Chinese artificial intelligence start-up DeepSeek reemerged in the public eye on Friday, delivering a rare glimpse into the ambitions and ethical considerations guiding one of China’s most secretive AI labs.

At the World Internet Conference in Wuzhen, reported by SCMP, senior researcher Chen Deli reaffirmed the company’s commitment to developing artificial general intelligence (AGI) — while acknowledging the technology’s potentially “dangerous” societal impact.

Speaking on a panel alongside the heads of five other companies collectively known as China’s “six little dragons” of AI, Chen emphasized both optimism about AI’s technical possibilities and concern for its disruptive social consequences.

“Humans will be completely freed from work in the end, which might sound good but will actually shake society to its core,” he said, urging AI firms to act as “whistle-blowers” to warn the public about which professions will be automated first.

The Wuzhen appearance marked DeepSeek’s second recent public engagement. Earlier, Wu Shaoqing, the company’s head of AI governance, participated in a panel on ethical AI guardrails at the Global Open-Source Innovation Meetup in Hangzhou. DeepSeek, spun out from quantitative hedge fund High-Flyer in 2023, has maintained a low profile, with founder Liang Wenfeng largely absent from public view since meeting President Xi Jinping in February.

Chen described the current phase of AI development as a “honeymoon phase” between humans and machines, warning that most jobs could eventually be automated.

The pursuit of AGI and China’s industrial focus

Founded with the explicit mission of building AGI — a system capable of human-level cognitive reasoning — DeepSeek prioritizes long-term research over short-term commercial applications. Chen highlighted that the firm avoids following transient market trends, a strategy he said was essential for tackling the technical and ethical challenges inherent to AGI.

Nevertheless, Chen acknowledged that such systems could be dangerous, echoing the concerns of hundreds of AI experts worldwide who signed an open letter last month calling for a temporary moratorium on superintelligent AI until there is a broad public consensus and safety verification. Chinese signatories include Zhipu AI CEO Zhang Peng and Tsinghua University professor Andrew Yao, signaling that caution is not absent from China’s own AI research community.

Despite these warnings, Chen argued that halting AI development is unrealistic given the sector’s profit incentives.

“You could even say the mark of success for this AI revolution is that it replaces the vast majority of human jobs,” he said.

The comments reflect a rare frankness in China’s AI discourse, where the potential risks of automation and societal disruption are typically muted in public statements.

Other Chinese firms are also accelerating efforts in advanced AI. Zhipu AI and Alibaba Group, whose CEO Eddie Wu Yongming announced a “super AI cloud” at the same conference, are developing computing infrastructure capable of handling the massive workloads needed for AGI. These companies, along with DeepSeek and others in the “six little dragons” cohort, are central to China’s push for technological leadership amid U.S. export restrictions on advanced AI chips.

China’s AI governance framework

China has rapidly established a structured approach to AI governance, combining state oversight, industry self-regulation, and ethical guidelines. Unlike the U.S., where regulation is largely reactive and sector-specific, and the EU, which enforces preemptive rules through frameworks like the AI Act, China’s approach blends top-down direction with incentive-driven innovation:

• State Planning and Strategic Directives: The government defines AI development as a strategic priority. Policy documents such as the New Generation Artificial Intelligence Development Plan (2017) and the 2023 Guidelines for Responsible AI set out long-term objectives, including leadership in foundational models, industrial AI, and ethics.
• Ethical Guidelines and Risk Management: China has issued standards emphasizing security, fairness, privacy, and controllability of AI systems. Firms are expected to conduct risk assessments, but enforcement remains flexible, relying on a combination of industry self-regulation and government audits.
• Integration with Industrial Policy: AI development is closely linked to national initiatives such as Made in China 2025 and semiconductor self-sufficiency programs. Companies like DeepSeek are expected to align their research with broader industrial goals, including AI chips, cloud infrastructure, and applications in defense and finance.

In contrast, the U.S. has largely relied on a market-driven, reactive regulatory framework, focusing on sector-specific guidance rather than holistic rules. Agencies like the FTC, NIST, and SEC have issued principles on fairness, transparency, and risk management, but there is no comprehensive federal law governing AI safety or AGI development.

The EU, on the other hand, has pursued a precautionary model through the AI Act, which categorizes AI systems by risk level and imposes strict rules on high-risk applications, including mandatory documentation, auditing, and human oversight. The European approach emphasizes public trust and safety before adoption, reflecting a regulatory culture that prioritizes societal consensus over market speed.

China’s regulatory stance — permissive in pursuit of global leadership, yet increasingly codified in ethical standards — creates a unique environment for AGI research. It balances technological ambition, industrial strategy, and social stability, whereas the U.S. encourages rapid innovation with limited preemptive oversight, and the EU prioritizes caution and accountability over speed.

Chen’s warnings, set against this backdrop, illustrate the duality of China’s AI strategy: a race for global leadership in next-generation intelligence, coupled with acknowledgment of potential societal disruption.

“It would not be alarmist to consider such systems dangerous to society,” he said — a rare admission for a lab building toward that very frontier.

A quiet financial current is sweeping from Tokyo to Europe, reshaping how global venture capital is distributed. Huge swathes of cash are now flowing from Japan into European tech startups, as risk-averse Japanese investors seek a more mature entrepreneurial ecosystem.

While Europe’s startup and venture capital scene long operated under the long shadow of Silicon Valley, some analysts believe the continent has matured. Its combination of strong industrial heritage, government-backed innovation programs, and corporate discipline is drawing in capital from Japan’s conglomerates and funds looking for stable but high-tech growth opportunities.

According to a report by venture capital firm NordicNinja and data platform Dealroom, Japanese corporates and venture capital funds with Japanese limited partners have taken part in European financing rounds worth over €33 billion ($38 billion) since 2019, when the EU-Japan Economic Partnership Agreement came into effect. The figure dwarfs the €5.3 billion recorded in the five years before the deal — a sixfold jump that signals a strategic realignment.

Before that agreement, “there was no Japanese capital other than SoftBank,” said Tomosaku Sohara, co-founder and managing partner of NordicNinja. His firm, which manages €250 million in assets, is itself a bridge between Tokyo and Europe, formed through a collaboration between its partners and JBIC IG Partners, an investment arm of the Japan Bank for International Cooperation.

“SoftBank was pretty active already at that moment because they had acquired Finnish gaming company Supercell,” Sohara told CNBC, noting that the move breathed life into Finland’s early-stage startup ecosystem.

That deal, back in 2016, marked one of the first major Japanese bets on Europe’s innovation scene.

Since then, a wider cast of Japanese giants — including Mitsubishi, Sanden, Yamato Holdings, and Marunouchi Innovation Partners — have quietly stepped in to back European startups directly. Meanwhile, Japan-linked VC funds such as NordicNinja, ByFounders, and Toyota’s Woven Capital are signing checks for European ventures across the continent.

Part of the appeal is scale. Europe now hosts more than twice as many VC-backed startups per capita as Japan and 4.3 times more unicorns, according to the same report.

Silicon Valley’s shadow gives way to a cultural fit

Japan’s appetite for tech investment has never been in doubt — but its earlier focus leaned heavily toward the U.S. In the early 2000s, Japanese conglomerates raced to set up corporate venture capital arms in Silicon Valley, hoping to tap into the next Google or Facebook.

But that bet came with limits. “Nobody wanted to look at Europe at that moment,” Sohara recalled. “After a couple of years they realized, ‘Hey, maybe the U.S. culture is totally different from the Japanese culture,’ and they began thinking, ‘Maybe we need to look at another region like Europe.’”

The difference, he said, lies in mindset. European founders often emerge from large corporates — veterans of Nokia, Ericsson, Airbus, or Skype — who combine industrial experience with entrepreneurial drive. That profile resonates with Japan’s business culture, where long-term planning and engineering rigor are prized but the raw entrepreneurial spirit is harder to find.

“They have experience at the corporates and also they have a mindset of entrepreneurship,” Sohara said. “Japan, unfortunately, is lacking the entrepreneurship mindset.”

The deep tech magnet

For Japanese investors, Europe’s strongest pull lies in deep tech — companies rooted in scientific and engineering breakthroughs rather than consumer-facing apps. These are firms working on artificial intelligence, quantum computing, autonomous systems, clean energy, and defense technologies.

Deep tech and AI together accounted for 70% of Japanese-linked investment deals in Europe in 2024, mirroring global trends where governments and investors alike are betting on technologies with long-term strategic importance.

Among the top-funded startups with Japanese participation this year are:

• Wayve, the U.K. autonomous vehicle startup that raised $1.05 billion in May 2024, backed by SoftBank.
• Quantinuum, a British quantum computing firm that secured €273 million in January 2024, with Mitsui among investors.
• Multiverse Computing, a Spanish quantum company that landed €189 million in June 2025 from Toshiba and others.

These are bets on science-heavy ventures that typically require not only patient capital but also deep industrial knowledge — both of which Japanese investors bring in abundance.

Yet this surge in funding also highlights Europe’s lingering weakness: scaling such companies into global leaders. While the continent produces plenty of world-class engineering talent and research, its venture ecosystem remains thinner than America’s when it comes to late-stage capital and exits.

Deep tech firms are said to require a lot of growth capital and industrial experience to scale successfully — two elements that Europe famously lacks.

For Japan, this new focus on Europe marks more than just diversification. With an aging population and a risk-averse domestic market, Japanese corporates are under pressure to find growth beyond their borders. Europe, with its tightening ties through the EU-Japan trade agreement and its emphasis on technology sovereignty, offers a natural match.

In many ways, these investments reflect Japan’s own industrial philosophy — slow, methodical, long-term. Europe’s blend of academic excellence and public-private collaboration has become a mirror for that ethos, contrasting sharply with Silicon Valley’s rapid-fire, disruption-first culture.

Uber Technologies is broadening its scope far beyond rides and deliveries, with CEO Dara Khosrowshahi declaring that the company is transforming into a global “platform for work.”

The company’s newest ambition is to connect its millions of app users with digital tasks — including jobs training, and artificial intelligence — as part of a strategic shift toward diversifying income opportunities in an era of automation.

Speaking during Uber’s third-quarter earnings call on Tuesday, Khosrowshahi said the company’s platform is no longer just a marketplace for rides or food orders.

“Another way of looking at our platform is that we’re a platform for work,” he said. “Besides transportation, we can empower other kinds of work as well.”

Last month, Uber launched a pilot program in the United States allowing users to complete short-term gigs that involve training AI systems. The initiative, called Digital Tasks, was first tested in India and involves labeling video footage, annotating images, or refining AI voice responses. The company said such tasks are designed to be simple enough for existing Uber drivers or couriers to perform using the same app they use for rides or deliveries.

Khosrowshahi described the effort as a “natural extension” of Uber’s core business. “Digital Tasks represent a potential answer for drivers who might be displaced by robotaxis in the future,” he said, adding that the initiative could help mitigate job losses as automation becomes more prevalent in the transport industry.

Uber, alongside rivals like Waymo and Tesla, has invested heavily in autonomous vehicle research, which many analysts believe could eventually reduce the need for human drivers. That looming shift has prompted Khosrowshahi to position Uber as a bridge between today’s gig economy and the AI-driven workforce of tomorrow.

Some of Uber’s digital tasks, however, require more advanced skills than driving or delivery. “Some of the roles require PhDs, for example, in physics, in order to get the gig done,” Khosrowshahi said. “The pay for such gigs is higher than for Uber drivers.”

The move is seen as part of Uber’s broader plan to secure relevance in a rapidly changing labor market dominated by AI and automation. Tech firms such as Amazon Mechanical Turk and Scale AI have long offered similar micro-tasking opportunities to train AI systems, but Uber’s vast user base could give it a unique advantage in scale and accessibility.

The AI training market has grown substantially in recent years, with global demand for data labeling projected to exceed $8 billion by 2030, according to Grand View Research. For Uber, this creates a new revenue stream while leveraging its existing platform and logistics network to connect workers with digital opportunities.

Khosrowshahi emphasized that the digital task business is still in its infancy but could grow to become a major revenue driver, just as Uber Eats evolved from an experimental feature into a global delivery powerhouse.

“We think this can ultimately be another profitable line of business for us,” he said. “We’re already landing a ton of customers that need people to train AI for them.”

Given the growing competition and potential threat posed by robotaxi rollouts to its core ride-hailing business, Uber’s pivot into AI-related work is seen as a strategic repositioning — especially as the future of the tech economy seems to be tied to AI. Although it’s a gamble that its pay remains uncertain, Uber appears intent on ensuring it has a place in the future of work — even if that future is powered by the same technology that could one day replace many of its drivers.