When most people imagine artificial intelligence, they think of humanoid robots in science fiction, simulated opponents in video games and frustrating chatbots. However, AI has many other applications. These functions are delivering very significant and practical benefits today. In particular, it is having a big impact on how scientific research is conducted.
What is Artificial Intelligence?
First and foremost, it is helpful to understand exactly what AI is in the modern context. Essentially, artificial intelligence is a computer program that can take inputs and produce outputs that are similar to those a human may come up with. This idea was described by computer science pioneer Alan Turning as a computer being indistinguishable from a human when interacted with.
While current AI is not the equivalent of the completely human-like androids of science fiction, it is capable of some very impressive work. One of the key areas is machine learning, systems that can be trained to perform tasks such as classifying data inputs. ML systems can find patterns in a similar manner to human thought. Plus, they can do so very quickly and very consistently.
How is This Used in Scientific Research?
Not so long ago, the only research involving artificial intelligence was on how to create it. However, recent advancements in machine learning and neural networks have helped to make it a valuable tool. It is being used by all sorts of researchers to more efficiently process data.
Previously, data analysis was largely limited to the capacity of the researchers themselves. They may use data tools such as MATLAB to run tests, but they were largely interacting with it directly.
In some cases, a programmer could create an algorithm for analyzing data. But the process would need to be completely defined. With modern super computer AI systems, researchers can train artificial intelligence programs to analyze data for them. Thus, it can handle far more varied and complex data sets. This is very useful when working with large amounts of data or data that is traditionally difficult for computers to analyze.
For example, researchers may want to gather data from images. In the past, if they wanted to use those images, they would need to be manually tagged by team members. This is because the computer system couldn’t understand what was in the image otherwise. With AI, the computer can classify images with impressive accuracy.
AI is being used by physicists to accelerate computation and achieve mathematical analysis that would be prohibitively resource-heavy using traditional approaches. It is also being used by public health researchers who are gathering enormous amounts of epidemiological data from many sources. Others are using AI to develop new sensors and other products.
Are There Challenges?
The application of AI in research and many new products is a relatively new field. Even in the past decade, the field has been revolutionized multiple times. This spells great news for researchers in many different areas. But, it is not without challenges. One of the key growing pains is that many researchers are currently unsure how to use AI. It is so new that most people outside of cutting-edge AI research and development simply don’t understand it.
Another key growing pain is that, even with modern AI algorithms, the computational requirements are very high. A typical workstation is not equipped to perform the types of calculations that are needed by researchers. While massive organizations like Google and certain universities can invest in traditional supercomputers to handle the work, there exists a need for other teams to have access to appropriate resources. Fortunately, this problem is rapidly being resolved with new products on the market.
Learn More
Are you interested in applications for artificial intelligence? Could your research be improved through the use of AI? Learn more about this topic today. The world of artificial intelligence is cutting-edge, but it promises to truly revolutionize many areas of life, including how scientific research is completed.
