Start-Up Raises Millions in Seed Funding to Train AI to Make Decisions Like Humans Do

A London-based, deep-tech start-up recently raised $2.9 million in funding to train artificial intelligence to make decisions in the same way that human beings do. Stanhope AI, which has a robust background in robotics, neuroscience and fintech, was founded as an independent entity from University College London.

Renowned names in artificial intelligence research and neuroscience involved in its formation include Professor Rosalyn Moran (current CEO, active inference specialist); Professor Karl Friston of the UCL Queen Square Institute of Neurology (current director); and Dr. Biswa Sengupta (current technical advisor, specialized in dynamical systems, energy optimization and efficiency).

The start-up is pioneering a new AI generation technology called agentic artificial intelligence. It has designed an algorithm that, similar to the human brain, tries to guess what may happen next. This algorithm learns from any differences between actual and predicted events and updates its internal models.

Agentic AI models are also responsible for their own learning. They do this by continuously feeding themselves data generated in real-time from the environment through onboard sensors. This eliminates the need to train large language models to make decisions based on data observed.

Stanhope based this approach on active inference, a principle in neuroscience that discusses how our brains always make forecasts from sensory data obtained from our surrounding environment. Changes in data prompt the brain to adjust and update its forecasts in a bid to help refine how we view the world.

The start-up’s models and machines are smaller in size and use little energy to run, which makes it easier for them to be operated on small devices such as drones. This is a stark contrast to current machine-learning techniques used to train current artificial intelligence systems such as large language models.

Current models solely operate within the domains of the training given, which makes it hard for them to continuously learn and update their information. Additionally, they need a lot of observed data as well as high amounts of energy and processing power to run and train.

The company’s approach is also propped up by free energy as well as thorough research conducted by the team of founders. For instance, the free-energy theory principle coined by Friston focuses on how the human brain minimizes uncertainty and surprise.

The company remains focused on transforming AI’s capabilities and enhancing its impact in real-world scenarios. It also hopes to address some of the issues in AI today while also better understanding the science behind this technology.

The AI that Stanhope AI is looking to develop could be a technology that entities such as Meta Platforms Inc. (NASDAQ: META) would have plenty of use for — if they don’t come up with something themselves for their own products.

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