Vikas Chandra, Senior Director at Meta Reality Labs presents “Scaling Down Is the New Scaling Up” at the May 2026 Embedded Vision Summit. The AI industry spent the last decade scaling up. The next decade will be about scaling down: AI that runs on your device, reasons across what you… “Scaling Down Is the New […]
“Scaling Down Is the New Scaling Up,” a Presentation from Meta Reality Labs Read More +
Eric Xing, President and Professor at Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University presents “AGI Meets the Real World—Toward Reasoning, Planning and Acting Beyond Book Intelligence” at the May 2026 Embedded Vision Summit. LLMs like OpenAI’s GPTs have fascinated the public with their astounding capabilities on… “AGI Meets the Real World—Toward
Perforated AI has released an enhanced version of ResNet-18 designed to approach the accuracy of larger vision models without imposing a comparable increase in model size or computational cost. The pretrained model is now available for evaluation and transfer learning on Hugging Face. The company’s technology adds artificial dendrites—additional computational structures inspired by biological neurons—to
Perforated AI Releases Enhanced ResNet-18 Model on Hugging Face Read More +
Assessing tire defects is another use case in the market for neuromorphic AI chip solutions LAGUNA HILLS, CA, UNITED STATES, August 13, 2026 /EINPresswire.com/ — A global leader in ultra-low power, fully digital, event-based neuromorphic AI, today announced a partnership with Atlanta-based Orama.AOI, which has retrained and optimized BrainChip’s Akida models using its industrial inspection
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James Imber, Director of Research at Imagination Technologies presents “Self-Compression for Edge Inference” at the May 2026 Embedded Vision Summit. Self-compression is a quantization-aware training technique to reduce neural network size and optimize performance for edge inference. By learning optimal bit depths for weights and activations during training, self-compression achieves… “Self-Compression for Edge Inference,” a
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This blog post was originally published at ModelCat’s website. It is reprinted here with the permission of ModelCat. Artificial intelligence has advanced rapidly over the past decade, fueled in large part by the availability of pre-trained models and shared research. One of the most visible outcomes of this progress is the rise of the “model zoo”—collections
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Amit Gupta, Associate Director–Solution Architecture and Head of Robotics CoE at eInfochips (an Arrow company) presents “Introduction to Simultaneous Localization and Mapping: From Block Diagrams to Real Systems” at the May 2026 Embedded Vision Summit. Simultaneous localization and mapping (SLAM) is the core capability that allows robots and autonomous systems… “Introduction to Simultaneous Localization and
Tom Michiels, System Architect at Synopsys presents “Understanding Transformers: From LLMs to Context-Aware Multimodal Models” at the May 2026 Embedded Vision Summit. Transformers have become the foundation of modern AI, reshaping how products are built and how businesses operate. In this talk Michiels explains why transformers replaced earlier models, what… “Understanding Transformers: From LLMs to
Whisper runs end-to-end on Chimera. Encoder and decoder compiled as native GPNPU kernels, INT4 weights, FP16 attention, top-1 token match against the float32 reference. Scales to four cores with a flag, no recompile. This blog post was originally published at Quadric’s website. It is reprinted here with the permission of Quadric. I ran a
Your NPU Learned to Listen Read More +
Open commercial licensing, benchmark‑leading reasoning and inspectable decisions bring autonomous vehicles, including robotaxis, closer to production and widescale deployment. This news blog was originally published at NVIDIA’ website. It is reprinted here with the permission of NVIDIA. For robotaxis and other autonomous vehicles (AVs), the hardest problems aren’t the everyday scenarios. They’re the rare, complex situations that
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