Artificial Intelligence

Machine learning is a branch of artificial intelligence that enables machine to develop the ability for self-learning and adaption through experience without being explicitly programmed. It is considered as a method of data analysis that automates analytical model building. Machine learning has been present from decades but not been widely used due to lack of big data it requires for processing. Over the last several decades, enterprises have been dependent greatly on analytics to provide them with competitive advantage and enable them to be more effective. But, enterprises now want real time analytics and the capability to transform data into actionable insight. This has steered the development of machine learning chip. The rising complex and large dataset has steered the need for artificial intelligence solutions has majorly driven the machine learning chip market . Further, declining hardware cost has supplemented the demand for machine learning chip across diverse verticals.

Artificial intelligence (AI) is creation of unique systems using algorithms and software that can perform certain tasks without human intervention and instructions. Artificial intelligence comprises integration of several technologies such as machine learning, natural language processing, reasoning, and perception. Artificial intelligence is used in healthcare for approximation of human cognition and analysis of complex medical and diagnostic imaging data. Artificial intelligence has revolutionized the healthcare industry by designing treatment plans, medication management, assisting in repetitive tasks, and drug discovery. Increasing adoption of precision medicine has made enabled simplicity of management and cost reduction. Increasing application in genomics research coupled with incremental innovation in robotic personal digital assistants boost industry growth. According to the The Insight Partners Knowledge Services market research report, the artificial intelligence

Internet of Things (IoT) has taken businesses today by storm and has become one of the centric strategies for businesses to emerge as the leaders in the market. Most of the businesses have laid enhanced importance towards IoT implementations into the business models for achieving enhanced levels of customer service. Harnessing the power of IoT, business models have witnessed a paradigm shift in their operations. With IoT, the analysis and processing remained limited to the central authority, however, with the advent of AI in edge computing, the analysis and processing power has been transferred to the edge devices.  Increasing penetration of machine learning and advancements in the Artificial Intelligence technologies is anticipated to be one of the major factors driving the AI edge computing market. Higher cost of implementations coupled with weak infrastructures for AI, hinders the adoptions of this technology further posing a challenge to the growth of AI edge computing market.