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Synaptics, EmbedUR Collaborate to Build Cost-Effective AI Chips For India

  • Synaptics and embedUR are collaborating to create energy-efficient and compute-efficient edge devices for India's semiconductor industry.
  • The two companies aim to manufacture low power, low-cost neuro-processing units and microcontrollers with embedded software that can operate AI.
  • The expectation, according to Synaptics' CEO, Michael Hurlston, is to replace traditional MCUs completely with chips from embedUR to provide the same product more affordably, supported by AI capabilities.
  • The cost of AI-enabled MCU is estimated to fall between $10 and $20 using Synaptics chipsets and embedUR's efficient software solutions.
  • Companies like NVIDIA offer high-performance semiconductors, such as the Blackwell processors, which can cost up to $10k per chip.
  • By optimising software, and reducing the overall bill of materials, AI could easily be added to existing mid-level and low-cost devices such as washing machines without significantly driving up prices.
  • Synaptics already has 25% of its global workforce stationed in Bengaluru intending to double that number over the next three years to support the growth of its engineering skills headquartered there.
  • embedUR's proprietary AI model framework, ModelNova, strengthens the company's expertise in connectivity and embedded software, by providing lightweight, efficient models designed to run on low cost, resource-constrained devices.
  • The Synaptics-embedUR partnership is designed to democratise the application of AI, with potential implications for everyday devices in the mass market, particularly in India.
  • Edge AI aims to remove the need for large-scale data centres by running machine learning (ML) algorithms using software and models devices at the device level, potentially leading to significant advancements for India's semiconductor industry.

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