Part 7/10:
With the increasing complexity of AI applications, many believe that open-source models have the potential to outperform their closed-source counterparts. The reasoning is that open-source models can provide greater transparency, reduced vendor risk, and a more flexible adaptation to changing requirements. This transparency allows organizations to mitigate both operational and financial risks inherent in singular, proprietary solutions.
Moreover, as foundational models come to light, the emphasis on tailored use cases where the flexibility of open-source can shine becomes ever clearer. The flawed assumption has been to concentrate on singular powerful models, ignoring the multiplicity of needs and the predictability required in high-stakes industries such as healthcare or finance.