China Says US Spreading Disinformation, Suppressing TikTok

The TikTok logo is pictured outside the company's US head office in Culver City, California, US, September 15, 2020. REUTERS/Mike Blake
The TikTok logo is pictured outside the company's US head office in Culver City, California, US, September 15, 2020. REUTERS/Mike Blake
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China Says US Spreading Disinformation, Suppressing TikTok

The TikTok logo is pictured outside the company's US head office in Culver City, California, US, September 15, 2020. REUTERS/Mike Blake
The TikTok logo is pictured outside the company's US head office in Culver City, California, US, September 15, 2020. REUTERS/Mike Blake

China accused the United States on Thursday of spreading disinformation and suppressing TikTok following reports that the Biden administration was calling for its Chinese owners to sell their stakes in the popular video-sharing app.

The US has yet to present evidence that TikTok threatens its national security and was using the excuse of data security to abuse its power to suppress foreign companies, Foreign Ministry spokesperson Wang Wenbin told reporters at a daily briefing.

“The US should stop spreading disinformation about data security, stop suppressing the relevant company, and provide an open, fair and non-discriminatory environment for foreign businesses to invest and operate in the US,” Wang said.

TikTok was dismissive Wednesday of a report in The Wall Street Journal that said the Committee on Foreign Investment in the US, part of the Treasury Department, was threatening a US ban on the app unless its owners, Beijing-based ByteDance Ltd., divested.

“If protecting national security is the objective, divestment doesn’t solve the problem: A change in ownership would not impose any new restrictions on data flows or access,” TikTok spokesperson Maureen Shanahan said.

Shanahan said TikTok was already answering concerns through “transparent, US-based protection of US user data and systems, with robust third-party monitoring, vetting, and verification.”

The Journal report cited anonymous “people familiar with the matter.” The Treasury Department and the White House’s National Security Council declined to comment.



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.