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Try semantic search with the Amazon OpenSearch Service vector engine

AWS Big Data

For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. Amazon OpenSearch Service has long supported both lexical and vector search, since the introduction of its kNN plugin in 2020. With OpenSearch’s Search Comparison Tool , you can compare the different approaches.

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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. This has serious implications for software testing, versioning, deployment, and other core development processes. AI product estimation strategies.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. This personalized approach might lead to more effective therapies with fewer side effects.

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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

This can include comparing lexical search, semantic search, and hybrid search techniques to understand the benefits of each technique against your corpus, or adjustments such as field weighting and different stemming or lemmatization strategies. This functionality was initially released as experimental in OpenSearch Service version 2.4,

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Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

Speaking of the Four Seasons, consider how sad their nudging strategy is vs. the one that booking.com has on display: All the data you need for this nudge… You already have. That’s what makes the Four Seasons strategy, and that of most sites, so heartbreaking. Money will start falling from the sky. Please find it, please use it.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

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The DataOps Vendor Landscape, 2021

DataKitchen

Testing and Data Observability. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Testing and Data Observability. Production Monitoring and Development Testing.

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