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Three Mind-Blowing GPT-4o Examples You Haven’t Seen!

Last week, GPT-4o broke the Internet.

The world is running out of text data.

There is an open discussion about how many useful tokens are still out there. Most tokens are already contained in Common Crawl dataset - the dataset that makes up the majority of training data in today’s LLMs.

The problem: The production of human-written text is slow. Very slow.

Even with all the social media shitposting that is going on, it is going to take years before we see any meaningful increase in the world’s text data. Other data, however, are available in near-infinite quantities. Image, text, and video data can be produced quickly and cheaply.

This inevitably pushes us towards a multi-modal future. And it is going to be nothing short of amazing.

GPT-4o gives us a very clear glimpse at what this will look like.
Below are four of my favorite examples, that I came across on the internet.

Let’s jump in!

It Correctly Identifies The Origins Of Missile Fragments

I have obviously no way of fact-checking this. However, if this is true, the amount of multi-step reasoning that is necessary to come up with this answer is truly mind-bending.

God-tier OCR

If you are the type that follows AI because you love the Terminator movies this next one is not for you. However, if you are like me and have spent countless hours using ML for document processing, this will make you weak at the knees.

Imagine the things you could build with this!

Compliance Automation

If you are building something in AI chances are you will have to deal with compliance. And it will suck! Trust me!

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Lightning Fast Data Analysis

LLMs have been capable of simple data analysis tasks for a while. However, the speed is new.

One can imagine how this will quickly start feeling more like conversing with your data instead of analyzing it.

These are such exciting times to be alive!

As always, I really enjoyed making this for you! And I sincerely hope you found it useful!

If you have questions or comments, tweet at me on X or reach out to me on LinkedIn.

Lots of love and see you next time!

P.S. Spread the news! Please, share this with a friend who could find this useful. I am very grateful for your support!