What it takes to turn an embedded computer vision demo into a device that makes reliable decisions, shown through four real edge AI projects.
Source: https://www.embedded.com/how-to-make-embedded-computer-vision-work-in-the-real-world. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.
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Large language models remain far less efficient than biological brains at learning, representing knowledge, and planning, the post argues. A child hears roughly one token per second, reaching a billion tokens only after 31 years, while GPT-4-class models reportedly use four orders of magnitude more data. The Phi model series, trained on 10 trillion tokens, still trails GPT-4 along most axes. A Portia spider plans prey-catching behavior with a brain a million times smaller than a human's, and squirrels recall cached food after months, suggesting that existing models may be far less representationally and memory efficient.
My rescue USB now also helps me make sense of disk errors.
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Not all my information is meant to reach OpenAI's servers
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