You have a chatbot up and running, offering help to your customers. But how do you know whether the help you are providing is correct or not? Evaluating chatbots can be complex, especially because it is affected by many factors.
All machine learning engines (including the ones that make chatbots work) need training data to be useful. The better the training data is, the better results you will get. What’s a data scientist to do if they lack sufficient data to train a machine learning model?
Data scarcity is one of the major bottlenecks for Artificial Intelligence (AI) to reach production levels. The reason is simple: data, or the lack of it, is the number one reason why AI/Natural Language Understanding (NLU) projects fail. So the AI community is working extremely hard to come up with a solution.
Bitext’s is industrializing training data production for any voice-controlled device, chatbot or IVR using artificial training data to accelerate customer support automation. At Bitext we solve data scarcity and legal risks with Multilingual Synthetic Training Data to enhance Conversational AI and to derive insights from text-based and unstructured data such as contact center interactions, chat-bot and live chat transcripts, product reviews, open-ended survey responses and email. We can natively analyze text in up to 80 languages.
According to Gartner, companies working with AI should stop combining training and learning activities, one of the reasons being the slowing down of conversational agents’ learning processes. The most recommended course of action for data managers is exploring emerging middleware tools that allow them to use the same training data set for multiple AI service providers.
When searching for innovative solutions, it is crucial for leaders and decision makers to have the information that allows them to make informed decisions. Bitext is currently at the forefront of technology since it has been mentioned lately in no less than 20 Gartner reports and was selected as Cool Vendor in AI Core Technologies in 2018. But we keep working hard and Gartner, once again, mentioned Bitext in 4 new Hype Cycle reports.