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Australian researchers touch the latest technology for artificial intelligence to increase biosafety – Xinhua



The technology of artificial intelligence, which digitally identifies plants and animals suspected of being biosafety threats, could form a serious tool to protect Australia from pests, other invasive species and diseases, according to recent research.

Researchers at Murdoch University are working on a major project to identify biosafety risks in a matter of seconds, with significant savings in time and money, local media reported on Friday.

"Artificial intelligence has now reached the point where it's very fast and is very accurate," said Professor Simon McKearry on the ABC news channel.

"It can prove to be a very effective friction tool for us in screening samples in the field and in the laboratory," he said.

"We take the process of face recognition and apply it to other organisms, whether they are rat, geckos or insects."

"It begins to identify the special characteristics of different animals and plants that we, as humans, do not have to regard as a recognizable point."

The latest software is learning new information and adapting at an impressive pace, helping biosafety specialists, instead of replacing them, the channel announced.

For example, if you display 100 images, it will do the triangle and return and say: "We actually think there are four images here to consider the human expert," said McCurdy.

"Then the human expert can spend much more time, pretending to get the right answer to the diagnosis."

The latest study is in line with a national initiative involving more than 300 million Australian dollars ($ 217.6 million) invested to step up biosecurity measures over the next five years.

Artificial intelligence technology can first be used at checkpoints at airports and crossing the state border, McCready said.

"Our goal is to reach that point where we could see biosecurity officials at borders, on the ground, and even farmers to be in a position where they can be a phone application that allows them to make a good image" said.

"Then, near real-time they can get a response from the system that has either a good chance it's a pest of concern or not."


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