Artificial Intelligence Empowers Drug Discovery: New AI-startups Focus On Biotech

Not just a powerful computer but a human’s brain simulation

Being a sub-set of artificial intelligence, machine learning involves algorithms allowing computers to autonomously learn from input data. A fundamental distinction from “usual” software programs, such as Photoshop or, say, Excel, is that in machine learning computers don’t have to be explicitly programmed but can change and improve their algorithms by themselves.

The history of machine learning goes back to the 1950th. The first learning program was created by Arthur Samuel in 1952 and it was the game of checkers. Implemented in IBM computer, the program was able to improve itself the more it played studying winning moves and incorporating them into the next rounds.

Five years later Frank Rosenblatt designed the first neural network for computers - the perceptron, which simulated the thought processes of the human brain. And just a decade later the “nearest neighbor” algorithm was written, which was a conceptual step towards pattern recognition technology...

Today, machine learning algorithms enable computers to “see” and distinguish objects and text in images and videos, discover and categorize real-world things, communicate with humans, drive cars on auto-pilot, write and publish sport match reports, and ... help discover new drugs.

The stumbling stone of modern drug development