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In Today’s Caveminds Journey…

We bring some fire for your weekend!

• 🚀 From Dusk to Dawn: ChatGPT’s Gives Way to the real AI Epoch

• 💼 Business Buzz: Adapting Your Strategies for the LLM Evolution

• 📈 Actionable Use Cases: The Fast Lane to an In-Context Learning Future!

Alright, let’s get started!

LLMs are here and while all of you on Twitter are watching people build tools on top of ChatGPT and bragging about quick 💰, be glad that we are inviting you to dive deeper than surface level and learn about what the big boys and girls are doing with AI.

So if you haven’t yet, go ahead subscribe and share this post!

The Real AI Dawn: Adapting Your Strategies for the LLM Evolution

While we all gloat about the simplicity to login to our favorite LLM and ask questions until our ♥️’s content - not everyone is excited about the ease of use.

Consider Amazon's blanket restriction against Bard, ChatGPT, and other LLMs usage for its employees.

The reason? One word: security.

Is this a mistake? No. It’s going to become the norm.

Because what many do not realize is that when www was created, the same security problems existed. Well, it was simpler back then - there were very few computers 💾 connected to the internet - but very quickly firewalls were built. And the enterprise companies were protected 🔒

LLM’s pose the same risk. Instead of being restricted on which www you can search inside of your companies firewalls - Amazon is restricting which LLMs you can use. Because anything you type into the LLM is always and forever public.

Even Law Offices are restricting the use of LLM’s. Why? Because if the lawyer types in confidential information to formulate the agreement; well, that is a violation of their attorney-client confidentiality pledge. 🤝

So don’t go thinking lawyers will be extinct soon ☠️ — the only thing that will happen is their prices will decrease as software agencies build out private LLM’s for their offices. (More on this soon.)

But what about all the tools on Twitter that are “making life easier” for lawyers, accountants, tax advisors, content writers, film makers, and every person’s job ever created? 🤔

I am not saying that all tools are junk 🗑️. But the Lindy effect proves that if you build something in a month - it will die in a month. Things need to be built to last for customers that plan to use your product for years - not microseconds.

So if “new tools” will die, how will AI advance? 

Bard is now released public to the world and destroys any tool that was created on ChatGPT promoting a “fine-tuned” data set. I’m looking at those Jasper-style “make me something in my brand voice” tools by uploading all my website content and then hitting “Give me a hero image”. Double 🥱🥱

So, what’s going to happen?

Something that no one saw coming. 👀

It’s called “In Context Learning” and Enterprise clients are drooling over its capabilities. 🤤

What is in-context learning❓

Kind of like asking an intern to label all the movies in Netflix 🍿by genre. 🥱

Previously, you would need to hire a team of laborers to go into Netflix and label movie, after movie, after movie, after movie of alllll the genres that exist.

– What even is Neo Noir anyways? 

Then, after it’s properly labeled, finally a data scientist can come in and create predictions on the dataset so that after your done watching “10 Things I hate about you” you can roll right into “Never Been Kissed.”

– Yes, 90s movies are the best. 

With in-context learning, you can instead train your AI model by observing examples of how humans are labeling those movies based on the context of the movie itself. 

Maybe, the machine notices that if the word “Love” appears more than 4 times then it’s a Romantic Movie. But it is not doing this in post-production. The machine is inferring the data from only a few labels that the human provided. Then predicting the rest of the labeling by some other content it discovers about the movie itself - sometimes even things humans don’t notice.

Maybe there are millions of movies and after 20 labels, the machine can start self-labeling the genres. That is a ridiculous time-saving tasks to prepare information for prediction models. 

This. Is. MindBlowing. 🤯

That is great, but how can I use In-Context Learning for my Small Biz?

Regardless of whether you're running a mom-and-pop shop or a software startup, there are still ways you should be educating yourself to prepare your biz.

– Because if you don’t your competitors will.

Here are some ways to future-proof your business:

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