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
- Very Low Latency BCH Codec
- 5G-NTN Modem IP for Satellite User Terminals
- 400G UDP/IP Hardware Protocol Stack
- AXI-S Protocol Layer for UCIe
- HBM4E Controller IP
Related Blogs
- Powering Up Efficiency: A Deep Dive into CXL L0p and its Verification
- Design, Verification, and Software Development Decisions Require a Single Source of Truth
- Analog Bits Steals the Show with Working IP on TSMC 3nm and 2nm and a New Design Strategy
- System-on-Chip Design: Integrating Complex Systems into a Single Silicon Solution
Latest Blogs
- Embedded Security explained: Post-Quantum Cryptography (PQC) for embedded Systems
- Accreditation Without Compromise: Making eFPGA Assurable for Decades
- Synopsys Delivers First Complete UFS 5.0 and M‑PHY v6.0 IP Solution for Next‑Gen Storage
- World First: Synopsys MACsec IP Receives ISO/PAS 8800 Certification for Automotive and Physical AI Security
- Last-level cache has become a critical SoC design element