Valis Corporation Technology Used in Large Brain Model Project – PR.com
San Diego, CA, September 16, 2024 –(PR.com)– Valis is excited to announce The Large Brain Model (LBM). This project will couple one thousand “miniature brains” using quantum entangled photons to form a biological quantum computer. This innovation promises to transform our understanding of the human brain and enable new information-processing systems.
Whether the brain functions as a quantum structure remains a hotly contested issue in the scientific world. The recent discovery that microtubules – part of neurons – transport energy using a quantum similar effect to that found in photosynthesis has reignited the debate. If the brain is a quantum structure, entangling the input photons will allow the entire model to form a single biological quantum computer. If brains are not quantum, the model will still be the largest biological neural network in the world and the first to approach the scale of the human brain.
Central to the project are brain organoids – miniaturized versions of the brain grown in vitro. Developed by Alysson R. Muotri, PhD, professor of medicine at University of California San Diego, they mimic the structure and function of the human brain but are much simpler. The LBM will be formed of an array of 1,024 of these organoids, each containing around one million neurons. The resulting array will have approximately 500 million neurons, roughly 1/16th of the capacity of the cerebral cortex—the part of the human brain involved in complex reasoning and language.
The model will be coupled to existing silicon-based neural networks using patented technology developed by Valis, providing a hybrid natural-artificial intelligence system that can be applied to problems that present AI systems struggle to perform. This includes complex reasoning tasks and tasks where we need to model human behavior, such as stock trading.
Applications include non-linguistic reasoning, such as visual design, “crossing the chasm,” where we try to persuade the human brain that a scene or digital avatar is real, financial market modeling, where predicting human behavior is key, and mathematical theorem proving—the gold standard in the Turing test hierarchy.
In addition to forming an advanced quantum information processor, The Large Brain Model may help with the scientific problems of brain mapping, energy-efficient AI, cognitive brain diseases such as epilepsy and Alzheimer’s, and anesthesia.
One of the biggest challenges will be dealing with the bandwidth. The array will output 11 terabits of data per second, a rate that vastly exceeds the capabilities of current EEG or Neural link projects. For perspective, that’s over 230 high-definition 8K video feeds.
“We are thrilled to collaborate with UC San Diego and the Muotri Lab on this groundbreaking project,” said James Tagg, President of Valis Corporation. “By combining our technological expertise with UC San Diego’s cutting-edge research, we aim to push the boundaries of neuroscience and unlock new possibilities in AI.”
“We’re excited to work with Valis Corporation to advance methods for developing brain models that more accurately represent human behavior,” said Muotri. “This technology has the potential to open up new avenues of research related to brain health and treatment therapies.”
About Valis Corporation
Valis Corporation is a quantum AI company committed to understanding advanced quantum effects and their broad impact. It is especially interested in the human brain and how it might distinguish humans’ natural intelligence from artificial intelligence. The laboratory operates in quantum communications, sensing, and computation.
This press release contains forward-looking statements, which are based on management’s current assumptions and are subject to risks and uncertainties that may cause actual results to differ materially. These statements, identified by terms such as “expects,” “intends,” and “anticipates,” involve expectations about the partnership, the potential benefits of incorporating biological processes in neural networks, and the success of the project. The Company does not undertake any obligation to update these statements, and readers are cautioned not to place undue reliance on them, as actual outcomes may vary.