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How AI Can Improve Your Annotation Quality?

Smart Data Collective

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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Data Labeling Improves Machine Learning & AI Efficiency

Smart Data Collective

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. 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 Amazon has a very good overview if you want to learn more.

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How Aster DM Healthcare used federated learning to better secure AI analysis of sensitive data

CIO

In a distributed learning setup, data from different hospitals must be brought together to create a centralised data repository for model training, raising lot of concerns on data privacy. Federated learning is a method of training AI algorithms with data stored at multiple decentralised sources without moving that data.

Learning 368
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Equinix goes partner prospecting with AI

CIO

Multinational data infrastructure company Equinix has been capitalizing on machine learning (ML) since 2018, thanks to an initiative that uses ML probabilistic modeling to predict prospective customers’ likelihood of buying Equinix offerings — a program that has contributed millions of dollars in revenue since its inception.

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How guardrails allow enterprises to deploy safe, effective AI

CIO

Take for example its sentiment analysis tools, which analyze social media and news content related to individual companies. People would look at samples of news and annotate them as positive, negative, or neutral. People would look at samples of news and annotate them as positive, negative, or neutral.

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The Future of AI: High Quality, Human Powered Data

Smart Data Collective

Human labeling and data labeling are however important aspects of the AI function as they help to identify and convert raw data into a more meaningful form for AI and machine learning to learn. Faster and Better Learning. AI and Machine Learning ensure that data trends are identified. Elimination of Human Mistakes.

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8 tips for unleashing the power of unstructured data

CIO

Using voice recognition and sound analysis, we extract nuances such as mood and sentiment.” Features such as in-game chat sentiment analysis needed real-time processing to filter out inappropriate behavior by players. Going into analysis without ensuring data quality can be counterproductive. Quality is job one.

Gaming 488