The retail giant said today that it will deploy the generative chatbot as an aid to human agents for the time being but plans to eventually have it deal with customers directly. The company is also rolling out a separate consumer-facing chatbot that uses a neural network to better match human-authored response templates to customer queries. The project marks one of the first commercial tests of a state-of-the-art new natural language processing technology that researchers think has the potential to supercharge progress in the field. The model, which has also powered cutting-edge systems like OpenAI's GPT-2, draws on massive training datasets and predictive text to generate realistic-sounding copy or dialogue. "It is difficult to determine what types of conversational models other customer service systems are running, but we are unaware of any announced deployments of end-to-end, neural-network-based dialogue models like ours," wrote Jared Kramer, an applied-science manager on Amazon's Customer Service Tech team, in a blog post. Despite these advances in machine learning, most chatbots on the market today still run on automation rather than true AI.