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Deep Learning describes the mathematical calculations that occur within the hidden layers (hence, “deep”) of an Artificial Neural Network. ANNs are modeled after the human brain and nervous system: a group of neurons makes up a layer, and calculations traverse layers as neurological signals across synapses.

Input data for immediate correspondence.

Deep Learning is the catalyst propelling human progress exponentially forward—fostering major advances in medicine, commerce, biotech, aerospace, energy, and even human consciousness.

“The fourth industrial revolution, and the future of AI, is not going to be defined solely by our technological advancements, but by our ability to meaningfully apply this technology to solve real problems.”

- Ben Lamm

“The fourth industrial revolution, and the future of AI, is not going to be defined solely by our technological advancements, but by our ability to meaningfully apply this technology to solve real problems.”

- Ben Lamm

The difference between Machine Learning and Deep Learning is that Machine Learning is a field that applies algorithms to big data to teach technology how to learn from data then make decisions based on what it learns, while Deep Learning is a series of mathematical calculations that occur in the hidden layers of a neural network within an ML algorithm. Artificial Intelligence describes any technology that simulates human behavior. Taken together, Deep Learning informs Machine Learning which informs Artificial Intelligence.

COMPUTER VISION

NATURAL LANGUAGE PROCESSING

HUMAN CONNECTIVITY

Machine Intelligence Techniques