Chinese technology giants are making a serious foray into Web3, but their potential is currently constrained

Two exhibition booths stood out at the Staking Summit in Istanbul, a conference attended by hundreds of individuals involved in staking practices in the cryptocurrency ecosystem. They belonged to Tencent and Huawei. In a backdrop dominated by people in their 20s wearing trendy corporate hoodies and handing out well-designed merchandise, China’s two tech giants feel a little out of place under the more formal corporate flag. It looked like there was.

Next to them were engineers, marketers, and business developers deeply into staking, where individuals pledge crypto assets like Ethereum to protocols in exchange for a return. The borrowed assets are then used to verify transactions within the blockchain, which implements a “proof-of-stake” method.

Over the past year, several Chinese tech giants, including Alibaba, Tencent, and Huawei, have appeared at crypto events around the world. Hoping to carve market share in the nascent Web3 space, they appear at these events with a more low-profile presence, either as official sponsors or simply as participants.

The Chinese tech giant’s participation in crypto falls somewhere at the intersection of Web 2 and Web 3, thanks to a widespread ban on crypto trading and initial coin offerings in its home country. In the most common case, these technology companies are selling their computing resources to his Web3 startups in a manner not too different from how they have sold cloud services to more established technology industry companies. Masu.

Cloud costs for companies building or leveraging decentralized networks are still understood to be negligible. While it’s not uncommon for Web2 “midsize” companies to spend $1 million or more on cloud computing, companies that qualify as Web3 midsize may only spend in the low hundreds of thousands of dollars, the speakers said. said several participants at the meeting. said the event.

However, the limited ticket size does not prevent Chinese cloud providers from venturing into cryptocurrencies. Chinese companies, the underdogs in the global cloud market, have less brand recognition, especially in the West, and are far more proactive and flexible with their customers. Therefore, companies must compete by offering cheaper or better services.

In addition to providing cloud infrastructure, Chinese companies are moving into areas outside of their core products, exposing them to competition from crypto-native companies. This includes building blockchain for enterprises. Most Chinese tech companies have stayed away from the public blockchain space, where tokens play a key role, due to the country’s cryptocurrency crackdown.

Some players also offer node-as-a-service business. A blockchain is a decentralized database that stores and encrypts transaction data and runs on distributed nodes.However, these nodes are expensive and complex to maintain, making companies like Huawei Provide node hosting services for developersis an attractive solution for companies that want to build decentralized applications but lack the technical sophistication to do so in-house.

Tencent and Alibaba were the first Chinese technology giants to enter the Web3 space and have also worked on high-profile projects to improve their reputation in the industry.

For example, Tencent has partnered with public blockchains such as Sui and Avalanche, as well as Ethereum scaling solution Scroll.

Meanwhile, Alibaba partnered with Aptos, a blockchain developed by a former Meta employee, to make its name known in the world of Web3. In a joint announcement today, Alibaba Cloud and Aptos Foundation announced that they will jointly host a hackathon using the Move programming language in the Asia Pacific region.

So far, Web3 is barely making inroads into the revenue of China’s technology giants, but these companies recognize the potential of a rapidly growing industry and are willing to take advantage of significant market swings and financial system collapse. Even in the face of it, we understand that we cannot afford to miss this opportunity. Major companies such as FTX.

Source: techcrunch.com

Australian Divers Sustain Injuries from Sonar Pulse of Chinese Navy

The Australian government stated that divers were injured when the Chinese navy used sonar while removing fishing nets underwater.

Australian Defense Minister Richard Marles raised concerns with the Chinese government regarding the “unsafe and unprofessional” use of the technology, following similar complaints from the United States, Canada, and Australia about alleged actions by the Chinese military in the Western Pacific.

Marles mentioned that HMAS Toowoomba was in international waters in Japan’s exclusive economic zone on Tuesday when a fishing net got caught in its propeller and that it supported the United Nations in imposing sanctions on the region.

He described how a PLA-N destroyer (DDG-139) approached HMAS Toowoomba during a dive operation and attached to the hull, causing Australian divers to sustain minor injuries likely due to sonar pulses from the Chinese destroyer.

Sonar uses sound waves to create images of what’s happening underwater. When used at high levels, it can cause dizziness and possibly organ damage.

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Opposition politician James Patterson stated that the incident occurred after the prime minister visited China to build closer ties. He mentioned that “While China wants to improve relations with Australia, it is taking dangerous actions that put the safety of Australian personnel at risk,”

China did not immediately respond to the accusation.

Source: news.sky.com

Chinese tech giants vie for $340 million investment in rival to OpenAI

It is becoming increasingly clear that two parallel AI universes are forming between the United States and China. While the US has produced notable players such as her OpenAI and Anthropic, China has its own emerging candidates. One of these basic model developers, Zhipu AI, announced Today, the company announced that it has raised a total of 2.5 billion yuan ($340 million) so far this year.

Established in 2019, Chipu was Spun out from China’s prestigious Tsinghua University and is led by Tang and Jieprofessor in the university’s Department of Computer Science and Technology.

This announcement came at a sensitive time. This week, the Biden administration imposed additional restrictions on Nvidia AI chip exports to China, further hampering rivals’ ability to train large-scale language models. In anticipation of Washington’s semiconductor ban, China’s deep-pocketed AI companies are stockpiling semiconductors, spending hundreds of millions of dollars on these coveted chips.

To stay in this expensive AI race, Zhipu is keeping itself well-funded by raising money from local investors. The $340 million investment was made from a renminbi-denominated fund, marking a shift from a two-decade trend in which US dollar funds were the preferred funding source until geopolitical tensions created a technology gap.

In August, President Joe Biden signed the agreement. presidential order Excludes U.S. investments in key Chinese technology areas including AI, semiconductors, and quantum computing. Although aimed at curbing China’s military buildup, the order also had a negative impact on China-focused U.S. venture capital, which currently avoids investing in sensitive areas. Some companies, such as Sequoia Capital China and GGV Capital, which were renamed Hongshan, are looking for solutions to continue operating in the market by spinning off their China divisions.

HonShan invested in Zhipu along with other prominent VCs such as Shunwei Capital and Hillhouse Capital, as well as state funds managed by Legend Capital.

The AI ​​startup has also raised funding from an impressive roster of Chinese internet giants, bringing together even its biggest rivals like Alibaba and Tencent, which rarely co-invest. The lineup includes Ant Group, Alibaba, Tencent, Xiaomi, Meituan, Kingsoft, TAL Education Group, and Boss Zhipin.

Zhipu recently open sourced a bilingual (Chinese and English) conversational AI model. Chat GLM-6Bhas been trained with 6 billion parameters and claims to be able to: Run inference on a single consumer graphics card. We also have an open source foundational model, GLM-130B, trained with 130 billion parameters.

Source: techcrunch.com