The Dawn of Synthetic Biological Intelligence: A First Look at the CL1 Bio-Computer
Are you ready to use a computer unlike any other – one that blends living brain neurons with silicon chips to create advanced artificial intelligence? In this analysis, we’ll delve into the recently unveiled bio-computer that fuses everyday silicon chips with living brain neurons. This breakthrough promises to revolutionize artificial intelligence. Adding to the excitement, this brain-in-a-box is priced at a surprisingly affordable $35,000! It’s a technological marvel poised to redefine the future of computing.
This exploration of cutting-edge AI innovations builds upon my ongoing coverage of the field, aiming to identify and explain intricate aspects of artificial intelligence.
The Nature of Neurons and Neural Networks
Before we explore this new bio-computer, it’s important to understand neurons. The human brain is composed of billions of neurons, which create our thoughts and enable our thinking processes. These neurons are interconnected and constantly send signals back and forth. This vast network of connections, numbering in the trillions, is known as a neural network (NN). In the human brain, the biological neural network is often referred to as wetware.
One of the greatest mysteries in science is how these activated neurons give rise to sentience and consciousness. Active research seeks to crack this code.
AI and Artificial Neural Networks
Modern AI, including applications like generative AI and large language models (LLMs), utilizes artificial neural networks (ANNs). These are computer simulations of neural networks, employing data and mathematical models to mimic neurons. While ANNs are a remarkable technological feat, they are drastically different from real, living neurons. It is important to emphasize that AI uses artificial neural networks. The AI industry sometimes blurs this distinction, potentially misleading people into thinking that an ANN is equivalent to a wetware neural network. The goal is that with computational neurons working in a faked or artificial neural network, we will get close to having AI that thinks.
At the very least, ANNs can help us better understand real biological NNs.
Connecting to Human Brains
Significant progress has been made in the realm of brain-computer interfaces (BCIs), also termed brain-machine interfaces (BMIs). These technologies aim to connect to and utilize a person’s living neural network. As an example, companies like Neuralink are developing ways to connect to human brains. The goal of BCIs is to gain access to the living brain, similar to a USB port on a computer. Signals can be sent into the brain to trigger activation, with the technology reading the ensuing signals. These interfaces may allow the reading or sending of these signals.
The question of how living neurons in a wetware neural network produce human thought remains a complex puzzle. We are only capable of determining the most preliminary aspects.
Brain-in-a-Box: A New Approach
Sci-fi movies have frequently depicted the possibility of removing a person’s brain and having it function independently in a vat. However, no such capability exists currently. An alternative approach is to create a computer that replicates a human brain using ANNs, thereby forming a brain-in-a-box. It is possible to transfer the contents of a human brain into the computer-based version and copy the contents of the ANN into a human brain.
Melding the Real with the Artificial
Let’s consider a new approach: Integrating living brain neurons onto silicon chips. This innovation melds artificial and biological components intimately together. This represents the best of both worlds.
The computer could leverage living neurons to solve problems and perform thought processes. The AI, complete with its artificial neurons, would interact with the living neurons. In this process, signals activate the living neurons, and the responses generated feed back into the computer, which then processes the information using the artificial neural network. This symbiotic interaction represents a fusion of wetware and artificial neural networks.
A Somewhat Scary Proposition
Where do these living brain neurons originate? These are grown in a lab, using synthetic methods. The upside is that this approach allows the creation of a bio-computer, which incorporates aspects of wetware and ANN, without harming any human being.
There is an ongoing debate about the ethics of growing such neurons, particularly if the intent is solely for use with a computer. The ethical questions multiply as the number of synthetic neurons approaches the number needed to trigger human-like thought or consciousness. In the context of AI, this potential shift toward human-like consciousness is referred to as the minimal viable brain (MVB).
Synthetic Neurons and Embodiment
Another thought-provoking question is whether human brains require our senses to develop sufficiently. The reliance on our senses (eyes, ears, touch, limbs, etc.) for brain development raises an important consideration. Synthetic neurons, which do not have a physical body, therefore lack this embodiment. Some argue that these neurons are unable to be of any real substance. A core question is whether synthetic neurons that have never gone through embodiment are useful or would be limited.
Energy Efficiency: An Unexpected Benefit
One intriguing aspect of the human brain is its remarkable energy efficiency. An adult human brain consumes approximately 12 watts, compared to a light bulb that consumes about 60 watts. A brain thinks using a tiny amount of energy. The AI industry is rapidly increasing its energy consumption through the use of data centers with thousands of servers. The melding of synthetic neurons with silicon could dramatically conserve energy. AI in a bio-computer could calculate that the artificial neural network would consume some Z amount of energy, while the synthetic neurons could do the same processing for a lesser amount than Z. This suggests a notable boost to sustainable computing.
Where This is Heading
The interaction of living neurons with silicon chips necessitates rethinking computer processing. Considerations like when to use the onboard wetware neural network and when to use the AI artificial neural network arise. These issues include identifying the right balance between the two methods for processing requests and solving problems. The question of how these arrangements will be defined is quickly evolving.
The current state of technology is not best described as a brain-in-a-box because the scant number of wetware neurons doesn’t constitute a “brain.” One potential new term is synthetic biological intelligence (SBI).
The Upcoming Bio-Computer: CL1 from Cortical Labs
The company behind this remarkable bio-computer is Cortical Labs, located in Australia. The system is called the CL1, with the tagline “the world’s first code deployable biological computer.” The CL1 contains living neurons, which require an environmental containment system to keep the neurons alive for up to 6 months. This provides a self-contained life support capability. With the CL1 bio-computer, the user has a touchscreen display to monitor the environmental containment and the synthetic neurons. The rest of the computer has regular components, including USB ports, a built-in camera, and so on.
The firm and its researchers have spent years working on this configuration. In 2022, the company announced an early version that was able to play the video game, Pong. A 2023 research paper, “The Technology, Opportunities, And Challenges Of Synthetic Biological Intelligence” by Brett J. Kagan and others, highlighted several key points. Their findings include advancements in hardware, software, and synthetic biology (wetware) that have led to new methods for interacting with in vitro biological neural systems. They also defined SBI as the result of intentionally synthesizing a combination of biological and silicon substrates in vitro for the purpose of goal-directed or otherwise intelligent behavior. The CL1 has a specialized operating system, the Biological Intelligence Operating System (biOS). The biOS builds a simulated world for the living neurons, receiving and sending signals that influence this simulated world.
The Future is Approaching
What is your reaction to a computer that encompasses living neurons and can be kept at home or in the office? The initial reaction could be shock or excitement. These kinds of setups are typically expensive, only found in high-tech labs of large companies. Consumers can now access this capability.
At $35,000, this price is low enough for tech-related start-ups to acquire the system. This will undoubtedly be a direction for furthering advances in AI. Issues of scale are present. If the complexity and volume of the synthetic neurons fail to increase to an effective level, then the functionality will remain limited. It is certain that this area will draw ongoing interest and be used for basic research pursuits.
We often hear assertions that we all live in a Matrix-like world, in simulations. Do you think that the synthetic neurons are considering the same idea? Will these neurons wonder if they are awake or dreaming? This will be the first question I pose when I have the chance to try out the new bio-computer.
