NVIDIA, Intel and Google Alums Launch Lemurian Labs and Secure $9 Million in Funding to Solve AI’s Compute Capacity Limitations

Lemurian Labs today announced it has secured $9 million in seed funding to develop an accelerated computing platform specifically tailored for AI applications. The round was led by Oval Park Capital, with participation from Good Growth Capital, Raptor Group and Alumni Ventures among others.

Composed of a core team with experience at Google, Microsoft, NVIDIA, AMD and Intel, Lemurian Labs was founded with the mission to democratize AI, and through the development and deployment of novel mathematical formulas, address several of the key challenges currently facing the industry.

Outsized Demand, Prohibitive Cost

Artificial intelligence is advancing with unprecedented speed, but the computing power needed to develop accurate models is outpacing current hardware capabilities. To keep up with increasingly demanding applications, GPUs are burning an exorbitant amount of power, making AI development extremely costly and environmentally unsustainable. For example, deploying GPT3 at the scale of Google search would consume 400 megawatts, enough electricity to power up to ~360K conventionally-powered homes for an entire year, with costs exceeding $100B. In addition, the demand has created chip shortages, further halting development, resulting in only a select handful of massively capitalized companies that can even afford to run high-end AI models.

“AI models have grown in complexity and adoption at a rate so rapid that it is now stressing our current hardware infrastructure to the point of fracture,” said Jay Dawani, CEO and co-founder of Lemurian Labs. “Models will continue to grow so we need fundamental changes in hardware in order to keep pace. We reimagined accelerated computing around the needs of AI models and its developers to bring down the cost and power consumption by 10X. This way we can fundamentally change the economics of AI such that any company can train and deploy LLMs, not just the fortunate few.”

Unlocking Greater Performance through New Arithmetic

Lemurian Labs is addressing these challenges by developing an accelerated computing platform that leverages a novel number system, referred to as PAL (parallel adaptive logarithm), to expedite AI workloads by up to 20x greater throughput at a 1/10th of the total cost of legacy GPUs. This combination of a new number system and co-designed hardware and software in their compute platform unleashes performance gains without scaling up power, allowing users to deploy more within the same power envelope. With faster AI workload deployments at a lower cost, Lemurian Labs is accelerating developer productivity while making these solutions accessible to a wider range of businesses and organizations.

“Lemurian Labs is a venture that epitomizes our mission to invest in exceptional founders developing and commercializing disruptive technologies aimed at solving mission-critical global challenges,” said Justin Wright-Eakes, Managing Partner at Oval Park Capital. “Unlike many of its hardware-first competitors, Lemurian leverages its proprietary parallel adaptive logarithm (PAL) numbering system and takes a software-centric approach to generate improvements in both realizable performance and energy efficiency, positioning Lemurian to redefine the AI processor landscape while enabling scalable, precise and energy-efficient AI solutions for nearly any use case.”

For more information about Lemurian Labs and its technology, please visit https://www.lemurianlabs.com/.

Additional investments came from Untapped Ventures, Plug and Play Ventures, Silicon Catalyst Angels, Blue Lake Capital, Futureland Ventures, AI Operators Fund and Tola Capital.

About Lemurian Labs

Founded by accomplished experts in the domains of AI, technology and business at leading companies and organizations like NVIDIA, Intel, and Microsoft, Lemurian Labs is committed to solving AI’s compute capacity limitations. The company is pioneering computing solutions of remarkable performance that redefine the boundaries of processing power, democratizing AI for broader accessibility.

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