Market Trends of LA Neuromorphic Chip Industry
This section covers the major market trends shaping the Latin America Neuromorphic Chip Market according to our research experts:
Automotive is the Fastest Growing Industry to Adapt Neuromorphic Chip
- The automotive industry is one of the fastest-growing industries for neuromorphic chips. All the premium car manufacturers are investing heavily to achieve Level 5 of Vehicle Autonomy, which in turn, is anticipated to generate huge demand for AI-powered neuromorphic chips.
- The autonomous driving market requires constant improvement in AI algorithms for high throughput with low power requirements. Neuromorphic chips are ideal for classification tasks and could be utilized for several scenarios in autonomous driving. Compared with static deep learning solutions, they are also more efficient in a noisy environment, such as self-driving vehicles.
- According to Intel, four terabytes is the estimated amount of data that an autonomous car may generate through almost an hour and a half of driving or the amount of time a general person spends in their car each day. Autonomous vehicles face a significant challenge in efficiently managing all the data generated during these trips.
- The computers running the latest self-driving cars are effectively small supercomputers. The companies, such as Nvidia, aim to achieve Level 5 autonomous driving in 2022, delivering 200TOPS (trillions of operations per second) using 750W of power. However, spending 750W an hour on processing is poised to have a noticeable impact on the driving range of electric vehicles.
- ADAS (Advanced Driver Assistance System) applications include image learning and recognition functions among various automotive applications of neuromorphic chips. It works like conventional ADAS functions, such as cruise control or intelligent speed, assist system in passenger cars. It can control vehicle speed by recognizing the traffic information marked on roads, such as crosswalks, school zone, road-bump, etc.
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Increasing Demand for Artificial Intelligence-based Microchips drive the market growth
- The Latin American neuromorphic chip market is experiencing high growth due to increasing demand for artificial intelligence and consumer preference towards small-sized products leading to the requirement of miniaturization of ICs. With the advent of smart technologies, smart sensors are being used in many end-user industries like automotive, electronics, and medical.
- Currently available semiconductors for AI applications are CPUs and AI accelerators. The AI accelerators are leading the market because of the computing limitations of CPUs. Available AI accelerators are GPUs, Application-Specific Integrated Circuits (ASICs), and Field-Programmable Gate Arrays (FPGAs). GPUs have many parallel processing cores, which give them a significant advantage for processing AI training and inference. However, they do have a high-power consumption cost which is not sustainable for future applications.
- On the other hand, emerging FPGAs can have ten times more power efficiency than GPUs but have lower performance. In applications where energy efficiency is the top priority, FPGAs can be the alternative solution. Among AI Accelerators, ASICs show the best performance, lesser power consumption, and efficiency. However, designing unique functioning ASIC is highly costly and is not reconfigurable. Therefore, ASICs should be used when the market of specific AI applications is adequate for the design investment.
- Compared to AI Accelerators, neuromorphic chips are poised to be the prominent option concerning parallelism, energy efficiency, and performance. They can handle both AI inference and training in real-time. Moreover, edge training is possible through neuromorphic chips. However, learning methodologies should be improved their accuracy.
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