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Making Coffee with the MAX78000 and Some AI (Part 1)


Making Coffee with the MAX78000 and Some AI (Part 1)
04/22/2021
Getting Started
Modern hardware can accelerate the use of convolutional neural networks (CNN), a kind of deep neural network, that are mostly used to analyze visual imagery or audio. For an application, this opens up a new way to process data and interact with its environment.
The required data processing for a CNN is a lot for a single CPU and something that can be heavily paralyzing; therefore, an accelerator is included. For your PC, this can be done with the help of your graphics card or special accelerator units like the NVIDIA Tesla cards (or these accelerators are built into the system itself, as seen on the new Apple M1 processor). The Maxim Integrated MAX78000 MCU brings a CNN accelerator, a Cortex-M4F and a RISC-V core together, as you can read from the datasheet. Aimed at CNN processing while operating in low-power modes, this allows for new ways to integrate AI in embedded designs. ....

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Move Your Career Forward With These Online Masters in Computer Science


Move Your Career Forward With These Online Masters in Computer Science
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Computer science and tech advanced degrees are an increasingly valuable credential to have. The world is driven by technology. Understanding technology, the use of big data, and the ability to make data-driven decisions are essential skillsets today. Modern business leaders have to know the language and understand the world of technology.
Finding the right degree can be challenging, but there are several great online options for the working professional. Below are degrees that can help you build your tech expertise and position you to take the next step in your career. ....

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Say Hello to Deep Vision's Polymorphic Dataflow Architecture – EEJournal


by Max Maxfield
Over the years (actually, decades, now I come to think about it), I’ve seen a lot of great silicon chip architectures and technologies pop up like hopeful contenders in a semiconductor Whack-A-Mole competition, only to fail because their developers focused on the hardware side of things and largely relegated the software in the form of design, analysis, and verification tools to be “something we’ll definitely get around to sorting out later.”
Of course, these companies did eventually cobble some low-level software tools together, something sufficient to allow them to talk to the hardware, but these pseudo-tools could be used only by the designers of the chips themselves because no one else could wrap their brains around how the little rascals (by which I mean the tools, not their creators) performed their magic. Thus, even when these companies had working silicon in their hands, they still didn’t have real-world tools that ....

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