There’s no question that AI is everywhere, with new use cases emerging almost daily, but the endless buzz obscures a far more complex reality. We are entering an AI paradox: although excitement for these new technologies has never been higher, large language models (LLMs) are hitting their limits and are only seeing marginal improvements. This has sparked debate among AI insiders as to whether these tools are “hitting a wall” or if such concerns are overblown. What’s clear is that, at this stage, simply training LLMs with more data…
