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Applications of artificial intelligence that are in use today

To be fair, there is NONE, but much imitation of AI-like automation.

Strictly speaking, real AI implies the deep understanding of the world, instead of automatic deep learning of big data; full autonomy, instead of mechanical automation; and meaningful relations in the data structures, instead of computarized pattern matching.

All AI Market innovations are just advanced automatic tools of special types, tasks, applications and industries:

Agriculture

BFSI

IT & Telecom

Gaming & Consumer Electronics

Education

Automotive & Transportation

Healthcare

Manufacturing

Power Sector

Government

Oil & Gas

Legal

Entertainment

Defense & Aerospace

Types:

Automated Robotic System,

Expert System,

Embedded System,

Digital Assistance System,

Artificial Neural Network;

Applications:

Cyber Security,

Context Aware Processing,

Speech Recognition,

Video Analysis,

Gesture Control,

Language Processing,

Querying Method,

Digital Personal Assistant,

Image Recognitio,

Face Recognition,

Smart Robots,

On-device AI,

Deep Learning Platforms.

Amazon AI Services, Data Robot, TensorFlow, Google AI, H20, Petuum, Polyaxon, Neural designer, etc. are not any AI platforms.

AI is impersonated by Automated Machine Learning, “the science of training systems to emulate human tasks through learning and automation”.

The most innovative deep learning techniques deploying artificial neural networks, make it possible for machines to mechanically learn from experience, adjust to new inputs and imitate the performance of human-like tasks.

Still there are “AI imitation” innovations shifting from the centralized “cloud AI” to the distributed edge AI (IoT) services and devices.

“The latest wave is the emergence of on-device artificial intelligence (AI). Instead of relying entirely on the cloud for AI insights, a new wave of specialized algorithms and chips is delivering deep insights wherever work is done. According to ABI Research

, shipments of devices with edge AI capabilities will grow fifteenfold by 2023, to 1.2 billion units. The share of AI tasks that take place on edge devices instead of in the cloud will grow more than sevenfold, from 6 percent in 2017 to 43 percent in 2023”.


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