Intel Slides as Foundry Business Loss Spotlights Wide Gap with Rival TSMC

The logo for the Intel Corporation is seen on a sign outside the Fab 42 microprocessor manufacturing site in Chandler, Arizona, US, October 2, 2020. (Reuters)
The logo for the Intel Corporation is seen on a sign outside the Fab 42 microprocessor manufacturing site in Chandler, Arizona, US, October 2, 2020. (Reuters)
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Intel Slides as Foundry Business Loss Spotlights Wide Gap with Rival TSMC

The logo for the Intel Corporation is seen on a sign outside the Fab 42 microprocessor manufacturing site in Chandler, Arizona, US, October 2, 2020. (Reuters)
The logo for the Intel Corporation is seen on a sign outside the Fab 42 microprocessor manufacturing site in Chandler, Arizona, US, October 2, 2020. (Reuters)

Intel shares fell nearly 7% on Wednesday, as ballooning losses at its contract chip-making business signaled the company could take years to catch up with the profitability of rival Taiwan Semiconductor Manufacturing Co.

Disclosing new financials details for its foundry unit on late Tuesday, Intel said the business posted operating losses of $7 billion in 2023 compared with $5.2 billion in 2022.

"We expected foundry economics to be bad, and they truly are," said Bernstein analyst Stacy Rasgon. "We likely have several years of substantial headwinds still in front of us."

Intel is set to lose more than $12 billion in market value if the losses hold.

The company has been spending billions of dollars to return as the dominant maker of cutting-edge chips, a position that it lost to Taiwan Semiconductor Manufacturing Co., which is now the world's biggest contract chipmaker.

The US chipmaker's capital investments classified as "construction in progress" totaled $43.4 billion as of Dec. 30, 2023, compared with $36.7 billion a year earlier.

Intel also plans to spend $100 billion on plants across four states in the United States, in part helped by funding from the US Chips Act.

CEO Pat Gelsinger said operating losses for its contract chip-making business would peak in 2024 before breaking even by about 2027. It accounted for about 35% of Intel's total net revenue in 2023.

Intel expects the foundry business to have a gross margin of about 40% by 2030, which would still trail the 53% margin TSMC reported for the fourth quarter of 2023.

At T$625.5 billion ($19.52 billion) in just the final three months of the 2023, TSMC's revenue is also much larger than the $18.9 billion in sales Intel's foundry unit had in 2023.

"The incumbents' geographic and talent advantages, as well as their established rolodex of tier-1 customers, have jolted investor confidence in Intel's foundry prospects," said Parv Sharma, a senior analyst at research firm Counterpoint.



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.