This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. At Qualcomm Technologies, we’ve long believed that AI assistants will be ubiquitous, personal and on-device. Today, we’re excited to share a major milestone in that journey: OpenAI has open-sourced its first reasoning model, gpt-oss-20b, a chain-of-thought reasoning […]
Omid Azizi, Co-Founder of Gimlet Labs, presents the “Visual Search: Fine-grained Recognition with Embedding Models for the Edge” tutorial at the May 2025 Embedded Vision Summit. In the domain of AI vision, we have seen an explosion of models that can reliably detect objects of various types, from people to… “Visual Search: Fine-grained Recognition with
Naitik Nakrani, Solution Architect Manager at eInfochips, presents the “Optimizing Real-time SLAM Performance for Autonomous Robots with GPU Acceleration” tutorial at the May 2025 Embedded Vision Summit. Optimizing execution time of long-term and large-scale SLAM algorithms is essential for real-time deployments on edge compute platforms. Faster SLAM output means faster… “Optimizing Real-time SLAM Performance for
Modalix in Production, Now Shipping SoM Pin-Compatible with leading GPU SoM, Dev Kits, and LLiMa for Seamless LLM-to-Modalix Integration SAN JOSE, Calif., August 12, 2025 — SiMa.ai, a pioneer in Physical AI solutions, today is making three significant product announcements to accelerate the scaling of Physical AI. Production and immediate availability of its next-generation Physical
SiMa.ai Next-Gen Platform for Physical AI in Production Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. As physical AI systems advance, the demand for richly labeled datasets is accelerating beyond what we can manually capture in the real world. World foundation models (WFMs), which are generative AI models trained to simulate, predict, and
Lazar Trifunovic, Solutions Architect at Camio, presents the “LLMs and VLMs for Regulatory Compliance, Quality Control and Safety Applications” tutorial at the May 2025 Embedded Vision Summit. By using vision-language models (VLMs) or combining large language models (LLMs) with conventional computer vision models, we can create vision systems that are… “LLMs and VLMs for Regulatory
New NVIDIA Omniverse NuRec 3D Gaussian Splatting Libraries Enable Large-Scale World Reconstruction New NVIDIA Cosmos Models Enable World Generation and Spatial Reasoning New NVIDIA RTX PRO Blackwell Servers and NVIDIA DGX Cloud Let Developers Run the Most Demanding Simulations Anywhere Physical AI Leaders Amazon Devices & Services, Boston Dynamics, Figure AI and Hexagon Embrace Simulation and Synthetic Data Generation August 11, 2025—SIGGRAPH—NVIDIA
Kiriti Nagesh Gowda, Staff Engineer at AMD, presents the “Simplifying Portable Computer Vision with OpenVX 2.0” tutorial at the May 2025 Embedded Vision Summit. The Khronos OpenVX API offers a set of optimized primitives for low-level image processing, computer vision and neural network operators. It provides a simple method for… “Simplifying Portable Computer Vision with
“Simplifying Portable Computer Vision with OpenVX 2.0,” a Presentation from AMD Read More +
Dwith Chenna, MTS Product Engineer for AI Inference at AMD, presents the “Quantization Techniques for Efficient Deployment of Large Language Models: A Comprehensive Review” tutorial at the May 2025 Embedded Vision Summit. The deployment of large language models (LLMs) in resource-constrained environments is challenging due to the significant computational and… “Quantization Techniques for Efficient Deployment
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Dive in to learn how we achieve a 1.4x latency decrease on Qualcomm Cloud AI 100 Ultra accelerators by applying an innovative DeepCache technique to text-to-image generation. What’s more, the throughput can be further improved by 3x
Learn to Optimize Stable Diffusion on Qualcomm Cloud AI 100 Read More +
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