The concept of Artificial Intelligence (AI) is rampant in this machine-dominated world as a vision conjuring tool that helps Human beings use these machines. Unfortunately, not even a single AI is able to learn as fast as the human brain. And perhaps not happy with this, Intelligence Advanced Research Projects Activity (IARPA) has granted three different departments within Harvard University a total sum of $28 million to find out the reasons why the brain is so good at learning things in comparison to artificial systems.

In such a comparison, IARPA is wondering why a human brain can, for instance, see a car once or a few times and instantly recognize it while even the most advanced AIs have to look at thousands of those car samples before conjuring that what they are seeing is indeed a car. For that matter, researchers from John A. Paulson School of Engineering and Applied Sciences, Center for Brain Science (CBS) and Department of Molecular and Cellular Biology have all been tasked to take a closer look at the activities going on in a brain’s visual cortex and find out how neurons are connected to each other. They should then gather information and find a method of building much better AI systems.

Even though this is an utterly ambitious project, researchers are quick to admit that this task will not be an easy walk in the park with more than 1.6 million CDs worth of data expected to come out of this project. No matter the outcome of this specific research aim, experts are adamant that this would lead to other advances in computing, as well as many new ways of managing data and speeding up its processing time.