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Press Release

SiMa.ai raises £55.7M to fuel innovation in generative edge AI platforms

Thu 4 Apr 2024

Embedded edge machine learning system-on-chip (MLSoC) technology company, SiMa.ai, announced today it has secured an additional £55.7 million ($70 million) in funding.

The round was led by Maverick Capital, with contributions from Point72, Jericho, and existing investors including Amplify Partners, Dell Technologies Capital, Lip-Bu Tan, among others.

With a total of £213.1 million ($270 million) raised to date, SiMa.ai hopes to further meet the growing customer demand for edge artificial intelligence (AI) and machine learning (ML) with its inaugural MLSoC, while also expediting the launch of its next-generation MLSoC slated for Q1 of 2025.

SiMa.ai’s forthcoming second-generation MLSoC will introduce a unified, software-centric platform catering to all edge AI needs. This platform promises scalability for customers’ AI/ML applications, ranging from computer vision and transformers to multimodal generative AI, adapting to the evolving AI/ML landscape.

The advent of generative AI is transforming interactions with AI/ML, necessitating edge devices like robots, drones, and autonomous vehicles to process multimodal inputs seamlessly. SiMa.ai’s MLSoC is designed to address these demands, ensuring high performance and power efficiency across various AI modalities.

Founder and CEO at SiMa.ai, Krishna Rangasayee, said the surge of generative AI is redefining human-machine collaboration.

“With our first-generation MLSoC establishing our technology leadership, we are now focused on providing a versatile platform that supports all AI modalities, backed by our strengthened investor base,” said Rangasayee.

“The rise of generative AI is catalysing a shift in data centre architecture, and the next wave of innovation will be AI’s expansion to the edge,” said Andrew Homan, Senior Managing Director at Maverick Capital.

SiMa.ai’s collaboration with Arm, Synopsys, and TSMC brings forth critical components and technological innovations to the MLSoC, to meet the diverse needs of edge AI applications.

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