaningful insights in this Zettabyte era would be near impossible without Big Data technologies. In simple terms, Big Data is a collection and management of copious volumes of data, including structured and unstructured data. However, the ‘Big’ in Big Data is not so much about the volume, but rather its ability to gain actionable insights – either strategic or operational – from the data collected.

6 Things to Consider Before Businesses Plan Their AI Strategy

Everyone has an opinion on AI these days.  You often hear conflicting arguments claiming “AI has arrived and it will be the big game changer” or how “AI is overhyped and the adoption is still in the early stages”. Now, whichever side you are on, it is prudent to start thinking about how AI can help you achieve your future business goals.

Here are 6 things to consider before you plan your AI strategy:

Bridging the Insights Gap: Why Traditional BI and Analytics Fail?

Data is the key building block of organizational intelligence. Rapid advances in technology has resulted in an exponential increase in organizational data being generated today. Efficient management of large volumes of data has become an essential function for achieving regular business goals, and long-term strategic and tactical decision making. Businesses today require intelligent systems with sophisticated algorithms, higher computational powers and storage to succeed in the market.

Why Human Intelligence Will Drive AI’s Future?

Some of our best inspiration for cutting edge technologies comes from nature. Aircrafts were inspired from birds, the helical motion of falling maple seeds inspired drones, even the Japanese bullet trains were streamlined by observing kingfishers. So, it’s no surprise that Artificial Intelligence (AI) takes inspiration from the most complex super computer on earth – the human brain.

Why do we need a more human-like computing system?

Do you really need to fear AI?

 As I open my Facebook profile, I see offers by Amazon on the side with the title, “Here are some black dresses especially recommended for you”. Wait what? How did Facebook know I was looking for a black dress? And how does it know what styles I like? How does Saavn (a music streaming service) know what songs I’d like to hear? How does Google Now know what I want even though I muttered something to it groggily? The answer is simple, and it’s everywhere!

Robotically Yours...!!!

 Will robots take our jobs? That’s not even a question any more, the answer is a resounding YES, the more pertinent question and one I think a lot of people have chosen to take an ostrich head in the sand approach to (though I think the English language has given ostriches a bad rap, they don’t really do that…anyway I digress and I have just started)




Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines


Lymbyc, a leading edge innovator in AI and Machine Learning takes inspiration from the “Limbic” brain — the part that stores, dissects, rationalizes and generates memories and actions. That’s exactly what we do — giving business users the power of a virtual analyst that is intuitive, actionable and context driven to answer all their business queries


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