Samsung Electronics Wins Cutting-edge AI Chip Order from Japan's Preferred Networks

FILE PHOTO: The logo of Samsung is seen on a building during the Mobile World Congress in Barcelona, Spain February 25, 2018. REUTERS/Yves Herman/File Photo
FILE PHOTO: The logo of Samsung is seen on a building during the Mobile World Congress in Barcelona, Spain February 25, 2018. REUTERS/Yves Herman/File Photo
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Samsung Electronics Wins Cutting-edge AI Chip Order from Japan's Preferred Networks

FILE PHOTO: The logo of Samsung is seen on a building during the Mobile World Congress in Barcelona, Spain February 25, 2018. REUTERS/Yves Herman/File Photo
FILE PHOTO: The logo of Samsung is seen on a building during the Mobile World Congress in Barcelona, Spain February 25, 2018. REUTERS/Yves Herman/File Photo

Samsung Electronics said on Tuesday it won an order from Japanese artificial intelligence company Preferred Networks to make chips for AI applications using the South Korean firm's 2-nanometre foundry process and advanced chip packaging service.
It is the first order Samsung has revealed for its cutting-edge 2-nanometre chip contract manufacturing process. Samsung did not elaborate on the size of the order, Reuters reported.
The chips will be made using high-tech chip architecture known as gate all-around (GAA) and multiple chips will be integrated in one package to enhance inter-connection speed and reduce size, Samsung said in a statement.
South Korea's Gaonchips Co designed the chips, Samsung said.
The chips will go toward Preferred Networks' high-performance computing hardware for generative AI technologies such as large language models, Junichiro Makino, Preferred Networks vice president and chief technology officer of computing architecture, said in the statement.



Paris Olympics Expected to Face 4 Billion Cyber Incidents

A general view of the Olympic rings on the Eiffel Tower a day before the opening ceremony of the Paris 2024 Olympics, in Paris, France June 25, 2024. (Reuters)
A general view of the Olympic rings on the Eiffel Tower a day before the opening ceremony of the Paris 2024 Olympics, in Paris, France June 25, 2024. (Reuters)
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Paris Olympics Expected to Face 4 Billion Cyber Incidents

A general view of the Olympic rings on the Eiffel Tower a day before the opening ceremony of the Paris 2024 Olympics, in Paris, France June 25, 2024. (Reuters)
A general view of the Olympic rings on the Eiffel Tower a day before the opening ceremony of the Paris 2024 Olympics, in Paris, France June 25, 2024. (Reuters)

As the Paris 2024 Olympic Games approach, cybersecurity officials are bracing for over 4 billion cyber incidents. They are setting up a new centralized cybersecurity center for the Games, supported by advanced intelligence teams and artificial intelligence (AI) models.

Eric Greffier, the technical director for Paris 2024 at Cisco France, told Asharq Al-Awsat that the Tokyo 2020 Games saw around 450 million cyber incidents. He added that the number of incidents expected for Paris is at least ten times higher, requiring a more efficient response.

Greffier explained that a single cybersecurity center allows for better coordination and a faster response to incidents.

This approach has proven effective in other areas, such as banking and the NFL, where his company also handles cybersecurity, he added.

The Extended Detection and Response (XDR) system is central to the company’s security strategy.

Greffier described it as a “comprehensive dashboard” that gathers data from various sources, links events, and automates threat responses.

It offers a complete view of cybersecurity and helps manage threats proactively, he affirmed.

The system covers all aspects of the Olympic Games’ digital security, from network and cloud protection to application security and end-user safety.

In cybersecurity, AI is vital for managing large amounts of data and spotting potential threats. Greffier noted that with 4 billion expected incidents, filtering out irrelevant data is crucial.

The Olympic cybersecurity center uses AI and machine learning to automate threat responses, letting analysts focus on real issues, he explained.

One example is a network analytics tool that monitors traffic to find unusual patterns.

Greffier said that by creating models of normal behavior, the system can detect anomalies that might indicate a potential attack. While this might generate false alarms, it helps ensure that unusual activity is flagged for further review.