A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

The starting point of a FlexOlmo project is a so-called anchor AI model. Every organization that participates in the project ...

Training teaches the model to recognize patterns and make predictions based on data. Models learn from a labeled dataset and adjust internal parameters to maximize confidence in predictions.

Artificial intelligence (AI) systems are increasingly central to critical infrastructure, business operations, and national ...

1. Prepare the Data. The first step in training an AI model is preparing your data by collecting, cleaning, and preprocessing the information you will use to train the model.

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to ...

Consider, for example, the need to expose an AI model to large amounts of data for training. When data may not yet exist or may lack comprehensiveness, synthetic data comes into the training equation.

Strict training data management is needed throughout the model-building process by controlling and mediating the influence of multiple stakeholders. The scope and definitions of the model need to ...

Ari Morcos, who’s worked in the AI industry for nearly a decade, wants to abstract away many of the data prep processes around AI model training — and he’s founded a startup to do just that.

While AI companies make efforts to anonymize your data, it’s something you may not feel comfortable with. In most cases, you can find a setting to turn the training off.

Data poisoning is a type of attack that involves tampering with and polluting a machine learning model's training data, impacting the model's ability to produce accurate predictions.