AI Chipsets Market

The report "AI Chip Market by Offerings (GPU, CPU, FPGA, NPU, TPU, Trainium, Inferentia, T-head, Athena ASIC, MTIA, LPU, Memory (DRAM (HBM, DDR)), Network (NIC/Network Adapters, Interconnects)), Function (Training, Inference) & Region – Global Forecast to 2029" The AI Chip Market is projected to grow from USD 123.16 billion in 2024 and is estimated to reach USD 311.58 billion by 2029; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 20.4% from 2024 to 2029.AI chips have emerged as the epitome of technological growth. The growing emphasis on parallel computing in Al data centers is bound to drive innovation across industries such as BFSI, Healthcare, Retail, and E-commerce. Moreover, the growth in AI server shipment is likely to fuel the demand for AI chips. Moreover, the growth of the market is attributed to growing adoption of industrial robotics and automation that rely on AI capabilities.

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By technology, the natural language processing segment is projected to grow at a significant CAGR of the AI Chip market during the forecast period.

The segment for natural language processing technology is expected to grow at a significant rate from during the forecast period. Applications, such as chatbots, virtual assistants, language translation services, sentiment analysis, and text analytics, all need NLP in processing and understanding human languages. Since the application is very wide, huge demand has been created for the powerful AI chips that could handle extensive computational requirements for NLP tasks, hence driving growth in the AI chip market. From the invention of large-scale language models like GPT-4 and BERT, complexity and size for NLP models increased. For instance, last May 2024, OpenAI released GPT-40, which is capable of reasoning on text, video, and audio in real-time; deployment in applications from content generation to virtual assistants underlines the fast-rising demand for AI chips supporting NLP.

By offering, the memory segment is projected to grow at a significant rate during the forecast period.

The memory segment is expected to grow at the high CAGR during the forecast period. There is a rapid growth in AI applications due to which there is increase in data generation and processing requirements. This increase in data volumes leads to increasing demand for advanced memory solutions such as High Bandwidth Memory (HBM), and DDR5 which are capable of storing and accessing large amounts of data efficiently. AI applications involving machine learning and deep learning require high-speed processing capabilities and rapid data access. Dynamic Random-Access Memory (DRAM) supports the need for faster computational performance with increasing complexity of AI algorithms. Advancements in DRAM such as shift to DDR5 provides high data transfer rate and improved energy efficiency. For instance, in May 2024, Micron Technology, Inc. (US) launched 32GB server DRAM with 128GB DDR5 memory that provides 22% better energy efficiency, 45% better bit density, and offers a speed of 5,600 MT/s on server platforms. The high-speed memory module is designed to support the most critical data center applications, such as artificial intelligence, machine learning, in-memory databases, high-performance computing, and efficient processing. Improvements in these technologies for memory solutions driving the workload of AI are drivers for the adoption of DRAM solutions and fuel memory segment growth.

The Healthcare segment is projected to grow at a high CAGR of the AI Chip market during the forecast period.

The adoption rate for AI chips in healthcare is currently on the rise. The medical institutions and technology companies have started spurring advanced AI capabilities for improved diagnostics, treatment planning, and personalized medicine. In this respect, the adoption of AI chips in the development of large language models and other AI-driven medical applications has totally revolutionized health sectors in terms of their enabling more accurate and timely medical interventions. In October 2022, Cerebras announced it was partnering with the Mayo Clinic to develop large language models for medical applications. They created the Rheumatoid Arthritis diagnostic model using the Cerebras CS-2 to integrate patient records, DNA data, and drug information to pair patients with the most effective therapeutics. Such AI chips would thus be most critical in furthering personalized medicine, in which treatment plans are tailored for a unique genetic and medical profile for each patient, within the processing of these vast data sets and intricate algorithms.

Noth America is poised for high growth in the AI Chip market by 2029.

The US, Canada, and Mexico are the major contributors to the North American AI chip market. North America is a dominant contributor to the AI chip market in terms of market share. The AI chip manufacturers in North America collaborate with industry partners, research institutions, and government agencies to expand market reach and drive technological innovation. These players are participating in strategic alliances to accelerate the adoption of AI chips technology in emerging sectors thus supporting the market growth in North America. Leading companies in North America, such as Qualcomm Technologies, Inc. (US), Advanced Micro devices, Inc. (AMD) (US), Intel Corporation (US), Google (US), provide AI chips for data centers and various industries. These companies significantly invest in R&D to improve the reliability, performance, and efficiency of AI Chip technology. This includes advancements in manufacturing processes and design techniques to meet the evolving demands of different industries in the region. Extensive focus of regional players in new product development and innovations will boost the AI chip market growth across North America over the forecast timeline.

Key Players

Key companies operating in the AI Chip market are NVIDIA Corporation (US), Advanced Micro Devices, Inc. (AMD) (US), Intel Corporation (US), Micron Technology, Inc. (US), Google (US), Qualcomm Technologies, Inc. (US), Apple Inc. (US), Huawei Technologies Co., Ltd. (China), SK Hynix Inc. (South Korea), Samsung (South Korea), Imagination Technologies (UK), Graphcore (UK), and Cerebras (US).

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