Biocomputing is the term given to the effort to create a computer based on biological parts or biologically derived molecules such as DNA and/or proteins to function as a computer. It is an evolving field with a huge potential that is aiming to create a computer similar to the human brain which is a phenomenally powerful machine. As per some of the research that I found, the human brain can apparently process 11 Terabytes of information per second and store about 2.5 petabytes (2.5 million gigabytes) of data. Another advantage of a biological computer is that it is relatively easier to power and can be powered by something as simple as glucose mixed in water that is converted to energy by the cells. This would allow the system to become independent of unreliable power sources and the advantages of that are limitless.
Researchers have been working on Bio Computers for more than 30 years now, I first wrote about them back in early 2000’s. They are still in early stages where they can play games such as Pong.
A Swiss startup FinalSpark is taking this to the next level and have successfully grown human neurons from stem cells which are then connected to electrode arrays allowing them to be accessed over the internet. This platform is called Neuroplatform and supports both electrical and chemical stimulation methods. Users can programmatically trigger neurotransmitters like dopamine, glutamate, and serotonin through a Python-based stimulation API. Neuroplatform is used by multiple universities, such as the University of Michigan, Free University of Berlin, University of Exeter, Lancaster University Leipzig, University of York etc.
Wetware computing and organoid intelligence is an emerging research field at the intersection of electrophysiology and artificial intelligence. The core concept involves using living neurons to perform computations, similar to how Artificial Neural Networks (ANNs) are used today. However, unlike ANNs, where updating digital tensors (weights) can instantly modify network responses, entirely new methods must be developed for neural networks using biological neurons. Discovering these methods is challenging and requires a system capable of conducting numerous experiments, ideally accessible to researchers worldwide. For this reason, we developed a hardware and software system that allows for electrophysiological experiments on an unmatched scale. The Neuroplatform enables researchers to run experiments on neural organoids with a lifetime of even more than 100 days. To do so, we streamlined the experimental process to quickly produce new organoids, monitor action potentials 24/7, and provide electrical stimulations. We also designed a microfluidic system that allows for fully automated medium flow and change, thus reducing the disruptions by physical interventions in the incubator and ensuring stable environmental conditions. Over the past three years, the Neuroplatform was utilized with over 1,000 brain organoids, enabling the collection of more than 18 terabytes of data. A dedicated Application Programming Interface (API) has been developed to conduct remote research directly via our Python library or using interactive compute such as Jupyter Notebooks. In addition to electrophysiological operations, our API also controls pumps, digital cameras and UV lights for molecule uncaging. This allows for the execution of complex 24/7 experiments, including closed-loop strategies and processing using the latest deep learning or reinforcement learning libraries. Furthermore, the infrastructure supports entirely remote use. Currently in 2024, the system is freely available for research purposes, and numerous research groups have begun using it for their experiments. This article outlines the system’s architecture and provides specific examples of experiments and results.
FinalSpark has also released the code related to Neuroplatform as Opensource on GitHub.
Am excited to see what folks come up with on this platform.
Source: itsfoss.com: This Company Uses Lab-Grown Human Neurons for Energy-efficient Computing
– Suramya