No human, or team of humans

Future of Artificial Intelligence

No human, or team of humans, could possibly keep up with the avalanche of information produced by many of today’s physics and astronomy experiments. Some of them record terabytes of data every day- and the torrent is only increasing. The Square Kilometer Array, a radio telescope slated to switch on in the mid-2020s, will generate about as much data traffic each year as the entire internet.

Artificial Intelligence(AI) is the  making machines emulate human intelligence in today’s world. In simpler terms, this is a procedure where machines use raw data, learn, reiterate and verify aspects of data without human intervention at all points of time.

It is unconditional that Artificial Intelligence has been a prime entity in today’s world and it has shown nothing but strong exponential growth throughout. Tesla’s Autopilot and Google’s DeepMind are prime examples of the future scope of Artificial Intelligence.

Analytics and surveys suggest the same, the future scope of Artificial Intelligence is bright and it will bring about a revolution in the way we interact with the world. Listed below are the numerous ways in which AI can change the future for good:

Artificial Intelligence in Science

Forbes says that Artificial Intelligence has a good scope in adding value to life, and numbers have been proving this claim since then. For example, in 2019, there was a breakthrough in medicine and AI when researchers found out that the onset of breast cancer can be detected accurately early on and can help doctors identify better in terms of benign and malignant cells.

The future scope of Artificial Intelligence to understand that AI can be put to effective use in any field. Here’s another- BlueDot, an AI platform, detected abnormal levels of pneumonia in Wuhan, China, at the end of 2019, and just 9 days later, the World Health Organization (WHO) declared the detection of the ‘novel coronavirus’ – This indicates that AI has a greater role to play in terms of medicine, clinical research and in the vast fields of biology.

Take considering all of this, it is safe to presume that AI will accelerate scientific research and application rapidly.

Huge numbers of scientists turning to artificial intelligence for help. With minimal human input, AI systems such as artificial neural networks- computer-simulated networks of neurons that mimic the function of brains- can plow through mountains of data, highlighting anomalies and detecting patterns that humans could never have spotted.

Computers to aid in scientific research goes back about 75 years, and the method of manually poring over data in search of meaningful patterns originated millennia earlier. But some scientists are arguing that the latest techniques in machine learning and AI represent a fundamentally new way of doing science. One such approach, known as generative modeling, can help identify the most plausible theory among competing explanations for observational data, based solely on the data, and, importantly, without any pre programmed knowledge of what physical processes might be at work in the system under study. Proponents of generative modeling see it as novel enough to be considered a potential “third way” of learning about the universe.