Literal Labs in funding for energy-efficient logic-based AI models
Headquartered in Newcastle, Literal Labs has announced it has raised £4.6M ($6.2M USD) in pre-seed funding to commercialise its energy-efficient, logic-based AI model technology.
Literal Labs, led by former Arm VP Noel Hurley, is pioneering logic-based AI models that are orders of magnitude faster, offer higher energy efficiency, and are more explainable than current neural networks. The work of Mikhail Tsetlin inspires its approach, a mathematician and contemporary of John Macarthy, who pioneered neural networks.
Much like neural networks, the Tsetlin machine can perform complex machine learning training. However, in contrast to neural networks, it is based on propositional logic, making it more efficient regarding computation and energy consumption, while also facilitating quicker inferencing.
Recent MLPerf Anomaly detection benchmarking shows Literal Labs can achieve 54x faster inferencing than “classic techniques” for machine learning applications, with 52x less energy consumption than equivalent neural networks. It also achieved 250 times faster performance than XGBoost for machine learning applications.
The funding round was led by Northern Gritstone, a science and tech-focused investment firm based in Northern England, and co-led by Mercuri, a London-based fund focused on companies at the intersection of the media, entertainment, and technology sectors. Other participants were Sure Valley Ventures, Cambridge Future Tech SPV, and several angel investors.
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Literal Labs was spun out of Newcastle University by world leaders in logic-based AI, Dr Alex Yakovlev and Dr Rishad Shafik, along with company builder Cambridge Future Tech. Noel Hurley was later appointed CEO of Literal Labs in 2023 after spending more than 20 years at Arm, where he led its product marketing and its CPU division, which accounted for over 70% of revenue, totalling approximately $1 billion.
The company doubled its headcount from 6 to 12 in 2024, which includes the appointment of Leon Fedden – formerly the AI Deep Learning platform lead at AstraZeneca – as Chief Technology Officer. The new injection of funding will be used to further expand its engineering team and to bring its first commercial product to market later in 2025 for customers with EdgeAI who need to replace GPU-intensive algorithms that are too large, costly, or energy-intensive; operate in strict social or regulatory markets where the explainability of AI is essential; and/or require more efficient AI models for battery-operated products.
Noel Hurley, CEO of Literal Labs, said: “We’re at a pivotal moment for AI with adoption continuing to accelerate alongside sustainability and cost concerns. Our logic-based AI offers a new solution for those who want and need high-performing AI that’s faster, more energy-efficient, and more explainable than what is currently available via neural networks. This funding comes at a time when we’re ready to speed up our product development significantly and will enable us to bring our first product to market later this year.”
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