Global Smartphone Market Sees Growth after over 2 Years in October

People rest eating ice cream and reading their smartphones outside the GUM department store, enjoying a warm autumn day in Red Square in Moscow, Russia, on Wednesday, Nov. 1, 2023. (AP)
People rest eating ice cream and reading their smartphones outside the GUM department store, enjoying a warm autumn day in Red Square in Moscow, Russia, on Wednesday, Nov. 1, 2023. (AP)
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Global Smartphone Market Sees Growth after over 2 Years in October

People rest eating ice cream and reading their smartphones outside the GUM department store, enjoying a warm autumn day in Red Square in Moscow, Russia, on Wednesday, Nov. 1, 2023. (AP)
People rest eating ice cream and reading their smartphones outside the GUM department store, enjoying a warm autumn day in Red Square in Moscow, Russia, on Wednesday, Nov. 1, 2023. (AP)

The global smartphone market returned to growth in October after more than two years of slump, helped by a recovery in the emerging markets, according to data from Counterpoint Research.

The data showed that global monthly smartphone sell-through volumes grew 5%, making October the first month to record year-on-year growth since June 2021, breaking the streak of 27 consecutive months of negative year-on-year growth.

Global smartphone sales have been under stress for the last two years affected by various issues starting with component shortages, inventory build-up and lengthening of replacement cycles, Counterpoint said in its report.

"Following strong growth in October, we expect the market to grow year-on-year in the fourth quarter of 2023 as well, setting the market on the path to gradual recovery in the coming quarters," the market research firm said.

The growth, which was last seen in June 2021 coming from a COVID-19 induced pent up demand, has now been led by emerging markets with a continuous recovery in the Middle East and Africa, Huawei's comeback in China and onset of festive season in India, it added.

Huawei's China smartphone sales grew strongly in the third quarter, surging 37%, as shoppers snapped up its Mate 60 series phones.

The developed markets with relatively higher smartphone saturation have been slower to recover, the report said, but it cited the launch of Apple's iPhone 15 series as another factor for the growth.



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.