Umesh Sachdev is CEO & co-founder of Uniphore, a large AI-native, multimodal enterprise-class SaaS company. He's based in Palo Alto, CA. Read Umesh Sachdev's full executive profile here.
In today's rapidly evolving digital landscape, the role of artificial intelligence in reshaping enterprise tech stacks cannot be overstated. As businesses strive for competitive advantage, they increasingly recognize the transformative potential of integrating AI across every layer of their operations.
This transformation is happening in real time. As I've traveled around the world meeting with CEOs and CIOs of some of the largest companies, the conversations around AI have evolved from understanding the basics of the technology to understanding how they can maximize the value of the technology for their organization. That means reimagining the tech stack.
At the foundation of this reimagined tech stack is data. An organization's data lake is where all data is gathered—no matter where it's from or in what form —before it's prepared for AI models. Knowing where your data is, its quality, its lineage and the ability to capture it is the lifeblood of the modern AI stack.However, data alone holds limited value without the ability to extract meaningful insights and knowledge.
It's my view that enterprises should have a choice when it comes to model building and should consider multiple large language models in various sizes based on the use cases and opportunities they are looking to address.
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