Tuesday, March 19, 2024
HomeHeadlinesSambaNova Systems Raises $676 Million In Series D Funding

SambaNova Systems Raises $676 Million In Series D Funding

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  • SambaNova will use its latest injection to aggressively challenge legacy competitors
  • This Series D brings SambaNova’s total funding to more than $1 billion and rockets its valuation to more than $5 billion

SambaNova Systems has announced a $676 million Series D funding round led by SoftBank Vision Fund 2. The round includes additional new investors Temasek and GIC, plus existing backers including funds and accounts managed by BlackRock, Intel Capital, GV (formerly Google Ventures), Walden International and WRVI.This Series D brings SambaNova’s total funding to more than $1 billion and rockets its valuation to more than $5 billion.SambaNova will use its latest injection to aggressively challenge legacy competitors.

Rodrigo Liang, SambaNova co-founder and CEO said, “We’re here to revolutionize the AI market, and this round greatly accelerates that mission. Traditional CPU and GPU architectures have reached their computational limits. To truly unleash AI’s potential to solve humanity’s greatest technology challenges, a new approach is needed. We’ve figured out that approach, and it’s exciting to see a wealth of prudent investors validate that.”

Enterprise-level AI initiatives

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SambaNova’s flagship offering is Dataflow-as-a-Service (DaaS), a subscription-based, extensible AI services platform designed to jump-start enterprise-level AI initiatives, augmenting organisations’ AI capabilities and accelerating the work of existing data centers, allowing the organization to focus on its business objectives instead of infrastructure.

It said, “At the core of DaaS is SambaNova’s DataScale, an integrated software and hardware systems platform with optimized algorithms and next-generation processors delivering unmatched capabilities and efficiency across applications for training, inference, data analytics, and high-performance computing. SambaNova’s software-defined-hardware approach has set world records in AI performance, accuracy, scale, and ease of use.”

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