Epic Venture Partners Invests $8.1m in Rain AI after Accelerated Customer Demand

Epic Venture Partners has invested $8.1 million in Rain AI's mission to create energy-efficient AI hardware using in-memory compute technology, enabling advanced AI models to run locally on various devices.

GAINESVILLE, Fla., May 26, 2024 /PRNewswire-PRWeb/ -- Epic Venture Partners has invested $8.1m into Rain AI, a Sam Altman-backed startup. This was part of Rain AI's $25 million Series A extension round. Rain AI is an AI chip startup led by CEO William Passo, with a mission to build the world's most cost and energy-efficient hardware for AI. GPUs have powered the AI revolution with brute force, yet AI's demand for energy remains insatiable. Rain AI is addressing this core problem via its in-memory compute proprietary technology that will bring the AI technologies of tomorrow, from personalized robotics to putting models the size of ChatGPT on your phone.

AI is defining the Fourth Industrial Revolution, yet we are only scratching the surface on use cases. Rain AI's in-memory compute technology and upcoming AI accelerator chips will continue to unlock the myriad of use cases.

William Passo, CEO of Rain AI, expressed enthusiasm to be partnering with Epic Venture Partners, "The AI problem is an energy problem. Being able to run the most advanced models locally in any form factor is AI's holy grail, including running massive LLMs, such as GPT-4, on any device. Creating this future with abundant and scalable artificial intelligence is critical for the coming AI revolution. We've never seen more customer demand for our technology than we do now, and I'm excited for what's to come in 2024 and beyond."

Rain AI's secret sauce is its unique approach that eliminates the biggest drivers of energy usage. Unlike other AI hardware where 90% of energy is consumed by data flow, Rain AI's proprietary digital in-memory compute technology combines both memory and processing. And by co-designing their chips with some of the world's best AI models, they are able to dramatically reduce the energy consumption of AI compute compared to other solutions.

Rain AI is now in talks with major hyperscalers and semiconductor companies to license its IP, with plans to launch its first chip ready for customers in 2025. The use-cases will span across multiple industries, including drones, VR goggles, smartphones, robotics, wearables, and more.

Arthur Lee, managing partner of Epic Venture Partners expressed his viewpoint, "AI is defining the Fourth Industrial Revolution, yet we are only scratching the surface on use cases across enterprise, military, and consumer applications. There's a wide range of capabilities to explore. Rain AI's in-memory compute technology and upcoming AI accelerator chips will continue to unlock the myriad of use cases and allow them to be performed faster, more efficiently, and with more privacy protection at the Edge."

Bryan Edelstein, managing partner of Epic Venture Partners added, "Custom AI hardware needs to evolve as rapidly as software to fully capitalize on the continued advancements in AI. We are excited to support Rain AI's mission in achieving this."

Rain AI was founded in 2017 and quickly gained recognition after being accepted into Y-Combinator in 2018. The company secured a $5 million seed round led by Sam Altman, co-founder of OpenAI, and subsequently relocated to Silicon Valley to further its research and development efforts. In 2022, Rain AI raised a $25 million Series A round. Rain AI has now raised over $40m from notable investors including Sam Altman, co-founder/CEO of OpenAI, which created ChatGPT; Jeff Rothschild, a founding engineer at Facebook; Daniel Gross, co-founder of AI startup Cue (acquired by Apple); Oliver Cameron, Founder of autonomous vehicle startup Voyage (Acquired by Cruise); Jaan Tallinn, founding engineer at Skype; and Scott Gray, an AI hardware expert and early member of OpenAI's technical team. Rain AI has also assembled a strong advisory board which includes Dr. Jackson Hu, the former CEO & Chairman of UMC, the 2nd largest semiconductor manufacturer in the world; and Dr. Arijit Raychowdhury, a leading expert of in-memory compute and Chair of the Electrical and Computer Engineering Department at Georgia Tech university.