AI experts say that AGI will remain out of reach until this major challenge is overcome

In the fascinating field of artificial intelligence, a sobering realization is emerging: Artificial General Intelligence (AGI), the promise of a machine capable of understanding and interacting like a human being, still seems to elude us. Experts agree that without resolving a major challenge related to the very structure of current systems, AGI will never become a tangible reality. Despite rapid advances and impressive technological demonstrations, the real problem lies not in computing power or the size of datasets, but in how these systems are designed. The road to AGI is fraught with obstacles, and deep reflection is more necessary than ever. While AI is progressing at breakneck speed, voices are rising to sound the alarm. Experts believe that access to AGI, or Artificial General Intelligence, remains a distant dream until a fundamental obstacle is overcome. It’s not a question of computing power or data volume, but rather how AI systems are designed and structured. In this article, we’ll explore the implications of these statements and the challenges involved in envisioning a future where AGI could become a reality. The Myth of Raw Power In recent years, AI has permeated our daily lives. From applications to self-driving cars, AI is often perceived as imminent and unavoidable. At NeurIPS 2025, experts made it clear that the idea that ever-increasing computing power will be enough to achieve AGI is a myth. It’s not enough to have cutting-edge GPUs or massive datasets. The fundamental aspect hindering our progress lies in the very structure of the models we build. The Scale Limit and Its Consequences The real challenge here is the scalability limit. We’ve managed to design massive models, but one thing is clear: the marginal gain we receive no longer justifies this colossal investment. Even the most sophisticated systems, like Gemini 3, show structural weaknesses. Instead of creating intelligences capable of replicating human behavior, we’re building machines that can only recognize patterns without deep understanding. It’s like building a skyscraper on sand: the impressive appearance doesn’t hide an unstable foundation.Understanding: A Major Obstacle

Imagine a chatbot that poetically describes an event, like a plate falling, but has no idea why it happened. This gap between performance and understanding is a major obstacle in our quest for AGI. While technologies continue to evolve, they struggle to establish cause-and-effect relationships, a crucial element when it comes to acting autonomously without making unacceptable errors.

Towards avenues of innovation Research is not standing still. Experts are pointing to promising directions such as neurosymbolic architectures and systems adept at integrating causality

. These new avenues are getting closer to human functioning, offering hope of solving the problem of simply imitating behaviors without real understanding. However, it would be wrong to think that these advances aim to make AI more « likeable. » The challenge is significant: it is about making these systems reliable and operational beyond a superficial level.

A call for collective reflection At NeurIPS 2025, we reached a pivotal moment. The consensus seems clear: without a fundamental overhaul of the very model that structures our AI systems, AGI will remain a mere empty promise. The applications we are developing today are undeniably impressive. Nevertheless, let us never forget that appearing intelligent does not equate to being intelligent. Overcoming this obstacle is essential to envisioning a future where AGI is more than just a pipe dream.

The scientific community must now answer this crucial question: what are we prepared to change to prevent AGI from remaining a utopia? The road ahead will be long and fraught with challenges, but the opportunities are immense. Adopting this critical perspective today could lead us to a future where AGI is not just a marketing slogan, but a tangible reality.

To read OpenAI lance enfin l’extension Codex pour Chrome, mais une surprise pourrait freiner son adoption