The fourth edition of the Machine Learning Developers Summit (MLDS) aims to bring together India's leading experts in the machine learning domain. In an interesting tech talk on the first day of the summit, titled "Move over ML, It's Time for XL" by Soumendra Mohanty, Chief Strategy Officer & Chief Innovation Officer at Tredence, stressed on how energies should be spent on "experience learning", rather than just on building machine learning algorithms. "The intent is not to forget machine learning concepts and the whole thing about algorithms, data, and cloud. Over the last two decades or so, there has been so much advancements and experimentation in this area of machine learning, but an area that has been neglected is what and for whom we are doing all of this," Mohanty said.

Deep learning techniques do a good job at building models by correlating data points. But many AI researchers believe that more work needs to be done to understand causation and not just correlation. The field of causal deep learning -- useful in determining why something happened -- is still in its infancy, and it is much more difficult to automate than neural networks. Much of AI is about finding hidden patterns in large amounts of data. Soumendra Mohanty, executive vice president and chief data analytics officer at L&T Infotech, a global IT service company, said, "Obviously, this aspect drives us to the'what,' but rarely do we go down the path of understanding the'why.'"

Although both AI and blockchain are probably at the peak of the'hype cycle' at the moment, that is where their similarities end; these two technologies actually represent contrasting ways of understanding and ordering the world.

The future of the language industry is bright. In a world where globalization brings us closer together, advances in technology make it easier than ever to communicate and conduct our work efficiently. The primary purpose of a machine is to facilitate a specific task; so, the question remains, why do so many of us fear the rise of artificial intelligence (AI)? Admittedly, the notion of a machine learning to navigate an area so intimately human as language is disquieting. Where do humans fit in an industry that is so eager to introduce machine learning technologies?

Penguins inhabit one of the most secluded parts of the planet, yet human activity is threatening their existence. Warmer temperatures associated with climate change are melting the Antarctic ice faster than ever, eroding the grounds where penguins live, feed and breed, while commercial overfishing and incidents like oil spills are depleting their food supply. A 2008 World Wildlife Fund study reveals that if the global average temperatures increase by just 2 C – a distinct possibility over the next 40 years – around 50 percent of emperor penguins and 75 percent of Adelie penguins could disappear. Conservation efforts for penguins are easier said than done. Their secluded existence in the Antarctic region means there is very little data available, and manned missions are difficult, especially during the harsh winters.