Google Semantic Reactor
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- Semantic Reactor: A tool for experimenting with NLU models | B. Pietrzak, S. Pucci, & A. Cohen — Google AI
- Google releases Semantic Reactor for natural language understanding experimentation | Kyle Wiggers - VentureBeat
A tool for experimenting with natural language understanding (NLU) models via a Google Sheets add-on that allows the user to sort lines of text in a sheet using a variety of machine-learning models. Beyond ranking lists, Semantic Reactor can help write dialog for a chatbot, such as a customer service chatbot, using semantic similarity. Specifically, it can quickly add new question/answer pairs and test different phrasings, enabling developers to see how the model reacts to them. Semantic Reactor can also search through text using input-response, meaning it can examine a list of potential responses and rank each according to which the model thinks is the most likely. In input-response mode, the model predicts the most conversational response to an input, and in semantic similarity mode, it returns the answer that’s semantically closest to the input.
Why use the Semantic Reactor? There are a lot of interesting things you can do with the Semantic Reactor, but let’s look at the following two:
- Writing dialogue for a bot that exists within a well-defined environment and has a clear purpose (like a customer service bot) using semantic similarity.
- Searching within large collections of text, like from a message board. For that, we will use input-response.
Mystery of the Three Bots
To dispel some of the intimidation of using NLU, and to demonstrate how it can be easily used with pre-trained, generic models, Google has released a tool for creating dialog-based games, the Semantic Reactor, and open-sourced example code, The Mystery of the Three Bots that allows you to experiment with machine-learned language models...
This simple dialog-based game is an example of using a machine-learning model inside of a web application. The model it uses is called Universal Sentence Encoder Lite and is available at Tensorflow Hub. To learn more, go to the Google Cloud AI Workshop Page.
- Play Here <<<<<<<<
Mystery of the Three Bots is a simple dialog-based game utilizing machine learning to enable you to communicate with three characters. The goal is to determine which of several guests stole the precious MacGuffin Diamond. You interrogate the butler, the maid and the chef--three robot servants who were present during the crime.
The game is built as an Angular app in Typescript. The machine learning model uses a Javascript implementation of the Universal Sentence Encoder Lite, which it preloads using JSON files that were generated from CSV files (butler.csv, maid.csv, chef.csv) for each of the characters (see generate_models.js).
The game works by matching a representation of the player's input to precomputed representations of candidate strings and calculates a similarity score. For example, if the player types "Where'd the diamond go?", the game might determine that it has a similarity of 0.86 to "Where is the diamond?", and if that's a greater score than the other candidates, the game will use that as the question to the bot and return the corresponding response. See getResponse() in BotResponseService for implementation.
