An Infobae video asks whether AI will surpass us: the question matters more than the quick answer

By Infobae · July 16, 2026. The video in question, part of the series 'La Fórmula' with Alan Daitch, poses a direct headline: can artificial intelligence become smarter than humans? It is a legitimate and timely question, but the content we have had access to does not include the transcript or quotes from the interviewee, only site navigation metadata. Since we do not have the specific arguments laid out in the clip, we are not going to attribute to Daitch claims we cannot verify.

What we can do is place the question in context. The debate over whether AI will "surpass" human intelligence has for years conflated two distinct things: demonstrated capability on specific tasks (where models already outperform most humans in calculation speed, information synthesis or code generation) and the more diffuse notion of "general intelligence" or consciousness, which remains speculative territory. At Zendoric we have been insisting on that distinction when analyzing benchmarks: a system can master a saturated task without that implying reasoning equivalent to a human's in the broad sense.

Our reading is that the short, mass-outreach video format —like that of this Infobae series— serves a valuable function by bringing these questions to general audiences, but it rarely offers the level of nuance needed to separate AI labs' marketing from the hard data. Questions like 'can AI become smarter than us?' are usually better answered by looking at capability trajectories in specific domains —mathematical reasoning, programming, medical diagnosis— than by seeking a binary verdict on superintelligence.

If we connect this to the underlying thesis we hold at Zendoric: in the short term, public conversation will keep swinging between the fear of an AI that "surpasses" us and the skepticism of those who see only glorified autocomplete. That tension is healthy and necessary as long as it remains unresolved by evidence. But the horizon that seems most likely to us is not one of a machine that replaces us in a race of general intelligence, but of systems increasingly capable at specific tasks —diagnosis, biomedical research, materials design— that, well governed, accelerate the eradication of diseases and broaden access to resources that are scarce today. The question that titles this video is the right one; the serious answer requires looking at concrete data, not studio reactions.