Alibaba eyes hiring spree, predicts AI bubble in the US

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Chinese technology giant Alibaba (NASDAQ: BABA) has confirmed plans to increase its staff strength following a high-level meeting with Chinese President Xi Jinping.

Alibaba Group Chairman Joe Tsai and company founder Jack Ma disclosed the plans to embark on a hiring spree after massive job cuts over the last three years. Both executives and key industry technology players met with President Xi to discuss the state of China’s technology development.

At the meeting, Chinese authorities appeared to move from stringent policies threatening Big Tech in Mainland Technology businesses. A wave of government clampdowns saw Alibaba reduce its headcount, and its metaverse and quantum computing departments bore the brunt of the decline.

Going forward, Beijing says it will enable Big Tech firms to grow as they try to keep pace with their U.S.-based counterparts.

“I think we have seen a very clear sign of business entrepreneurs becoming more confident… since President Xi met with private businesses,” said Tsai.

Alibaba executives say it will reboot hiring to fill out its ranks, given fresh assurances from China. Tsai disclosed in an interview that the technology giant had reached the bottom of layoffs while predicting a massive hiring spree of local talent.

“So I think we’ve reached the bottom, and we’re going to start to reboot and rehire,” added Tsai.

Analysts say Alibaba’s hiring spree could see it adopt blockchainmetaverse, and quantum computing units. However, there is consensus that the Chinese-based company will increase the headcount of its artificial intelligence (AI) departments, focusing on the consumer side of things.

Despite the negative government stance toward Big Tech, Alibaba has rolled out its large language model (LLM), Tongyi Qianwen. Furthermore, the firm has launched a text-to-video generator to rival U.S.-based offerings while adding the technology to its e-commerce platforms.

Tsai sees an AI bubble in the US

Although Alibaba plans to shell out nearly $52 billion into its AI objectives over three years, Tsai is alarmed by the figures around AI in the United States. The U.S. AI market is valued at over $300 billion, which Tsai says is a clear indicator of a bubble forming.

“I think in a way, people are investing ahead of the demand that they’re seeing today,” said Tsai.

The launch of the low-cost DeepSeek adversely affected the valuation of U.S.-based AI firms.

China turns to AI to improve agricultural processes

Meanwhile, China’s AI ambition is to be more sustainable, with the government eyeing integration into agriculture.

According to a report, players in the Chinese agriculture sectors are eyeing smart breeding processes powered by AI to revolutionize the food industry. Key sector players converged at the 2025 Seed Congress in Hainan Province to explore AI integration techniques for the sector.

At the Congress, over 40 participants exhibited solutions revolving around AI and other emerging technologies. The exhibitions displayed AI-powered smart breeding solutions and applications, ranging from genetic analysis to yield prediction for farmers.

A key area of focus in the Congress is AI-based genomic analysis, with nearly a third of participants showcasing their variations of the use case. Others portrayed the use of cloud-based systems for data storage and real-time monitoring and phenotyping.

“Understanding the relationship between genes and traits requires computational power and advanced algorithms,” said Qian Qian, a academic at the Chinese Academy of Sciences (CAS).

At the moment, AI-based breeding has demonstrated significant promise, with China National Seed Group recording early wins. A cloud-based monitoring system laced with AI functionalities has improved breeding processes, with the net effect being improved yield.

Furthermore, hybrid rice development is expected to benefit from AI integration in China. While breeders have relied on manually testing combinations to find the best hybrid, AI-powered systems can identify the best seeds in minutes, saving cost and time for researchers.

“We have moved from experience-driven to data-driven breeding,” Li Huihui, deputy director of the National Nanfan Research Institute of the Chinese Academy of Agricultural Sciences, remarked.

Attendees at the Seed Congress saw the launch of a seed-centric large language model (LLM) dubbed Fengdeng, designed to support farmers and researchers across China. With a core knowledge base in genetic engineering native to the Chinese landscape, developers are confident of broad utility.

Rising applications in agriculture

AI application in agriculture is rising rapidly, with a report predicting the market capitalization to soar as high as $10 billion by 2032. While the U.S. and Europe dominate the industry, Southeast Asia and the rest of the Asia Pacific are recording high adoption rates.

Japan has launched an AI-based robot for labor-intensive tasks in the agricultural sector, targeting harvesting use cases. India is joining the race of AI integration in agriculture, while Thailand is proceeding with an AI mobile application to support local farmers.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

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