Built on unique academic research

LGN developed from a unique collaboration between MIT/Zagreb and Oxford/Cambridge academics specialising in quantum optics, deep learning and on-chip AI.

Professor Vladimir Čeperić

Professor Čeperić is a double PHD research scientist specialising in on-chip artificial intelligence at the University of Zagreb Faculty of Electrical Engineering & Computing. He has an MBA and a wide range of industrial experience advising companies like Bosch, Ericsson, Infineon and On Semi.

As a visiting professor at MIT, he developed an on-chip optical neural network running at the speed of light. His fundamental interest in the intersection between optical signal processing, on chip artificial intelligence and deep learning algorithms led to the formation of LGN.


Dr Luke Robinson

Dr Robinson has a PhD in Quantum Computing from Cambridge University and is a Research Fellow of both Cambridge and Oxford. He has founded a range of AI and deep-tech companies, including CS Photonics, Earth Rover, Flox, Hazy, Sociate and Sunfish Energy.

Having first collaborated with Professor Čeperić on the use of quantum beam shaping to improve LiDAR resilience, their shared interest in in the intersection between optical computing and deep learning algorithms led them to form LGN together with Daniel Warner.


Daniel Warner

Daniel Warner has a BEng in Electrical and Electronic engineering. He begun his career designing manufacturing lines for major manufacturers including BMW. During his time at Apple he was part of the team responsible for opening new stores around Europe, before moving into the adtech industry, where he built teams from the ground up as a startup founder and CEO.

Daniel and Luke first collaborated on a mobility sensor company to push for new levels of safety in cities. They share a passion for improving how things work and using cutting edge technology to achieve that goal.


Unique, patent pending technology

LGN views the world through a unique latent space "lens" (LSL), a compact yet powerful description of space and temporal observations that changes yielding performance way past the current state-of-the-art deep learning algorithms.

The benefits of using LSL are multiple: ability to detect interesting and surprising elements of a scene, optimal compression of data for AI, stability to changes and defects in data and sensors, graceful degradation and much more.

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Inspired by the human perception system

As posted about in LGN: What does it mean?, LGN mimics the Lateral Geniculate Nucleus found in our brains. The system directs attention and filters for the most important information and compresses the signal before it reaches your visual cortex.

We are building the artificial LGN for Artifical Intelligence. As sensors and data grow exponentially at the edge the need for data efficiencies has never been greater.

There is a reason we've evolved with an LGN. It's time your system did too.


London, UK

LGN is based in the London Connectory, the destination for London’s mobility leaders, near Old Street, Shoreditch and the City of London.

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San Francisco, USA

Our US hub is perfectly placed in the hustle of San Francisco, surrounded by the greatest companies and minds in the valley.

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Zagreb, Croatia

LGN is based in the University of Zagreb’s Faculty of Electrical Engineering & Computing, just south of the main station in central Zagreb.

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