AI (Artificial Intelligence) processor Ecosystem will grow more than twice in the next 5 Years. The IT industry is witnessing a lot of transformations and growth with new technological breakthroughs like "Artificial Intelligence processor". Demand from the communications, data processing, and consumer electronics sectors is largely driving this market. The AI Processor and System on Chip (SoC) will make up most of the total market over the forecast period. The rising acceptance of IoT has also led to a need for powerful smart electronics, which in turn, has increased the demand for powerful AI-enabled Processor. Nvidia and Intel are the current leaders in this market, with upcoming competitors like GraphCore, Habana Labs, and Qualcomm. The growth of AI-enabled processor will rise by 2022, as the autonomous automotive industry will require this Processor for powering the performance of cars’ upcoming "full self-driving" abilities. The Renault-Nissan-Mitsubishi Alliance has planned to launch 40 vehicle models with autonomous drive vehicle technologies by 2022, which will open a larger market for AI processor manufacturers. New manufactured processor units are designed and optimized to quicken the performance of AI workloads and computations. Several companies, including Apple, Samsung, and Tesla, are developing their own AI processors, which are customized to the requirements of their products. Recently, Apple has created its A12 Bionic for iPhone XR and iPhone XS smartphones. The product includes a neural engine for Face ID and Animoji (animated emoji) applications, and it contains an image processor for computational photography and pixel processing functions. A12 offers 15% improved CPU performance for the performance cores and a 50% lower power consumption for the efficiency cores. According to our estimates, the AI Processor Ecosystem is expected to witness a growth of ~25% CAGR from 2019 to 2020.

Figure 1: Ecosystem Snapshot: AI (Artificial Intelligence) processor

Today, companies are investing more in AI software and technology and with this, there is a drastic rise in the number of startups that are targeting new AI processor manufacturing to meet the unique processing requirements by AI workloads. The top 19 AI semiconductor startups working on AI-enabled processers are based in the US. These startups are working on building deep-learning Processor, neuromorphic Processor, etc., which try to imitate the way human brain functions. This is going to raise the number of Processor produced and will increase the competition in the market, thereby affecting the pricing of processers. The rise of AI will almost certainly be the most powerful driving force in the semiconductor industry for the coming decade. Maximum AI startups are based in the US and Europe, whereas in the Asia-Pacific region, countries like China, Japan, India, Singapore, Taiwan, and South Korea are driving AI Processor innovation through various incubation hubs. For example, Chinese startups like Cambricon Technologies, Horizon Robotics, ThinkForce, and DeePhi Technologies, have cumulatively raised $300 million in venture capital funding

Figure 2: AI Processor Ecosystem: Segmentation

Components Product Technology Industry Vertical Micro Processor Smartphone Predictive Maintenance/Self Diagnostics Consumer Electronics ASIC Wearables Machine learning Automotive CPU Automotive ADAS & Infotainment Devices Deep learning Others FPGA NLP GPU Computer Vision Others Predictive Analytics Others

Global AI Processor Ecosystem

The global AI Processor Ecosystem size was valued at $14.8 billion in 2018. At present, the US dominates the artificial intelligence processor market owing to technological advancements. Increasing penetration of HUD screens in luxury cars, smart wearables, smartphones, etc., will raise the adoption of AI solutions in Europe. Asia-Pacific is still in the early stage of this technology, but China is currently dominating the AI Processor Ecosystem. China is gradually competing with the U.S. in technological innovation in AI processor. Leaders such as Nvidia are supplying GPUs adapted for AI training loads to Microsoft, Amazon Web services, and Tesla. But gradually, Google, Facebook, Huawei, Alibaba, Baidu, and Amazon are becoming active in this area, as these companies feel that they can also produce AI Processor that will address their specific needs and trade-offs between performance and power consumption.

Figure 3 – AI Processor Ecosystem: Market Statistics Glimpse

There are many trends that are having an impact on the market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

The major players operating in the Global AI Processor Ecosystem are as follows:

Company Ecosystem Positioning Total Revenue (US$) Industry Region Nvidia Hardware Manufacturers $ 11.7 Billion Semiconductors Global Intel Hardware Manufacturers $70.8 Billion Semiconductors Global Qualcomm Hardware Manufacturers $22.73 Billion Semiconductors Global Samsung Hardware Manufacturers $210.9 Billion Semiconductors Global ARM Hardware Manufacturers $1.39 Billion Semiconductors Global

Very few markets have interconnectivity with other markets like AI. Our Interconnectivity module focuses on the key nodes of heterogeneous markets in detail. CPU, GPU, Machine learning, and Consumer Goods markets are some of our key researched markets.

Figure 4 – AI Processor Major Interconnectivities

Glance on AI Processor Ecosystem Trends:

Trends Components Products Industry vertical Technology Impact on Market New Processor from Intel and AMD provide higher processing power, especially for the healthcare industry. GPU Wearables 0.30% Processor are developed natively with more security and encryption especially for Aerospace & Defense FPGA Automotive 0.68% Increasing usage of voice-based commands in Next Generation Transportation and Logistics industry will fuel the growth of NLP Consumer electronics NLP 0.50% Trend 4 XX XX Trend 5 XX XX

Research methodology: