Technology has never had a shortage of acronyms and AI is no different.

And if there is one acronym that you’ve read over and over and over and over again, its . . .

LLM

Here’s the inner monologue for a lot of people these days . . .

“What’s an LLM? Is that like ChatGPT?”

“Facebook offers something called Llama or something like that. What is that?”

“Some people are running ‘local LLM’ instead of ChatGPT. Should I do that?”

It’s a bit confusing on the surface, but not really.

Let me simplify it.

LLM stands for “Large Language Model.”—this is the massive brain where you are sending your prompt.

If you used ChatGPT for a while, you’ve probably used ChatGPT 3.5 and then switched to 4 and now 4o.

Those are all LLMs.

If you used Claude, then you may have used Claud 3.5 Sonnet or Claud 3 Opus.

Both are LLMs.

And if you use AI on Facebook, it now uses their very own Llama 3.

That’s an LLM.

(BTW, if when you read Llama . . think LLaMa)

I get it, but what’s the difference between all of these LLMs?

That’s where it gets really interesting.

It’s all about the training.

Imagine seven children are born on the same day, each to the richest family on each continent.

They have all the financial and educational resources they would ever need.

Will these children all have the same personality and knowledge and expertise?

Absolutely not.

Australia has different views on family than Asia.

South America has different philosophies than Europe.

Similarly, Africa has diverse cultural perspectives compared to North America.

And so even though all seven children have access to the same educational resources, the way that they are trained influences their individual learning outcomes and overall development.

Each child's unique experiences, learning styles, and personal interests play a significant role in shaping their understanding and mastery of the material.

Some will be better writers.

Some will be better mathematicians.

Some will be more creative.

THAT’S the difference between LLMs.

There are THOUSANDS of LLMs in the world — but Claude, OpenAI and Meta are kind of like the Coke and Pepsi (and Dr. Pepper?) of the AI world.

Claud and OpenAI and Meta all use similar MASSIVE data sets with billions (or trillions?) of pages of data.

But each of them trains the data in different ways using their own “secret sauce” fine-tuning.

I say “secret,” because as private companies with proprietary software, they don’t provide much transparency into all of the training and biases they used to build their model.

Some LLMs are trained with more focus on creating content.

Other LLMs are trained with medical expertise or deep reasoning.

ChatGPT 4o is advertised as “great for all tasks.”

Claude 3 Opus “excels at writing and complex tasks.”

It’s all about how they were trained.

So which is the “best” LLM?

Let me ask you this—among the seven children born to the wealthiest parents in the world, which child is the "best?"

There’s NOT a “best.”

It depends on what you are looking for.

If you were going to hire one of those seven children as an adult, you would interview each of them based on what you needed.

That’s literally how you determine which is the “best” LLM — you interview each of the LLMs.

Here’s my suggestion on “interviewing” your LLMs:

Create a list of common prompts that you might use regularly to create content.

• How many times did you have to go back-and-forth to get what you want?

• Did it follow your instructions or did you have to re-rewrite the prompt several times?

• Did you get the quality you expected?

And remember, you don’t have to choose just ONE LLM.

Maybe you like Claude for content creation, but ChatGPT for business questions.

It’s very personal and you just need to use what works best for your situation.

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