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What does Data Feature mean?

Common activities related to data hygiene include checking for accuracy, ensuring formats are the same in each dataset (such as the format for date & time), determining or creating a unique identifier (such as an email address or phone number, which allows

What does Conversational AI mean?

"The conversational AI field has reached an inflection point as the size and accuracy of LLMs like GPT have become sufficient (and sufficiently accessible) to allow everyday productivity improvements.". Overview. How to Think About. Conversational AI.

What does Code Assistant (or AI Code Assistant) mean?

A tool that allows users (such as software developers) to generate some or all of the code needed to make a program work, increasing the accuracy and velocity of coding efforts. OpenAI's Codex and Github's Copilot are two examples of code assistants.

What does Red Team mean?

Humans who deliberately attempt to trick or negatively influence a machine system to increase its quality, accuracy, security, or consistency.

What does Synthetic Data mean?

Synthetic data use is intended to reduce bias, quickly train models, and improve accuracy.

What does Graph Retrieval-Augmented Generation (Graph RAG) mean?

"In order to make sure answers relevant to users, based in the articles our newspaper had actually written, and accurate, we chose a Graph RAG model for our 'fact-checker bot.'". Overview.

Causeit Guide to Digital Fluency

Accuracy of Materials. The materials appearing on our website are not comprehensive and are for general information purposes only.

Introduction to Machines That Learn | Machines That Learn Guidebook

In the medical diagnosis example from before, the accuracy of that system is limited to what it already 'knows.'

Analyze | Data Supply Chain Guidebook

In the past, such alerts might only have been based on human prediction, but now machines and humans work together to make quicker, more accurate predictions. Natural Language Processing & Sentiment Analysis.

Attributes of Data

If so, are you clear about how it was error-corrected so that you can avoid downstream accuracy, bias or forensic problems? Example: 'guessing' gender based on a user's submitted name vs. the user directly reporting it. Publishing Lag.