The first computers were mostly used for doing numbers. However, as any information can be numerically encoded, people soon realized that computers are capable of general-purpose information processing. The range and accuracy of weather forecasting have increased as a result of their capacity to handle large amounts of data. Their speed has allowed them to make decisions about routing telephone connections through a network and to control mechanical systems such as automobiles, nuclear reactors, and robotic surgical tools. They are also cheap enough to be embedded in everyday appliances and to make clothes dryers and rice cookers “smart.”
We can now ask and answer questions that were previously difficult to pursue thanks to computers. These inquiries might focus on DNA sequences in genes, consumer market activity patterns, or all of a word’s uses in a database of texts. Increasingly, computers can also learn and adapt as they operate by using processes such as machine learning.
Additionally, computers have restrictions, some of which are theoretical. The logical structure of a computer, for instance, is an example of an undecidable proposition, whose truth cannot be determined within a particular set of rules. The “halting problem” occurs when a computer is asked to determine the truth of a proposition because there is no universal algorithmic method that can identify such propositions. Unless forced to stop, the computer will continue to investigate the proposition indefinitely. (Look up the Turing machine.) Other limitations are due to technology at the moment. For instance, despite the fact that computers have made significant progress in terms of the processing of data and the application of algorithms developed by artificial intelligence, they are constrained by their inability to think more holistically. Computers may imitate humans—quite effectively, even—but imitation may not replace the human element in social interaction. Computers are also limited by ethical concerns because they make decisions based on data rather than a moral compass or human conscience. Quantitative data is represented by continuous physical magnitudes in analog computers. At first they represented quantities with mechanical components (see differential analyzer and integrator), but after World War II voltages were used; by the 1960s digital computers had largely replaced them. Nevertheless, through the 1960s, analog computers and some hybrid digital-analog systems continued to be utilized for aircraft and spaceflight simulation. One advantage of analog computation is that it can be relatively easy to design and construct a single-problem analog computer. Another advantage is that analog computers frequently have the ability to represent and solve a problem in “real time,” or at the same rate as the system they are modeling. The main drawbacks of analog representations are that they have limited precision—typically a few decimal places—and that general-purpose devices are expensive and difficult to program.