You may have heard of ChatGPT it is the fastest website to get 100 million users, reaching this in just 2 months from launch. ChatGPT is a powerful language model that can generate realistic and coherent text for various purposes. It is developed by OpenAI, a research organization founded by Elon Musk and others and invested in by Microsoft. ChatGPT is a type of artificial intelligence that is classified as a large language model (LLM). It uses its dataset accompanied by human input to create its responses in real time.
What is a Large Language Model?
A large language model (LLM) is a deep learning algorithm that performs various natural language processing tasks, such as generating and classifying text. LLMs use self-supervised learning to learn from massive datasets of unlabelled text and predict the next word in a given text. For example, ChatGPT’s dataset size isn’t public, however GPT-3’s dataset was recorded to be 570GB.
What does this mean?
Basically, a large language model is an algorithm that processes human language. These algorithms learn from a large dataset to predict what word is going to go next in a sentence.
What can Large Language Models do?
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Language Translation
LLMs can translate text from one language to another, using large amounts of bilingual or multilingual data.
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Text summarization
LLMs can generate concise summaries of long texts, using techniques such as extractive or abstractive summarization.
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Sentiment Analysis
LLMs can classify text according to its emotional tone, such as positive, negative, or neutral, using techniques such as fine-tuning or zero-shot prompting.
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Creative writing
LLMs can generate original texts that are coherent and engaging, such as stories, poems, or songs, using techniques such as prompt chaining or few-shot prompting. However, note that LLMs may create an output that is similar to other works that exist.
What can't they do?
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Reliability
LLMs may produce inaccurate or misleading outputs that are influenced by the quality and diversity of the training data, which may contain false information, bias, or toxicity. LLMs may also produce outputs that contain factual content that is not supported by the training data or the user’s prompt, which may create false impressions or harmful consequences. This is called hallucination.
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Scalability
LLMs require a lot of time, money, and data to train and fine-tune, which may pose challenges for developers and enterprises who want to access or customize them.
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Originality
LLM are unable to create very original content their ideas will come from ideas relating to what is in their dataset. Meaning, LLM can be very good at creating things that they were trained on. However, when it comes to creating an original idea or code that has never been written before, they will tend to fall short.
What is the future for AI?
In the near future, LLMs such as ChatGPT could become more advanced and capable of engaging in natural and fluent conversations with humans across many more languages. ChatGPT could leverage its massive pre-trained knowledge and fine-tune it on specific tasks and contexts to provide personalized and relevant responses. ChatGPT could be integrated into various platforms and applications such as social media, education, entertainment, and health care to enhance human communication and collaboration. Recently, Snapchat added it's own AI chatbot to it's platform
ChatGPT Facts
- GPT stands form Generative Pre-trained Transformer
- ChatGPT was launched on November 30th, 2022
- •ChatGPT has 175 billion parameters, that is more than the stars in the Milky Way Galaxy (100 Billion)
Thanks for reading.
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