tag: ML

Learning properties of ordered and disordered materials from multi-fidelity data
By Technical Paper Link - 14 Jan, 2021 - Comments: 0

Source: Chen, C., Zuo, Y., Ye, W. et al. Learning properties of ordered and disordered materials from multi-fidelity data. Nat Comput Sci 1, 46–53 (2021). https://doi.org/10.1038/s43588-020-00002-x Abstract: "Predicting the properties of a material from the arrangement of its atoms is a fundamental goal in materials science. While machine learning has emerged in recent years as a n... » read more

Why AI Systems Are So Hard To Predict
By Ed Sperling - 12 Jan, 2021 - Comments: 0

AI can do many things, but how to ensure that it does the right things is anything but clear. Much of this stems from the fact that AI/ML/DL systems are built to adapt and self-optimize. With properly adjusted weights, training algorithms can be used to make sure these systems don't stray too far from the starting point. But how to test for that, in the lab, the fab and in the field is far f... » read more

5 Predictions For AI Innovation In 2021
By Arun Venkatachar - 22 Dec, 2020 - Comments: 0

By Arun Venkatachar and Stelios Diamantidis Artificial intelligence (AI) has emerged as one of the most important watchwords in all of technology. The once-utopian vision of developing machines that can think and behave like humans is becoming more of a reality as engineering innovations enable the performance required to process and interpret previously unimaginable amounts of data efficien... » read more

A Collaborative Data Model For AI/ML In EDA
By Si2 - 21 Dec, 2020 - Comments: 0

This work explores industry perspectives on: Machine Learning and IC Design Demand for Data Structure of a Data Model A Unified Data Model: Digital and Analog examples Definition and Characteristics of Derived Data for ML Applications Need for IP Protection Unique Requirements for Inferencing Models Key Analysis Domains Conclusions and Proposed Future Work Abstra... » read more

Power Models For Machine Learning
By Brian Bailey - 14 Dec, 2020 - Comments: 1

AI and machine learning are being designed into just about everything, but the chip industry lacks sufficient tools to gauge how much power and energy an algorithm is using when it runs on a particular hardware platform. The missing information is a serious limiter for energy-sensitive devices. As the old maxim goes, you can't optimize what you can't measure. Today, the focus is on functiona... » read more

Infrastructure Impacts Data Analytics
By Anne Meixner - 08 Dec, 2020 - Comments: 2

Semiconductor data analytics relies upon timely, error-free data from the manufacturing processes, but the IT infrastructure investment and engineering effort needed to deliver that data is, expensive, enormous, and still growing. The volume of data has ballooned at all points of data generation as equipment makers add more sensors into their tools, and as monitors are embedded into the chip... » read more

Transforming Vision Inspection With Machine Learning
By Optimal Plus - 07 Dec, 2020 - Comments: 0

How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and... » read more

Using AI And Bugs To Find Other Bugs
By Ann Mutschler - 24 Nov, 2020 - Comments: 0

Debug is starting to be rethought and retooled as chips become more complex and more tightly integrated into packages or other systems, particularly in safety- and mission-critical applications where life expectancy is significantly longer. Today, the predominant bug-finding approaches use the ubiquitous constrained random/coverage driven verification technology, or formal verification techn... » read more

The Expanding Universe Of MIPI Applications
By Joseph Rodriguez - 12 Nov, 2020 - Comments: 0

It’s hard to imagine today, but there was a time when mobile phones had no cameras and displays were tiny monochrome LCDs capable of displaying a phone number and not much more. The iconic Nokia 3310 announced Sept. 1, 2000, had an 84 x 48 pixel monochrome display and went on to sell 126 million units worldwide. You may still have one in your junk drawer. By the time of the original iPhone... » read more

Blog Review: Oct. 14
By Jesse Allen - 14 Oct, 2020 - Comments: 0

Arm's Hongsup Shin explains a machine learning application that can determine which tests are most likely to find hardware bugs, improving efficiency and reducing the number of tests that need to be run. Synopsys' Pieter van der Wolf and Dmitry Zakharov take a look at the increasing need for low power processors optimized for machine learning tasks as IoT, smart home, and wearable devices pr... » read more

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