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Facebook open-sources DLRM, a deep learning recommendation model

This recommendation model needs to help the AI community tackle challenges presented by recommender engines.

Facebook’s recommendation tools have been controversial in the past, to say the least. People believe that Facebook is using personal information to target their users with more personalised advertisements.

Recommendation engines consists in improving customer journey and increasing conversions by showing to customers products recommendations that are relevant to them. Thus they decide a lot of what people see on their newsfeed today.

Facebook AI Research (FAIR) open-sources a lot of its work, but its parent company is making DLRM (Deep Learning Recommendation Model) available for free to help the wider AI community address challenges presented by recommendation engines, like a need for neural networks to associate categorical data with certain higher-level attributes. The makers of DLRM suggest the model be used for benchmarking the speed and accuracy performance of recommendation engines.

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