Tools like Google NotebookLM and custom generative AI services are fundamentally changing how users interact with information. We're seeing a transition from static reports and interfaces to dynamic chat-based tools that give users exactly what they need, and even things they didn't know they needed.
If you're not familiar with NotebookLM, it's a tool that allows you to provide your own documents (like PDF, text files, audio), and then chat with the data. You can even listen to an AI-generated podcast that explains all the information. For example, I had loaded a project with PDF documents containing the rule book, technical rules, and officials briefing information for USA Swimming, and was then able to get answers to questions like "how is a breaststroke turn judged?"
It was kinda magical.
We've been working with clients on permutations of this scenario for some time. For example, we partnered with a client in the life sciences space to build a chat-based tool that connects various third party API services with disparate information, providing account managers with a single source for helping their customers recommend products and services to ensure better health outcomes.
This is no small feat when the goal is a best-of-breed user experience (UX) like ChatGPT. It can involve multiple service providers like Microsoft Azure and Amazon Web Services, as well as various tools like cloud-based large language models (LLM), vector search, speech services, cloud storage, charting tools, location services, AI telemetry, and more. But when it's done right, the result is amazing. You can ask questions that span disciplines and contexts and see results you may not have ever seen before.
Most organizations can really benefit from exploring how generative AI can positively impact their offerings and give them a competitive advantage. Like we always say, it's not about the organizations that use AI, it's about the ones that don't.
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