How 5G is Driving AI at the Edge
Introduction
The ongoing transition from 4G to 5G is driving major infrastructure upgrades that include the integration of AI and machine learning capabilities at the edge. This is due to several major factors, the most important of which is the relentless growth in the amount of the world’s digital data. According to a recent Forbes article, approximately 2.5 quintillion bytes of data are created each day. By 2020, DOMO estimates that for every person on earth, 1.7 MB of data will be created every second.
Beyond the incredible rate of global data growth, carriers see 5G as a lucrative opportunity to generate new revenue streams and bolster the average revenue per user (ARPU). Neural networks and machine learning will continue playing prominent roles in supporting a range of low-latency, bandwidth-intensive applications at the edge including augmented reality, virtual reality, the IoT and Industry 4.0. As such, companies like Nvidia, Google, Intel and ARM are all shipping AI-optimized edge computing platforms.
To read the full article, click here
Related Semiconductor IP
Related Blogs
- How Is AI Driving the Next Innovation Wave for Electronic Design?
- The Future of Driving: How Advanced DSP is Shaping Car Infotainment Systems
- AI Is Driving a New Frontier in Chip Design
- A Trillion-Dollar Industry: How AI Is Reinventing EDA and Semiconductors
Latest Blogs
- Cadence Announces Industry's First Verification IP for Embedded USB2v2 (eUSB2v2)
- The Industry’s First USB4 Device IP Certification Will Speed Innovation and Edge AI Enablement
- Understanding Extended Metadata in CXL 3.1: What It Means for Your Systems
- 2025 Outlook with Mahesh Tirupattur of Analog Bits
- eUSB2 Version 2 with 4.8Gbps and the Use Cases: A Comprehensive Overview