Chatbots, like other artificially intelligent systems can draw from vast resources of data at a moment’s notice.It’s memory can store the dictionary definition for every word in existence.
Facebook did succeed in automating some of the work its army of contractors used to perform in the guise of M.If you ask the bot to get flowers delivered, it can automatically get suggestions from online florists, only asking a human to choose which quotes to present to the user. The people who used the service and role-played as the omniscient assistant have generated valuable data that can be used by the company's AI researchers.Using machine learning to make software better at understanding natural language and conversation is one of the group's primary interests.“We launched this project to learn what people needed and expected of an assistant, and we learned a lot," Facebook said in a statement."We're taking these useful insights to power other AI projects at Facebook.Then, based on what it’s programmed to do, it will give a response.
Chatbots take a while to program because they have to learn as a human customer service agent would have to learn.The free service was only offered to 10,000 people in the San Francisco area, who used it to do things like book restaurant reservations, change flights, send gifts, and wait on hold with customer service. Facebook’s goal with M was to develop artificial-intelligence technology that could automate almost all of M’s tasks.But despite Facebook’s vast engineering resources, M fell short: One source familiar with the program estimates M never surpassed 30 percent automation.If you’re considering developing a chatbot for your brand, then it’s helpful to know a little about how chatbots work, where they are in their development (their abilities and limitations), and what artificial intelligence researchers are working on to improve them.Chatbots use elements of natural language processing (NLP) and machine learning to try to determine what a human conversant is saying to it.Last spring, M’s leaders admitted the problems they were trying to solve were more difficult than they’d initially realized.