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At the Edge: AI performance Cannot be Tiny Anymore (Part 2 of 2)
Blog George Medici Blog George Medici

At the Edge: AI performance Cannot be Tiny Anymore (Part 2 of 2)

In the first part of this series, we explored the challenges posed by the current approach to edge AI, such as scalability issues, escalating network and cloud costs, and the limitations of legacy processors. As the demand for smarter, faster, and more secure AI applications grows, it is becoming increasingly clear that edge AI cannot be tiny anymore. In this follow-up, we will discuss the reasons behind this shift and introduce Syntiant’s new NDP250 chip as a prime example of how advanced edge AI processors are addressing these challenges and making Edge AI a reality.

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Syntiant Core 2 Achieves Outstanding Results in Latest MLPerf Tiny v1.1 Benchmark Suite
Press Release Jared Geilich Press Release Jared Geilich

Syntiant Core 2 Achieves Outstanding Results in Latest MLPerf Tiny v1.1 Benchmark Suite

Syntiant Corp., a leader in edge AI deployment, today announced that its Syntiant Core 2™ programmable deep learning architecture delivered the lowest power energy performance across three categories in the most recent MLCommons’ MLPerf™ Tiny v1.1 benchmark suite, which measures how quickly a trained neural network can process new data for extremely low-power devices in the smallest form factors.

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