PALO ALTO, Calif.–(BUSINESS WIRE:)–SambaNova Systems, the company delivering the industry’s only comprehensive software, hardware, and solutions platform to run Artificial Intelligence (AI), deep learning, and foundation models, today announced its Dataflow-as-a-Service™ product has been recognized as the “Best Big Data Deep Learning/AI Solution” by the 2022 Tech Ascension Awards.
SambaNova’s Dataflow-as-a-Service delivers the industry’s most powerful integrated software-defined hardware platform for AI, complete with out-of-the-box pre-trained deep learning and foundation models accessed through simple APIs. This enables organizations to accelerate and scale their AI and deep learning capabilities, getting time to value 22x faster.
“Building complex, deep learning models requires significant investments in resources, personnel, and advanced technology, which has historically placed it out of reach for all but a few companies,” said Rodrigo Liang, CEO and co-founder, SambaNova Systems. “With Dataflow-as-a-Service we’re delivering pre-trained foundation models with the highest accuracy that are production ready and can be deployed anywhere. Making deep learning more accessible helps organizations across industries leverage AI to drive cost savings and fuel growth. We are honored to be recognized as the best solution for this need.”
The Tech Ascension Awards recognize the very best innovations in technology. Applicants are judged based on technological innovation, market research, and competitive differentiators. The class-leading vendors that received recognition from the Tech Ascension Awards showcased technology that solves critical industry challenges and produces invaluable business outcomes for their customers.
“Data is the new oil, and organizations are constantly seeking new innovative solutions to help them better harness, analyze, and understand their data,” said David Campbell, CEO, Tech Ascension Awards. “These leaders in big data have helped shape the industry. We’re honored to recognize them for moving the market forward.”
For more information about SambaNova’s Dataflow-as-a-Service™ please visit: https://sambanova.ai/products/dataflow-as-a-service/. For more information about the Tech Ascension Awards, please visit www.techascensionawards.com.
About SambaNova Systems:
Customers turn to SambaNova to quickly deploy state-of-the-art AI capabilities to meet the demands of the AI-enabled world. Our purpose-built enterprise-scale AI platform is the technological backbone for the next generation of AI computing. We enable customers to unlock the valuable business insights trapped in their data. Our flagship offering, Dataflow-as-a-Service™, overcomes the limitations of legacy technology to power the large complex foundation models that enable customers to discover new services and revenue streams, and boost operational efficiency. Headquartered in Palo Alto, California, SambaNova Systems was founded in 2017 by industry luminaries, and hardware and software design experts from Sun/Oracle and Stanford University. Investors include SoftBank Vision Fund 2, funds and accounts managed by BlackRock, Intel Capital, GV, Walden International, Temasek, GIC, Redline Capital, Atlantic Bridge Ventures, Celesta, and several others.
Visit us at sambanova.ai or contact us at firstname.lastname@example.org. Follow SambaNova Systems on LinkedIn.
About the Tech Ascension Awards:
The Tech Ascension Awards elevate companies that possess cutting-edge, innovative technology that solve critical challenges in their respective markets. Tech Ascension winners rise above the crowded consumer and enterprise technology industries and receive validation from an independent organization. Applicants are judged based on technological innovation and uniqueness, market research (analyst reports, media coverage, customer case studies), hard performance statistics, and competitive differentiators. The awards recognize leaders in cybersecurity, DevOps, big data and more. For information about the Tech Ascension Awards, please visit www.techascensionawards.com.