AI Chipsets Industry worth $131.8 billion by 2028
"AI Chipsets Market by Hardware (Processor, Memory, Network), Technology (Machine Learning, Natural Language Processing, Computer Vision), Function (Training, Interference), End-User Industry and Region - Global Forecast to 2028" The AI Chipsets market is projected to grow from USD 51.2 billion in 2023 and is estimated to reach USD 131.8 billion by 2028; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 20.8% from 2023 to 2028. The growth of the AI Chipsets market is driven by the increasing data traffic and need for high computing power, emerging trend of autonomous vehicles, growing adoption of industrial robots, and rising focus on parallel computing in Al data centers.
Browse 183 market data Tables and 63 Figures spread through 295 Pages and in-depth TOC on "AI Chipsets Market by Hardware (Processor, Memory, Network), Technology (Machine Learning, Natural Language Processing, Computer Vision), Function (Training, Interference), End-User Industry and Region - Global Forecast to 2028"
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By hardware device, memory segment projected to grow at a high CAGR of AI Chipsets market during the forecast period.
AI-based memory is revolutionizing the way we store and access information. Traditional computer memory systems have been limited by their fixed architecture and capacity, requiring constant upgrades and replacements to keep up with expanding data needs. However, Al-based memory can dynamically adapt and learn from user behavior to optimize storage and retrieval efficiency. By utilizing machine learning algorithms, Al-based memory systems can analyze patterns in user behavior and data usage to predict future needs and adjust accordingly. This technology is particularly beneficial for large-scale data centers and cloud storage systems, where storing and accessing vast amounts of data efficiently is crucial. Additionally, Al-based memory can enhance security measures by using predictive analysis to detect and prevent potential threats. Implementing Al-based memory can greatly enhance data storage and management capabilities, leading to more efficient and secure systems.
Machine Learning in technology segment in AI Chipsets market is expected to account for second highest share during the forecast period.
Machine learning allows systems to learn deprived of being explicitly programmed. Machine learning technology can reliably and quickly scan, parse, and react to anomalies. It enables systems to improve their performance with experience automatically. It aims to advance a computer program/algorithm which can access data and can be used to train itself with no human intervention. Machine learning technology is predominantly used in AI solutions due to the availability of big data to train machine learning models and the high adoption of machine learning technology by enterprises and federal agencies to gain useful insights.
Training segment will account for highest CAGR during the forecast period.
In the context of Al, training is the process of developing an algorithm that can infer a result from data or processes. Training an Al model involves providing the learning algorithm with training data to learn from. The training data must include the correct answer, known as a target or target attribute. The learning algorithm finds patterns in the training data, maps the input data attributed to the target, and outputs an ML model that captures these patterns. Training is computationally costly and is best accelerated with GPUs. The time undertaken to go through all the training samples can be decreased using GPU compared with CPU, even when using a small dataset.
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