🔍 Vector search alone is not sufficient for effective knowledge management.
🤖 Generative AI tools like chat bots lack context and integration with the organization.
📚 The video offers insights from various disciplines to help become a transdisciplinary AI product design manager and strategist.
📚 Data ontologies are important for understanding the nature of data.
🔎 Reconciliation and validation are crucial for dealing with data from different sources.
🔬 Factual grounding is essential in language technology to provide a baseline of facts.
🔍 Having a single source of truth is important for authentication and access control.
🌐 Identifying sources of truth for different types of data establishes reliability and validity.
📚 Creating data taxonomies and classification systems improves searchability and accessibility.
🔑 Different taxonomical systems, such as the Dewey Decimal System and the Library of Congress, allow for the classification of information.
🗂️ Metadata and data curation are essential in managing and organizing data, including version control and expiration dates.
🔧 Generative AI is a new tool that can automate data processing and provide more options for data transformation.
🔍 Information foraging refers to the process of seeking and gathering information to fulfill an information need.
💡 Implementing a data-centric model is crucial for effective knowledge management in organizations.
📚 Treating everything in a company as an information need can change the orientation to business and improve outcomes.
💡 Data-centric approach with generative AI can enhance business by understanding the importance of information.
🔍 Four fundamental search strategies: vector search, information foraging, shrinking transformations, and expanding transformations.
💡 Vector search is primarily used for clustering similar documents based on their semantic similarity.
🔍 Knowledge graphs are a combination of relational databases and web-like structures that contain semantic links between different pages.
🔖 Metadata filtering allows for the filtering of search results based on specific metadata criteria.
📚 Indexes or table of contents can be used to efficiently navigate and fetch specific documents.
⚙️ Implementing a gated process can improve practical implementation of AI systems.
🔍 The first step in addressing any information need is the information query, where the validity and appropriateness of the question are judged.
📚 After obtaining a legitimate information query, the next step is to distill, extract, and utilize the relevant information to solve the problem.
🏭 Treating business processes as assembly lines, with inputs, stations, interfaces, and outputs, can lead to better automation and efficient workflows.
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