Paperspace intends to assist developers in building machine learning and artificial intelligence applications, primarily with a software/hardware development platform driven by GPU among other powerful chips.
Recently, the Y Combinator grads of Winter 2015 revealed that they had secured a $13 million in a Series A round of financing.
Battery Ventures led the Series A round alongside other participants such as Sorenson Ventures, Intel Capital and SineWave Ventures. Existing investors such as Initialized Capital also took part in the exercise. The recent investment brings the sum to $19M.
As both machine learning and artificial intelligence (AI) begin to take off, developers require a set of tools as well as GPU- driven hardware for processing it all.
In statement Thakker: “Major silicon, systems and Web-scale computing providers need a cloud-based solution and software ‘glue’ to make deep learning truly consumable by data-driven organizations, and Paperspace is helping to provide that.”
Paperspace offers its own GPU-driven servers to assist in this regard. However, the Chief Executive Officer and Co-founder Dillion Erb said that they do not intend to compete with large cloud vendors.
The solution provided to customers goes beyond hardware. In the previous spring, Paperscape unveiled Gradient, which is a serverless tool in an attempt to smoothen the deployment and management of machine learning and artificial intelligence (AI) workloads.
By developing Gradient, clients do not have considered the fundamental infrastructure. Paperspace deals with such issues for them by delivering the resources as required. “We do a lot of GPU compute, but the big focus right now and really where the investors are buying into with this fundraising, is the idea that we are in a really unique position to build out a software layer and abstract a lot of that infrastructure away [for our customers],” Dillon Erb told TechCrunch.
According to Erb, creating such infrastructure marked a vital initial step. However, they do not intend to engage in any competition with cloud vendors. In fact, they are striving to deliver a set of tools to aid developers in creating complex machine learning/ deep learning and artificial intelligence (AI), whether it is on the mainstream cloud providers such as Microsoft, Google, and Amazon or on their own infrastructure.
They have also gone beyond GPUs in a bid to support a wide array of powerful chips being created to support machine learning and artificial intelligence workloads. This is most likely among the reasons that Intel joined the financing exercise as an investor.
According to Erb, financing helps to validate something that they began working on when they initially commenced the project in 2014.
Paperscape was formed out of Y Combinator back in 2015. At the time, Erb had to say what a GPU was in all his pitch decks. Nonetheless, he does not need to do that nowadays, even though there is some room left for growth in such a space.
“It’s really a greenfield opportunity, and we want to be the go-to platform that you can start building out into intelligent applications without thinking about infrastructure,” said Erb.
