Nvidia Unveils Latest Chips, Technology to Speed up AI Computing

The Nvidia's new Grace CPU Superchip unveiled at the chipmaker's AI developer conference is seen in this undated handout image obtained by Reuters. (Nvidia/Handout via Reuters)
The Nvidia's new Grace CPU Superchip unveiled at the chipmaker's AI developer conference is seen in this undated handout image obtained by Reuters. (Nvidia/Handout via Reuters)
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Nvidia Unveils Latest Chips, Technology to Speed up AI Computing

The Nvidia's new Grace CPU Superchip unveiled at the chipmaker's AI developer conference is seen in this undated handout image obtained by Reuters. (Nvidia/Handout via Reuters)
The Nvidia's new Grace CPU Superchip unveiled at the chipmaker's AI developer conference is seen in this undated handout image obtained by Reuters. (Nvidia/Handout via Reuters)

Nvidia Corp on Tuesday announced several new chips and technologies that it said will boost the computing speed of increasingly complicated artificial intelligence algorithms, stepping up competition against rival chipmakers vying for lucrative data center business.

Nvidia's graphic chips (GPU), which initially helped propel and enhance the quality of videos in the gaming market, have become the dominant chips for companies to use for AI workloads. The latest GPU, called the H100, can help reduce computing times from weeks to days for some work involving training AI models, the company said.

The announcements were made at Nvidia's AI developers conference online.

"Data centers are becoming AI factories - processing and refining mountains of data to produce intelligence," said Nvidia Chief Executive Officer Jensen Huang in a statement, calling the H100 chip the "engine" of AI infrastructure.

Companies have been using AI and machine learning for everything from making recommendations of the next video to watch to new drug discovery, and the technology is increasingly becoming an important tool for business.

The H100 chip will be produced on Taiwan Manufacturing Semiconductor Company's cutting edge four nanometer process with 80 billion transistors and will be available in the third quarter, Nvidia said.

The H100 will also be used to build Nvidia's new "Eos" supercomputer, which Nvidia said will be the world's fastest AI system when it begins operation later this year.

Facebook parent Meta announced in January that it would build the world's fastest AI supercomputer this year and it would perform at nearly 5 exaflops. Nvidia on Tuesday said its supercomputer will run at over 18 exaflops.

Exaflop performance is the ability to perform 1 quintillion - or 1,000,000,000,000,000,000 - calculations per second.

In addition to the GPU chip, Nvidia introduced a new processor chip (CPU) called the Grace CPU Superchip that is based on Arm technology. It's the first new chip by Nvidia based on the Arm architecture to be announced since the company's deal to buy Arm Ltd fell apart last month due to regulatory hurdles.

The Grace CPU Superchip, which will be available in the first half of next year, connects two CPU chips and will focus on AI and other tasks that require intensive computing power.

More companies are connecting chips using technology that allows faster data flow between them. Earlier this month Apple Inc unveiled its M1 Ultra chip connecting two M1 Max chips.

Nvidia said the two CPU chips were connected using its NVLink-C2C technology, which was also unveiled on Tuesday.

Nvidia shares were up more than 1% in midday trade.



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.