Apple to Make Messaging between iPhone and Android Devices Easier

An Android mascot is seen in front of a displayed logo of Apple in this photo illustration taken in Zenica, Bosnia and Herzegovina, May 5, 2015. Picture taken on May 5. (Reuters)
An Android mascot is seen in front of a displayed logo of Apple in this photo illustration taken in Zenica, Bosnia and Herzegovina, May 5, 2015. Picture taken on May 5. (Reuters)
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Apple to Make Messaging between iPhone and Android Devices Easier

An Android mascot is seen in front of a displayed logo of Apple in this photo illustration taken in Zenica, Bosnia and Herzegovina, May 5, 2015. Picture taken on May 5. (Reuters)
An Android mascot is seen in front of a displayed logo of Apple in this photo illustration taken in Zenica, Bosnia and Herzegovina, May 5, 2015. Picture taken on May 5. (Reuters)

Apple said it plans to adopt a messaging standard next year that will allow for a smoother texting experience between iPhones and Android devices.

The company had been resisting the Rich Communication Services (RCS) standard for more than a year, with Alphabet's Google and others pushing for the iPhone maker to adopt the technology.

Apple said the new technology would work alongside iMessage and offer better interoperability than SMS or MMS.

RCS, considered an industry standard for messaging, allows users to send and receive high-quality photos and videos, chat over WiFi or cellular data and know when messages were read, among other features.



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.