Tencent Cloud Casts Doubt on Widespread AI Use in Gaming, Citing High Costs and Early Stage of Development
Liang Chen, the general manager of Tencent Holdings‘s Tencent Cloud internet industry department, has raised concerns about the widespread adoption of artificial intelligence (AI) in the gaming industry. Despite the buzz surrounding generative AI, Chen believes its application in gaming is still in its early stages and faces significant challenges, including high costs and technical limitations.
Key Takeaways:
- AI Hype vs. Reality: Chen believes large-scale application of generative AI in gaming is still some time away, highlighting the potential gap between AI hype and its practical implementation.
- Costly Development: Chen emphasizes the high costs associated with training and developing generative AI models for gaming applications, warning that achieving cost-effective results is a major hurdle.
- Technical Limitations: Chen points to the technical complexity of integrating AI into games, particularly when it comes to ensuring historical accuracy and consistent interaction with virtual characters.
- Industry-Wide Skepticism: Tencent’s cautious stance echoes similar concerns voiced by other industry leaders like Sir Demis Hassabis, co-founder of Google DeepMind, who has warned about the "excessive hype" surrounding AI.
- Limited Real-World Adoption: Despite the market hype, only a small fraction of US companies have integrated generative AI into their production processes, highlighting the technology’s limited practical application. This trend is reflected in the gaming industry as well.
AI’s Potential and its Limitations in Gaming
While Chen acknowledges the potential of AI to revolutionize game development, he also stresses the significant challenges that need to be overcome before it becomes widely adopted. He points out that while AI can be used for pattern recognition and other tasks in game development, integrating generative AI into the gameplay itself presents unique challenges.
For example, training a generative AI model to provide historically accurate answers when a user interacts with a virtual character within a game set several hundred years ago is a complex task. This complexity is further amplified by the need to ensure that the AI responses are consistent with the game’s narrative and world-building.
The Cost Factor
Beyond the technical challenges, Chen highlights the high costs associated with developing and deploying generative AI models for gaming purposes. Training these models requires massive datasets and significant computational power, which can be prohibitively expensive for many game developers.
Chen acknowledges that Tencent is using its in-house developed models, such as the Hunyuan AI model, to address these costs and technical limitations. However, he also points out that the widespread adoption of AI in gaming will require significant advancements in both technology and cost-effectiveness.
The AI Industry’s Reality Check
Tencent Cloud’s cautious stance reflects a broader industry-wide sentiment. While AI has generated significant excitement and investment, there is a growing awareness of the limitations of current technology and the need for real-world applications.
This trend is evident in the recent warnings from industry leaders like Sir Demis Hassabis, who have called for a more nuanced approach to AI hype. Additionally, reports from Goldman Sachs and Wolfe Research highlight the limited practical adoption of AI in various sectors, including gaming.
The concerns expressed by Tencent Cloud and other industry leaders suggest that the AI landscape is entering a phase of "trough of disillusionment." Investors are now demanding tangible results and return on investments, placing greater emphasis on the practical application of AI rather than its theoretical potential.
The Future of AI in Gaming
Despite the challenges, the potential of AI to revolutionize gaming remains undeniable. Recent advancements in generative AI technology have already begun to impact the industry, with companies like Tencent using AI tools for tasks such as 3D rendering and city scene development.
However, the widespread adoption of AI in gaming will require significant technological advancements, cost reduction, and a more nuanced understanding of AI’s limitations. Chen’s comments serve as a reminder that while AI holds immense potential, its practical application in gaming is still evolving and will require careful consideration.
