In a groundbreaking move, Monash University has secured nearly $600,000 AUD from the esteemed National Intelligence and Security Discovery Research Grants Program for a unique project. Associate Professor Adeel Razi, in partnership with Melbourne start-up, Cortical Labs, is leading research to integrate human brain cells and artificial intelligence (AI).
Enhancing Machine Learning with Human Brain Cells
The pioneering project involves nurturing around 800,000 brain cells in a laboratory setting. These cells are subsequently trained to complete specific tasks. An exemplary achievement last year was teaching the brain cells to play a simple computer game, Pong, propelling the team’s research into the global spotlight.
This revolutionary approach embeds lab-grown brain cells onto silicon chips. “This fusion of artificial intelligence and synthetic biology has paved the way for programmable biological computing platforms,” Professor Razi explains.
Potential Impact on Various Fields
The implications of such advancements could resonate across several domains including planning, robotics, brain-machine interfaces, advanced automation, and drug discovery. This could provide Australia with a considerable strategic edge.
The initiative secured funding as the upcoming wave of machine learning applications will necessitate a fresh kind of machine intelligence. Examples include self-driving vehicles, autonomous drones, and intelligent handheld or wearable devices.
Lifelong Continual Learning: The Game Changer
One of the critical aspects of this new type of machine intelligence is its capability for “continual lifelong learning”. Current AI systems struggle with this, often experiencing “catastrophic forgetting”. Conversely, the human brain excels at acquiring new skills without losing old ones, adjusting to changes, and applying past knowledge to new tasks, all while conserving limited resources like memory, energy, and computing power.
This novel research project aims to cultivate human brain cells in a laboratory dish, referred to as the DishBrain system. The goal is to understand the biological mechanisms that facilitate lifelong continual learning.
“We’ll use this grant to develop superior AI machines that mimic the learning capacity of these biological neural networks,” Professor Razi said. “Our objective is to increase the hardware and methods to a level where they could potentially replace in silico computing.”
In conclusion, this research promises to push the boundaries of AI and machine learning, fostering innovations that can reshape our world.
Related Articles
