Google is testing AI chatbot that can answer medical questions: Report


At I/O 2023, Google CEO Sundar Pichai announced PaLM 2 large language model (LLM) with improved multilingual, reasoning and coding capabilities. The company said that the model is trained on 100 languages and performs a broad range of tasks. At that time, Pichai highlighted that the AI model will be available in Workspace apps, Med-PaLM for medical uses and Sec-PaLM for security. A report has now said that Google has been testing an AI chatbot for expertly answering medical questions.

According to a report by The Verge (via The Wall Street Journal), Med-PaLM 2 has been in testing at the Mayo Clinic research hospital – a non-profit organisation based in the US, among others, since April.

The report noted that Google believes the LLM will be useful in places where there is “limited access to doctors”. Google’s senior research director Greg Corrado said that Med-PaLM 2 is still in its early stages.

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According to Corrado, he would not want it to be a part of his own family’s “healthcare journey”, but he believed Med-PaLM 2 “takes the places in healthcare where AI can be beneficial and expands them by 10-fold”.

Why is Med-PaLM better than other AI chatbots?
According to Google, Med-PaLM 2 will be better at healthcare conversations than general chat bots such as Bard, Bing and ChatGPT. Med-PaLM is trained on a curated set of medical expert demonstrations.

The report also mentioned that the customers who will be testing Med-PaLM 2 will control their data. The data will also be encrypted and Google won’t have access to it.

Read Also

Google needs data to train its AI chatbot models, and this week, a report said that the company updated its policy saying that it will use all publically available data to train Bard and other AI models.

Google confirmed this and spokesperson Christa Muldoon said, “Our privacy policy has long been transparent that Google uses publicly available information from the open web to train language models for services like Google Translate.”

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At I/O 2023, Google CEO Sundar Pichai announced PaLM 2 large language model (LLM) with improved multilingual, reasoning and coding capabilities. The company said that the model is trained on 100 languages and performs a broad range of tasks. At that time, Pichai highlighted that the AI model will be available in Workspace apps, Med-PaLM for medical uses and Sec-PaLM for security. A report has now said that Google has been testing an AI chatbot for expertly answering medical questions.

According to a report by The Verge (via The Wall Street Journal), Med-PaLM 2 has been in testing at the Mayo Clinic research hospital – a non-profit organisation based in the US, among others, since April.

The report noted that Google believes the LLM will be useful in places where there is “limited access to doctors”. Google’s senior research director Greg Corrado said that Med-PaLM 2 is still in its early stages.

Read Also

According to Corrado, he would not want it to be a part of his own family’s “healthcare journey”, but he believed Med-PaLM 2 “takes the places in healthcare where AI can be beneficial and expands them by 10-fold”.

Why is Med-PaLM better than other AI chatbots?
According to Google, Med-PaLM 2 will be better at healthcare conversations than general chat bots such as Bard, Bing and ChatGPT. Med-PaLM is trained on a curated set of medical expert demonstrations.

The report also mentioned that the customers who will be testing Med-PaLM 2 will control their data. The data will also be encrypted and Google won’t have access to it.

Read Also

Google needs data to train its AI chatbot models, and this week, a report said that the company updated its policy saying that it will use all publically available data to train Bard and other AI models.

Google confirmed this and spokesperson Christa Muldoon said, “Our privacy policy has long been transparent that Google uses publicly available information from the open web to train language models for services like Google Translate.”

FacebookTwitterLinkedin



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