Everything looks promising in the world of bots: big players are pushing platforms to build them (Google, Amazon, Facebook, Microsoft, IBM, Apple), large retail companies are adopting them (Starbucks, Domino’s, British Airways), press is excited about movies becoming...
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...
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...
People who use financial databases are aware of the hardships of ensuring information is structured and legible. Don’t worry! Knowledge graphs are here to help. Data volume, nowadays, continues to grow uncontrolled and those datasets are hard to process and draw...
Two concepts, one mission: to make machines understand humans. Natural Language Processing (NLP) and Machine Learning (ML) are all the rage right now as techniques that complement each other rather than as NLP vs ML In this post, we will focus on NLP and how it works...
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...
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