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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. It might suggest a restaurant based on preferences and current popularity.

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Data – the Octane Accelerating Intelligent Connected Vehicles

Cloudera

As advanced use cases, like advanced driver assistance systems featuring lane change departure detection, advanced vehicle diagnostics, or predictive maintenance move forward, the existing infrastructure of the connected car is being stressed. billion in 2019, and is projected to reach $225.16 billion by 2027, registering a CAGR of 17.1%

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The most valuable AI use cases for business

IBM Big Data Hub

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

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Optimizing energy production with the latest smart grid technologies

IBM Big Data Hub

Smart grids turn this model on its head. To manage, analyze and interpret this data, utilities rely on advanced software and analytics tools. This software, and the insights it provides, can help providers predict demand patterns, identify potential issues and optimize the distribution network.

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AI Product Management After Deployment

O'Reilly on Data

In traditional software engineering, precedent has been established for the transition of responsibility from development teams to maintenance, user operations, and site reliability teams. In contrast, many production AI systems rely on feedback loops that require the same technical skills used during initial development.

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Understanding the different types and kinds of Artificial Intelligence

IBM Big Data Hub

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. The three kinds of AI based on capabilities 1. Any other form of AI is theoretical.