Next Generation AI

Posted on 2021-01-16 10:42:06 by admin

As one of the global #technology leaders, we are leveraging next-generation #AI & #ML powered smart solutions and providing a cost-effective, flexible, and scalable framework to extensively support your #IT requirements

The field of artificial intelligence moves fast. It has only been 8 years since the modern era of deep learning began at the 2012 ImageNet competition. Progress in the field since then has been breathtaking and relentless. While supervised learning has driven remarkable progress in AI over the past decade, from autonomous vehicles to voice assistants, it has serious limitations.

The process of manually labeling thousands or millions of data points can be enormously expensive and cumbersome. The fact that humans must label data by hand before machine learning models can ingest it has become a major bottleneck in AI.

At a deeper level, supervised learning represents a narrow and circumscribed form of learning. Rather than being able to explore and absorb all the latent information, relationships and implications in a given dataset, supervised algorithms orient only to the concepts and categories that researchers have identified ahead of time.

In contrast, unsupervised learning is an approach to AI in which algorithms learn from data without human-provided labels or guidance.

Many AI leaders see unsupervised learning as the next great frontier in artificial intelligence. In the words of AI legend Yann LeCun: “The next AI revolution will not be supervised.” UC Berkeley professor Jitenda Malik put it even more colorfully: “Labels are the opium of the machine learning researcher.”

How does unsupervised learning work? In a nutshell, the system learns about some parts of the world based on other parts of the world. By observing the behavior of, patterns among, and relationships between entities—for example, words in a text or people in a video—the system bootstraps an overall understanding of its environment. Some researchers sum this up with the phrase “predicting everything from everything else.”

Unsupervised learning more closely mirrors the way that humans learn about the world: through open-ended exploration and inference, without a need for the “training wheels” of supervised learning. One of its fundamental advantages is that there will always be far more unlabeled data than labeled data in the world (and the former is much easier to come by).

If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.