tag: neural networks

Artificial Intelligence Chips: Past, Present and Future
By Ty Garibay - 02 Aug, 2018 - Comments: 0

Artificial Intelligence (AI) is much in the news these days. AI is making medical diagnoses, synthesizing new chemicals, identifying the faces of criminals in a huge crowd, driving cars, and even creating new works of art. Sometimes it seems as if there is nothing that AI cannot do and that we will all soon be out of our jobs, watching the AIs do everything for us. To understand the origins ... » read more

Power/Performance Bits: July 31
By Jesse Allen - 31 Jul, 2018 - Comments: 0

Training optical neural networks Researchers from Stanford University used an optical chip to train an artificial neural network, a step that could lead to faster, more efficient AI tasks. Although optical neural networks have been recently demonstrated, the training step was performed using a model on a traditional digital computer and the final settings were then imported into the optical... » read more

Where ML Works Best
By Ed Sperling - 26 Jul, 2018 - Comments: 0

Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to discuss machine learning inside and outside of EDA tools and how that will affect the future of chip and system design. What follows are excerpts of that discussion. SE: How do you see the market and use of machine learning shaping up? Devgan: There are three main areas—machine learning inside, machine lear... » read more

Synthesizing Computer Vision Designs To Hardware
By Mike Fingeroff - 26 Jul, 2018 - Comments: 0

Computer vision is one of the hottest markets in electronic design today. Digital processing of images and video with complex algorithms in order to interpret meaning has almost as many applications and markets as there are uses for the human eye. The biggest problem that designers face is that the computer vision system requirements and algorithms change quickly and often. Even the targ... » read more

Five DAC Keynotes
By Brian Bailey - 17 Jul, 2018 - Comments: 0

The ending of Moore's Law may be about to create a new golden age for design, especially one fueled by artificial intelligence and machine learning. But design will become task-, application- and domain-specific, and will require that we think about the lifecycle of the products in a different way. In the future, we also will have to design for augmentation of experience, not just automation... » read more

Preparing For A 5G World
By Ed Sperling - 12 Jul, 2018 - Comments: 0

Semiconductor Engineering sat down to talk about challenges and progress in 5G with Yorgos Koutsoyannopoulos, president and CEO of Helic; Mike Fitton, senior director of strategic planning and business development at Achronix; Sarah Yost, senior product marketing manager at National Instruments; and Arvind Vel, director of product management at ANSYS. What follows are excerpts of that conversat... » read more

Reconfigurable AI Building Blocks For SoCs And MCUs
By Geoff Tate - 10 Jul, 2018 - Comments: 0

FPGA chips are in use in many AI applications today, including Cloud datacenters. Embedded FPGA (eFPGA) is now becoming used for AI applications as well. Our first public customer doing AI with EFLX eFPGA is Harvard University, who will present a paper at Hot Chips August 20th on Edge AI processing using EFLX: "A 16nm SoC with Efficient and Flexible DNN Acceleration for Intelligent IoT Devi... » read more

7nm Design Challenges
By Ed Sperling - 09 Jul, 2018 - Comments: 0

Ty Garibay, CTO at ArterisIP, talks about the challenges of moving to 7nm, who’s likely to head there, how long it will take to develop chips at that node, and why it will be so expensive. This also raises questions about whether chips will begin to disaggregate at 7nm and 5nm. https://youtu.be/ZqCAbH678GE » read more

Machine Learning’s Limits
By Ed Sperling - 03 Jul, 2018 - Comments: 0

Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that conversation. To view part one, click here. SE: How much of what goes wrong in machine learning depends on the algorithm being wrong... » read more

Syntiant: Analog Deep Learning Chips
By Kevin Fogarty - 12 Jun, 2018 - Comments: 1

Startup Syntiant Corp. is an Irvine, Calif. semiconductor company led by former top Broadcom engineers with experience in both innovative design and in producing chips designed to be produced in the billions, according to company CEO Kurt Busch. The chip they’ll be building is an inference accelerator designed to run deep-learning processes 50x more efficiently than traditional stored-prog... » read more

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