Getting GPT to Answer Consistently and with Style GPT, and any other generative model, tends to provide disparate answers for the same question, sometimes they are just a bit different, sometimes very different or even contradictory. Behavior of GPT-3.5 Standard These...
ChatGPT has major flaws that prevent it from becoming a useful tool in industries like Customer Experience. That’s what Blake Morgan, a CX expert, published in Forbes recently: Cons Of ChatGPT For Customer Experience One relevant fragment: “One of the lauded benefits...
The advent of Generative Large Language Models (LLMs) has revolutionized a myriad of business operations, ranging from creating enthralling blog articles to the brilliant classification of sentiments across statements. These models, when spiced with tailored datasets,...
In a previous post, we conducted a comprehensive benchmark on the role of synthetic text generation for intent detection using traditional Natural Language Understanding (NLU) platforms. In that study, we specifically examined the performance of Rasa as an example,...
We have shown in previous posts why Synthetic Training Data is the best way to boost the accuracy of any chatbot, and the solution to the most important problem of chatbots nowadays: data scarcity, namely, the lack of accurate and useful training data for the problems...
A couple of weeks ago, Facebook introduced an upgrade for its Messenger platform. The upgrade of Messenger was aimed to improve the user experience. According to the announcement, they have taken into consideration user’s feedback to create new features. It sounds...
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