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The Great Debate of AI Architecture | Engineering.com
Review of ASIC accelerators for deep neural network - ScienceDirect
Arch-Net: A Family Of Neural Networks Built With Operators To Bridge The Gap Between Computer Architecture of ASIC Chips And Neural Network Model Architectures - MarkTechPost
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Deep Learning Accelerators Foundation IP| DesignWare IP| Synopsys
The New Deep Learning Memory Architectures You Should Know About — eSilicon Technical Article | ChipEstimate.com
Intel Speeds AI Development, Deployment and Performance with New Class of AI Hardware from Cloud to Edge | Business Wire
Processing AI at the Edge: GPU, VPU, FPGA, ASIC Explained - ADLINK Blog
Google AI Blog: Chip Design with Deep Reinforcement Learning
FPGA Based Deep Learning Accelerators Take on ASICs
Are ASIC Chips The Future of AI?
8-Bit Precision for Training Deep Learning Systems | IBM Research Blog
Intel Unveils FPGA to Accelerate Neural Networks
How to develop high-performance deep neural network object detection/recognition applications for FPGA-based edge devices - Blog - Company - Aldec
How to Develop High-Performance Deep Neural Network Object Detection/Recognition Applications for FPGA-based Edge Devices - Embedded Computing Design
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
My take on the Gartner Hype Cycle | by Jens Møllerhøj | Medium
ASIC Design Services | Microsemi
FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review
FPGA vs GPU for Machine Learning Applications: Which one is better? - Blog - Company - Aldec
My take on the Gartner Hype Cycle | by Jens Møllerhøj | Medium