Find out about tools that can help you configure hardware, develop software, share code, and manage machine learning models for connected devices.
Silicon Labs has introduced tools for AI-assisted embedded development, hardware configuration, open-source collaboration, and edge artificial intelligence (AI) management. The updates include a public beta of the Simplicity AI Software Development Kit (SDK), a hardware configuration tool, a Bluetooth Low Energy (BLE) developer community, and an integration with Databricks for machine learning.
The Simplicity AI SDK connects AI coding assistants, including GitHub Copilot, Cursor, and Codex, with Silicon Labs’ software development kits, documentation, tools, and hardware. Its initial Bluetooth Low Energy workflows cover project creation, configuration, building, firmware flashing, debugging, network and power analysis, and documentation searches.
Silicon Labs has introduced Simplicity Design Intelligence to help engineers translate hardware and software requirements into working implementations. Its first capability, Hardware Intent, uses product requirements, board schematics, datasheets, meeting notes, and other hardware documentation to guide pin assignments, peripheral selection, and software configuration.
Hardware Intent checks configurations against requirements to identify pin conflicts, peripheral mismatches, and missing constraints before fabrication. This can help prevent errors that require circuit board revisions.
Silicon Labs’ machine learning operations (MLOps) SDK connects devices to Databricks for data collection. After training, the company’s ML Profiler estimates whether a model fits the target hardware, including its memory and central processing unit (CPU) requirements. Engineers can use these estimates to adjust models before deployment.
“More capable silicon should not create more development complexity,” said Manish Kothari, Senior Vice President of Software at Silicon Labs. “We are giving developers and their AI agents a connected path from hardware and software intent through implementation, community contribution, and the complete AI lifecycle.”
The integration brings embedded AI development into existing enterprise data management and governance workflows, reducing the need for separate infrastructure to manage data and models for edge applications.
“We’ve been working closely with Silicon Labs as an Alpha customer, evaluating how the Hardware Intent Agent can streamline hardware development across our current and future products while providing feedback on new features as it progresses towards general release,” said Limor Alkelai, Co-CEO, at Risco Group.
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