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Deep Learning Interfaces: Future of AI (Technical Insights) 

  • July 2015
  • -
  • Frost & Sullivan
  • -
  • 45 pages

Summary

Table of Contents

Deep Learning Interfaces: Future of AI (Technical Insights) : Deep Learning Unravels Layers of Patterns in Large Data

Deep learning refers to the latest futuristic advancements in which machines are trained to think like the human brain, which includes recognizing patterns and making inferences about the surrounding environment. Innovation trends and applications are evolving in this space to make an effective contribution to growing segments such as artificial intelligence (AI), Internet of Things (IoT), social computing, voice recognition, speech and text analyses, image and object recognition. The objective of the research service is to offer a detailed account of deep learning technology segments, technology innovations, and application innovations across sectors. This research service provides insights on deep learning interfaces and their impact on key sectors. It also provides notes on futuristic applications and major convergence scenarios.

Key Findings

Deep learning has the capability to find patterns among layers of data by enabling wide range of abstractions. These abstractions are considered to be non existent while using conventional learning algorithms. The deep learning based abstractions help in enabling in depth human like cognition

Conventional machine learning algorithms are difficult to implement in small data sets as they fail to find patterns or abstraction which can help machines learn. Deep learning can be implemented in both small and large data enabling easier integration and in turn enables easier understanding of various patterns within any form of data sets

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