Two of the biggest players in the semiconductor industry will be merging in a $40 billion cash plus stock deal. The acquisition of Arm by NVIDIA will make this the biggest semiconductor deal of the century and will result in creating the world’s premier computing company tailored to the age of Artificial Intelligence (AI). This means that our data intensive applications will soon be running on ARM designed chips with NVIDIA support leading to world-class innovation and high growth markets.
Arm is the kernel powering the world’s largest computing ecosystem and is owned solely and wholly by Japan’s SoftBank Group Corp. With this acquisition, SoftBank will remain a constituent of Arm by holding under 10 percent stake in NVIDIA.
The semiconductor industry has been on the modernization trend by shifting its focus to specialized chips that serve greater performance and efficiency. In the competitive field where Intel and AMD perform, NVIDIA has maintained its name in the market with its GPU technology backed up by the AI market. NVIDIA has been on a portfolio completion hunt to build its computing ecosystem for the past year. The gaming company completed the purchase of Mellanox Technologies for $7 billion in April and by signing various acquisition deals with SwiftStack and Cumulus. The acquisition of Arm will undoubtedly be the focal point in NVIDIA’s strategy over the next decade.
The data shows the patent strength of Arm and NVIDIA in different technology domains with the computer technology domain securing over 3,000 patents. Thus, it shows that with passing times, more computing is likely to hover the cloud specifically when more companies make use of AI for plenty of applications and manufacture new opportunities for data sharing and applications.
The graphs data show NVIDIA and Arm’s patent filing trend over the past decade. With NVIDIA having 4,724 patents and Arm having 5,410 patents to their name exhibit their focus on strengthening their IP. NVIDIA and Arm had their respective peaks in 2013 and 2016 respectively.
Thus designating ARM’s highly lucrative position in the market and NVIDIA’s own licensing model.
Arm being ranked the world’s learning tech provider of silicone IP for chips that remain the core of billions of devices, and its complete IoT products would complete NVIDIA’s portfolio.
Over 95 percent of the smartphone market is monopolistically powered by Arms Designs. Along with that its IP is essential for data centers, PCs, and IoT devices. However, its primary business is licensing its IP and thus NVIDIA managed to earn a 13% revenue when it licensed an Arm design for the Tegra CPUs.
To understand the same, the graph below explains the number of patents individually held by Arms and NVIDIA geographically.
NVIDIA, as seen in the chart, holds 600 patents in Taiwan but Arm holds 1,361. On the other hand, Arm has 2,955 patents in the United States, whereas NVIDIA has 3,849. Both the companies would be able to gain holistic control over Licensing IPs with the combined soundness of their patent counts.
“This combination has tremendous benefits for both companies, our customers, and the industry. For Arm’s ecosystem, the combination will turbocharge Arm’s R&D capacity and expand its IP portfolio with NVIDIA’s world-leading GPU and AI technology,” said Jensen Huang, founder, and CEO of NVIDIA.
“Arm and NVIDIA share a vision and passion that ubiquitous, energy-efficient computing will help address the world’s most pressing issues from climate change to healthcare, from agriculture to education,” said Simon Segars, CEO of Arm.
This biggest of the biggest deals is set to unite the strand of AI from NVIDIA with the vast computing ecosystem of Arm. AI technology is a huge part of NVIDIA providing plenty of hardware systems, thus bringing their research and technology into the ARM biosphere. Arm’s IP licensing portfolio will be expanded with the help of NVIDIA technology. Thus, as said, this enormous acquisition is going to be a power boost, and we might be able to see the continued innovation of this on an exponential scale.
This story was originally published here.