Smart Data Collective

JULY 1, 2023

One development that AI has led to is the growth of image annotation. Image annotation is the act of labeling images for AI and machine learning models. It involves human annotators using a tool to label images or tag relevant information. The resulting structured data is then used to train a machine learning algorithm.

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Smart Data Collective

JUNE 22, 2023

Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Simply put, data labeling involves annotating data to instruct a model on how to do the same. The quality and accuracy of data labeling have significantly improved due to AI and ML algorithms.

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CIO

AUGUST 24, 2023

As part of that work, Bala and his team of data scientists undertook extensive analysis of internal and third-party data to identify data sets critical for developing an effective partner prioritization data science strategy. “We

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Smart Data Collective

MAY 29, 2023

This bias can emerge due to multiple factors, such as the training data, algorithmic design, and human influence. Recognizing and comprehending the different forms of algorithm bias is crucial to develop effective strategies for bias mitigation. AI translation models must collect and annotate data fairly.

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Smart Data Collective

AUGUST 11, 2022

This massive undertaking requires input from groups of people to help correctly identify objects, including digitization of data, Natural Language Processing, Data Tagging, Video Annotation, and Image Processing. However, Ai uses algorithms that can screen and handle large data sets. Elimination of Human Mistakes.

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CIO

AUGUST 1, 2022

Federated learning is a method of training AI algorithms with data stored at multiple decentralised sources without moving that data. Annotation was already in our PACS system. We used its API for data extraction.

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Alpha Sense BI

JANUARY 5, 2024

Our suite of tools currently includes: Smart Summaries This feature allows you to glean instant earnings insights (reducing time spent on research during earnings season), quickly capture company outlook, and generate an expert-approved SWOT analysis straight from former competitors, partners, and employees.

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