The global AI analytics market size accounted for USD 29,150 million in 2024 and is expected to exceed around USD 2,25,470 million by 2034, growing at a CAGR of 22.7% from 2024 to 2034.
Industry verticals like manufacturing, automotive, healthcare, retail, and finance are adopting cutting-edge technology as a result of the ongoing research and innovation led by tech giants. For instance, Google LLC introduced "Gemini," a huge language Al model, in December 2023. It comes in three sizes: Gemini Nano, Gemini Pro, and Gemini Ultra. Gemini's inherent multimodal feature sets it apart from its rivals.
Access to historical datasets is the key element driving Al's rate of invention. Healthcare organizations and government organizations create unstructured data that is available to the research domain since data storage and recovery have gotten more affordable. Rich datasets, including clinical imaging and historical rainfall trends, are available to researchers. Researchers and information scientists are being encouraged to develop more quickly by next-generation computing architectures, which provide access to rich datasets. Additionally, advancements in deep learning and artificial neural networks (ANN) have accelerated the use of Al in a number of sectors, including manufacturing, automotive, healthcare, and aerospace. ANN helps provide modified answers by identifying similar patterns. ANN has been used by tech businesses such as Google Maps to enhance its routes and address feedback. Conventional machine learning methods are being replaced by ANNs to create more accurate and precise versions.
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| Stats ID: | 7767 |
| Format: | Databook |
| Published: | January 2025 |
| Delivery: | Immediate |
| Price | US$ 1550 |
| Stats ID: | 7767 |
| Format: | Databook |
| Published: | January 2025 |
| Delivery: | Immediate |
| Price | US$ 1550 |
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