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Upcoming Silicon Valley Presentation Discusses Deep Learning and Embedded Vision

SiliconCatalyst

On the evening of Wednesday, March 22, Embedded Vision Alliance Founder Jeff Bier will present "When Every Device Can See-AI & Embedded Vision in Products," sponsored by Silicon Catalyst and taking place at the Techcode Accelerator in Mountain View, CA. From the event page:

In nature, intelligence and vision are tightly linked: virtually every species we consider to be intelligent has been equipped by evolution with vision. Similarly, to truly be intelligent, our devices and applications need visual perception. Most systems today lack vision because computer vision technology has been too expensive, too power-hungry, too complex – and too unreliable. But this is now changing with breathtaking speed. Accelerating advances in processors, algorithms, sensors, and development tools and techniques are increasingly making it both attractive and practical to equip all kinds of systems with vision, including high-volume, battery-powered devices. Artificial neural networks play a critical part of this transformation.

In this presentation, Jeff will share his unique perspective – informed both by product development projects and by interactions with many industry players – on the most important technology trends enabling the widespread use of embedded vision in products, with particular emphasis on deep learning. Jeff will also highlight examples of innovative products that illustrate the potential for vision to fundamentally change the capabilities of devices and to enable new business models.

The free presentation begins at 6:30 pm, preceded by a meet-and-greet at 6:00 pm and followed by a Q&A session. For more information and to register, please see the event page.

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.

Contact

Address

1646 N. California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA

Phone
Phone: +1 (925) 954-1411
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