Spinout News / UCLB News

Stanhope AI's 'humanlike' machines gain £2.3m boost

21 March 2024

Stanhope AI team

UCLB is delighted that Stanhope AI, which we supported in its formation as a spinout last year by working closely with its founders from UCL and Kings College, has reached a major milestone this week. The company announced it has attracted £2.3m in additional funding to put it at the forefront of the new generation of AI technology known as ‘agentic’ AI.

Stanhope is truly at the cutting edge of this technology –  applying decades of neuroscience and AI research with the aim of creating machines that are able for the first time to make human-like decisions in the real world, in real time, autonomously.

The news has already gained attention from media outlets including Sifted, which ran a long read on Stanhope AI’s story so far. UCLB is proud to have been a key part of that journey – having supported StanhopeAI’s formation as a spinout from University College London, working closely with three of the most eminent names in neuroscience and AI research – CEO Professor Rosalyn Moran (former Deputy Director of King’s Institute for Artificial Intelligence), Director Karl Friston, Professor at the UCL Queen Square Institute of Neurology and Technical Advisor Dr Biswa Sengupta (MD of AI and Cloud products at JP Morgan Chase).  This latest funding round was led by the UCL Technology Fund – an investment set up by UCLB to support the growth of emerging technology businesses – alongside Creator Fund, MMC Ventures, Moonfire Ventures and Rockmount Capital and angel investors.

By using key neuroscience principles and applying them to AI and mathematics, Stanhope AI has built algorithms that, like the human brain, are always trying to guess what will happen next; learning from any discrepancies between predicted and actual events to continuously update their “internal models of the world.” Instead of training vast LLMs to make decisions based on seen data, Stanhope agentic AI’s models are in charge of their own learning. They autonomously decode their environments and rebuild and refine their “world models” using real-time data, continuously fed to them via onboard sensors.

Marina Santilli, Associate Director at UCLB is confident that this latest investment will propel StanhopeAI to develop their technology to the next crucial stage: “In the immediate term, the technology is being tested with delivery drones and autonomous machines used by partners including Germany’s Federal Agency for Disruptive Innovation and the Royal Navy. In the long term, the technology holds huge promise in the realms of manufacturing, industrial robotics and embodied AI. The investment will be used to further the company’s development of its agentic AI models and the practical application of its research.”

The rise of agentic AI

This approach, and Stanhope AI’s technology, are based on the neuroscience principle of Active Inference – the idea that our brains, in order to minimise free energy, are constantly making predictions about incoming sensory data around us. As this data changes, our brains adapt and update our predictions in response to rebuild and refine our world view.

This is very different to the traditional machine learning methods used to train today’s AI systems such as LLMs. Today’s models can only operate within the realms of the training they are given, and can only make best-guess decisions based on the information they have. They can’t learn on the go. They require extreme amounts of processing power and energy to train and run, as well as vast amounts of seen data.

By contrast, Stanhope AI’s Active Inference models are truly autonomous. They can constantly rebuild and refine their predictions. Uncertainty is minimised by default, which removes the risk of hallucinations about what the AI thinks is true, and this moves Stanhope’s unique models towards reasoning and human-like decision-making. What’s more, by drastically reducing the size and energy required to run the models and the machines, Stanhope AI’s models can operate on small devices such as drones and similar.

“The most all-encompassing idea since natural selection”

Friston’s principle theory centres on how our brains minimise surprise and uncertainty. It explains that all living things are driven to minimise free energy, and thus the energy needed to predict and perceive the world. Such is its impact, the Free Energy Theory Principle has been described as the “most all-encompassing idea since the theory of natural selection.” Active Inference sits within this theory to explain the process our brains use in order to minimise this energy. This idea infuses Stanhope AI’s work, led by Professor Moran, a specialist in Active Inference and its application through AI; and Dr Biswa Sengupta, whose doctoral research was in dynamical systems, optimisation and energy efficiency from the University of Cambridge.

Real-world application

Professor Rosalyn Moran, CEO and co-founder of Stanhope AI said the promise offered by Stanhope AI’s approach to Artificial Intelligence is to bridge the gap between neuroscience and artificial intelligence, creating a new generation of AI systems that can think, adapt, and decide like humans. “We believe this technology will transform the capabilities of AI and robotics and make them more impactful in real-world scenarios. We trust the math and we’re delighted to have the backing of investors like UCL Technology Fund who deeply understand the science behind this technology and their support will be significant on our journey to revolutionise AI technology,” she adds.

Read more in this article from Sifted.

David Grimm, Partner UCL Technology Fund, added: “AI spinouts may be some of the hottest investments right now but few have the calibre and deep scientific and technical know-how as the Stanhope AI team. This is emblematic of their unique approach, combining neuroscience insights with advanced AI, which presents a ground-breaking opportunity to advance the field and address some of the most challenging problems in AI today. We can’t wait to see what this team achieves.”

Discover more about Stanhope AI:

Visit the Stanhope AI website.