Remove Document Remove Experimentation Remove Metadata Remove Testing
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Since ChatGPT is built from large language models that are trained against massive data sets (mostly business documents, internal text repositories, and similar resources) within your organization, consequently attention must be given to the stability, accessibility, and reliability of those resources. Test early and often.

Strategy 289
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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Without clarity in metrics, it’s impossible to do meaningful experimentation. Ongoing monitoring of critical metrics is yet another form of experimentation.

Marketing 362
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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. 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.

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What’s new with Amazon MWAA support for Apache Airflow version 2.4.3

AWS Big Data

Test the feature To test this feature, run the producer DAG. Removal of experimental Smart Sensors. For detailed release documentation with sample code, visit the Apache Airflow v2.4.0 How dynamic task mapping works Let’s see an example using the reference code available in the Airflow documentation. Airflow v2.4.0

Testing 100
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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

Data Collection The AIgent leverages book synopses and book metadata. To my knowledge, the most extensive repository of synopses and metadata is Goodreads. To collect these genre tags and other metadata, I took advantage of the well-documented Goodreads API. features) and metadata (i.e. In other words, if 0.1%

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

Occam's Razor

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature. If you have access to existing data, take some time to document what the current performance looks like. Identify, hypothesize, test, react. But it is not routine.

Metrics 156
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How the DataRobot AI Platform Is Delivering Value-Driven AI

DataRobot Blog

This means they need the tools that can help with testing and documenting the model, automation across the entire pipeline and they need to be able to seamlessly integrate the model into business critical applications or workflows. Assured Compliance and Governance – DataRobot has always been strong on ensuring governance.