Google's core leadership team gathered in India, where they addressed market concerns over massive capital expenditures, disclosed key business metrics, and compared the current AI wave to an "industrial revolution moving ten times faster."

On February 18th, at an AI summit held in India, Alphabet CEO Sundar Pichai, Google DeepMind CEO Demis Hassabis, and Google Senior Vice President James Manyika made a rare joint appearance.

Responding to market skepticism about AI investment returns and fears of an "AI bubble," the Google executives provided detailed explanations across three dimensions: the technology evolution cycle, commercial data validation, and future macroeconomic impact. During the dialogue, Pichai revealed that the backlog for Google's cloud business has doubled year-over-year, reaching $240 billion.

Addressing the "elephant in the room," Pichai stated this is not a bubble but new infrastructure. As tech giants ramp up capital spending on AI infrastructure, Wall Street's anxiety about cost recovery periods is growing. When asked how CEOs justify these costs to their boards, Pichai directly compared the current AI moment to major historical infrastructure cycles.

"In some contexts, people talk about this as an industrial revolution, but one that is ten times faster and ten times larger," Pichai said.

He analogized current AI investments to the US railway system or the national highway system, describing them as highly leveraged investments capable of driving immense growth and value. To support this view, Pichai highlighted a core data point: "Just for the cloud business in the past year, the backlog has doubled year-over-year to $240 billion. This indicates the potential for returns on the other side. Therefore, we are investing to meet this demand."

For Google, this investment serves not only the cloud business but also permeates emerging areas like Search, YouTube, Waymo, and Isomorphic Labs. Pichai emphasized that given the technological progress and visible opportunities, "these investments are justified."

On the timeline for Artificial General Intelligence (AGI), DeepMind's Hassabis provided a cautious forecast. He set a high bar for AGI, requiring a system to demonstrate all human cognitive abilities, including creativity, long-term planning, and better memory utilization. He admitted that while today's systems are impressive, they have not yet reached that level.

"I think we still have a way to go, at least another 5 to 10 years," Hassabis stated.

He views AGI as the ultimate tool for accelerating scientific discovery and shared updates on AlphaFold, noting it is now used by over 3 million researchers globally, including over 200,000 scientists in India alone using AI for biological exploration.

Regarding employment and the economy, James Manyika proposed analyzing "tasks" separately from "jobs" when considering AI's impact. Manyika pointed out that "most jobs are composed of different tasks... some occupations may decline, many will grow, and many more will change."

He highlighted the "lag effect" in technological change, where a time gap exists between the disappearance of old jobs and the creation of new ones. For small and medium-sized enterprises (SMEs), Manyika believes AI is the first technology that can fundamentally grant "superpowers" to small businesses. Through initiatives like "Project Vani," Google is working to break down language barriers, allowing SME owners to build technology systems via voice commands without needing to be technical experts.

Discussing regional strategy, Pichai described a significant shift in India's positioning. He no longer sees India merely as a vast user market but defines it as a "full-stack player" in the AI field.

"I see Google as a full-stack company. I think India will obviously become a full-stack player in AI as well," Pichai said.

He reflected on the "Digital India" transformation over the past decade, suggesting this is the beginning of a "decade-long AI transformation." From Bangalore's vibrant developer ecosystem to the construction of local AI models, Google sees potential for India to comprehensively excel across AI infrastructure, the application layer, and the innovation layer.