Sakana AI's CTO: Sick of Transformers in AI Research
Llion Jones, CTO of Sakana AI, calls for a shift away from transformer dependency in AI research, urging for exploration and collaboration to unlock new innovations.

Is the Future of AI Stuck in a Loop?
At the TED AI conference in San Francisco, Llion Jones, CTO of Sakana AI, made a bold statement. He's tired of transformers, the technology he helped create. This technology drives AI models like ChatGPT and Claude. His frustration signals a crucial moment for AI research and innovation.
Jones's critique highlights a problem in the AI field: the focus is too narrow. With all the investment and talent coming in, researchers are sticking to known paths rather than exploring new ones. This could limit creativity and originality.
Why Are Researchers Hesitating to Innovate?
Jones points out two main reasons for this trend. First, the pressure from investors for quick returns. Second, the desire to stand out in a crowded market. This has created a situation where more funding actually means less creativity. Researchers opt for safer projects, fearing competition might get ahead.
- Pressure to Perform: The fear of being outpaced by competitors keeps researchers on familiar ground.
- Lack of Freedom: The once vibrant environment for innovation is now overshadowed by metrics and deadlines.
- Exploration vs. Exploitation: The current trend mirrors the exploration vs. exploitation dilemma, where too little exploration leads to average results.
What Needs to Change?
Jones calls for a significant shift in AI research. He wants to bring back the environment that led to the creation of transformers. This means less pressure and more freedom to explore. Here are his suggestions:
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