Lambda, the AI-infrastructure company specializing in GPU cloud solutions, has successfully raised $320 million in a recent funding round led by Thomas Tull’s US Innovative Technology Fund. The proceeds from this series C funding will be utilized to expand the company’s AI cloud business, focusing on Lambda’s popular on-demand and reserved cloud offerings.
With a foundation established in 2012, Lambda boasts extensive experience in building AI infrastructure at scale. Their platform, powered by NVIDIA GPUs, has garnered the interest of over 100,000 customers who have signed up for Lambda Cloud services. Their early adoption of NVIDIA H100 Tensor Core GPUs has made them a preferred choice among AI developers, providing them with quick access to the latest training architectures for various AI models.
Lambda’s hardware and private cloud services currently cater to over 5,000 customers across diverse sectors such as manufacturing, healthcare, pharmaceuticals, finance, and the U.S. government. This includes numerous leading enterprises and research institutions like Rakuten, The AI Institute, and Anyscale.
The CEO and co-founder of Lambda, Stephen Balaban, acknowledged the increasing demand for GPUs in the AI field. He stated, “This AI rollout is going to require a lot of GPUs. This latest financing supports our mission to make GPU compute as ubiquitous as electricity.”
Recognizing the importance of investing in robust infrastructure for AI advancement, Thomas Tull, Chairman of USIT, emphasized Lambda’s unparalleled combination of hardware, cloud infrastructure, and software tools that enable efficient and speedy AI development. Tull expressed confidence in Lambda’s platform, envisioning it as the foundation for the AI hyperscalers of the future.
Lambda has demonstrated its commitment to pushing AI technology forward by incorporating the latest NVIDIA H100 GPUs and GH200 Superchip-powered systems into its public cloud. Despite the surge in demand for generative AI, Lambda has managed to maintain high availability of the latest NVIDIA GPUs, offering competitive pricing for customers.
To further enhance the capabilities of their platform, Lambda has also partnered with Anyscale, leveraging their open-source framework, Ray. This collaboration allows customers to easily access multiple GPUs and nodes for large-scale distributed training and inference, reaffirming Lambda’s dedication to providing accessible and cost-effective cloud infrastructure specifically designed for AI workloads.
Lambda’s recent funding success serves as a testament to the growing recognition of the vital role GPU cloud technology plays in driving AI innovation. By securing substantial investments, Lambda is poised to continue expanding its services and shaping the future of AI infrastructure.
FAQ Section:
1. What is Lambda?
Lambda is an AI-infrastructure company specializing in GPU cloud solutions.
2. What was Lambda’s recent funding round for?
Lambda successfully raised $320 million in a recent funding round. The proceeds will be used to expand the company’s AI cloud business, particularly focusing on their on-demand and reserved cloud offerings.
3. How long has Lambda been in operation?
Lambda was established in 2012 and has since gained extensive experience in building AI infrastructure at scale.
4. What makes Lambda’s platform popular among AI developers?
Lambda’s platform is powered by NVIDIA GPUs and offers quick access to the latest training architectures for various AI models, making it a preferred choice among AI developers.
5. What sectors does Lambda cater to?
Lambda currently caters to diverse sectors such as manufacturing, healthcare, pharmaceuticals, finance, and the U.S. government.
6. Who are some of Lambda’s notable customers?
Some of Lambda’s notable customers include Rakuten, The AI Institute, and Anyscale.
7. What is Lambda’s CEO’s perspective on the demand for GPUs in the AI field?
Lambda’s CEO, Stephen Balaban, acknowledges the increasing demand for GPUs in the AI field and aims to make GPU compute as ubiquitous as electricity.
8. What is Thomas Tull’s view on Lambda’s platform?
Thomas Tull, Chairman of USIT, recognizes Lambda’s combination of hardware, cloud infrastructure, and software tools as crucial for efficient AI development, envisioning it as the foundation for the AI hyperscalers of the future.
9. How does Lambda ensure availability of the latest NVIDIA GPUs?
Despite the surge in demand for generative AI, Lambda has managed to maintain high availability of the latest NVIDIA GPUs, offering competitive pricing for customers.
10. Who has Lambda partnered with to enhance their platform?
Lambda has partnered with Anyscale, leveraging their open-source framework, Ray. This partnership allows customers to easily access multiple GPUs and nodes for large-scale distributed training and inference.
Definitions:
– GPU: Stands for graphics processing unit, a specialized electronic circuit that accelerates the creation and rendering of images, videos, and animations.
– AI: Stands for artificial intelligence, referring to the simulation of human intelligence in machines to perform tasks typically requiring human intelligence.
– Cloud Infrastructure: Refers to the virtualized pool of resources, including hardware, storage, and networking resources, provided over the internet to support cloud computing services.
Related Links:
– Lambda Official Website
The source of the article is from the blog yanoticias.es