I recently came across a post claiming that GPT 5.1 is dumber than its predecessor, GPT 4. The author couldn’t find a single thing that the new version does better. This got me thinking – what’s going on with the latest AI models? Are they really improving, or are we just getting caught up in the hype?
It’s no secret that AI technology is advancing rapidly. New models are being released all the time, each promising to be more powerful and efficient than the last. But is this always the case? It’s possible that in the rush to innovate, some models might actually be taking a step backwards.
So, what could be causing this? Maybe it’s a case of over-complication. As AI models get more complex, they can sometimes lose sight of what made their predecessors great in the first place. It’s like trying to add too many features to a product – eventually, it can become bloated and difficult to use.
On the other hand, it’s also possible that the author of the post just hadn’t found the right use case for GPT 5.1 yet. Maybe there are certain tasks that the new model excels at, but they haven’t been discovered yet.
Either way, it’s an interesting discussion to have. Are AI models always getting better, or are there times when they take a step backwards? What do you think?
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