The Enduring Power of Specialized Apps in an AI World

Recent tech chatter has been buzzing with predictions about "large models devouring applications" - the idea that powerful general AI might make specialized apps redundant. But Wu Xinhong, CEO of visual tech company Meitu, paints a different picture at their annual meeting.

Swiss Army Knives vs Surgical Tools

Wu offers a clever analogy: "Think of large language models like Swiss Army knives - incredibly versatile but not always the best tool for specific jobs," he explains. "Meanwhile, vertical applications are like surgical instruments - designed to perform one task exceptionally well."

This distinction matters because while general AI can handle broad tasks reasonably well, it often stumbles when precision and deep domain knowledge are required. "Ever tried using a pocketknife's tiny scissors for serious crafting?" Wu asks rhetorically. "That's the limitation we're talking about."

Where General AI Falls Short

The Meitu CEO identifies several areas where specialized apps maintain clear advantages:

• Industry-specific workflows: Standard operating procedures in fields like medicine or engineering require precise understanding that general models lack
• High-precision editing: Tasks demanding pixel-perfect accuracy still need dedicated tools
• Conversational depth: Current chatbots struggle maintaining context in extended professional dialogues

"It's not about raw power," Wu emphasizes. "It's about applying that power surgically where it creates real value."

Meitu's Vertical Vision

The company plans to focus on what Wu calls "the last mile problem" - those specific pain points where users need tailored solutions rather than general capabilities. For Meitu, this means doubling down on their imaging application platform while strategically integrating AI capabilities.

"We're not competing with large models," Wu clarifies. "We're giving them sharper tools to work with."

The strategy reflects broader industry trends where companies increasingly recognize that successful AI implementation requires marrying broad capabilities with deep specialization.

Key Points:

• Specialized apps complement rather than compete with general AI models
• Vertical applications solve specific problems better than jack-of-all-trade solutions
• Industry knowledge and precision workflows remain challenging for general AI
• Meitu focuses on imaging tools that combine AI power with surgical accuracy