Photo by Google
DeepMind on Unsplash
Hey there, curious minds! Today is the second in my series
on Generative AI. Picking up where we left off last time, today we're diving
into the fascinating world of neural networks and large language models. Don't
worry if these sound like big words – we'll break them down into bite-sized
pieces so you can understand them like a pro!
What are Neural Networks?
Imagine you are solving a puzzle, and to do that, you have
many friends helping you. Each friend is good at solving a specific part of the
puzzle. Similarly, a neural network is like a team of friends that work
together to solve a problem. But instead of a puzzle, they handle tasks that
computers find challenging, like recognizing objects in images or understanding
human language.
The neural network is made up of artificial brain cells
called "neurons." Each neuron takes some input, thinks about it, and
then gives an output. They work together in layers, with each layer adding more
complexity to the problem-solving process. The information flows through the
layers, just like passing a message along from one friend to another until they
solve the puzzle together.
For example, when you show a neural network a picture of a
dog, the first layer might notice basic shapes, like circles and lines. Then
the next layer combines these shapes to identify parts of the dog, like its
nose or ears. Finally, the last layer puts everything together and says,
"Hey, this is a dog!"
What about Large Language Models?
Alright, let's shift gears a bit and talk about large
language models. Have you ever asked a smart assistant a question or typed
something into a search engine, like, "What is the tallest mountain in the
world?" Well, behind the scenes, there might be a large language model
working hard to give you the answer! Large language models are like super-smart
robots that can understand and generate human-like language. They can read
stories, answer questions, write essays and even have conversations!
Language models are trained on a vast amount of text from
books, articles, and websites. They learn patterns and relationships between
words, just like you learn new things by reading lots of books. With this
knowledge, they can predict what words come next in a sentence or even complete
a whole paragraph by themselves!
When you ask a language model a question, it uses its vast
memory to find the most likely answer based on what it has learned from all the
text it has read. It's like having access to the world's biggest library, and
the model can fetch the most relevant information for you!
How They Work Together
Now, the magic happens when we combine Neural Networks and
Large Language Models. Imagine a giant puzzle, one that is so big that it would
take a team of people a very long time to solve. But with a neural network and
a language model working together, it's like having a super team of puzzle
solvers!
The neural network can understand the puzzle's structure and
divide it into smaller parts, just like your friends in the puzzle example.
Then, the language model comes in, using its vast knowledge to help solve each
part. It's like your friends asking for advice from the smartest people they
know!
Just imagine having your very own super helper who can
assist you with anything you need, like solving math problems, explaining
tricky topics, or even telling you fun facts!
Applications of These Technologies
You might be wondering how we use these incredible
technologies. Well, they power many things around us! When you use voice
assistants like Siri or Alexa, they rely on language models to understand and
respond to your questions. When you watch videos on platforms like YouTube,
neural networks help recommend videos you might like based on what you've
watched before.
Final Thoughts
Neural networks and large language models are incredible
creations that use the power of computers to make our lives better and easier.
They can do amazing things that would take humans a very long time to
accomplish. They are kind of like a dream team of problem solvers and knowledge
gatherers that make our digital world more exciting, helpful and smarter. As we
continue through this series, we will dive deeper into how you can use the
applications backed by these models in your business and personal life and even
look at how you can integrate these into your programs.
