OpenAI sets benchmark for sentiment analysis using an efficient mLSTM

Because the model was trained to be generative, it was also able to output reviews with preset sentiments. The table below is pulled from the paper and shows a random assortment of examples for both positive and negative reviews. These results are cool, but if you're totally new to this, let's take a few steps back. Even before machine learning, engineers interested in classifying sentiment would employ relatively dumb heuristics like keyword search to get the job done. However, with these methods, a sentence like, "I hope you're happy," could easily be misinterpreted as having a positive connotation simply because it possesses the word happy.