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
- Ultra-Low-Power LPDDR3/LPDDR2/DDR3L Combo Subsystem
- Parameterizable compact BCH codec
- 1G BASE-T Ethernet Verification IP
- Network-on-Chip (NoC)
- Microsecond Channel (MSC/MSC-Plus) Controller
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
- Exploring AI / Machine Learning Implementations with Stratus HLS
- Analog Bits Steals the Show with Working IP on TSMC 3nm and 2nm and a New Design Strategy
Latest Blogs
- Physical AI at the Edge: A New Chapter in Device Intelligence
- Rivian’s autonomy breakthrough built with Arm: the compute foundation for the rise of physical AI
- AV1 Image File Format Specification Gets an Upgrade with AVIF v1.2.0
- Industry’s First End-to-End eUSB2V2 Demo for Edge AI and AI PCs at CES
- Integrating Post-Quantum Cryptography (PQC) on Arty-Z7