With the launch of Palette Edgematic on AWS Marketplace, SiMa.ai aims to enhance low-code development for machine learning (ML) at the edge by providing a platform that allows developers to evaluate and deploy ML models on SiMa.ai MLSoC devices in the cloud. This visual design interface simplifies iteration and deployment, making it accessible even to those without specialized coding skills. Such collaboration with AWS is designed to broaden access to edge AI development, making it easier for a larger community of developers and businesses to adopt these technologies.
Elizabeth Samara-Rubio, Chief Business Officer at SiMa.ai, emphasizes that this initiative signifies a major advancement in the accessibility and usability of next-generation ML. By leveraging AWS’s vast infrastructure, SiMa.ai aims to reach a wider audience prepared to integrate edge AI technologies. Additionally, SiMa.ai offers an Early Access Program that enables developers to explore new features and optimize their ML applications on SiMa.ai Developer or Production boards. This initiative aligns with SiMa.ai’s commitment to fostering a robust development ecosystem around its technology.
In conjunction with its partnership with AWS, SiMa.ai has attained Foundational Technical Review status, underscoring the technical rigor and reliability of their solutions. Such recognition demonstrates their dedication to meeting high standards in their offerings. Furthermore, SiMa.ai has successfully secured $70 million in funding aimed at developing second-generation MLSoC, highlighting their long-term commitment to advancing edge AI capabilities. This funding is expected to drive innovation and accelerate the development of their products.
Overall, SiMa.ai’s strategic initiative represents a concerted effort to democratize ML development at the edge. By providing tools and platforms that empower developers to create and deploy AI solutions efficiently, leveraging AWS’s scale and resources, they aim to make edge AI accessible to a broader audience. This move holds the potential to significantly impact how businesses and developers implement and benefit from AI technologies at the edge.
