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Democratizing data science is an ambitious mission, but that’s just what the founders of Hypernet Labs hope to achieve with Galileo. It’s a low-code solution that eliminates the need to set up virtual machines and spend excessive time on DevOps tasks, an idea so attractive that it’s caught the attention of a raft of investors.
Palo Alto-based Hypernet today announced that it’s secured $10 million from 500 Startups, Sovereigns Capital, DHVC, Velorum Capital, Southpark Commons, and Decentral Park Capital, which CEO Ivan Ravlich says will lay the runway for the launch of Galileo. “The worlds of engineering and science are greatly in need of modern tools to help engineers, researchers, and scientists achieve their goals without needing to hire expensive, specialized DevOps or cloud engineers,” said Ravlich, who cofounded Hypernet earlier this year with Todd Chapman and Daniel Maren, alongside a team of Stanford physicists, computer scientists, aerospace engineers, and entrepreneurs.
In the simplest of terms, Galileo is a platform-agnostic app that expedites code deployment for compute-intensive work (like machine leraning model training). Project folders can be dragged and dropped into visual representations of office workstations, servers, or shared PCs to run immediately, while assets including data sets, models, and results can be shared using any network drive or cloud storage provider. Galileo can run in parallel across several or many machines, and it’s designed to scale to hundreds or even thousands of runs for simulations.
Galileo works atop existing file systems and can automatically allocate resources to teammates, all while tracking running jobs. It handles containerized code in a wide variety of software and languages, including Python, C++, and R. And it affords admins control over which users can run jobs and the degree to which they’re able to modify those jobs — as well as whether they receive status notifications.
In the future, Hypernet plans to add a marketplace to increase the number of available hardware options. A bespoke API (the Hypernet API) and protocol (Hypernet Protocol) will allow customers to buy and sell compute time in a decentralized and peer-to-peer fashion, on a blockchain-based “sharing economy” model.
According to Ravlich, the goal is to further streamline hardware access and software development processes for scientific research and development across disciplines. “With Galileo, we want to immediately upskill your entire team by eliminating the need for specialized knowledge to access compute power through a fast and easy-to-use platform,” said Ravlich. “This [model] allows people to spend minutes, rather than weeks, accessing required computing power. In terms of accessibility and usability, Galileo and Hypernet do for cloud tools and distributed computing what the desktop and mouse did for the operating system and PC revolution. Galileo is the next step in automation that will allow people to concentrate on what they do best: solving the world’s greatest problems.”
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