The New AI Model Paradox: When “Upgrades” Feel Like Downgrades (Claude 3.7)

Author(s): Mandar Karhade, MD. PhD.

Originally published on Towards AI.

The Allure of the New is misleading when the speed of development is too fast!

The tech world buzzes with excitement each time a new Artificial Intelligence (AI) model is unveiled. We’re conditioned to expect these digital brains to be significantly faster, demonstrably smarter, and unequivocally better than their predecessors. Companies fuel this anticipation with announcements of major breakthroughs, showcasing impressive demonstrations that promise to revolutionize how we work, create, and interact. It’s easy to get swept up in this wave of optimism and believe that each new release is a universal leap forward.

But what happens when the shiny new AI, despite all the fanfare and positive press, doesn’t quite live up to the hype for your specific, day-to-day needs? What if, for your particular use case, it feels less like an upgrade and more like an unexpected step backward? This is a situation an increasing number of users are finding themselves in. It’s a phenomenon that prompts a deeper reflection on what “better” truly means in the rapidly evolving landscape of AI and highlights that progress isn’t always a straight line for everyone.

Photo by Milad Fakurian on Unsplash

New AI models often launch accompanied by bold claims of vastly improved capabilities, frequently backed by strong performances on standardized benchmarks. We see statistics showing the AI… Read the full blog for free on Medium.

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Published via Towards AI