And here it is, the first synthetic biological intelligence CL1. CL1 biological computer is positioned at the intersection of artificial intelligence and biology. Developed by Cortical Labs, this system is pioneering the concept of synthetic biological intelligence. CL1 combines real neurons derived from human stem cells with chips. These chips enable biological cells to process information and learn tasks. What makes CL1 unique is that it operates entirely with living cells. Unlike traditional computers, data processing occurs through biological pathways.
In short, CL1 brings together digital hardware and living intelligence. This technology is called “wetware” because it contains living tissue in the hardware. This approach is not only technical but also conceptual. Therefore, the CL1 biological computer is not just a device but the beginning of a new paradigm. The information processing capabilities of biological systems have largely been overlooked until now.
CL1 is the first example to make this potential a reality. Developers have demonstrated that biological intelligence can be actively used in computer systems. In short, CL1 biological computer technology could shape the future of artificial intelligence. In this context, CL1 could be one of the most important turning points in the history of technology
Technical Structure and Functioning of CL1
CL1’s technical structure is noteworthy as a joint product of biology and engineering. The neurons used are produced from stem cells in a laboratory environment. These neurons are then placed on specially developed silicon chips. There are 59 microelectrodes inside the chips. These electrodes enable two-way communication with the neurons. In other words, the system both sends signals and records incoming signals. This allows the neurons within CL1 to begin learning. In an artificial game environment, the neurons learn by repeating various tasks. This simulation environment is provided by the Biological Intelligence Operating System (biOS).
Thanks to biOS, users can create their own experiments. New tasks can be loaded onto the neurons in an interactive environment. For example, the system can be taught to play Pong. In the DishBrain experiment, the neurons learned the game in seconds. CL1 has successfully scaled this system for commercial use. This proves that biological learning can be digitized. CL1 works not only with algorithms, but also with cell-based thinking. Although technically complex, CL1’s operating principle is based on natural learning.
CL1 Advantage Energy Efficiency and Fast Learning
The most notable feature of CL1 is its energy efficiency. Traditional artificial intelligence systems require high processing power, which translates to significant energy consumption. For example, an artificial intelligence model may consume 1,000 watts of energy. CL1, however, operates using only a few watts. This difference offers significant advantages in large-scale systems. As energy consumption decreases, sustainability increases. For this reason, CL1 stands out among environmentally friendly artificial intelligence technologies.
CL1 also stands out with its fast learning capacity. Natural neurons have the ability to learn from repetitive data. This feature has been developed through biological evolution and works very effectively. CL1 brings this ability to computer systems. Neurons can increase their success rate after a few attempts. While this process can take weeks in artificial neural networks, CL1 can do it in minutes. CL1’s fast learning capacity provides a significant advantage, especially in dynamic environments. Thus, CL1 works both faster and more efficiently than traditional artificial intelligence.
CL1’s Application Areas and Accessibility
CL1’s application areas appear to be quite broad. Medicine, biotechnology, neuroscience, and drug development are the main areas where it is expected to be used. These are just the beginning… It is expected to provide significant benefits, especially in drug testing. Neurons with the same structure as the human brain provide realistic results. This allows for more accurate disease modeling, which can accelerate treatment processes and reduce risks. Research centers can develop new experiments with the CL1 biological computer. This enables scientific advancements to be achieved in a shorter timeframe.
CL1 is also partially accessible in terms of affordability. The system costs approximately $35,000 in hardware. However, Cortical Labs also offers a “Wetware as a Service” (WaaS) model. With this model, researchers can use the device via a cloud system without purchasing it. Access to neurons is available through the online system. With this system, developers can integrate their data directly into CL1. It is this option that seems to give CL1 the potential to reach a wide user base. In other words, not only large laboratories but also independent developers can benefit from the system. This democratizes technology and accelerates innovation.
Ethical Debates and Future Vision
The ethical dimension of CL1 is just as important as its technical dimension. Systems that enable learning through biological cells raise some questions. Can these neurons gain consciousness? Could CL1 one day become capable of thinking? Scientists have various opinions on this matter. Some believe that neurons cannot achieve such complexity. Others argue that the formation of consciousness is a possibility.
Cortical Labs works with ethical advisors to ensure that the system develops in a safe and responsible manner. Every step in the development process is monitored by ethical protocols. For now, CL1’s actions remain at a reflexive level, resembling learning algorithms rather than consciousness. However, as technology advances, more complex structures may emerge. The possibility of biological systems producing digital consciousness is being discussed for the future. As a result, ethical debates are likely to continue and grow. The future vision is based on a very broad perspective.
Systems like CL1 could form the basis for hybrid artificial intelligence models. Biological and digital structures could work together. This could expand the boundaries of artificial intelligence and open new doors to understanding the human brain. CL1 is quite successful at simulating the mechanisms of the nervous system. Therefore, CL1 stands as both a technological tool and a scientific bridge. The artificial intelligence of the future will likely merge biological and digital intelligence. What do you
