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The MIT-Pillar AI Collective has announced its first six seed grant recipients for projects related to AI, data science, and machine learning with potential commercial applications.
A new technique eliminates a source of bias in a popular simulation method, which could enable scientists to create new algorithms that are more accurate and boost the performance of applications and networks.
The team said this system is more accurate than deep learning methods when predicting future values and filling in missing data points.
Whether someone is trying to predict tomorrow’s weather, forecast future stock prices, identify missed opportunities for sales in retail, or estimate a
By adapting a powerful algorithm, MIT researchers created a user-friendly tool that enables a nonexpert to make predictions with high accuracy using time-series data with just a few keystrokes and in a matter of seconds.