Let’s take a look at the tremendous penetration of intelligent vision in so many and various applications. A few years ago, computer vision algorithms were implemented in applications directly linked with imaging, like computational photography for smartphones and cameras. We can mention today a bunch of segments like automotive,… Read More
Tag: machine learning
NetSpeed Leverages Machine Learning for Automotive IC End-to-End QoS Solutions
A couple of weeks back I wrote an article about the use of machine learning and deep neural networks in self-driving cars. Now I find that machine learning is also being applied to help build advanced end-to-end QoS (quality of service) solutions for the automotive IC market. With the advent of self-driving cars comes requirements… Read More
NVIDIA’s Deep Learning GPUs Driving Your Car!
In a recent SemiWiki article it was noted that 5 of the top 20 semiconductor suppliers are showing double-digit gains for 2016. At the top of the list was NVIDIA with an annual growth rate of 35%. Most of this gain is due to sales of its graphics processors (GPUs) which one normally associates with high performance computer gaming engines.… Read More
CEO Interview: Albert Li of Platform DA
Platform Design Automation, Inc (PDA). recently closed a US$6 million pre Series A investment round, and the company has shifted its focus from providing SPICE modeling related software and services to forming a complete AI-driven ecosystem from probing to simulation. Albert Li was the GM of Accelicon, a leading EDA tool and … Read More
These 6 new technology rules will govern our future
Technology is advancing so rapidly that we will experience radical changes in society not only in our lifetimes but in the coming years. We have already begun to see ways in which computing, sensors, artificial intelligence and genomics are reshaping entire industries and our daily lives. As we undergo this rapid change, many … Read More
AI on the Edge
A lot of the press we see on AI tends to be of the “big iron” variety – recognition algorithms for Facebook images, Google TensorFlow and IBM Watson systems. But AI is already on edge-nodes such as smartphones and home automation hubs, for functions like voice-recognition, facial recognition and natural language understanding.… Read More
Disarming Trolls
An unintended consequence of the ubiquity of the Internet, particularly in social media, is the rise of the troll. Trolls post comments of unbelievable vitriol in some cases, comments that if issued in person and in public might lead to arrest and psych evaluations. Then vitriol turns into viral vitriol and the helpless target … Read More
Machine Learning – Turning Up the Sizzle in EDA
There’s always a lot of activity in EDA to innovate and refine specialized algorithms in functional modeling, implementation, verification and many other aspects of design automation. But when Google, Facebook, Amazon, IBM and Microsoft are pushing AI, deep learning, Big Data and cloud technologies, it can be hard not to see… Read More
Could Machine Learning be Available for Mass Market?
Machine Learning is at the hype peak, according with Gartner’s August 2016 Hype Cycle for Emerging Technologies. The demand for vision processor IP is strong in smartphone, automotive and consumer electronics segments. ASSP based solutions can make the job, but how can OEM create differentiation, control their destiny and … Read More
It’s a heterogeneous world and cache rules it now
Cache evolved when the world was all about homogeneous processing and slow and expensive shared memory. Now, compute is just part of the problem – devices need to handle display, connectivity, storage, and other tasks, all at the same time. Different, heterogeneous cores handle different workflows in the modern SoC, and the burden… Read More