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Ambiq adds AI models to sub-threshold chips for hearing, seeing

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January 07, 2025

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Ambiq Inc. (Austin, Texas) is offering AI-based audio and graphics processing models combined with its sub-threshold voltage logic chips.

A neural network based speech de-noiser (NNSD) uses a real-time learning model to analyse audio and isolate speech and remove background audio.

A neural-network based acoustic environment detector (NNAED) is a model that uses audio cues such as reverberation tails to adjust audio processing based on the user’s environment, such as a railway station, airport or office.

Both of these can run on Ambiq’s Apollo510 microcontroller (MCU), which is based on a Cortex M55 processor core implemented in sub-threshold voltage process for low power to help reach battery life requirements in hearable and wearable equipment.

The company already has a design win in an over-the-counter hearing aid.

“By radically reducing the power needs of the highly complex audio processing and AI features required by advanced hearing aids, Ambiq has eliminated the need for specialized and expensive ASICs, accelerating product cycles while reducing costs,” said Carlos Morales, vice president of AI, in a statement.

Meanwhile Ambiq has partnered with ThinkAR to develop lightweight smart glasses called AiLens.

The AiLens provide an AI personal assistant that helps manage:

  • Real-time language translation
  • Notes and reminders
  • Healthcare information via connection to data from wearables and healthcare devices
  • Workflow optimization

The AiLens glasses applications run on Ambiq’s Apollo4 SoC, which includes a Cortex-M4F

microprocessor, running at up to 192 MHz for processing graphics, audio, and AI models. The glasses weigh 37 grams and offer more than 10 hours battery life in ThinkAR lab tests.

“Our collaboration with ThinkAR marks the start of a new era for smart AR glasses,” said

Fumihide Esaka, CEO of Ambiq, in a statement. “The leap in energy efficiency, performance, functionality, and practicality offers a major shift in wearable edge AI technology for consumers.”

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