The advent of television dramas like “Person of Interest” which explore artificial intelligence has raised interest in biocomputing. If the term is unfamiliar to you, the concept will not be; it has been at the center of fictional characters such as Dr. Frankenstein’s monster and futuristic works for centuries. Biocomputing is defined as the process of building computers that use biological materials, mimic biological organisms or are used to study biological organisms. The website Dr. Dobbs simplifies the definition like this: “It is a biologically inspired approach to creating software.”
Why Mimic Life?
The DNA for a human male could fit into a container with the volume of a millionth of a cubic inch. In contrast, the specifications for a passenger airliner are the size of the plane. Comparing processing speed of computers to biological neurons, a Macintosh computer compares to a snail. Although science has not succeeded in understanding the complete functions of the human brain, there are some processes that can be simulated in computer programs to make them more reliable. You may be familiar with the term “algorithm.” Basically, an algorithm is a list of tasks that a computer has to perform to do a specific task. If you wrote an algorithm for making an omelet, it would include getting out the eggs, breaking them and discarding the shells, mixing the eggs with milk and seasoning them, and so on. Computer algorithms are far more complex and much more detailed, but the concept is similar. The problem is that the longer an algorithm is, and the more lines it contains, the more chance there is for error. The Dr. Dobbs website gives the example of an algorithm with ten million lines of code, that halted the countdown for a space shuttle mission because of a missing comma.
How are the Computer Systems Similar to Biological Organisms?
Two of the terms used in biological computing are “genetic algorithms” and “neural networks.” Both of these refer to the ability of computing systems to learn and to make decisions based on the information they are given. Human brains contain an average of 86 billion neurons that transmit and process information. Neural networks are artificial systems built on the same principle. Genetic algorithms are code sequences that help the computer decide upon a course of action based on predetermined or predicted outcomes. Regular computers must be programmed for every reaction, but biologically-based computers could use the data to evaluate and “learn” how to react.
What is the Future of Biologically-based Computers?
Biologically based computing is not just making computers that resemble organic functioning. It also may involve using organic material to build the computers, such as the magnet-making bacteria used in experiments in the UK. As the machines become more sophisticated they will be used in increasingly complicated tasks. For instance, many genetic diseases are the result of faulty DNA, like the missing comma in the space shuttle example. A computer system that can isolate the faulty “code” can someday fix it.
Interestingly, one of the best uses, according to Quora.com is the construction of simulated organisms in applications to study how they will react to certain environments. Mimicked life will mimic life. In fact, today biocomputing is science fiction becoming just accepted science.