Machine Learning And Design Into 2018 - A Quick Recap
How could we differentiate between deep learning and machine learning as there are many ways of describing them? A simple definition of these software terms can be found here. Let's look into Artificial Intelligence (AI), which was coined back in 1956. The term AI can be defined as human intelligence exhibited by machines. While machine learning is an approach to achieve AI and deep learning is a technique for implementing subset of machine learning.
During last year 30-Year Anniversary of TSMC Forum, nVidia CEO Jen-Hsen Huang mentioned two concurrent dynamics disrupting the computer industry today, i.e.,how software development is done by means of deep learning and how computing is done through the more adoption of GPU as replacement to single-threaded/multi-core CPU, which is no longer scale and satisfy the current increased computing needs. The following charts illustrate his message.
To read the full article, click here
Related Semiconductor IP
- Zigbee Transceiver PHY
- Data Flow Architecture IP
- AMBA SPI Controller MRAM Controller
- Ethernet MAC
- Protocol Bridges
Related Blogs
- System-on-Chip Design: Integrating Complex Systems into a Single Silicon Solution
- Powering Up Efficiency: A Deep Dive into CXL L0p and its Verification
- Design, Verification, and Software Development Decisions Require a Single Source of Truth
- The Wonders of Machine Learning: Tackling Lint Debug Quickly with Root-Cause Analysis (Part 3)
Latest Blogs
- IDS-NoC: A Scalable Interconnect Solution for Modern SoC Design
- Leading-edge AI IC designs demand comprehensive HAV methodologies
- Beyond the Fab: Building Europe’s Next Generation of Semiconductor Champions
- AI Semiconductor Design at 3nm and 2nm: Silicon-Proven IP
- Samsung Foundry and Cadence Expand Infrastructure and Physical AI Solution