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Rodrigo Liang is a seasoned technology executive and the co-founder and Chief Executive Officer of SambaNova Systems, a pioneering company developing the next generation of AI and dataflow computing hardware and software. With a deep background in high-performance microprocessor design and enterprise systems, Rodrigo leads SambaNova's mission to make advanced AI capabilities accessible to organizations worldwide. Before co-founding SambaNova in 2017, he spent over two decades at Sun Microsystems and Oracle, where he rose to become the Senior Vice President of SPARC Processor and VLSI Development. In that role, he was instrumental in leading the teams that developed some of the world's fastest and most complex microprocessors, driving innovation for enterprise-scale computing.
Rodrigo Liang's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Co-founded SambaNova in 2017, securing over $1 billion in funding and establishing the company as a leader in the enterprise AI market with its full-stack, subscription-based AI services platform.
Led the SPARC processor development organization, overseeing the creation of multiple generations of high-performance microprocessors that powered Oracle's and Sun's flagship enterprise servers.
Spearheaded the innovative business model of offering a complete, pre-trained, and managed AI platform as a service, significantly lowering the barrier for enterprises to adopt and deploy sophisticated AI models.
Stanford University
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SambaNova Systems is a leading developer of advanced, full-stack AI solutions designed for enterprise and government organizations. The company provides a subscription-based platform, Dataflow-as-a-Service, which integrates its proprietary software and hardware, including its Reconfigurable Dataflow Unit (RDU) chips. This allows customers to rapidly deploy powerful, custom AI models for complex applications like natural language processing (NLP) and computer vision, aiming to make sophisticated AI accessible without requiring extensive in-house expertise.
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