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China's Baidu Launches $145 Million Venture Capital AI Fund

FILE PHOTO: Baidu's logo is pictured at the 2018 Baidu World conference and exhibit to showcase its latest AI technology in Beijing, China, November 1, 2018. REUTERS/Jason Lee/File Photo
FILE PHOTO: Baidu's logo is pictured at the 2018 Baidu World conference and exhibit to showcase its latest AI technology in Beijing, China, November 1, 2018. REUTERS/Jason Lee/File Photo
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China's Baidu Launches $145 Million Venture Capital AI Fund

FILE PHOTO: Baidu's logo is pictured at the 2018 Baidu World conference and exhibit to showcase its latest AI technology in Beijing, China, November 1, 2018. REUTERS/Jason Lee/File Photo
FILE PHOTO: Baidu's logo is pictured at the 2018 Baidu World conference and exhibit to showcase its latest AI technology in Beijing, China, November 1, 2018. REUTERS/Jason Lee/File Photo

Chinese search giant Baidu Inc will set up a venture capital fund of 1 billion yuan ($145 million) to back start-ups focused on content generated by artificial intelligence applications, it said on Wednesday.

The company will also launch a competition for developers to build applications off its ERNIE large language model (LLM) or integrate the model into their existing products, it added.

Chinese tech companies have raced to release their own LLMs following the dramatic success of ChatGPT, the AI-powered chatbot released by Microsft-backed OpenAI, Reuters reported.

Almost 80 organizations in China have launched their own LLMs since 2020, with releases this year slightly exceeding those of the United States, a report showed this week.

In March, Baidu unveiled Ernie Bot, its own AI-powered LLM. E-commerce giant Alibaba Group Holding Ltd was among the other Chinese companies that followed quickly.

In response to the surge of LLMs, China published draft regulations in April on the use of generative AI.

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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)
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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.