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Google is borrowing from Darwin to make a seismic leap in automatic machine learning. It could spell out the end of most human bias.

Researchers at Princeton and the Simons Foundation turned the traditional approach on its head, teaching a machine learning algorithm to look for the genetic relationships that could cause autism.

The world of computing is full of buzzwords: AI, supercomputers, machine learning, the cloud, quantum computing and more. One word in particular is used throughout computing – algorithm.

The new algorithm overcomes this barrier by exploring how numerous genetic mutations collectively influence a tumor's reaction to drugs that impede DNA replication.

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

However, particularly in the case of genetic variants that only rarely occur in the population, the influence on the presentation of certain pathological traits has so far been difficult to determine.

This study proposes a relatively simple computational model of organizational evolution based on the genetic algorithm. The model includes three organizational processes: variation, adaptation, and ...