Literal Labs Funding News-Literal Labs Raises £4.6M To Develop Energy-Efficient, Explainable AI Models

The company is developing logic-based AI models that are much faster, more energy efficient, and easier to explain than today’s neural networks.

Their approach is based on the Tsetlin machine—a model using propositional logic, inspired by mathematician Mikhail Tsetlin, a contemporary of neural network pioneer John McCarthy.

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Unlike neural networks, the Tsetlin machine uses less energy and computes results faster. In recent MLPerf tests, Literal Labs' technology delivered 54x faster inferencing and used 52x less energy than standard methods. It also outperformed XGBoost with 250x faster results.

Literal Labs was spun out of Newcastle University by Dr. Alex Yakovlev and Dr. Rishad Shafik, with support from company builder Cambridge Future Tech. In 2023, Noel Hurley—former Arm executive—joined as CEO.

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 that want and need high-performing AI that is faster, more energy efficient and more explainable than what’s currently available via neural networks.

This funding comes at a time when we’re ready to significantly speed up our product development and will enable us to bring our first product to market later this year.”

The round was co-led by Northern Gritstone and Mercuri, with support from Sure Valley Ventures, Cambridge Future Tech SPV, and several angel investors.

Duncan Johnson, CEO of Northern Gritstone, said: “Literal Labs is Northern Gritstone’s first investment linked to Newcastle University, renowned for its technology-related research.

We are delighted to support Noel Hurley and the Literal Labs team at a time when innovation can truly benefit from greater efficiency in AI.”

Esha Vatsa, Partner at Mercuri said: “We are excited to back Literal Labs as it redefines AI with a radically efficient alternative to existing neural networks. The team, combining deep research expertise and proven industry leadership, is uniquely positioned to commercialise this innovation.”

The new funding will help Literal Labs expand its engineering team and launch its first commercial product in 2025. The product is aimed at EdgeAI customers who need to replace GPU-heavy algorithms that are too big, costly, or energy-hungry.

It also targets those working in regulated markets where AI explainability is crucial, as well as companies looking for more efficient AI models for battery-powered devices.

About Literal Labs

Founded in 2023, Literal Labs is an AI company that builds custom models using logic-based techniques. Benchmark tests show their models are much faster, more energy-efficient, and easier to explain than traditional neural networks.

Their technology is designed for companies that want to replace large, costly, and energy-heavy GPU algorithms, need explainable AI for strict regulatory markets, or require efficient models for battery-powered devices.