The Nordic deep -sea startup announced a breakthrough of artificial intelligence thanks to the creation of the first functional “digital nervous system” capable of autonomous learning. IntuuscellSqueeze with Lund University, he revealed on March 19, 2025 that they successfully designed AI, who learns and adapts as biological organisms, potentially making the current AI paradigms in many applications.
Innovation is a significant departure from traditional static machine learning models by restoring the basic principles of how learning occurs in biological nervous systems. Unlike conventional artificial intelligence, which is based on extensive data sets and background propagation algorithms, intuuscell technology allows machines to learn through direct interaction with their environment.
“Intuuscell first decoded how learning in biology and designed it as software,” said the company in the advertisement, describing the breakthrough as “going beyond static machine learning models (the basis of traditional AI), creating a fully functional” digital nervous system “capable of natural scaling to human intelligence.”
The company demonstrated its innovation with “Luna”, a robot dog who learns to control its body and stand through trial and mistakes, just like a newborn animal. Video material released by the company shows that Luna learns to stand without previously programmed intelligence or instructions, relying only on the digital nervous system to learn from experience.
“In contrast to traditional AI models, which are associated with static training data, the robot dog – named Luna – perceives, processes and improves through direct interaction with his world”, in accordance with the company's press message.
How technology works
The heart of intuuscell innovation is a fundamental change in the learning of machines. Unlike conventional AI systems, which process huge sets of data using static algorithms, the intuuscell approach imitates biological mechanisms that allow people and animals to learn naturally.
Viktor Luthman, CEO and co -founder intuuscell, emphasized this distinction during the announcement. According to Luthman, traditional artificial intelligence has become in the processing of data, but there is no real intelligence, while their system inspired by Bio-Inviarted allows machines to evolution and interaction with the environment in an unprecedented way.
The system architecture is a significant departure from standard neural networks. Intuuscell has developed a technology that operates similarly to the biological spinal cord, creating a fundamental infrastructure of autonomous learning. This is part of a larger system designed to repeat the possibility of processing the hill, the brain region responsible for sensory processing and world modeling.
Instead of relying on backward propagation algorithms and mass training sets, the digital nervous system intuuscell uses repetitive networks with a decentralized learning algorithm that reflects brain processes. This architecture allows AI agents to gain knowledge through direct experience and adapt to new situations in real time – abilities that were elusive in traditional machine learning.
The practical application of this technology reflects its biological inspiration. Instead of programming behavior or nutritional data through conventional algorithms, intuuscell plans to hire dog trainers to teach their AI new skills. This approach is a radical shift from typical AI development practices, emphasizing real interaction on a calculation scale. As explained by Dr. Udaya Rongola, a researcher and co -founder, their work is due to three decades of neuroscience research, focused on understanding intelligence, because it emerges from the structure and dynamics of the nervous system.
“Obsession of scaling brutal strength, billions of parameters, more calculations and more data is a fundamentally improper approach to achieving intelligence,” said Rongola. “Intuuscell does not pursue a major paradigm. Intelligence is not our end gate, but our starting point.”
Intuicell technology aims to create “the first real systems that can be taught; machines that learn from us in the same way as we would teach a new skill to the animal.” The company predicts that its digital nervous system is becoming “infrastructure for all non-bacological intelligence-recovering to others solving real problems that we cannot predict today, without relying on massive sets of training data.”
(Source: intuuscell)
Research Foundation and Specialist Team Knowledge
The company's foundation is based on three decades of neuroscience research at the University of Lund. Professor Henrik Jörnttell, co -founder of Intuicell and professor of neurophysiology at the university, managed what the company describes as “the only laboratory in the world that is able to record the intracellular activity of one neuron in the entire nervous system”, ensuring a unique basic foundation of intuuscell.
The management team enters experienced entrepreneurs and researchers with specialist knowledge in the field of neuroscience, artificial intelligence, robotics and business. In addition to Luthman, Jörnttell and Rongala, the founder is included in Dr. Jonas Enander, a doctor with the knowledge of neuronouki; Linus Mårtensson, chief programmer responsible for translating software tests; and Robin Mellstrand, Operational Director with experience in technology companies based on AI.
Intuuscell secured EUR 3.5 million from investors, including Run AND Snow ventures. The company expects to end the development of the full digital nervous system in the next two years, with the final purpose of enabling any agent, physical or digital, with “learning throughout life and adaptation to unknown – opportunities considered to be unique to biological creatures.”
While the full realization of the Intiucell vision remains for many years, their demonstration with Luna provides convincing early evidence of the potential of their technology to transform the development of AI by creating systems capable of truly autonomous learning and adaptation through interactions in the real world.
