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CTOnews.com, June 8 (Xinhua) recently, some researchers have built a tomato picking robot with the help of ChatGPT.

OpenAI's ChatGPT is a language model that can process and understand large amounts of text data and use that information to answer questions. In a new case study, researchers from Delft University of Technology in the Netherlands and the Swiss Federal Institute of Technology turned to ChatGPT-3 for help in the design and manufacture of robots.

This sounds strange because ChatGPT-3 is a language model, not a mechanical model. "although ChatGPT-3 is a language model, its code generation is also text-based, providing important insights and intuition for physical design and showing great potential to stimulate human creativity," said Josie Hughes, co-author of the study.

First, the researchers asked the artificial intelligence model, "what are the challenges facing mankind in the future?" ChatGPT-3 proposes three: food supply, an ageing population and climate change. The researchers chose food supply as the direction of robot design, and then asked ChatGPT-3 what characteristics a tomato harvesting robot should have. ChatGPT-3 proposed a motor-driven clip for pulling ripe tomatoes from vines.

Once the rough design is determined, researchers can decide on the details of the design, including what materials to use and what control code to write. At present, the language model can not generate a complete computer-aided design (CAD) model, evaluation code or automatic manufacturing robot, so this step requires researchers to play the role of "technician" to help complete these aspects, optimize the code written by the language model, complete CAD and build robots.

Figure: an overview of the discussion between the researchers and the language model. the above are the questions posed by humans, and the following are the options provided by the language model. The green shadow represents the human decision tree, gradually focusing the problem in the direction that meets their goals. According to the technical advice provided by ChatGPT-3, the researchers made their robot clip, tested it in the real world, and used it to pick tomatoes, and the results were successful.

a. Some technical suggestions for the generation of language models, including shape indication, code, selection of components and materials, mechanical design, etc. b. Under the guidance of these inputs, a clip is made and tested in real-world tasks, such as tomato picking, as shown on the right. The researchers say their case study shows the potential of collaboration between humans and language models to change the design process, but they also realize that there may be varying degrees of collaboration.

At one extreme, they say, artificial intelligence acts as an "inventor", providing all robot design input, while humans just apply it blindly. Another way is to use the extensive knowledge of artificial intelligence to supplement human professional knowledge. The third way is to retain human beings as inventors, using artificial intelligence to troubleshoot, debug and deal with tedious or time-consuming processes, and optimize the design process.

The researchers raised some of the moral and common sense risks that may arise as a result of artificial intelligence collaborating with humans, pointing to issues such as bias, plagiarism and intellectual property rights as areas of concern.

"in our study, ChatGPT-3 believes that tomatoes are the most worthwhile crops to design a harvesting robot for," Hughes said. "but this may be biased against crops with more literature coverage, rather than those that are really needed. When decisions are beyond the knowledge of engineers, this can lead to serious moral, engineering or factual errors."

Despite these problems, researchers believe that if properly managed, there is great potential for collaboration between artificial intelligence and humans.

The case study, published in the journal Nature Machine Intelligence, can be found here.

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