From Artificial Problems to Real Solutions: Dr. Wang on AI’s Evolution and China’s Innovation Landscape
Dr. Wang has witnessed artificial intelligence transform from academic curiosity to practical necessity. His journey from studying AI in the 1980s to building Alibaba Cloud reveals how technology evolves when it addresses real problems rather than artificial ones.
The Shift from Toy Problems to Real Solutions
In the early 1980s, AI researchers tackled “toy problems” - artificial challenges that demonstrated concepts but solved nothing meaningful. The technology remained shaky, the applications limited.
Today’s AI addresses genuine problems. The technology has matured enough to handle real-world challenges that matter to businesses and users. This shift from artificial problems to practical solutions marks AI’s true evolution.
Computing Power Changes How We Think
Massive increases in computing power don’t just make things faster - they fundamentally change our approach to problems. Dr. Wang uses transportation as an analogy: a bicycle limits you to local travel, a car opens regional possibilities, an airplane enables global reach, and a rocket transforms space exploration.
Similarly, when computing power increases by millions of times, you don’t just do the same tasks faster. You rethink what’s possible entirely.
China’s AI Landscape: Competition Drives Innovation
China’s AI ecosystem thrives on rapid iteration and intense competition. Multiple companies - DeepSeek, Moonshot AI, Alibaba - push each other forward through collective advancement rather than individual dominance.
This competitive environment serves as a testing ground for new technologies. China’s market doesn’t just consume AI products; it helps mature them through real-world deployment and feedback.
The startup mindset flourishes particularly in cities like Hangzhou, where reportedly one in five people runs their own company. This entrepreneurial density creates natural experimentation with AI applications.
The Real Challenge: Creativity, Not Computing Power
Building successful AI applications today faces one primary bottleneck: creativity in application development. Foundation models from companies like OpenAI and DeepSeek already exceed human capabilities in many areas.
The challenge isn’t computing power or model quality - it’s finding creative people who can build meaningful applications beyond chatbots. Most developers remain constrained by ChatGPT’s success, limiting their vision to similar conversational interfaces.
Building Alibaba Cloud: Technology-First Business
Creating Alibaba Cloud required convincing skeptics that cloud computing represented a fundamental shift, not just another internet business. Unlike traditional businesses that use technology as support, cloud computing puts technology first.
Dr. Wang started without writing a single business proposal, believing innovation happens through experimentation rather than planning. The key insight: only 1% of technologies become viable businesses, but cloud computing promised longevity comparable to electricity - a 50-100 year opportunity.
The timing proved fortunate. China’s internet boom provided the perfect environment for cloud services, even though few understood what cloud computing meant initially.
Talent Strategy: Look Beyond the Obvious
Silicon Valley’s approach of paying hundreds of millions for proven talent misses opportunities. When everyone recognizes certain skills as valuable, those talents become expensive and may not drive true innovation.
Real innovation comes from identifying capabilities others overlook. The most valuable talent often works on technologies nobody understands yet - making them available and affordable for visionary companies.
The Marathon Perspective
AI development resembles a marathon, not a sprint. No single organization can maintain breakneck pace indefinitely, but collective competition drives continuous advancement.
Current advantages rarely create permanent barriers. The field moves too quickly for any company to establish unassailable leads. This creates exciting opportunities for newcomers who can identify overlooked approaches or applications.
Next Steps
Focus on creative application development rather than competing on model capabilities. Look for real problems that existing AI can solve but nobody has addressed yet. Consider China’s market as a testing ground for rapid iteration and feedback.
The transformation from artificial problems to real solutions continues. The companies that thrive will be those that identify genuine needs and apply mature AI technology creatively to address them.