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Musk Says Tesla Needs to Cut Staff by 10%, Pauses All Hiring

Tesla China-made Model 3 vehicles are seen during a delivery event at the carmaker's factory in Shanghai, China January 7, 2020. (Reuters)
Tesla China-made Model 3 vehicles are seen during a delivery event at the carmaker's factory in Shanghai, China January 7, 2020. (Reuters)
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Musk Says Tesla Needs to Cut Staff by 10%, Pauses All Hiring

Tesla China-made Model 3 vehicles are seen during a delivery event at the carmaker's factory in Shanghai, China January 7, 2020. (Reuters)
Tesla China-made Model 3 vehicles are seen during a delivery event at the carmaker's factory in Shanghai, China January 7, 2020. (Reuters)

Tesla chief executive Elon Musk said he had a "super bad feeling" about the economy and that the electric carmaker needed to cut staff by around 10%, according to an internal email seen by Reuters.

The email, titled "pause all hiring worldwide," was sent to Tesla executives on Thursday.

Tesla was not immediately available for comments.

Musk earlier this week asked Tesla employees to return to the office or leave the company.

"Everyone at Tesla is required to spend a minimum of 40 hours in the office per week," Musk wrote in another email sent to employees on Tuesday night.

"If you don't show up, we will assume you have resigned."

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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
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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.