Sydney-based machine learning tech startup Strong Compute has secured AU$10.9 million (US$7.8 million) in seed funding. The round saw participation from nearly 30 funds and angel investors, including the likes of Sequoia India, Folklore Ventures, Blackbird and Skip Capital, as well as Y Combinator, Starburst Ventures and founders and engineers from companies like Cruise, Waymo, Open AI, SpaceX and Virgin Galactic.
Explaining the working of AI in the current context, Founder Ben Sand noted that AI today refers to what's called neural networks, which is software that is essentially trying to simulate parts of the brain.
“When people are developing AI, what they want to do is train their AI, which means you take a large pile of data - in our case, we mostly work with images - and then you feed it through these spreadsheets (neural networks). The idea is that the neural network at the end of the day will be reasonably good, or at least good enough, at guessing the content or some characteristic of the image,” Sand said.
While the entire process of training and devising experiments to test specific kinds of neural network designs takes a lot of time, Strong Compute aims to accelerate the development of these networks.
With a vision to expand its purpose-built cloud computing AI business, Sand is looking to uncover ‘limitless’ opportunities in an industry estimated to be worth $2 trillion by 2030. He believes that he and his team are on the right path as their investors are well-connected to the market and are experiencing the same issues. He added that the Sydney-based team is motivated by the impact they are making in real-time while they work towards building the future of cloud computing.
“We were very impressed with the work that Strong Compute is doing to dramatically accelerate both performance and productivity of ML (machine learning) teams everywhere, and Sequoia Capital India is excited to partner with them to help bring this to the world,” Sequoia India principal Anandamoy Roychowdhary said.
Roychowdhary added that machine learning will unlock a new level of productivity in multiple $100 billion industries via the deployment of larger and larger models with significant complexity.
“It feels like the industry's properly taking off here in many ways; I think the unicorn counts in Australia are up significantly over the last 12 months. It just means that we've got people here with real experience that have helped build that, and they're coming on the journey with us, and we're pleased about that too,” said Sand.
“We had initially gone out with a smaller raise target, but the interest was enough that we can bring forward some of the bigger projects that we're looking to do, which we're excited about as well,” he said.
The new funding will be used to hire more deep learning engineers, doubling down on AI in Australia, and parallelly launching longer-range research and development projects.