Lambda, the GPU cloud company founded by AI engineers and powered by NVIDIA GPUs, has recently secured $320 million in a Series C funding round. The funding round was led by Thomas Tull’s US Innovative Technology, with participation from B Capital, SK Telecom, T. Rowe Price Associates, and several other investors.
With this new equity financing, Lambda plans to expand its AI cloud business, particularly focusing on its popular on-demand and reserved cloud offerings. The company has been building AI infrastructure at scale for over a decade and has gained over 100,000 customer sign-ups on Lambda Cloud.
Lambda is well-known for its fast access to the latest architectures for training, fine-tuning, and inferencing of generative AI, large language models, and foundation models. The company’s hardware and private cloud services cater to more than 5,000 customers across various industries, including manufacturing, healthcare, pharmaceuticals, financial services, and the U.S. government.
CEO and co-founder of Lambda, Stephen Balaban, believes that AI will reshape every aspect of human endeavor in the next 10 years. He stated, “This latest financing supports our mission to make GPU compute as ubiquitous as electricity.” The demand for GPUs in AI applications is projected to soar as the technology becomes essential for scientific, commercial, and industrial advancements.
The investment from Thomas Tull’s USIT highlights the importance of strong infrastructure to power and disseminate cutting-edge technologies, particularly in the field of AI. Lambda’s platform offers a unique combination of hardware, cloud infrastructure, and software tools that enable AI developers to build with efficiency and speed.
Since its previous funding announcement, Lambda has deployed NVIDIA H100 GPUs and GH200 Superchip-powered systems on its cloud. Despite the increased demand for generative AI, Lambda has managed to maintain high availability of the latest NVIDIA GPUs at competitive prices.
Lambda’s ongoing partnership with Anyscale, the creator of the open source framework Ray, further enhances its offerings for large-scale distributed training and inference workloads. Together, they aim to provide accessible and affordable cloud infrastructure designed specifically for AI applications.
Overall, Lambda’s substantial funding boost reinforces its position as a leading provider of GPU cloud services and demonstrates the growing significance of AI in various industries. With their expansion plans in motion, Lambda is poised to support the future growth of AI hyperscalers.
FAQ Section:
Q: What is Lambda?
Lambda is a GPU cloud company founded by AI engineers and powered by NVIDIA GPUs.
Q: How much funding did Lambda recently secure?
Lambda secured $320 million in a Series C funding round.
Q: Who led the funding round?
The funding round was led by Thomas Tull’s US Innovative Technology.
Q: Which industries does Lambda serve?
Lambda serves various industries including manufacturing, healthcare, pharmaceuticals, financial services, and the U.S. government.
Q: What does Lambda plan to do with its new funding?
With this new equity financing, Lambda plans to expand its AI cloud business, with a focus on its popular on-demand and reserved cloud offerings.
Q: What is Lambda well-known for?
Lambda is well-known for its fast access to the latest architectures for training, fine-tuning, and inferencing of generative AI, large language models, and foundation models.
Q: Who is the CEO and co-founder of Lambda?
The CEO and co-founder of Lambda is Stephen Balaban.
Q: What is Lambda’s mission?
Lambda’s mission is to make GPU compute as ubiquitous as electricity.
Q: How does Lambda support AI developers?
Lambda offers a platform that combines hardware, cloud infrastructure, and software tools to enable AI developers to build with efficiency and speed.
Q: What are Lambda’s partnership and collaboration?
Lambda has an ongoing partnership with Anyscale, the creator of the open source framework Ray, to enhance its offerings for large-scale distributed training and inference workloads.
Key Terms:
1. GPU: A Graphics Processing Unit, specialized hardware originally designed for rendering images and graphics but now widely used in AI and machine learning applications for its parallel processing capabilities.
2. AI: Artificial Intelligence, the simulation of human intelligence processes by machines, typically including tasks such as learning, reasoning, and problem-solving.
3. Cloud: A model of computing where resources, including computing power and storage, are accessed over the internet instead of being owned and operated locally.
4. Equity Financing: A method of raising capital for a company by selling shares of ownership to investors in exchange for funds.
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