The Latin America, Middle East and Africa Machine Learning Chip Market is expected to 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 is expected to 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.
The Brazil market dominated the LAMEA Machine Learning Chip Market by country in 2023, and is expected to 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.
List of Key Companies Profiled
- Advanced Micro Devices Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- NXP Semiconductors N.V.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- NVIDIA Corporation
- Intel Corporation
- Infineon Technologies AG
- IBM Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Cerebras Systems Inc.
Market Report Segmentation
By Technology
- System-on-Chip (SoC)
- System-in-Package
- Multi-chip Module
- Other Technology
By Chip Type
- GPU Chip
- ASIC Chip
- CPU Chip
- FPGA Chip
- Flash-Based Chip
- Neuromorphic Chip
- Others
By Industry Vertical
- IT & Telecom
- Consumer Electronics
- BFSI
- Retail
- Automotive
- Healthcare
- Media & Advertising
- Robotics Industry
- Others
By Country
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. LAMEA Machine Learning Chip Market by Technology
Chapter 6. LAMEA Machine Learning Chip Market by Chip Type
Chapter 7. LAMEA Machine Learning Chip Market by Industry Vertical
Chapter 8. LAMEA Machine Learning Chip Market by Country
Chapter 9. Company Profiles
Companies Mentioned
- Advanced Micro Devices Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- NXP Semiconductors N.V.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- NVIDIA Corporation
- Intel Corporation
- Infineon Technologies AG
- IBM Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Cerebras Systems Inc.
Methodology
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