Machine Learning Engineers

Artificial intelligence as we know it today can be traced to 1943, when Warren McCulloch and Walter Pitts, researchers at the University of Chicago, conceived of the first neural network. The analytics software developer SAS describes neural networks as “computing systems with interconnected nodes that work much like neurons in the human brain. Using algorithms, they can recognize hidden patterns and correlations in raw data, cluster and classify it, and—over time—continuously learn and improve.” In 1956, Allen Newell, Herbert A. Simon, and John Clifford Shaw of the Rand Corporation created a computer program called The Logic Theorist. It was the “first program deliberately engineered to mimic the problem solving skills of a human being,” according to Jeremy Norman’s HistoryofInformation.com. A mathematics professor named John McCarthy first coined the term “artificial intelligence” in 1956 at the Dartmouth Summer Research Project on Artificial Intelligence workshop. In his plan for the workshop, McCarthy stated that the event was “to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” In 1958, a psychologist named Frank Rosenblatt designed the first artificial neural network, called Perceptron, which demonstrated an ability to learn.

The first practical use of machine learning occurred in the early 2010s, when vast amounts of data began to be collected and analyzed and computer processing power increased significantly. Notable machine learning breakthroughs included IBM’s Watson (a supercomputer that utilized machine learning, natural language processing, and data retrieval technology) beating two human Jeopardy champions in a three-day competition (2011), the neural network Google Brain learning how to recognize humans and cats after reviewing unlabeled images in YouTube videos (2012), Google’s AlphaGo became the first program to beat a professional player at Go, which is considered the most difficult board game in the world (2016); and the release of generative AI technologies, which are being used to create new content, including audio, images, text, code, simulations, and videos (2020s). In 2024, the researchers John J. Hopfield and Geoffrey Hinton received the Nobel Prize for Physics. According to the Nobel Prize Web site, Hopfield and Hinton "used tools from physics to develop methods that are the foundation of today’s powerful machine learning."