AI technology is penetrating various fields at an unprecedented pace, and the toy industry is no exception. AI toys have broken the boundaries of traditional toys with their in-depth interactive experiences—being able to listen, speak, see, and "think". Behind all this, chips, as the key "brain", play an irreplaceable role.

The complex functions of AI toys rely on the strong computing power of chips. Take voice interaction as an example: after a child speaks to an AI toy, the chip needs to quickly process the voice signal, convert it into text, generate a response using built-in algorithms and connected cloud models, and finally convert the text back to voice for playback. This series of operations must be completed in a very short time, placing high demands on the chip’s computing speed and processing capability. For instance, Espressif Systems’ ESP32-S3 chip, equipped with a self-developed vector instruction set and optimized for neural network computing, can efficiently handle voice wake-up tasks. It allows AI toys to respond to children’s calls in milliseconds, greatly enhancing the smoothness of the interactive experience.

Different types of AI toys have diverse chip requirements:

• Voice interaction-focused products (e.g., smart plush toys): Chips with low power consumption and high integration are preferred. Since plush toys are usually battery-powered, the low-power feature of chips can extend battery life and reduce charging frequency. For example, Allwinner Technology’s R128-S3 high-integration wireless audio SoC integrates a high-performance dual-core processor, HiFi5 DSP, ADC, DAC, as well as wireless network and display functions. It can meet the multi-functional needs of plush toys in limited space, supporting voice interaction, expression display, and more.
• AI toys with visual recognition (e.g., educational robots that recognize children’s gestures/movements): Chips need strong image processing capabilities. Rockchip’s RK1808 chip, for example, integrates an NPU unit and supports on-device inference of lightweight AI models. It can quickly and accurately analyze images captured by cameras, recognize children’s gestures, and make corresponding responses—making the interaction between robots and children smarter and more natural.

Chip manufacturers continue to innovate to meet the specific needs of AI toys:

• Enhancing computing power: Actions Semiconductor’s ATS3703 chip integrates a 4-core CPU and an independent 3D GPU, with a built-in vector/floating-point acceleration unit. It provides approximately 0.3 TFLOPS@FP16 AI inference performance, easily handling edge AI tasks such as face recognition and voice noise reduction, and is known as the "cost-effective leader in the children’s market".
• Optimizing power consumption: Nordic’s nRF7002 supports dual protocols (Wi-Fi 6 and Bluetooth) and integrates Target Wake Time (TWT) functionality. It has extremely low standby power consumption and a measured latency of <100ms, making it suitable for high-end AI toys—ensuring high performance while minimizing power consumption.
• Prioritizing security: As AI toys collect and transmit large amounts of children’s data, data security is crucial. Some high-end AI toys have adopted dual-core isolation technology: the application processor handles interactive functions, while the security core specializes in privacy encryption. Through the Trusted Execution Environment (TEE), data sandboxing is achieved to effectively prevent data leakage and protect children’s privacy.

The importance of chips in AI toys is self-evident—their performance directly determines the functional richness, interactive experience, and security of AI toys. As AI technology advances and consumer needs become more diverse, chip manufacturers will continue to develop more powerful, intelligent, and secure products, injecting "core momentum" into the development of the AI toy industry and driving it to new heights.