Gartner Recognizes Latent AI as Unique Edge AI Tech Innovator
Gartner recently published a new report on Tech Innovators in Edge AI, covering the trends and impact of Edge AI on products and services by analysts Eric Goodness, Danielle Casey, and Anthony Bradley. Latent AI greatly appreciates Gartner’s interest in Latent AI and coverage in this analysis. The following is a summary of the report ...
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AI and the New Data Refinery for the Edge Continuum
In 2017, The Economist published an article about The Fuel of the Future: Data Giving Rise to a New Economy. Today, this is more true than ever, and prospecting for new data, in the form of new applications and various sensor-driven data acquisition continues at a rapid pace. According to Cisco, in 2020, we generate ...
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The Quantization Myth
Demystifying Quantization Do you need high bit-precision to operate neural networks? More specifically, do you need a high bit-precision processor to run neural network inferences in the same level of fidelity that you’ve trained them? These concepts seem to be popular myths but are not true. A large part of the confusion around these myths ...
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Defining the Edge
Edge Computing Started with the Abacus Edge computing and edge AI are extremely popular tech buzzwords today. Just do a quick Google search for this term and you’ll get about 233 million results in less than a few seconds. Yes, there’s an overwhelming amount of information about edge computing and especially the importance of moving ...
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Scaling Edge AI in a Data Driven World, Part Two
The Essence of Edge AI Many applications today need edge computing. However, due to privacy issues, the need for real-time responses, and lack of network connectivity, applications are often compromised. A similar position supporting edge computing comes from the argument around network scalability. The cost and latency for network backhaul can be problematic, especially when ...
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Scaling Edge AI in a Data-Driven World, Part One
Scaling Edge AI in a Data-Driven World, Part One Drowning in Data We live in a data-driven world where IoT devices are always on, always tracking, and always monitoring. Being perpetually connected also means that we’re producing mind-boggling amounts of data. In fact, IDC Research predicts by 2020 we will be generating 44 trillion gigabytes ...
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AI Moves to the Edge
Edge is Where the Opportunity is and Why AI Needs to Evolve This is a 2-part series on the impact of AI on the edge as compared to the core, and why the approach to building AI algorithms needs to change if they are to operate more efficiently on the edge Introduction From enabling autonomous ...
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