The larger question is how old character AI remains relevant as the industry marches forward so quickly. Still, the fact remains that these models still have a lot of inherent value. With customer service automation, for example, AI models as old as 2018 are still able to provide strong results, and companies such as X.ai have realized upwards of a 25% efficiency gain. But then that begs the question: are the more modern gears really all that great?
New data reports show that, despite much faster performance from newer AI models, the median response time of an old model is pretty darn close to these ranges (anywhere from 0.2–0.5 seconds). In user experience this difference is generally inconsequential, especially for simple interactions that do not leverage the processing power of new models.
On the other hand, think about IBM Watson which first flourished in 2011. Despite being over a decade and a half old by now, it is still used in healthcare and business solutions today, showing that older AI technologies are not necessarily defunct the moment newer ones appear. Another is the emphasis on cost-efficiency. While it costs millions to develop and train new AI models, upkeep of existing models is often only a tiny fraction of funds for innovation.
AI is far more dangerous than nukes, Tesla CEO Elon Musk once said – that's how powerful any AI could be. Sure, the old character ai may not be shiny new tech, but it's still a solid tool in user experience design particularly for engaging with users/customers or even learning.
In practice, a lot of companies run composite workloads that use both old and new AI to compromise on price and performance. For example, basic chatbots or simple userinterfaces often still run legacy models on the edge Cases — where precision and deep learning are not mission critical. This pragmatic approach is what enables businesses to keep up with the competition without having to invest in bleeding-edge tech that may not pan out.
This means from a function, cost and efficiency perspective existing character AI is still used in a lot of places today. While not the most groundbreaking implementation of new character AI at this point, it does remain one of the key roles played out in numerous industries to date.