06 Nov Role of AI in Cutting Edge Science
No human, whether individually or in a team, could possibly keep up with the avalanche of information produced by modern-day scientific experiments. A few of them even record terabytes of data on a daily basis. For instance, there is the Square Kilometer Array (SKA), a radio mega telescope thatâs slated to be switched on sometime this 2020. Gathering thousands of dishes and low-frequency antennae, it will be the worldâs largest radio telescope with over a square kilometer (one million square meters) of collecting area. The SKA is expected to generate as much data traffic annually as the entire internet!
This information deluge has many scientists turning to AI for help. AI systems can plough through mountains of data with minimal input â highlighting anomalies and patterns that humans can never spot. From scanning for supernovae to discovering new drugs, AI technology is increasingly being used to explore new avenues for researchers and scientists.
The ability of researchers to generate and store data has increased manifold over the years. However, it has also made it difficult to analyze this data for patterns and insights. The deep learning techniques of AI play a crucial role in easing data analysis. After adequate training, AI systems show an excellent ability for predicting results with high efficiency.
Human intellect combined with AIâs deep learning can help tap previously unexplored areas. Automating science could make running large experiments more competent. AI is already being used by pharmaceutical companies for extracting information from written materials such as academic papers to find new hypotheses for testing. This could lead to the formulation of new and more potent drugs. AI, therefore, helps researchers traverse terrains that were earlier perceived as challenging.
Academic publishing is an indispensable part of conducting research. However, the biggest concern among editors and peer reviewers is spotting incongruencies in statistics, data, images, or references in manuscripts. Detection of plagiarism is another important area that needs attention. AI comes into the picture here by flagging inconsistencies with precision and efficiency.
Assisting journaling processes
Since they have hundreds of submissions to process, journal publishing is perfect for AI applications. AI aids in recognizing suitable reviewers, manage submissions, and even decide on the acceptance or rejection of a paper. AI is playing a crucial role in simplifying the challenges faced by editors for faster publishing.
Artificial intelligence is propelling scientific development in the right direction to help science reach new heights.