Synaptics and EmbedUR Collaborate to Bring Cost-Effective AI Chips to India
Published on 1/4/2025 | 3 min read
Published on 1/4/2025 | 3 min read
The partnership aims to reduce the cost of AI-enabled microcontrollers to a range of $10–$20, making advanced AI capabilities accessible for mass-market and budget devices. According to Michael Hurlston, CEO of Synaptics, their chipset solutions, combined with EmbedUR's efficient software, will help Indian manufacturers create energy-efficient edge devices at significantly lower costs.
By optimizing software and shrinking AI models, the collaboration ensures that devices like washing machines can integrate AI at minimal incremental costs. For instance, upgrading a ₹5,000 washing machine to include AI features would raise its price to just ₹6,200, unlocking capabilities such as water usage optimization and user habit recognition.
India's cities of Bengaluru and Chennai are set to play a pivotal role in this venture. Synaptics plans to double its Bengaluru workforce from 400 to 800 employees over the next three years. Chennai, with its strong engineering ecosystem and low attrition rates, will focus on cutting-edge AI solutions.
Rajesh Subramaniam, CEO of EmbedUR, highlighted Tamil Nadu’s 1,000+ engineering institutions as a robust source of skilled graduates. Over the years, EmbedUR has built partnerships with key academic institutions, ensuring a steady pipeline of talent trained in the latest technologies.
The collaboration also has significant implications for Indian manufacturers and consumers. EmbedUR is working closely with original equipment manufacturers (OEMs) like Tata Electronics and TVS to create localized, AI-enabled products tailored to Indian needs.
Subramaniam emphasized the importance of upskilling industries to adopt energy-efficient and compute-efficient edge devices. The integration of AI into affordable household appliances has the potential to transform Indian homes, easing chores and enabling economic and societal changes, such as greater workforce participation.
While the Internet of Things (IoT) has long been a technological cornerstone, the integration of AI marks a new era. Devices equipped with AI microcontrollers can make independent decisions, reducing reliance on cloud-based processing.
For example, AI-enabled washing machines could dynamically adjust programs based on load type or optimize water and energy usage. Voice recognition features could further enhance convenience, allowing users to control appliances with simple commands.
As the tech industry moves away from power-hungry data centers, edge AI is emerging as a sustainable alternative. By running machine learning algorithms directly on devices, edge AI minimizes latency and energy consumption.
Hurlston pointed out that edge AI enables real-time decision-making without the need for frequent communication with remote data centers. This shift is expected to redefine AI applications and position India as a leader in the global semiconductor ecosystem.