Biocomputing with Human Neurons: The Future of Post-Silicon Computing

Biocomputing with Human Neurons

• 💡 FinalSpark is developing computers using living human neurons as processors, aiming for extreme energy efficiency.
• 🧠 Neurons are estimated to be 1 million times more energy efficient than silicon-based processors.
• 🔬 The process involves reprogramming human skin cells into stem cells, which then develop into neurons, not complete brains.

Neurons as Logic Gates

• 🎯 The goal is to use neurons as logic gates, though their information encoding is fundamentally different from digital computers.
• ⚡ Unlike digital computers with binary zeros and ones, neurons encode information through spatial and temporal activity, such as spike timing and location.
• 🧩 This difference necessitates developing entirely new programming paradigms and algorithms, similar to the challenges in quantum computing.

The Neuroplatform and Experiments

• 🌐 FinalSpark offers remote access to its laboratory, allowing users to write Python code to conduct experiments with real neurons.
• 🧪 Current experiments focus on programming and controlling neuron behavior, with the long-term goal of processing complex information like images and sounds.
• 🧠 Mini-brains, or organoids, grown over three months, contain about 10,000 neurons and function as real brain tissue, connected to electrodes for experimentation.

Challenges and Future Outlook

• ⚠️ A major challenge is understanding how neurons encode information and the inherent instability of living biological systems, which change over time.
• 📈 Despite challenges, progress has been made, including the consistent storage and retrieval of one bit of information.
• 🚀 The team anticipates it will take approximately 10 years to build useful biocomputers, focusing on general computing tasks rather than specialized ones.

Control and Environment

• 🔌 Control is achieved by sending electrical signals and, more recently, chemical signals like dopamine and serotonin, to influence neuron behavior and learning.
• 🔄 Dopamine is used as a reward mechanism to reinforce desired neuron activity, forming a feedback loop for learning.
• 🌡️ Maintaining a stable, physiological environment (temperature, pH, liquid medium) is critical for neuron stability and function, suggesting centralized server-like environments for future biocomputers.