Wave Computing, a start-up based in Campbell, California that is focused on artificial intelligence (AI) and deep learning, has acquired MIPS Tech, Inc. (formerly MIPS Technologies). Financial terms were not disclosed.
MIPS, which was founded in 1984 by a group of researchers from Stanford University that included John L. Hennessy, in known as a pioneer RISC processor Intellectual Property (IP) and licensable CPU cores. MIPS holds over 350 worldwide patents and currently has over 200 licensees.
MIPS will operate as an IP business unit within Wave and will continue to license MIPS IP solutions that can now integrate Wave’s dataflow technology.
Wave said the acquisition expands its strategy of offering AI acceleration from the Datacenter to the Edge of Cloud by extending the company’s products beyond AI systems to now also include AI-enabled embedded solutions.
Dado Banatao, Chairman of Wave Computing and MIPS Technologies, said, “Now is the right time for Wave Computing to expand, and I am pleased to see the company further evolve and grow into an AI powerhouse. Wave’s integration of two industry-leading compute architectures in a single data plane/control plane solution – Dataflow and Von Neumann – will be truly unique and an industry-first. It will fuel new, ground-breaking innovations in AI and other fields.”
“This is a major milestone not only in the history of our two companies, but also for the AI compute industry,” said Derek Meyer, CEO of Wave Computing. “With working DPU commercial silicon and being in the final stages of bringing our first AI systems to market, now is the time for us to expand to the Edge of Cloud. The acquisition of MIPS allows us to combine technologies to create products that will deliver a single ‘Datacenter-to-Edge’ platform ideal for AI and deep learning. We’ve already received very strong and enthusiastic support from leading suppliers and strategic partners, as they affirm the value of data scientists being able to experiment, develop, test and deploy their neural networks on a common platform spanning to the Edge of Cloud.”
Alexander Stojanovic, Vice President of Machine Learning and Applied Research at eBay, said, “For AI-driven Datacenters, leveraging purpose-built platforms for high throughput and low latency workloads is a game changer. They offer the promise of faster time-to-revenue and greater competitive differentiation using some of the latest AI trends such as GAN and attention-based models for time series and natural language data. Combined with the ability to more quickly create deeper and more complex machine learning models, hyperscale- and enterprise-class companies will be able to better leverage AI as a fundamental part of their digital strategies.”
