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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 361
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Expectations vs. reality: A real-world check on generative AI

CIO Business Intelligence

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. What are you measuring?

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Try semantic search with the Amazon OpenSearch Service vector engine

AWS Big Data

Lexical search looks for words in the documents that appear in the queries. Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. OpenSearch Service supports a variety of search and relevance ranking techniques.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

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Assembly required: 8 myths about knowledge management debunked

CIO Business Intelligence

Another study used smartphone geolocation data to measure face-to-face interactions among workers at various Silicon Valley firms. The study documents “substantial returns to face-to-face meetings … (and) returns to serendipity.” As a means of control, budgets measure performance against planned targets, influencing employee behavior.

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AI Product Management After Deployment

O'Reilly on Data

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.