In this lecture, we will start diving into agents.
Large language models are incredibly powerful, but they lack the ability to
perform certain tasks that even the simplest application can do easily.
For example, LLMs struggle with logic, calculation, or communicating with other
external components.
Let's see an example.
I am asking GPT -4 for the result of an exponentiation.
What is the answer to 5 .1 to the power
of 7 .3?
And the GPT -4, probably the most complex
computer application that has been ever built , fails.
Calculating powers where the exponent is not a whole number is a complex operation
and can't be done by an AI model.
This is not a good result.
This operation can be done easily by any calculator.
For example, in Python, you would use the
double star operator.
So, 5 .1 star star 7 .3.
And I've got a completely different answer.
Let's try another one.
5 .1 to the power of 1 .7.
And once again, GPT -4 fails.
Let's do this again using Python.
As you can see, the answer is different.
This is because GPT -4 is using an approximation, while Python is using the
exact mathematical formula.
In conclusion, LLMs are powerful tools,
but they are not perfect.
They can be used to generate text,
translate languages, and answer questions, but they cannot replace
calculators or other tools that are designed for specific tasks.
Let's try another one.
I am giving ChuckGPT the task of writing
an article about Lanchain Agents.
So write an article about Lanchain Agents.
We see how it hallucinates.
Nothing from what you see here is true.
It completely made up the answer.
That's because it was trained on data
that cuts off in late 2021.
You could say that there are plugins that
help GPT -4 browse the internet and access updated information, but that's
something different.
Plugins are external tools that are
similar to agents.
One solution to these problems is to use
Lanchain Agents.
Agents are enabling tools for LLMs.
Using agents, LLMs can run code, do calculations, search the web, or run SQL queries.
Now that you've learned why we need agents and what they are, we'll take a
break and in the next video, we'll see Lanchain Agents in action.