Generative AI Vs NLP Vs LLM - Explained in less than 2 min !!!
Summary
TLDRThis video script introduces the concepts of generative AI, natural language processing (NLP), and large language models. Generative AI is likened to an artist, creating new content from data inputs, which could be text, code, images, audio, or video. NLP is a subset focusing on models that understand and generate human language, performing tasks like translation and summarization. Large language models, a subset of NLP, are trained on vast text data to create highly relevant and coherent creative text. Examples include chatbots like Chat GBT, Microsoft Co-Pilot, and Google Gemini. The video promises future tutorials on creating custom chatbots.
Takeaways
- đ€ Generative AI is like an artist that creates new content from data inputs.
- đš The creative outputs of generative AI can include text, code, images, audio, and even videos.
- đ Natural Language Processing (NLP) is a subset of generative AI focused on understanding and generating human language.
- đ NLP models can perform various tasks such as translation and summarization.
- đ Large language models are a specific type of NLP that are trained on vast amounts of text data.
- đĄ Large language models can generate new, coherent, and relevant text based on the data they were trained on.
- đ Examples of large language models include Chat GBT, Microsoft Co-Pilot, Google Gemini, and more.
- đ ïž The video promises to show viewers how to create their own chatbot using personal data in upcoming videos.
- đ Large language models are significant in the AI field for their ability to produce highly coherent text.
- đ The script emphasizes the relationship between generative AI, NLP, and large language models.
- đšâđ« The video aims to educate viewers on the differences and applications of these AI concepts.
Q & A
What is generative AI?
-Generative AI refers to models that can create new, creative content from given data. It's like an artist with algorithms, capable of producing text, code, images, audio, and even videos.
How is generative AI different from natural language processing (NLP)?
-While generative AI is a broad concept that includes creating various types of content, NLP is a subset of generative AI specifically focused on understanding, interpreting, and generating human language.
What tasks can natural language processing models perform?
-NLP models can perform tasks such as translation, summarization, and other language-related tasks that involve understanding and generating human language.
What are large language models?
-Large language models are a subset of NLP, trained on vast amounts of text data, and capable of creating highly relevant and coherent new text content.
Can you provide examples of large language models mentioned in the script?
-Examples of large language models mentioned include Chat GBT, Microsoft Co-Pilot, and Google Gemini.
What is the main purpose of large language models?
-The main purpose of large language models is to generate new, creative, and contextually relevant text based on the data they have been trained on.
How do generative AI models differ from traditional AI models?
-Generative AI models differ from traditional AI models in that they are not just recognizing patterns or making predictions; they are capable of creating entirely new content from the data they process.
What is the significance of training large language models on vast amounts of text data?
-Training on vast amounts of text data allows large language models to understand the nuances and complexities of human language, enabling them to generate more accurate and contextually relevant responses.
What does the script suggest about the future content of the channel?
-The script suggests that future videos on the channel will demonstrate how to create your own chatbot using your own data.
Why is it important for viewers to subscribe to the channel?
-It is important for viewers to subscribe to stay updated on the latest videos, including upcoming tutorials on creating a custom chatbot.
What does the analogy of 'giving paints to an artist' imply about generative AI?
-The analogy implies that, like an artist uses paints to create paintings, generative AI uses input data to create new and creative content.
Outlines
đ€ Introduction to Generative AI and Language Models
This paragraph introduces the concepts of generative AI, natural language processing (NLP), and large language models. Generative AI is likened to an artist, creating new content from given data, which can span various formats like text, code, images, audio, and videos. NLP is a subset of generative AI, focusing on understanding and generating human language, capable of tasks such as translation and summarization. Large language models combine the creativity of generative AI with NLP, creating highly relevant and coherent text from vast amounts of training data. Examples of large language models include Chat GBT, Microsoft Co-Pilot, and Google Gemini. The paragraph concludes with a teaser for future videos on creating a chatbot using one's own data and a call to subscribe for updates.
Mindmap
Keywords
đĄGenerative AI
đĄNatural Language Processing (NLP)
đĄLarge Language Models
đĄAlgorithmic World
đĄData
đĄCreativity
đĄCoherent
đĄRelevant
đĄChat GBT
đĄMicrosoft Co-Pilot
đĄGoogle Gemini
Highlights
Introduction to the concepts of generative AI, natural language processing, and large language models.
Generative AI is likened to an artist that creates new content from given data.
The creative output of generative AI can include text, code, images, audio, and videos.
Natural language processing (NLP) is a subset of generative AI, focusing on understanding and generating human language.
NLP models can perform tasks such as translation and summarization.
Large language models are a subset of NLP, trained on vast amounts of text data.
Large language models can generate highly relevant and coherent creative text based on the original text.
Examples of large language models include Chat GBT, Microsoft Co-Pilot, and Google Gemini.
The video promises to show viewers how to create their own chatbot using personal data in upcoming videos.
The importance of subscribing to the channel for updates on creating a custom chatbot.
Generative AI's capability to produce new creative content out of data is emphasized.
The distinction between generative AI and natural language processing is clarified.
The role of large language models in enhancing the creativity of NLP is explained.
The practical applications of large language models in creating new text are highlighted.
The potential of large language models to revolutionize AI-driven content creation is discussed.
The video's educational goal to guide viewers in creating their own AI chatbot is introduced.
The call to action for viewers to stay updated on the latest AI developments through subscription.
Transcripts
hello everyone and welcome to the
channel generative AI natural language
processing and lar language models if
you are into the world of AI probably
you have heard one of these terms in
this video we will quickly go through
them and see what sets them apart so
generative AI you know when you give
paints to an artist and he comes up with
wonderful paintings generative AI is the
artist of the algorithmic world we give
data to a generative AI model and this
model comes up with a new creative
content out of this data this content
could be a text or code it could be an
image or it could be audio and more
recently even videos so generative AI
refers to the models that can come up
with new creative content out of data
natural language processing on the other
hand is a subset of generative Ai and it
refers to the models that are designed
to understand interpret and generate
human language they can perform tasks
like translation summarization and so on
and large language models when we add
the creativity of generative AI to the
natural language processing we come up
with something called large language
models so large language models are
subset of natural language processing
and it refers to the models that are
trained on vast amount of Text data and
these models can create or generate new
creative text out of this data that is
highly relevant and highly coherent to
the original text examples on large
language models includes chat gbt
Microsoft co-pilot Google Gemini and
many many others in the coming videos we
will show you how to create your own
chat Bo using your own data don't forget
to subscribe and stay updated
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