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The global AI (chipsets) market size is expected to be valued at USD 7.6 billion in 2020 and is likely to reach USD 57.8 billion by 2026, at a CAGR of 40.1% during the forecast period. Major drivers for the market are increasingly large and complex datasets driving the need for AI, the adoption of AI for improving consumer services and reducing operational costs, the growing number of AI applications, the improving computing power, and growing adoption of deep learning and neural networks.

Some of the major players in the AI (chipsets) market are NVIDIA Corporation (NVIDIA) (US), Intel Corporation (Intel) (US), Xilinx, Inc. (Xilinx) (US), Samsung Electronics Co., Ltd. (Samsung) (South Korea), Micron Technology, Inc. (Micron) (US), Qualcomm Technologies, Inc. (US), International Business Machines Corporation (IBM) (US), Google Inc. (Google) (US), Microsoft Corporation (Microsoft) (US), Amazon Web Services (an Amazon.com, Inc. subsidiary) (AWS) (US), Advanced Micro Devices, Inc. (AMD) (US), General Vision, Inc. (US), and Huawei Technologies Co., Ltd. (Huawei) (China).

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Top 2 players in the battery market for IoT are:

Intel (US)

Intel (US) holds the first position in the AI (chipsets) market. It enjoys a strong market presence and has been effectively defending the same. The company has dominated the market for microprocessors for many years. Moreover, the company’s dominant market position ensures a large addressable market. Intel’s market position also provides increased scale and related benefits. The established market position provides competitive advantages and allows the company to penetrate the adjacent markets effectively. One of the competitive advantages of Intel is the combination of a network of manufacturing, assembly, and test facilities with the global architecture design teams. This network enables the company to have more direct control over processes, quality control, product cost, production timing, performance, power consumption, and manufacturing yield.

• In August 2019, Intel and Lenovo (China) announced a multiyear collaboration focused on the rapidly growing opportunity in the convergence of high-performance computing (HPC) and artificial intelligence (AI) to help accelerate solutions for the world’s most challenging problems. Building on the companies’ long-standing partnership in the data center, the multiyear global collaboration will speed the convergence of HPC and AI, creating solutions for organizations of all sizes.
• In April 2019, Intel unveiled a new portfolio of data-centric solutions consisting of 2nd-Generation Intel Xeon Scalable processors, Intel Optane DC memory and storage solutions, and software and platform technologies optimized to help its customers extract more value from their data. Intel’s latest data center solutions target a wide range of use cases within cloud computing, network infrastructure, and intelligent edge applications, and support high-growth workloads, including AI and 5G.

NVIDIA (US)

NVIDIA (US) holds the second position in the AI (chipsets) market. NVIDIA is one of the global leaders in the visual computing business. It has a well-established geographic footprint and mainly deals with major OEMs, and ODMs spread across the globe. NVIDIA has made a substantial investment in its R&D division. This has resulted in its strong organic growth and robust market positioning in terms of hardware product development in the AI (chipsets) market. It uses its existing business channels, as part of its business strategy, to reach customers easily. NVIDIA has more than 40 offices worldwide, generating a major revenue from geographies such as Taiwan, China, the US, and Europe. Its global presence, along with the adoption of inorganic growth strategies, helped the company earn a very high rating.

In May 2020, NVIDIA announced two powerful products for its EGX Edge AI platform the EGX A100 for larger commercial off-the-shelf servers and the tiny EGX Jetson Xavier NX for micro-edge servers delivering high-performance, secure AI processing. With the NVIDIA EGX Edge AI platform, hospitals, stores, farms, and factories can carry out real-time processing and the protection of massive amounts of data streaming from trillions of edge sensors. The platform makes it possible to securely deploy, manage, and update fleets of servers remotely.

• In May 2020, NVIDIA announced that the first GPU based on the NVIDIA Ampere architecture, the NVIDIA A100, is in full production and shipping to customers worldwide. The A100 draws on design breakthroughs in the NVIDIA Ampere architecture — offering the company’s largest leap in performance to date within its eight generations of GPUs — to unify AI training and inference and boost performance by up to 20x over its predecessors. A universal workload accelerator, the A100 is also built for data analytics, scientific computing, and cloud graphics.

Related Reports:

Artificial Intelligence (Chipsets) Market by Technology (Machine learning, Natural Language Processing, Context Aware Computing, Computer Vision), Hardware (Processor, Memory, Network), End-User Industry, and region - Global Forecast to 2026

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