A brain chip is a hybrid entity wherein the nerve cells and chips interconnect to enable information transfer. A human brain consists of over 80 billion neurons and around 100 trillion synapses, which control and connect the passage of signals. When a chip uses connections similar to a synapse, the signals become much more varied, thus enabling synapse-like learning.
Artificial Intelligence, Genuine Diligence
The artificial intelligence technology is widespread across devices, apps, and services. The processor industry has revolutionized with a slew of new chips that accelerate AI tasks not only in smartphones or laptops but also in cars, cameras, and other applications.
A brain chip is a multi-processor chip, which has the ability of learning and reasoning. The integrated circuits detect patterns in data, which have been widely adopted among varied industry verticals.
Artificial intelligence (AI) chips are specialized Silicon chips incorporating AI technology and are used for machine learning. AI helps to eliminate or minimize the risk to human life in many industry verticals. The need for more efficient systems to solve mathematical and computational problems has been becoming crucial, because the volume of data has been increasing. Thus, majority of the key players in the IT industry have focused on developing AI chips and applications.
Companies buckling up in the race towards leaderCHIP
NVIDIA pioneered the graphics processor unit (GPU) and was instrumental in providing processors with the necessary AI advancements. It has been leading with its GPU chipset series and has been stepping positively towards the development architectures; for instance, NVIDIA incorporated Drive PX in automobiles, Jetson fitted in drones and robots, and Tesla accelerator applied to supercomputers and cloud, which enable algorithm acceleration for deep learning.
On the other hand, Intel has completed the testing of its Lake Crest AI chipset to enhance the efficiency of deep learning. In addition, Intel’s AI blueprint ranging from datacenters to network edges, with the AI chip platform, including field programmable gate array (FPGA) accelerators, Xeon, and Xeon Phi processors, supports the optimization of the specific data load. Furthermore, it has Myriad X, which is applied to drones, augmented reality (AR) devices, or smart cameras to understand and sense fast-sense external environment and facilitate learning.
In addition, in May 2018, Google launched a third version of its tensor process unit (TPU), as an alternative to NVIDIA’s GPU chips. Moreover, Huawei launched its Kirin 970 system-on-chip and claimed to be the world’s first chip that is fitted with a neural processing unit (NPU). Tencent and Baidu are also engaged in developing customized AI chips. This is evidence of the intense competition in the market.
Looking at the future of the AI hardware industry while considering the competitive scenario, Microsoft and Intel claim that the FPGA creates an edge for a growing number of the AI applications. FPGA accelerates AI-related workloads. Considering the growth potential of FPGA, Intel acquired Altera (a leading company that specializes in FPGAs) for $16.7 billion in December 2015 (the largest acquisition that Intel has made to date). Data Centre Group is one of the most profitable group at Intel. Intel is also expected to combine its CPU with Altera’s FPGA. Moreover, to compete with NVIDIA, Intel has started selling a new processor named Knights Mill. Furthermore, Microsoft has been presently using FPGA in its data centers, and it does not use GPUs. Microsoft does not build chips. Intel builds the FPGA, which is consumed by Microsoft. Furthermore, revenues of Xilinx, Inc. (market leader and inventor of FPGA) were steady and profitable during the last five years.
So says a study…….
According to a recent report published by Allied Market Research, titled, AI Chip Market by Technology and Application: Global Opportunity Analysis and Industry Forecast, 2017–2023, the global AI chip market was valued at $661 million in 2016, and is projected to reach at $11,167 million by 2023, growing at a CAGR of 49.6% from 2017 to 2023.
Access full summary at: https://www.alliedmarketresearch.com/artificial-intelligence-chip-market
AI is one of the fastest-growing technologies over the years. Continuous efforts and developments to manufacture more human-like robots and increase in the rate of deployment in developing regions have transformed the overall market.
At present, North America dominates this market, followed by Europe. In 2016, the U.S. dominated the North American market.
The market for AI chips is driven by a surge in implementation of AI chips in robotics and emergence of quantum computing. However, lack of skilled labor and other threats are some of the restraints of the market. Nonetheless, the impact of these factors would be minimal, owing to the introduction of new technologies in the market.