The Latin America, Middle East and Africa Machine Learning Chip Market would witness market growth of 24.7% CAGR during the forecast period (2024-2031).
The Brazil market dominated the LAMEA Machine Learning Chip Market by Country in 2023, and would continue to be a dominant market till 2031; thereby, achieving a market value of $936.6 million by 2031. The Argentina market is showcasing a CAGR of 25.4% during (2024 - 2031). Additionally, The UAE market would register a CAGR of 23.5% during (2024 - 2031).
Edge computing, where data is processed closer to the source rather than in centralized data centers, is a major driver of this chip adoption. Edge devices like smartphones, smart cameras, and IoT sensors must process data in real-time with minimal latency. These chips, specifically designed for low-power, high-performance edge computing, are increasingly embedded into these devices to enable quick, efficient processing of AI tasks without relying on the cloud.
In recent years, there has been a growing emphasis on energy efficiency and cost reduction. Traditional processors (CPUs) are not optimized for the heavy computational demands of AI and ML algorithms. These chips, especially ASICs and FPGAs, offer significant efficiency improvements, enabling organizations to reduce energy consumption and operational costs. As businesses seek to optimize their AI investments, ML chips provide a cost-effective solution for deploying large-scale AI models.
The integration of ML in the automotive industry is essential for various applications such as autonomous driving, predictive maintenance, and in-car infotainment systems. ML chips are crucial for processing the vast amounts of data required for these applications, enabling real-time decision-making and enhancing vehicle performance and safety. As Saudi Arabia's automotive sector continues to expand and innovate, the demand for ML chips is expected to increase, significantly contributing to the growth of this market. The UAE is rapidly embracing AI technologies, with AI expected to contribute over 14% to the country's GDP by 2030, equating to $96 billion. Between 2018 and 2030, the annual growth in AI's economic contribution to the UAE will increase by 33.5%. This substantial growth underscores the country's commitment to becoming a global leader in AI adoption and innovation across various sectors. Hence, the burgeoning automotive sector in Saudi Arabia and the increasing adoption of AI in the UAE are significant factors propelling the growth of the machine learning chip market.
Free Valuable Insights: The Worldwide Machine Learning Chip Market is Projected to reach USD 45.0 Billion by 2031, at a CAGR of 22.0%
Based on Technology, the market is segmented into System-on-Chip (SoC), System-in-Package, Multi-chip Module, and Other Technology. Based on Chip Type, the market is segmented into GPU Chip, ASIC Chip, CPU Chip, FPGA Chip, Flash-Based Chip, Neuromorphic Chip, and Others. Based on Industry Vertical, the market is segmented into IT & Telecom, Consumer Electronics, BFSI, Retail, Automotive, Healthcare, Media & Advertising, Robotics Industry, and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
By Technology
By Chip Type
By Industry Vertical
By Country
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