Deep Learning Debunked
Deep Learning (DL) is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge.
DL, a subset of machine learning, is essentially an artificial neural network with three or more “deep” layers. These neural networks (or algorithms) attempt to simulate the behavior of the human brain, allowing it to “learn” as they draw conclusions from large amounts of data continually analyzed within a given logical structure. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy. Whenever humans receive new information, the brain tries to compare it with known objects. The same concept is also used by deep neural networks.
DL neural networks, or artificial neural networks, attempt to mimic the human brain through a combination of data inputs, weights, and bias. These elements work together to accurately recognize, classify, and describe objects within the data. DL allows machines to solve complex problems even when using a data set that is very diverse, unstructured, and inter-connected. The more DL algorithms learn, the better they perform. Just about any problem that requires "thought" to figure out is a problem, DL can learn to solve.
This technology drives many AI applications and services that improve automation, performing analytical and physical tasks without human intervention. DL lies behind everyday products and services (such as digital assistants, voice-enabled TV remotes, and credit card fraud detection) as well as emerging technologies (such as self-driving cars).
The amount of data we generate every day is staggering—currently estimated at 2.6 quintillion bytes—and it’s the resource that makes DL possible. Since DL algorithms require a ton of data to learn from, this increase in data creation is one reason that DL capabilities have grown in recent years.
DL factors into Tomestic's Organic Living Book (OLB) in a very big way, as explained by our Founder and CEO, Poet De’Medici, “Synapses of thoughts create patterns. We decipher our environment with pattern recognition and make informed decisions to function in our daily lives. Humans are continually collecting and recycling data. DL, which is what breathes life into our OLB, is designed to do the same thing. It will collect and sort information about the reader and produce an assortment of outputs which will ultimately create a better user experience.”
DL algorithms, a critical component of our patent-pending technology, is one of many solutions Tomestic offers to advance long-term memory. We predict our OLB’s immersive reading experience will impact a worldwide audience and permanently transform learning retention by 2030.
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