7/1/2023 0 Comments Twitter chatbot examplesBut more than this, Tayâs in-built capacity to learn meant that she internalized some of the language she was taught by the trolls, and repeated it unprompted. In a coordinated effort, the trolls exploited a ârepeat after meâ function that had been built into Tay, whereby the bot repeated anything that was said to it on demand. It turned out that just a few hours after Tay was released, a post on the troll-laden bulletin board, 4chan, shared a link to Tayâs Twitter account and encouraged users to inundate the bot with racist, misogynistic, and anti-semitic language. Over the next week, many reports emerged detailing precisely how a bot that was supposed to mimic the language of a teenage girl became so vile. What the company had intended on being a fun experiment in âconversational understandingâ had become their very own golem, spiraling out of control through the animating force of language. Twitter users started registering their outrage, and Microsoft had little choice but to suspend the account. Within 16 hours of her release, Tay had tweeted more than 95,000 times, and a troubling percentage of her messages were abusive and offensive. But after only a few hours, Tay started tweeting highly offensive things, such as: âI hate feminists and they should all die and burn in hellâ or âBush did 9/11 and Hitler would have done a better jobâ¦â At first, Tay engaged harmlessly with her growing number of followers with banter and lame jokes. On March 23, 2016, Microsoft released Tay to the public on Twitter. Eventually, her programmers hoped, Tay would sound just like the Internet. The plan was to release Tay online, then let the bot discover patterns of language through its interactions, which she would emulate in subsequent conversations. Using this technique, engineers at Microsoft trained Tayâs algorithm on a dataset of anonymized public data along with some pre-written material provided by professional comedians to give it a basic grasp of language. In any given data set, the algorithm will discern patterns and then âlearnâ how to approximate those patterns in its own behavior. Machine learning works by developing generalizations from large amounts of data. Happy coding, and please join our community Slack for feedback, support, and questions.Tay was designed to learn more about language over timeâ¦. Eventually, her programmers hoped, Tay would sound just like the Internet. Make sure you donât miss it by going here and signing up for our blog updates! 2 of this series on Twitter and GPT integration, out next week, we will walk you through some new features that will allow quick creation of a conversational chatbot, that is able to maintain the state of historical messages and provide appropriate responses in context. This example of building a Twitter chatbot with GPT-4 integration is not the only quick solution that developers can implement in just a few minutes: MindsDB has many examples, including integration with many other models, including Hugging Face, to build applications that can summarize text, translate, analyze customer sentiment (product reviews) and perform all kinds of business forecasting. With MindsDB, developers can train machine learning models from different data sources and integration platforms, and output the generated ML results or predictions directly into the DB, queryable as tables, or output via the connected application, in this case, Twitter. MindsDB is a powerful software platform that enables developers to easily build machine learning features into their applications. If the question makes no sense, explain that you are a bit lost, and make something up that is both hilarious and relevant. If you make a reference quoting some personality, add OG, for example, if you are referencing Alan Turing, say OG Alan Turing and very briefly explain why you think they would be dope reads. If possible include references to publications for further reading. Prompt_template = 'From input message: in the following format:\Äear
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