The world is being driven on data, with generative AI unlocking new capabilities for organizations to harness that data, understand it and the context behind it. Yet generative AI is not just about technology, but it’s a cultural social shift with how we interact with technology and realize its benefits. With generative AI being touted as the next web moment, it is not yet clear what the future holds for it.
In this episode of TFiR: Let’s Talk About AI, Juan Sequeda, Principal Scientist and Head of AI Lab at data.world, talks about the evolution of data both from a technology point of view and a cultural one. He goes on to discuss how data.world is helping organizations unlock the value of their data and the role of AI.
Key highlights from this video interview:
- Sequeda talks about his background in data and AI. He goes on to give us an overview of the company, an enterprise data catalog platform, and how they help enterprises organize their data so they can be API ready. He talks about the three applications they focus on: search and discovery, governance, and DataOps or data lineage.
- There are three principles with data — moving data, storing compute data, and using it, and while the principles have stayed the same there have been evolutions of data to today where we have generative AI. Sequeda discusses how metadata is being moved to the forefront now with the prominence of AI and its role at proving more context.
- Sequeda believes we need to think of being in a data- or knowledge-first world rather than a data-driven one. He discusses this social technical paradigm shift and the trend of wanting to combine generative AI with knowledge graphs that represent the key context of organizations.
- Sequeda breaks down what a knowledge graph is saying — it is a representation of the real world concepts and relationships you have in the form of a graph. He discusses relational databases and the pros and cons of what they can offer and why knowledge graphs take this to a new level.
- Sequeda goes into detail about data.world’s three core applications and how they help customers deal with data. He goes on to discuss how their customers are using the platform to create new applications, such as creating an app around operational excellence or bringing in organizational charts into the data in data.world.
- We are seeing new roles emerge in data such as in product management in data or what Sequeda calls “Knowledge engineer 2.0”. He discusses the people changes he is seeing within organizations and how these roles are helping businesses understand and solve problems and unlocking value from the businesses data.
- More employees are getting involved in their organization’s data and Sequeda discusses how data.world is acting as a catalyst for adoption of data catalogs. He talks about the importance of getting employees involved in using the data and how this is driving change.
- Generative AI is another web moment ushering in a change in humanity, according to Sequeda, who feels that if you are not using generative AI you are going to stay behind. He discusses some of the latest studies on AI and their findings on the benefits such as productivity and economical benefits.
- Sequeda talks about the three challenges for organizations using generative AI: hallucinations since they do not know the facts of the organization, lack of trust as they cannot give you explanation but it could also be hallucinating, and a lack of governance.
- Sequeda discusses their work in the AI lab at data.world focusing on accuracy and how knowledge graphs can provide higher accuracy of LLMs to answer natural language questions.
- AI, particularly generative AI, is causing a lot of fear and Sequeda discusses if these fears are warranted. He likens the evolution of the AI to the web and discusses its journey and how regulation has come into play. Sequeda feels optimistic about the future of AI and talks about how organizations need to start if they want to be successful with it.
This summary was written by Emily Nicholls.