Apple in Talks to Let Google's Gemini Power iPhone AI Features

FILED - 16 September 2023, US, New York: The Apple logo, taken in Manhattan. Photo: Michael Kappeler/dpa
FILED - 16 September 2023, US, New York: The Apple logo, taken in Manhattan. Photo: Michael Kappeler/dpa
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Apple in Talks to Let Google's Gemini Power iPhone AI Features

FILED - 16 September 2023, US, New York: The Apple logo, taken in Manhattan. Photo: Michael Kappeler/dpa
FILED - 16 September 2023, US, New York: The Apple logo, taken in Manhattan. Photo: Michael Kappeler/dpa

Apple is in talks to build Google's Gemini artificial intelligence (AI) engine into the iPhone, Bloomberg News reported on Monday, citing people familiar with the situation.
Apple also recently held discussions with the Microsoft -backed OpenAI and has considered using its model, the report added.
Apple and Google are in active negotiations to let the iPhone maker license Gemini to power some new features coming to the phone's software this year, Bloomberg said.
Apple is preparing new capabilities as part of its upcoming iPhone iOS 18 based on its own homegrown AI models, but it is seeking a partner to power generative AI features, including functions for creating images and writing essays based on simple prompts, the report said.
The two parties have not decided the terms or branding of an AI agreement or finalized how it would be implemented, Bloomberg said, adding it was unlikely that any deal would be announced until June, when Apple plans to hold its annual Worldwide Developers Conference.
Both companies have an existing deal for Google to be the default search engine on Apple's Safari web browser, Reuters reported.
Apple, Google and OpenAI did not immediately respond to a Reuters request for comment outside business hours.
Apple has been slower in rolling out generative AI, which can generate human-like responses to written prompts, than rivals Microsoft and Google, which are weaving them into products.
Last month, Apple CEO Tim Cook said the company plans to disclose later this year more about its plans to put generative AI to use, adding that the company is investing "significantly" in the area.



SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI
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SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

The Center of Excellence for Data Science and Artificial Intelligence at the Saudi Data and Artificial Intelligence Authority (SDAIA) and King Abdullah University of Science and Technology (KAUST) have introduced the MiniGPT-Med model.

The large multi-modal language model is designed to help doctors quickly and accurately diagnose medical radiology using artificial intelligence techniques.

Dr. Ahmed Alsinan, the Artificial Intelligence Advisor at the National Center for Artificial Intelligence and head of the scientific team at SDAIA, explained that the MiniGPT-Med model is capable of performing various tasks such as generating medical reports, answering medical visual questions, describing diseases, locating diseases, identifying diseases, and documenting medical descriptions based on entered medical images.

The model was trained on different medical images, including X-rays, CT scans, and MRIs.

The MiniGPT-Med model, derived from large-scale language models, is specifically tailored for medical applications and demonstrates significant versatility across different imaging methods, including X-rays, CT scans, and MRI. This enhances its utility in medical diagnosis.

Dr. Alsinan highlighted that the MiniGPT-Med model was developed collaboratively by artificial intelligence specialists from SDAIA and KAUST.

The model exhibits advanced performance in generating medical reports, achieving 19% higher efficiency than previous models. It serves as a general interface for radiology diagnosis, enhancing diagnostic efficiency across various medical imaging applications.