The Stage | Noel Hurley, CEO, Literal Labs

Why It Matters

By reducing the compute‑intensive nature of AI models, Literal Labs could make industrial AI deployment cheaper and faster, unlocking a large, untapped market for intelligent automation.

Key Takeaways

• Literal Labs builds AI platform using logic‑based training to cut multiplication.
• New approach targets industrial AI, reducing silicon energy consumption.
• Company spun out of Newcastle University, raised £4.6 million pre‑seed.
• Focus on beachhead markets; aims to become “OpenAI for industry.”
• Preparing seed round to scale team and broaden technology across AI.

Summary

Noel Hurley, CEO of Literal Labs, outlined the company’s mission to create an AI training platform that relies on logic‑based techniques rather than traditional neural‑network multiplication, aiming to cut energy use on silicon chips.

The startup, spun out of Newcastle University in 2023, raised £4.6 million in a pre‑seed round and has spent 2024 building its product for industrial AI applications—its beachhead market. By sidestepping costly multiplication, the platform promises lower compute expenses and faster deployment in heavy‑industry settings.

Hurley described the vision as becoming the “OpenAI for the industrial marketplace,” emphasizing that the technology can scale across the broader AI ecosystem. He noted that the company is now preparing a seed round to expand the team and accelerate product rollout.

If successful, Literal Labs could lower the barrier to AI adoption in sectors such as manufacturing, energy, and logistics, driving cost efficiencies and attracting new capital into industrial AI solutions.

Original Description

In this episode of The Stage, Noel Hurley, CEO of Literal Labs, shares how the company is rethinking AI training to better suit industrial environments.

His focus goes beyond traditional neural networks. By using logic-based techniques, Literal Labs is developing more energy-efficient AI models that can be deployed at scale using existing data sets.

Because the future of AI depends on solutions that are both powerful and sustainable.

#TheStage #LiteralLabs

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