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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

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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The early returns on gen AI for software development

CIO Business Intelligence

Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others. The maturity of any development organization can easily be measured in terms of the size and type of investment made in QA,” he says.

Software 128
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Get AI in the hands of your employees

CIO Business Intelligence

We’ve seen an ongoing iteration of experimentation with a number of promising pilots in production,” he says. Samsara employees are applying these general-purpose assistants to a variety of use cases, like writing documentation and job descriptions, debugging code, or writing API endpoints.

KPI 87
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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. Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Only items that have words the user typed match the query.

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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. For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.