The edge AI hardware market is projected to grow from 1,056 million Units to reach 2,716 million units by 2027; it is expected to grow at a CAGR of 20.8% during the forecast period. The major opportunities for the edge AI hardware market include the growing demand for IoT-based edge computing solutions and the rising adoption of 5G networks to bring IT and telecom together and dedicated AI processors for on-device image analytics. Major restraints for the market are limited on-device training and the shortage of AI experts. Designing efficient AI system pose major challenges to the edge AI hardware market.
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Training to have second highest CAGR during the forecast period.
Training is the process of developing an algorithm that will be used to infer the output. ML models are trained to develop the ability to understand a data set and act on new data. No actual learning happens on devices as training requires high computational power. As mobile devices do not have high-performance computing, ML models are trained on the cloud. Moreover, on-device training is not required for each application, and it will be limited to certain devices such as automotive systems and robots. Considering its advantages, on-device training is expected to increase in the next few years. With on-device training capability, a model can learn from a user’s data available on the device, making the data more secure. With on-device training, an ML model can learn and update continuously.
US to grow with highest CAGR in North America during the forecast period.
The US is the major revenue generator for players dealing in edge AI hardware in North America. The US is a key market for AI application processors as the demand for smartphones, smart home appliances, and advanced products such as IoT devices, wearable electronics, and vehicles with high-security features is high in the country. The US government has announced significant investments in machine learning solutions across various sectors, including consumer electronics, healthcare, and government. The abundance of capital and strong support of the US government contribute to the large-scale adoption of ML/AI solutions. The country’s data center industry continues to grow with rising investments in artificial intelligence and technological advancements.
The report profiles key players in the edge AI hardware market and analyzes their market shares. Players profiled in this report are Apple (US), MediaTek (Taiwan), Qualcomm Technologies (US), Huawei Technologies (China), and Samsung Electronics (South Korea), Intel (US), NVIDIA (US), IBM(US), Google (US), Microsift (US), AMD (US), Micron Technology (US), Imagination Technologies (UK), Cambricon Technologies (China), Tenstorrent (Canada), Blaize (US), General Vision (US), Mythic (US), Zero ASIC (US), Applied Brain Research (Canada), Horizon Robotics (China), CEVA (US), Graph core (UK), SambaNova (US), Hailo (Israel), Veridify Security (US).
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The report defines, describes, and forecasts the edge AI hardware market based on device, function, power consumption, processor, vertical and geography. It provides detailed information regarding factors such as drivers, restraints, opportunities, and challenges influencing the growth of the edge AI hardware market. It also analyzes competitive developments such as product launches, acquisitions, expansions, contracts, partnerships, and developments carried out by the key players to grow in the market.
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