Preprocessing of learning data for artificial intelligence is also done through artificial intelligence.
Haebom
According to an article in Nature, an AI tool outperformed human experts at finding image manipulation in research papers. An independent biologist named Sholto David reviewed hundreds of papers to find duplicate images, and then ran the same papers through an AI tool. As a result, the AI tool found 41 papers that David had missed. One of these AI tools, Imagetwin, is already being used by more than 200 universities, publishers, and scientific organizations.
In fact, in addition to imagetwin, there are various services or models that find differences in various fields. Also, models that replace the preprocessing of AI learning datasets are being released one after another. I also have a vain expectation that pairing data sets will be created automatically in the future.
🤔 Things to think about 1: The limitations and advantages of AI
AI tools aren’t perfect either. For example, they can miss duplicates in images with low contrast. Nevertheless, it’s worth considering why these tools are increasingly being used.
🤔 Point to consider 2: Collaboration between humans and AI
If AI tools can’t replace the human eye, how can the two work together to achieve more effective results?
🤔 Point to consider 3: Using AI in the paper review process
It would be interesting to consider how AI tools could be integrated into the paper review process and what value this could add to the academic world.
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