The SDV and AI Cars market is set to be worth over US$700 billion by 2034, representing around 20% of the global car market, according to IDTechEx‘s “Software-Defined Vehicles, Connected Cars, and AI in Cars 2024-2034” report. That sum can be sourced from several areas, such as monthly connectivity subscriptions, commission from in-vehicle payments, and […]
Here’s Why the SDV Market Will Be Worth $700 Billion by 2034 Read More +
Kerry Shih of GenAI Nerds interviews Jeff Bier, Founder of the Edge AI and Vision Alliance, and Phil Lapsley, the Alliance’s Vice President of Business Development, about the opportunities and trends for generative AI at the edge. Shih, Bier and Lapsley discuss topics such as: Where we are in the generative AI hype cycle What
Edge AI and Vision Alliance Conversation with GenAI Nerds on Generative AI At the Edge Read More +
Innovative technology enhances AI-enabled intelligent edge solutions and increases neural networking capabilities CHANDLER, Ariz., April 15, 2024 — Microchip Technology (Nasdaq: MCHP) has acquired Neuronix AI Labs to expand its capabilities for power-efficient, AI-enabled edge solutions deployed on field programmable gate arrays (FPGAs). Neuronix AI Labs provides neural network sparsity optimization technology that enables a
Microchip Technology Acquires Neuronix AI Labs Read More +
April 11 2024 – Las Vegas, Nev. – Visidon was recognized by the Security Industry Association (SIA) as an awardee at the 2024 SIA New Products and Solutions (NPS) Awards, the flagship awards program presented in partnership with ISC West recognizing innovative security products, services and solutions. In video surveillance advanced imaging technologies, Visidon was selected
Visidon Wins SIA NPS Video Surveillance Advanced Imaging Technologies Award Read More +
This blog post was originally published at Ceva’s website. It is reprinted here with the permission of Ceva. Not so long ago, AI inference at the edge was a novelty easily supported by a single NPU IP accelerator embedded in the edge device. Expectations have accelerated rapidly since then. Now we want embedded AI inference
Partitioning Strategies to Optimize AI Inference for Multi-core Platforms Read More +
AI chips can empower the intelligence of robotics, with future potential for smarter and more independent cars and robots. Alongside the uses of Chat GPT and chatting with robots at home, the potential for this technology to enhance working environments and reinvent socializing is promising. Cars that can judge the difference between people and signposts
AI Chips and Chat GPT: Exploring AI and Robotics Read More +
See “Quantization of Convolutional Neural Networks: Model Quantization” for the previous article in this series. In the previous articles in this series, we discussed quantization schemes and the effect of different choices on model accuracy. The ultimate choice of quantization scheme depends on the available tools. TFlite and Pytorch are the most popular tools used
Quantization of Convolutional Neural Networks: Quantization Analysis Read More +
In an era where reality seems increasingly malleable, the emergence of deepfake technology has catapulted us into uncharted territory. Deepfakes, synthetic digital media generated by artificial intelligence to manipulate images, audio, or video, pose a profound threat to the fabric of truth and trust in our society. The allure of deepfake technology lies in its
The Rising Threat of Deepfakes: A Ticking Time Bomb for Society Read More +
This blog post was originally published at Ceva’s website. It is reprinted here with the permission of Ceva. Packing applications into constrained on-chip memory is a familiar problem in embedded design, and is now equally important in compacting neural network AI models into a constrained storage. In some ways this problem is even more challenging
Efficiently Packing Neural Network AI Model for the Edge Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Next Chat with RTX features showcased, TensorRT-LLM ecosystem grows, AI Workbench general availability, and NVIDIA NIM microservices launched. Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more
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