Global Google AI Platform report from Global Insight Services is the single authoritative source of intelligence on Google AI Platform market. The report will provide you with analysis of impact of latest market disruptions such as Russia-Ukraine war and Covid-19 on the market. Report provides qualitative analysis of the market using various frameworks such as Porters’ and PESTLE analysis. Report includes in-depth segmentation and market size data by categories, product types, applications, and geographies. Report also includes comprehensive analysis of key issues, trends and drivers, restraints and challenges, competitive landscape, as well as recent events such as M&A activities in the market.
Google AI Platform is a cloud-based platform for developing, training, and deploying machine learning models. It provides a managed environment for running Jupyter notebooks, training models, and deploying models. AI Platform also provides a variety of tools for monitoring and optimizing machine learning models.
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Market Segments
The AI Platform Market is segmented by component, deployment mode, application and region. By component, the market is divided into tools and services. Based on deployment mode, it is bifurcated into cloud and on-premises. On the basis of application, it is classified into forecasts & prescriptive models, chatbots, speech recognition, and text recognition. Region-wise the market is divided into North America, Europe, Asia-Pacific, and the Rest of the World.
Key Players
the AI Platform Market includes players such as Microsoft, Google, Salesforce, IBM, Intel, Amazon Web Services, HPE, Ayasdi, Qualcomm Technologies, and Absolutdata.
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Key Trends
There are four key trends in AI Platform technology:
1. Increased use of artificial intelligence (AI) in business: According to a recent study by McKinsey Global Institute, AI has the potential to create $13 trillion in value for businesses by 2030. As businesses become more aware of the potential of AI, they are increasingly investing in AI Platforms to help them automate processes, improve decision-making, and gain a competitive edge.
2. Advancements in machine learning: Machine learning is a key technology used in AI Platforms. Recent advancements in machine learning algorithms have made it possible for AI Platforms to provide more accurate results.
3. Increased use of big data: AI Platforms make use of large data sets to train their machine learning models. As the amount of data available increases, so does the accuracy of the results provided by AI Platforms.
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