<\/span><\/h3>\nThe core difference between traditional programming and machine learning lies in the approach to the problem. In traditional programming, a developer writes code that contains specific instructions to solve a task. The computer then follows these instructions when it encounters the relevant data.<\/p>\n
Machine learning, on the other hand, reverses this process. Instead of directly programming the computer to solve a task, it is fed with large amounts of data and the corresponding results. The computer then learns from this data by identifying patterns and relationships and develops a model that can make predictions about new data. This ability to self-improve and adapt to new situations without direct human input is what makes machine learning so powerful and challenging at the same time.<\/p>\n
<\/span>What are language models actually?<\/span><\/h2>\nLanguage models are at the heart of the interaction between humans and machines in the world of artificial intelligence (AI), especially in the field of natural language processing, also known as neuro-linguistic programming – NLP for short. They enable computers to understand and generate human language, which is the basis for many of today’s technologies, from virtual assistants to automatic translation systems.<\/p>\n
<\/span>Natural Language Processing (NLP): A fundamental concept to understand the technology behind ChatGPT<\/span><\/h3>\nNatural language processing enables machines to interpret and process text and speech in the same way that humans do. This ranges from understanding spoken words to recognizing and applying the complex rules that underlie our language. NLP uses language models to accomplish tasks such as translating text, answering questions and even creating new content.<\/p>