Two concepts, one mission: to make machines understand humans. Natural Language Processing (NLP) and Machine Learning (ML) are all the rage right now, but people tend to mix them up. In this post, there will be a distinction between these two different but complementary terms in the field of Artificial Intelligence.
Sentiment Analysis is a procedure used to determine if a chunk of text is positive, negative or neutral. In text analytics, natural language processing (NLP) and machine learning (ML) techniques are combined to assign sentiment scores to the topics, categories or entities within a phrase.
The most significant aspect of a virtual agent is how fast it is able to learn. With a human in the conversational loop, training AI goes much faster: your bot learns and changes, keeping knowledge up to date.
Google’s smart speaker, Google Home, has recently learned a new language. Launched at the end of June this year, Google Home is now speaking Spanish. As real as life itself, Spanish speakers can now listen to all summer hits without lifting a finger, or even look for restaurants nearby by indirectly saying, ‘Ok Google, tengo hambre’. This language update may serve to gain ground in the market of artificial intelligence-powered devices since Spanish is the second most widely spoken language in the world. Notwithstanding, Google Home's Spanish skills leave much to be desired. Bitext team has been testing it and, as a matter of fact, there is still room for improvement.
Although Machine Learning algorithms have been around since mid-20th century, this technology along with Deep Learning is the newest popular boy in town, with good reason. Due to recent advances in computing power and data availability, they're being more and more used to perform astonishing tasks.