Why AMI Labs’ Alexandre LeBrun won’t call his AI ‘AGI’ or ‘superintelligence’

As the artificial intelligence industry races toward increasingly ambitious capabilities, terminology has become a point of significant contention among leading researchers and entrepreneurs. Alexandre LeBrun, CEO of AMI Labs—the startup founded by renowned AI researcher Yann LeCun—represents a growing faction of AI leaders who deliberately avoid using terms like "AGI" (Artificial General Intelligence) and "superintelligence" when describing their systems and goals. This stance reflects a broader philosophical disagreement about how the industry should frame its ambitions and measure progress.

LeBrun's dismissal of conventional AI terminology stems from concerns about precision and accuracy in scientific discourse. By refusing to employ terms like "AGI" and "superintelligence," LeBrun emphasizes AMI Labs' focus on developing world models—systems designed to understand and predict patterns in complex environments—rather than chasing vaguely defined concepts. This approach aligns with Yann LeCun's established skepticism toward hyperbolic claims in the AI field.

The terminology debate reflects deeper divisions within the AI community. While some companies and researchers leverage terms like "superintelligence" for marketing purposes or to convey transformative potential, LeBrun argues that such language obscures meaningful scientific progress and introduces unnecessary speculation about capabilities that remain poorly defined.

• Represents a shift toward more rigorous scientific terminology in AI development
• Challenges the widespread use of aspirational framing that may overstate current capabilities
• Emphasizes measurable, technical progress over philosophical concepts
• Reflects tension between AI safety advocates and those prioritizing concrete engineering goals
• Suggests alternative frameworks may emerge for discussing advanced AI systems

LeBrun's linguistic stance carries implications beyond semantics. The choice of terminology shapes investor expectations, regulatory approaches, and public perception of AI development. By rejecting imprecise language, AMI Labs positions itself as a serious research organization focused on engineering problems rather than speculative leaps. This distinction becomes increasingly important as governments and institutions attempt to regulate and understand AI systems. The terminology debate ultimately reflects fundamental disagreements about how the industry should communicate progress, acknowledge uncertainty, and maintain credibility as systems become more capable.