Derek Chow, Software Engineer at Google, and Shang-Hung Lin, Vice President of NPU Technology at VeriSilicon, co-present the “Image Tokenization for Distributed Neural Cascades” tutorial at the May 2025 Embedded Vision Summit. Multimodal LLMs promise to bring exciting new abilities to devices! As we see foundational models become more capable, we see compute requirements grow […]
Gordon Cooper, Principal Product Manager at Synopsys, presents the “Key Requirements to Successfully Implement Generative AI in Edge Devices—Optimized Mapping to the Enhanced NPX6 Neural Processing Unit IP” tutorial at the May 2025 Embedded Vision Summit. In this talk, Cooper discusses emerging trends in generative AI for edge devices and the key role of transformer-based
Taesu Kim, Chief Technology Officer at SqueezeBits, presents the “Bridging the Gap: Streamlining the Process of Deploying AI onto Processors” tutorial at the May 2025 Embedded Vision Summit. Large language models (LLMs) often demand hand-coded conversion scripts for deployment on each distinct processor-specific software stack—a process that’s time-consuming and prone to error. In this presentation,
Amir Servi, Edge Deep Learning Product Manager at Sony Semiconductor Solutions, presents the “From Enterprise to Makers: Driving Vision AI Innovation at the Extreme Edge” tutorial at the May 2025 Embedded Vision Summit. Sony’s unique integrated sensor-processor technology is enabling ultra-efficient intelligence directly at the image source, transforming vision AI for enterprises and developers alike.
Wil Florentino, Senior Segment Marketing Manager at Micron, presents the “Addressing Evolving AI Model Challenges Through Memory and Storage” tutorial at the May 2025 Embedded Vision Summit. In the fast-changing world of artificial intelligence, the industry is deploying more AI compute at the edge. But the growing diversity and data footprint of transformers and models
Sreepada Hegade, Director of ML Systems and Software at Lattice Semiconductor, presents the “Why It’s Critical to Have an Integrated Development Methodology for Edge AI” tutorial at the May 2025 Embedded Vision Summit. The deployment of neural networks near sensors brings well-known advantages such as lower latency, privacy and reduced overall system cost—but also brings
Amol Borkar, Product Marketing Director at Cadence, presents the “Solving Tomorrow’s AI Problems Today with Cadence’s Newest Processor” tutorial at the May 2025 Embedded Vision Summit. Artificial intelligence is rapidly integrating into every aspect of technology. While the neural processing unit (NPU) often receives the majority of the spotlight as the ultimate AI problem solver,
Tony Lewis, Chief Technology Officer at BrainChip, presents the “State-space Models vs. Transformers for Ultra-low-power Edge AI” tutorial at the May 2025 Embedded Vision Summit. At the embedded edge, choices of language model architectures have profound implications on the ability to meet demanding performance, latency and energy efficiency requirements. In this presentation, Lewis contrasts state-space
Ning Bi, Vice President of Engineering at Qualcomm Technologies, presents the “How Qualcomm Is Powering AI-driven Multimedia at the Edge” tutorial at the May 2025 Embedded Vision Summit. In this talk, Bi explores the evolution of multimedia processing at the edge, from simple early use cases such as audio and video processing powered by algorithm-centric
Marcel Wouters, Senior Software Engineer at Network Optix, presents the “Rapid Development of AI-powered Embedded Vision Solutions—Without a Team of Experts” tutorial at the May 2025 Embedded Vision Summit. In this presentation, Wouters shows how developers new to AI can quickly and easily create embedded vision solutions that extract valuable information from camera streams. He
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.
Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596
