What is Bertėjas?
A system for interpreting and producing literature called bertėjas employs artificial intelligence to process natural language.
The word “Bertėjas” is derived from the Lithuanian word for “supervisor,” which can also be used colloquially to refer to someone who manages the work of others.
The History of Bertėjas
Bertėjas is a powerful tool for natural language processing. Its creation by a team of linguists and programmers from Lithuania, who wanted to make NLP accessible to everyone, has an interesting history.
Despite the long history of artificial intelligence (AI) and natural language processing (NLP), computers didn’t start to understand human speech in real time until the 1980s, and even then, such systems had limits when it came to understanding context and meaning. Many people still don’t realise how far things have progressed since then, in fact!
Where did the term bertėjas come from?
The term bertėjas has been in use since the 19th century. It derives from the term “ber” in Lithuanian, which means to say or speak.
How Does It Work?
The technology behind bertėjas was developed by a multidisciplinary team of academics at MIT and Stanford University with the aim of creating an AI system that could accurately categorise text based on its meaning—a feat that has long baffled computer scientists.
The result? A sophisticated NLP platform capable of understanding any language and providing accurate results based on this understanding, which you can use for free!
What do bertėjas do?
Bertėjas are used to help people solve problems. They provide a natural way of interacting with computers, which makes them ideal for tasks like searching for information on the internet or reading email. The bertėjos you’ll use most often are Siri, Alexa and Google Assistant (formerly known as Google Now).
How to start using Bertėjas?
You must install the bertėjas app on your phone or tablet before you can use it. construct a profile after completing those steps, then construct a chatbot for you or another person. The only thing left to do is start a dialogue with him.
You can use the chatbot to order a Domino’s pizza or find out the result of the previous night’s game while watching live sports online. Additionally, you can enquire about his age or favourite hue; he will answer any question!
Natural language processing and artificial intelligence: A Brief History
For many decades, scientists have been trying to develop machines that can understand and communicate in natural language.
Artificial intelligence (AI) has advanced significantly throughout this time. It has evolved from a mere curiosity into something far more powerful: an essential tool for tackling problems in business, science, and medicine.
AI is being employed in a variety of applications, including helping to diagnose diseases, anticipate weather trends, and even assist you organise your images!
Its use as an assistive technology for people with disabilities or impairments who, due to illness or injury, are unable to speak normally but still want access to computers and other devices that require verbal communication skills, like Siri on Apple phones or Cortana on Microsoft PCs, may be one of its most intriguing applications.
The Rise of Deep Learning and Neural Networks
A subset of artificial intelligence is deep learning, often known as machine learning. Computers may now learn from data without explicit programming thanks to this technology. Neural networks, which are layers of interconnected nodes (similar to neurons) that collaborate to interpret data and identify solutions, are used in deep learning.
Deep learning has been used for image identification for a long time, but has only recently gained popularity in natural language processing (NLP) due to advances in CPU power and more easily accessible datasets.
Despite the fact that neural networks have existed since the 1940s, they weren’t widely used until Alex Krizhevsky’s AlexNet, a deep convolutional neural network that he trained using graphics processing units rather than standard CPUs or GPUs, won the ImageNet competition in 2012.
Why else might we use natural language?
Natural language processing is a complicated field. For instance, it is employed in sectors like healthcare and pharmaceuticals in addition to social media sites. The difference between these two fields is that the former employs humans while the latter uses algorithms that can understand natural language.
Employing NLP in these industries has a number of advantages, including enabling companies to derive better insights from their data while also cutting down on the time and money spent on human work. We’ll go over some examples below!
Conclusion
The future of artificial intelligence and natural language processing excites us. It will be intriguing to see where this technology goes next as the capacity for machines to grasp our language represents a significant advancement for humanity.
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