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Silicon Labs
Silicon Labs is a trailblazer in wireless connectivity for the Internet of Things. The integrated hardware and software platform, intuitive development tools, and unmatched ecosystem support make us the ideal long-term partner in building advanced industrial, commercial, and home and life applications. It leads the industry in high-performance, low-power, and security, with support for the broadest set of multi-protocol solutions.
Manish Kothari, Senior VP, Software Development, Silicon Labs, tells us more. Excerpts from an interview:
DQ: What sets Silicon Labs apart in the highly competitive wireless connectivity space? How are you ensuring that your solutions remain ahead of the curve?
Manish Kothari: Innovation is at the core of our strategy, driving us to continually expand our portfolio and capabilities. At Silicon Labs, we differentiate ourselves in the wireless connectivity space through our industry-leading multiprotocol wireless solutions, scalable architecture, and unwavering commitment to security.
Our EFR32 Series 2 SoCs and MGM240 modules support a range of wireless protocols, including Bluetooth Low Energy, Zigbee, Thread, and proprietary wireless connectivity. This versatility empowers developers to create highly flexible IoT products while accelerating time-to-market.
A key milestone in this journey was our acquisition of Redpine Signals' Wi-Fi and Bluetooth businesses, which has significantly strengthened our expertise in low-power, secure Wi-Fi solutions in India. This acquisition allows us to offer more energy-efficient, high-performance connectivity options, ensuring seamless integration across a broad spectrum of IoT applications.
Beyond technology, we foster collaboration and knowledge-sharing within the developer community. Our Works With On-Demand developer conference is a prime example, bringing together industry leaders, engineers, and innovators to discuss emerging trends and best practices in wireless connectivity. By facilitating these interactions, we ensure that we remain ahead of the curve in meeting the evolving demands of the IoT ecosystem.
At Silicon Labs, our customer-centric approach, strategic industry partnerships, and relentless focus on cutting-edge technology enable us to not only meet but exceed market expectations. As IoT adoption accelerates, we remain committed to delivering robust, secure, and scalable solutions that empower businesses to thrive in an increasingly connected world.
DQ: In an era of connected intelligence, data security remains a significant concern. How is Silicon Labs balancing innovation with robust cyber security measures?
Manish Kothari: A key differentiator of Silicon Labs’ solutions is Secure Vault firmware, which holds PSA Certified Level 3 accreditation. This advanced security firmware provides robust protection against logical, physical, and wireless attacks, incorporating critical features such as Differential Power Analysis (DPA) countermeasures, anti-tamper mechanisms, and secure key management. These capabilities are essential for safeguarding smart meters, which are frequent targets of cyber threats.
Silicon Labs’ technology is also designed for ultra-low power consumption, enabling smart meters to operate for decades on a single battery, significantly reducing maintenance efforts and costs. Security enhancements are tailored to address region-specific challenges, such as India’s smart metering initiative.
For example, the FG23 sub-GHz SoC, integrated with the Wirepas network, adds multiple layers of security, including DPA countermeasures and its significant features ensuring resilience against both local and remote cyber threats.
Additionally, Silicon Labs upholds a Zero Trust security model, reinforcing the principle of never implicitly trusting any device or user. Their security services include IoT device identity injection certificates, 10-year Software Development Kit (SDK) support, and a Custom Provisioning and Manufacturing Service (CPMS) that enables developers to integrate advanced security features into connected devices.
With a holistic approach to security, power efficiency, and long-term reliability, Silicon Labs remains at the forefront of the IoT industry, delivering solutions that meet the evolving demands of modern energy management systems.
DQ: How is Silicon Labs leveraging AI to create smarter, more intuitive IoT solutions? Are there specific use cases you’d like to highlight?
Manish Kothari: At Silicon Labs, we are harnessing the power of artificial intelligence (AI) and machine learning (ML) to develop smarter, more efficient IoT solutions by integrating ML capabilities directly into our wireless SoCs. Our approach leverages Matrix Vector Processing(MVP) to accelerate computational speed while maintaining ultra-low power consumption, paving the way for innovative applications across industries.
One of the key applications is in smart home technology, where our EFR32MG24 Series 2 SoCs enable predictive maintenance, glass break detection, and wake-word recognition. By processing data locally at the edge, these devices reduce latency, minimize bandwidth usage, and enhance security, creating seamless and reliable smart home experiences.
In industrial IoT, our AI/ML hardware accelerators significantly improve learning speed and accuracy compared to classical ML models. This capability allows real-time decision-making and offline operation when network connectivity is limited.
Applications such as predictive maintenance, asset tracking, and environmental monitoring benefit from this resilience, ensuring uninterrupted operation even in challenging industrial environments.
By embedding ML directly into wireless connectivity solutions, Silicon Labs is redefining what’s possible in AI-powered IoT. Our focus on efficiency, security, and real-time intelligence ensures that industries can deploy smarter, more adaptive devices, driving the next wave of innovation in the connected world.
DQ: What are some flagship innovations or solutions that Silicon Labs has recently introduced to the market?
Manish Kothari: At Silicon Labs, we continue to push the boundaries of IoT innovation with our latest flagship technologies, designed to enhance efficiency, security, and performance.
One of our most ground-breaking advancements is the Si917W SoC, a Wi-Fi 6-optimized solution that consumes half the power of competing devices. This ultra-low-power capability makes it ideal for battery-operated IoT applications, delivering longer lifespans and cost-effective deployment across smart home, industrial, and commercial sectors.
Another transformative technology is our Delta DFU (Device Firmware Update) Technology, which optimizes over-the-air (OTA) updates. Traditional firmware updates can be bandwidth-intensive and slow, particularly in mesh networks or remote deployments. Delta DFU significantly reduces update sizes, ensuring seamless, efficient updates even in bandwidth-constrained environments, allowing devices to remain secure and up-to-date without excessive power consumption.
We have also made major strides in AI and ML integration with our Series 1 and Series 2 SoCs, including the EFR32MG24 and BG24. These SoCs feature built-in AI/ML hardware accelerators, enabling predictive maintenance, real-time decision-making, and offline operation—crucial for applications in smart homes, industrial automation, and asset tracking.
By continuously innovating across wireless connectivity, AI-driven intelligence, and power efficiency, Silicon Labs is empowering the IoT ecosystem, providing future-ready solutions that redefine performance, reliability, and scalability in connected devices.
DQ: What are the key challenges industries face when integrating AI with IoT ecosystems, and how can they be addressed?
Manish Kothari: At Silicon Labs, we have navigated several challenges in machine learning (ML) adoption, addressing them through innovative solutions and strategic initiatives.
Technical challenges: Optimizing ML for edge devices
One of the biggest hurdles in ML adoption is optimizing models for edge devices with limited power and processing capabilities. To tackle this, we developed the BG24 and MG24 families of wireless SoCs, featuring integrated AI/ML accelerators.
These accelerators enhance performance and energy efficiency, enabling on-device ML processing. This approach reduces latency, lowers cloud dependency, and ensures real-time decision-making, making our solutions ideal for IoT applications in smart homes, industrial automation, and healthcare.
Market readiness: Bridging adoption gap
Many industries are still in the early stages of ML adoption, with a gap between its potential and practical implementation. To accelerate adoption, we’ve invested in developer training and support. Our AI/ML Software Toolkit helps developers seamlessly build and deploy ML models using TensorFlow and other frameworks.
Additionally, our Works With Developers Conference provides hands-on training, fostering industry-wide adoption of ML-driven solutions.
Regulatory considerations: Ensuring compliance and security
With increasing regulatory scrutiny, ensuring data privacy and security is crucial, especially in finance, healthcare, and critical infrastructure. Our PSA Level 3-certified Secure Vault High provides robust protection against cyber threats, securing sensitive data at every level. We also collaborate with regulatory bodies to ensure compliance, simplifying market entry for ML-powered solutions.
By tackling these challenges head-on, Silicon Labs remains at the forefront of ML innovation, delivering scalable, secure, and high-performance solutions that drive the future of IoT and smart technology.
DQ: What trends or technologies is Silicon Labs betting on for the next five years?
Manish Kothari: At Silicon Labs, we envision a future where ML at the edge transforms data processing, making it more intelligent, efficient, and secure. Our goal is to integrate advanced ML algorithms directly into microcontrollers (MCUs) and wireless SoCs, enabling seamless real-time decision-making and reducing reliance on cloud computing.
Edge AI integration: Smarter, faster, more efficient
We are pioneering Edge AI with our BG24 and MG24 families of wireless SoCs, designed with built-in AI/ML accelerators. These accelerators allow complex computations to be processed locally on the device, reducing latency, bandwidth consumption, and power requirements. This makes our solutions ideal for smart homes, industrial automation, and healthcare applications that require instant responsiveness.
Empowering developers: Simplifying ML Implementation
To accelerate ML adoption, we provide an AI/ML Software Toolkit, which simplifies model development and deployment. By supporting popular frameworks like TensorFlow, we ensure that developers can easily build, train, and optimize ML applications for embedded systems without requiring extensive expertise.
Strong partnerships: Building a thriving AI/ML ecosystem
We collaborate with leading AI/ML tool providers such as Edge Impulse and SensiML, offering a comprehensive toolchain that streamlines ML model training, validation, and deployment. These partnerships ensure a seamless experience for developers, fostering innovation and accelerating the adoption of ML-powered IoT solutions.
Through these efforts, Silicon Labs is shaping a future where ML-driven intelligence is embedded into every connected device, unlocking new possibilities for IoT and data-driven applications.
DQ: How do you see the convergence of AI and IoT shaping the digital economy in 2025 and beyond?
Manish Kothari: The convergence of AI and IoT will fundamentally reshape the digital economy in 2025, and beyond, by creating smarter, more connected systems across industries. In manufacturing, AI-powered IoT sensors will enable predictive maintenance and real-time optimization of production lines, while smart cities will leverage this integration for dynamic traffic management and efficient resource allocation.
Healthcare will see a transformation through remote patient monitoring systems that use AI to analyze real-time data from IoT devices, enabling early disease detection and personalized treatment plans. This technological synergy will also revolutionize supply chains, with AI processing data from IoT sensors to optimize inventory management and predict demand patterns with unprecedented accuracy.
The consumer landscape will evolve as AI enhances IoT devices' ability to learn from and adapt to user behavior, creating more personalized and intuitive experiences. Smart homes will become truly intelligent, with AI systems coordinating various IoT devices to optimize energy usage, enhance security, and automate routine tasks.
However, this transformation will bring challenges around data privacy, security, and interoperability that organizations must address. The success of this convergence will depend on developing robust frameworks for managing these concerns, while maximizing the technology's potential to drive innovation and efficiency across the digital economy.