Software

Breaking Free from the CUDA Lock-in

This blog post was originally published at SiMa.ai’s website. It is reprinted here with the permission of SiMa.ai. The AI hardware landscape is dominated by one uncomfortable truth: most teams feel trapped by CUDA. You trained your models on NVIDIA GPUs, deployed them with TensorRT, and now the thought of switching hardware feels like rewriting […]

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Upcoming Seminar Explores the Latest Innovations in Mobile Robotics

On October 22, 2022 at 9:00 am PT, Alliance Member company NXP Semiconductors, along with Avnet, will deliver a free (advance registration required) half-day in-person robotics seminar at NXP’s office in San Jose, California. From the event page: Join us for a free in-depth seminar exploring the latest innovations in mobile robotics with a focus

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Free Webinar Explores Edge AI-enabled Microcontroller Capabilities and Trends

On November 18, 2025 at 9 am PT (noon ET), the Yole Group’s Tom Hackenberg, principal analyst for computing, will present the free hour webinar “How AI-enabled Microcontrollers Are Expanding Edge AI Opportunities,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: Running AI inference at the edge,

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“Lessons Learned Building and Deploying a Weed-killing Robot,” a Presentation from Tensorfield Agriculture

Xiong Chang, CEO and Co-founder of Tensorfield Agriculture, presents the “Lessons Learned Building and Deploying a Weed-Killing Robot” tutorial at the May 2025 Embedded Vision Summit. Agriculture today faces chronic labor shortages and growing challenges around herbicide resistance, as well as consumer backlash to chemical inputs. Smarter, more sustainable approaches… “Lessons Learned Building and Deploying

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Using the Qualcomm AI Inference Suite from Google Colab

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Building off of the blog post here, which shows how easy it is to call the Cirrascale AI Inference Cloud using the Qualcomm AI Inference Suite, we’ll use Google Colab to show the same scenario. In the previous blog

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“Transformer Networks: How They Work and Why They Matter,” a Presentation from Synthpop AI

Rakshit Agrawal, Principal AI Scientist at Synthpop AI, presents the “Transformer Networks: How They Work and Why They Matter” tutorial at the May 2025 Embedded Vision Summit. Transformer neural networks have revolutionized artificial intelligence by introducing an architecture built around self-attention mechanisms. This has enabled unprecedented advances in understanding sequential… “Transformer Networks: How They Work

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Deploy High-performance AI Models in Windows Applications on NVIDIA RTX AI PCs

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Microsoft is now making Windows ML available to developers. Windows ML enables C#, C++ and Python developers to optimally run AI models locally across PC hardware from CPU, NPU and GPUs. On NVIDIA RTX GPUs, it utilizes

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“Understanding Human Activity from Visual Data,” a Presentation from Sportlogiq

Mehrsan Javan, Chief Technology Officer at Sportlogiq, presents the “Understanding Human Activity from Visual Data” tutorial at the May 2025 Embedded Vision Summit. Activity detection and recognition are crucial tasks in various industries, including surveillance and sports analytics. In this talk, Javan provides an in-depth exploration of human activity understanding,… “Understanding Human Activity from Visual

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“Multimodal Enterprise-scale Applications in the Generative AI Era,” a Presentation from Skyworks Solutions

Mumtaz Vauhkonen, Senior Director of AI at Skyworks Solutions, presents the “Multimodal Enterprise-scale Applications in the Generative AI Era” tutorial at the May 2025 Embedded Vision Summit. As artificial intelligence is making rapid strides in use of large language models, the need for multimodality arises in multiple application scenarios. Similar… “Multimodal Enterprise-scale Applications in the

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How CLIKA’s Automated Hardware-aware AI Compression Toolkit Efficiently Enables Scalable Deployment of AI on Any Target Hardware

This blog post was originally published at CLIKA’s website. It is reprinted here with the permission of CLIKA. Organisations are making a shift from experimental spending on AI to long-term investments in this new technology but there are challenges involved. Here’s how CLIKA can help. With democratising AI and greater access to open-source AI models,

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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