Enterprise AI fails not because models are weak, but because of corner cases: unpredictable scenarios that break production systems. The real work isn't building AGI. It's making AI reliable enough for business.
Most of the model providers are targeting this elusive goal of AGI, artificial general intelligence, whereas our goal is to really target EGI, enterprise general intelligence, which is much more relevant. The truth is that AI is evolving very fast, so now we can use AI to build content, to generate different type of images, different type of text. When it comes to deploying those models for enterprise, often these models don't achieve the level performance that are critical for those applications. For enterprise, there are so many corner cases, so many situations which are difficult to predict, but this is the hard problem, right? How to ensure that all these corner cases are well handled, all these situations are taken care of?
