Press release
AI Training Dataset Market Statistics 2021: Record High Markets Ahead with New launches and Expansion
AI training dataset expected to witness a tremendous growth in the future, owing to rise in adoption of automation technology in various industries such as manufacturing and automotive. In addition, AI training dataset is sometimes referred as training dataset, learning set, or ground truth data. AI training dataset is basically information used to train a machine learning model, which includes both input data and corresponding output. MI and AI models use various datasets to learn and recognize various data patterns to use different technologies so that models can make accurate results when implemented in real world applications.Download a Sample copy of Report:- https://www.alliedmarketresearch.com/request-sample/8180
Top impacting factors: Market Scenario Analysis, Trends, Drivers, and Impact Analysis
Rise in adoption of artificial technology across various data-driven applications such as voice recognition and image recognition is the major factor that drives growth of the market. However, lack of technical expertise understanding and implementing complex AI model hampers the market growth. Furthermore, rise in need for machine and human interaction is expected to provide lucrative opportunities for the global AI training dataset market.
The market trends for global AI training dataset market are as follow:
Notable developments in the field of AI training dataset market:
The AI training dataset market is growing at a very fast pace, and is a very competitive market, hence prominent players are adopting different strategies such as expansion of their services, new product launches, collaborations, partnerships, and mergers to increase their reach in the market. For instance, in January 2019, IBM Corporation released a new dataset that comprises 1.0 million images of faces. The dataset would help developers to train their face recognition systems supported by artificial intelligence technology with diverse datasets. Moreover, it would help developers to increase accuracy of face identification. In March 2019, Appen Limited, a specialized dataset provider, announced acquisition of Figure Eight Inc., which is a provider of machine learning platform. The acquisition is expected to help the company to increase creation speed of a high-quality dataset for training AI to enhance quality of data.
Technology advancements and large amount of data generation:
Large volume of data generated from these technologies such as AI, machine learning, and big data have created demand for AI training dataset. Massive amount of unstructured and irrelevant data is generated from these technologies, therefore, it is important to train a machine learning model with accurate and relevant data only. Thus, to make accurate predictions and to improve performance of AI training datasets, various technologies have been adopted by different industries to improve their overall performance.
Asia-Pacific region is anticipated to dominate the market growth:
Asia-Pacific is expected to witness a significant growth, owing to emerging economies such as India, China, and South Korea. These countries are emerging as manufacturing hubs, owing to which many industries in the region are adopting AI and automated solutions to gain a competitive edge and achieve maximum productivity, which fuels growth of the market.
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Key benefits of the report:
This study presents analytical depiction of the global AI training dataset market along with the current trends and future estimations to determine the imminent investment pockets.
The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the market share.
The current market is quantitatively analyzed from 2020 to 2027 to highlight the global AI training dataset market growth scenario.
Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
The report provides a detailed market analysis based on competitive intensity and how the competition will take shape in coming years.
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