China Artificial Intelligence Research Study: Strong Distribution Channels Expected To Provide More Convenience To Various End Users In The Global Market 2022 – 2030

Artificial Intelligence Market: Introduction

Transparency Market Research delivers key insights on the global artificial intelligence market. In terms of revenue, the global artificial intelligence market is estimated to expand at a CAGR of ~29% during the forecast period, owing to numerous factors regarding which TMR offers thorough insights and forecasts in its report on the global artificial intelligence market.

Artificial intelligence is a fast emerging technology, dealing with development and study of intelligent machines and software. These software are being used across various applications such as manufacturing (assembly line robots), medical research, and speech recognition systems.

Replacement of workers with advanced manufacturing robots can be seen as one of the significant trends in the global artificial intelligence market. Artificial intelligence is being applied to robots to provide better intellectual, reasoning, and thinking abilities to enable real-time response. Moreover, these robots can be trained as required and have the capability to carry out any conversation and recalling historical details. As a result, the market is anticipated to witness a healthy growth rate during the forecast period.

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Artificial Intelligence Market: Dynamics

Availability of enormous amount of data and advancement in next-generation computing architecture: Data scientists need enough data for precise accuracy and efficiency to train machine learning models. The growing adoption of cloud for storage of data enables easy access of data for data scientists and research facilities for research. Hence, easy availability of data to research facilities to train machine learning/artificial intelligence models to solve complex problems is expected to boost the artificial intelligence market.

Additionally, growing innovation in processors such as Graphics Processing Unit (GPU) and Field Programmable Gate Array (FPGA) for computing work such as training machine learning models is likely to increase the demand for advanced artificial intelligence platforms in the upcoming years. Traditional CPUs are unable to manage development of machine learning models. However, GPUs come with a huge number of cores that accelerates the machine learning training process. GPUs are the key to artificial intelligence from consumer devices to virtual machines in the public cloud.

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