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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

encouraging and rewarding) a culture of experimentation across the organization. Know thy data: understand what it is (formats, types, sampling, who, what, when, where, why), encourage the use of data across the enterprise, and enrich your datasets with searchable (semantic and content-based) metadata (labels, annotations, tags).

Strategy 289
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Bringing an AI Product to Market

O'Reilly on Data

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 362
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AI Governance: Break open the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. While the promise of AI isn’t guaranteed and doesn’t always come easy, adoption is no longer a choice.

Metadata 102
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Bring light to the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. While the promise of AI isn’t guaranteed and may not come easy, adoption is no longer a choice.

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Prioritizing AI? Don’t shortchange IT fundamentals

CIO Business Intelligence

The other problem is gen AI tools and users not seeing information that should be included because the metadata tagging and sensitivity labels haven’t been correctly applied to the data. Do you want to have an even more powerful search capability with AI in your data, and to be unsure about how you’ve organized that data?”

IT 143
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What you need to know about product management for AI

O'Reilly on Data

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

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Success Stories: Applications and Benefits of Knowledge Graphs in Financial Services

Ontotext

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. internal metadata, industry ontologies, etc.) names, locations, brands, industry codes, etc.)