It's been more than 6 months of hearing about the chatGPT pandemic, in which everyone from a 6-year-old to an 80-year-old is fiddling around with it, trying to make sense of it. Start-ups building a UI on top of it and getting millions of dollars in funding, people claiming to know prompt engineering and others warning us of how this could be a beginning of a 10-year AI-driven apocalypse.
And to add to all that, Facebook/ Meta just made their large language machine learning model called LLaMA open source, which means ideally anyone, including you and me can use it and contribute to improve it. But the extent to which it is “open-source” is still as clear as a misty winter morning car windshield.
Anyway, back to our topic — the following set of paragraphs will walk you through what large language models are and how are they different from the AI curated by the god, i.e. humans.
What is an LLM or what is ChatGPT?
A large language model in AI is like a super-smart computer program that can understand and generate human-like language. It’s like having a really clever friend who can read and write in a way that’s almost like how we do!
Imagine the human brain as a big library with lots of books. Each book represents knowledge or information about different things. Now, a large language model is like a librarian who reads and memorizes all the books in that library. It gets smarter and smarter as it reads more books!
The large language model can use this vast knowledge to have conversations with people and answer their questions. Just like you might ask your smart friend for help with homework or advice on a problem, you can ask the large language model anything you want to know.
Can it be my friend?
It’s like a virtual buddy who can help you understand complex topics, come up with creative ideas, and even write stories or poems for you! It’s a bit like having an AI brain that can process language and think in some ways, just like we do.
But remember, as cool as it is, a large language model is still a machine, so it doesn’t have feelings or emotions like humans. It’s just a really smart tool that can assist and make our lives easier by understanding and generating language in amazing ways!
Well, what are LLMs made of?
Let’s dive a bit deeper into how a large language model works and how it can understand and generate human-like language.
A large language model, like the one we’re talking about, is a type of artificial intelligence called a “neural network.” Think of it as a digital brain made up of tiny interconnected cells, called neurons, just like the billions of neurons in our human brains. These neurons work together to process information and solve problems.
How does it learn everything so quickly?
The large language model’s neurons learn from lots and lots of text data, like books, articles, and websites. It’s like feeding the brain of the AI with a huge library of information, and the AI gets really good at remembering and understanding what it reads.
Once it has learned from all that data, the AI can use that knowledge to answer questions or generate text on its own. So, when you ask it a question, it looks into its digital library and gives you an answer based on what it has learned. It’s a bit like having a super-smart friend who knows so much because they’ve read a massive number of books!
Can it converse in English or in any other language that has words?
Yes, that's what the ChatGPT is all about. It can talk back to you in almost all languages that have words and sentence structure.
Now, let’s talk about how it can generate language. When you ask the AI to write a story or a poem, it uses its neural network to piece together words and sentences that make sense based on what it has learned.
It’s like an incredible storyteller who can create new tales just by combining all the stories it has read before!
Can it develop feelings for humans?
But remember, despite its amazing abilities, the large language model is still just a computer program. It doesn’t truly understand things as we do, with emotions and experiences. It processes language purely based on patterns it has learned from data.
However, this large language model has become a valuable tool in various fields. It’s used for language translation, helping researchers with data analysis, and even creating chatbots for customer service. It’s like a super-powered language assistant that can support us in countless ways!
So, while it may not have feelings or consciousness, a large language model’s capabilities are awe-inspiring, and it continues to push the boundaries of what AI can do in our modern world.
Can LLMs make predictions?
Language models, like LLMs (Large Language Models), are indeed capable of making predictions based on the information they’ve learned from vast amounts of text data. They can analyze patterns and relationships within the data to anticipate what might happen next or provide plausible answers to questions.
However, it’s essential to understand that while LLMs have a massive amount of knowledge at their disposal, they are still limited in some ways. Their predictions are only as good as the data they have been trained on. If the data is biased or incomplete, their predictions may reflect those limitations.
Similarly, LLMs can outperform humans in certain areas because they can process and analyze information at an extraordinary speed. They have the ability to recall vast amounts of information quickly, making them excellent resources for tasks like language translation, summarization, and information retrieval.
However, they are not infallible. If the data they learned from is incorrect or biased, their predictions may also be skewed or inaccurate. Moreover, LLMs lack a deeper understanding of context and the real world. They don’t possess the intuition, empathy, and experience that humans bring to the table.
In essence, LLMs are powerful tools that can augment human capabilities and provide valuable insights. They excel at processing vast amounts of information and generating responses based on patterns. However, they should be used with care and in conjunction with human judgment.
Will they replace human intelligence?
Not yet, but in future? Hard to say.
While LLMs can indeed outperform humans in specific tasks due to their vast knowledge, they will never replace human intelligence and understanding. The human touch remains vital to assess the accuracy and implications of LLM predictions, ensuring a more balanced and informed approach to decision-making and problem-solving. The future lies in harnessing the potential of LLMs while acknowledging the irreplaceable value of human insight and judgment. Together, humans and LLMs can forge a path towards a more advanced and sophisticated world of information processing and analysis.
