Business Intelligence & Analytics Trends 2019

    In 2019, Advanced Analytics capabilities with minimal manual efforts will remain the hallmark of all competitive Business Intelligence solutions. The Business Application Research Center (BARC) 2018 Business Intelligence Survey indicates that the global BI solutions market is slated for major technological changes. The primary technology initiatives that BI users can expect in 2019 are Cloud BI deployments, BI

Continue Reading

The Future of NLP in Data Science

According to many market statistics, data volume is doubling every two years, but in future this time span may get further reduced. The vast portion of this data (about 79 percent) is text data. Natural Language Processing (NLP) is the sub-branch of Data Science that attempts to extract insights from “text.” Thus, NLP is assuming an important role

Continue Reading

Will AI Kill the Data Scientist?

Humans see less data as businesses collect more of it, which means we need something beyond data scientists. Long before data science became “a thing,” I trained as a “real” scientist, researching arcane and less-than-world-changing topics in physical chemistry. At the heart of that work was data, collected mostly manually during late-night experimental runs in

Continue Reading

AI Will Spell the End of Capitalism

Feng Xiang, a professor of law at Tsinghua University, is one of China’s most prominent legal scholars. He spoke at the Berggruen Institute’s China Center workshop on artificial intelligence in March in Beijing. BEIJING — The most momentous challenge facing socio-economic systems today is the arrival of artificial intelligence. If AI remains under the control of market

Continue Reading

Learning Complex Goals with Iterated Amplification

We’re proposing an AI safety technique called iterated amplification that lets us specify complicated behaviors and goals that are beyond human scale, by demonstrating how to decompose a task into simpler sub-tasks, rather than by providing labeled data or a reward function. Although this idea is in its very early stages and we have only completed

Continue Reading

Top 10 Big Data Tools of 2018

There are plenty of Big Data tools in the market. We have handpicked the best tools that big data professionals are using in 2018. Big data has been a game changer for organisations across industries and revenue size. Big data helps companies to process data of great complexity and size at a speed and accuracy

Continue Reading

Don’t worry about AI going bad – the minds behind it are the problem!

As the science fiction novelist William Gibson famously observed: “The future is already here – it’s just not very evenly distributed.” I wish people would pay more attention to that adage whenever the subject of artificial intelligence (AI) comes up. Public discourse about it invariably focuses on the threat (or promise, depending on your point

Continue Reading

How Will Data Science Evolve Over The Next Decade?

Shutterstock How do you think data science will change over the next 10 years?originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. Answer by Eric Mayefsky, Head of Data Science at Quora, on Quora: There are many aspects to data science and being a data scientist that

Continue Reading

What is Deep Learning? Everything you need to know!

WHAT IS DEEP LEARNING? Deep learning is a subset of machine learning, which itself falls within the field of artificial intelligence. WHAT IS THE DIFFERENCE BETWEEN DEEP LEARNING, MACHINE LEARNING AND AI? Artificial intelligence is the study of how to build machines capable of carrying out tasks that would typically require human intelligence. That rather

Continue Reading

Machine learning — Is the emperor wearing clothes? (A behind-the-scenes look at how ML works)

Machine learning uses patterns in data to label things. Sounds magical? The core concepts are actually embarrassingly simple. I say “embarrassingly” because if someone made you think it’s mystical, they should be embarrassed. Here, let me fix that for you. The core concepts are embarrassingly simple. Our thing-labeling example will involve classifying wine as yummy or not-so-yummy

Continue Reading