Texas Instruments Introduces New Family of Vision Processors to Enable Scalable Edge AI Performance in Smart Camera Applications

【Lansheng Technology Information】To drive the development of edge intelligence based on innovation, Texas Instruments launched a new series of six Arm® Cortex®-based vision processors, enabling designers to add more vision and artificial intelligence (AI) processing functions at a lower cost and with higher power efficiency in applications such as video doorbells, machine vision and autonomous mobile robots.

The new family includes the AM62A, AM68A and AM69A processors, supported by open-source evaluation and model development tools, and general-purpose software programmable through industry-common application programming interfaces (APIs), frameworks and models. Using this platform of vision processors, software and tools, designers can easily develop and scale edge AI designs across multiple systems while reducing time-to-market.

"Real-time responsiveness in the world of electronic devices that matter most to the world requires decision-making locally and improved power efficiency," said Sameer Wasson, vice president of Texas Instruments' Processor Division. "This new processor family's affordable, highly integrated SoCs enable the use of more cameras and added vision processing in edge applications, enabling the future of embedded AI."

Scalable AI camera performance at the edge with vision processors

When implementing vision processing and deep learning capabilities in low-power edge AI applications, Texas Instruments' new vision processors bring intelligence from the cloud to the real world by removing barriers of cost and design complexity.

These processors feature a system-on-chip (SoC) architecture that supports extensive integration. The integrated components include an Arm Cortex-A53 or Cortex-A72 central processing unit, a third-generation Texas Instruments image signal processor, internal memory, interfaces, and hardware accelerators to provide deep learning algorithms with 1 trillion to 32 trillion operations per second (TOPS) of AI processing.

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