tag: machine learning

Tech Talk: Improving Verification
By Ann Mutschler - 26 Apr, 2018 - Comments: 0

Frank Schirrmeister, senior group director for product management and marketing at Cadence, discusses how to verify different use cases, focusing on software, low-power designs, connectivity, and a variety of end markets. https://youtu.be/gK-0vmIWxJs » read more

AI Accelerating Discovery
By Joanne Itow - 25 Apr, 2018 - Comments: 0

In early April 2018, the Materials Research Society held their spring meeting and exhibit at the Phoenix, Arizona convention center. With more than 110 symposium presentations, it was difficult to select which sessions to attend. But one forum caught my eye, “AI for Materials Development”. These days AI seems to be everywhere. As we all speculate about the impact of AI on autonomous driv... » read more

Tech Tackles Health Care
By Jeff Dorsch - 23 Apr, 2018 - Comments: 0

Can technology make humans healthier? If technology investments in this market are any indication, the answer is a firm “yes.” Massive growth in this market has been predicted for years. In fact, it was the initial driver behind many of the initial IoT devices, which fizzled largely because of insufficiently developed end applications and poor battery life of wearable devices. Much has c... » read more

Designing 5G Chips
By Ann Mutschler - 18 Apr, 2018 - Comments: 0

5G is the wireless technology of the future, and it’s coming fast. The technology boasts very high-speed data transfer rates, much lower latency than 4G LTE, and the ability to handle significantly higher densities of devices per cell site. In short, it is the best technology for the massive amount of data that will be generated by sensors in cars, IoT devices, and a growing list of next-g... » read more

The Week in Review: IoT
By Jeff Dorsch - 13 Apr, 2018 - Comments: 0

Finance Palo Alto, Calif.-based Armis raised $30 million in Series B funding, bringing total funding for the provider of enterprise Internet of Things security to $47 million. Red Dot Capital Partners of Israel led the round, joined by Bain Capital Ventures. Existing investors Sequoia Capital and Tenaya Capital also participated in the latest funding, which Armis will use to expand sales and m... » read more

Architecture, Materials And Software
By Ed Sperling - 12 Apr, 2018 - Comments: 0

AI, machine learning and autonomous vehicles will require massive improvements in performance, at the same power consumption level (or better), over today's chips. But it's obvious that the usual approach of shrinking features to improve power/performance isn't going to be sufficient. Scaling will certainly help, particularly on the logic side. More transistors are needed to process a huge i... » read more

AI Signals A New Change Of Perspective
By John Hengeveld - 12 Apr, 2018 - Comments: 0

A very long time ago, I was a student at MIT, programming with card decks in APL on IBM mainframes and studying AI in a class from Patrick Winston (who took over MIT’s AI lab from the legendary Marvin Minsky). I kept the text book as a reminder of where the world would go. Over four titanic shifts, mainframes/card decks became VAX/VT100, thence to IBM PCs and PC clients tied by Ethernet to co... » read more

High-Performance Memory Challenges
By Ann Mutschler - 12 Apr, 2018 - Comments: 1

Designing memories for high-performance applications is becoming far more complex at 7/5nm. There are more factors to consider, more bottlenecks to contend with, and more tradeoffs required to solve them. One of the biggest challenges is the sheer volume of data that needs to be processed for AI, machine learning or deep learning, or even in classic data center server racks. “The design... » read more

Get Ready For Integrated Silicon Photonics
By Brian Bailey - 12 Apr, 2018 - Comments: 1

Long-haul communications and data centers are huge buyers of photonics components, and that is leading to rapid advances in the technology and opening new markets and opportunities. The industry has to adapt to meet the demands being placed on it and solve the bottlenecks in the design, development and fabrication of integrated silicon photonics. "Look at the networking bandwidth used across... » read more

Optimizing Machine Learning Workloads On Power-Efficient Devices
By Arm - 11 Apr, 2018 - Comments: 0

Software frameworks for neural networks, such as TensorFlow, PyTorch, and Caffe, have made it easier to use machine learning as an everyday feature, but it can be difficult to run these frameworks in an embedded environment. Limited budgets for power, memory, and computation can all make this more difficult. At Arm, we’ve developed Arm NN, an inference engine that makes it easier to target di... » read more

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