GPT-4 is here. This is what you need to know.

Hey there,

Before we get started, two PSAs:

First, next Monday the new AI Academy courses will be out. This means that your opportunity to save up to 70€ with the pre-launch sale ends on Sunday. You may have noticed AI is exploding, and this is your chance to join the party. Don’t let it go, join now.

Also: Next Tuesday I’ll be hosting a workshop titled “Democratising access to AI education - why and how” for the Mozilla Festival.

I’ll guide you through an exercise to understand how you can kickstart your AI education and help others join the revolution too. Join me at MozFest! Get your ticket here.

This week’s news:

  • GPT-4 is here. This is what you need to know.
  • Pizza Bytes 🍕: well, lots of AI stuff.

GPT-4 is here. This is what you need to know.

GPT-3 was released almost 3 years ago. Barely anyone cared.

GPT-4 was released two days ago. Everyone knows this will change everything.

Today I want to help you navigate what’s going on covering three aspects:

  • What GPT-4 can do that GPT-3 can’t
  • Why now?
  • What now?

Understanding GPT-4.

The fundamental difference with GPT-4 is that it’s multimodal, which is a fancy word to say that it’s not limited anymore to text, but it can “understand” images too.

It doesn’t sound that impactful until you see some applications. Here are a few:

Be My Eyes has built a product to help people who are blind or have low vision. They can now take a picture of their fridge and ask GPT-4 “what can I cook with this?”, GPT-4 will understand the items in the fridge and develop a recipe.

This demo blew everyone’s mind though: you draw a mockup of a website on a piece of paper, send it to GPT-4, and ask it to turn it into an actual working website. It’ll do it.

The other differences are more incremental than transformational. In short, GPT-4 is smarter and safer than GPT-3.

Normally, I wouldn’t say that “incremental improvement” is something to be extremely excited about. The first iPhone was a transformational innovation, but the iPhone 14 is a small incremental improvement over the 13 that few people care about.

However, if technology improves by an increment large enough to surpass some threshold for adoption, things can get really exciting because some applications may go from “impossible” to “possible”.

So how much smarter is GPT-4? The most outstanding example is the US Uniform Bar exam: a series of questions to test the knowledge that every lawyer should be able to demonstrate prior to becoming licensed to practice law.

ChatGPT was in the bottom 10% of humans taking the test. GPT-4 is in the top 10%.

In the International Biology Olympiad (a biological olympiad for pre-university students under the age of 20), ChatGPT was better than 31% of participants. GPT-4 is in the top 1%.

So yeah, it’s much better. Is it better enough to enable it to have reached a tipping point?

It definitely feels like it, especially because it’s made great improvements also in safety (less likely to say BS) and “steerability” (how well it follows prompts).

My bet here is that we did reach a tipping point IF this “steerability” is given in the hands of subject matter experts. In simpler terms: GPT-4 alone may not be enough to replace a lawyer. But we are in a moment where a lawyer could build around it through prompt engineering (+ other resources) to confidently let it run part of his job.

And by the way, I used “lawyer” as an example, but you can replace it with many professions today.

Why now?

The attention around the release of GPT-4 is 1 million times higher than what I saw when GPT-3 came out. Yet, GPT-4 is not 1 million times better. Why did we all wake up now?

I think ChatGPT was the key. While not smarter than GPT-3 (it’s actually dumber), ChatGPT was easier to understand and use. GPT-3 had a very odd pitch that I failed to understand too: give it text and it’ll continue writing text. So what?

ChatGPT was much more user-friendly: talk to it like you’d do with a person, and it’ll answer you. A 5-year-old kid could understand it and use it.

ChatGPT’s main role was to show humanity what this technology can do and inspire us on what we could build with it. From that point of view, we could say that ChatGPT’s biggest marvel and contribution was not the technology itself, but the user experience and marketing outcomes.

I think this underlines a very important point about generative AI that too many people are ignoring: people don’t care about the technology. People care about the problems technology solves them.

While GPT-4 is amazing, it’s still entirely useless unless companies include it within compelling, delightful products that solve real problems. It’s a tool.

What now?

You’ll see in the Pizza Bytes section of this newsletter how many companies released products that integrate the “GPT-X” experience (spoiler: a lot).

What impresses me is the speed at which everyone is integrating this experience within their products. To me there are a few questions that still need answer:

  1. Is ANY product better if you add a conversational experience to it?
  2. If GPT-4 is SO good, is there space to build new products with it or people will go “straight to the source” an use ChatGPT instead?
  3. Are we heading towards a world where every company has to integrate a chat-like experience in their product and pay OpenAI a tax for it?

I could write a giant essay about it, so I’ll keep it short for now and you reply to this email if you want me to go deeper on one of those topics in the future. In short:

  1. No, I don’t think any product gets better if you add a GPT-4-powered conversational interface. Once again: people care about their problems being solved, they don’t care about the how.
  2. Yes. Using GPT-4 is magical, but if you have a job to do you don’t want to spend time thinking about a clever prompt, explaining what you want to do, read the text GPT-4 spits out and put it somewhere else. There’s tremendous space in developing a compelling UX around GPT-4’s capabilities.
  3. No. I’ve talked often about the “race to zero”: how and why LLMs like GPT-4 will become free. This week was another step towards that vision: while everyone was busy talking about GPT-4, Google announced that they will start their own LLM for companies who want to integrate it. The real competition is coming, and you know what competition does? Drives prices down. In the meantime, open-source models are developed (or leaked), which means that people will be able to use them for free.

A short conclusion

GPT-4 is freaking amazing, but it’s not the product that will change our world.

The products that will change our world are the ones that entrepreneurs will build on top of it.

On that note…I’m working on a couple, stay tuned 👀

AI Pizza Bytes 🍕

Other quick news.

Tiramisù 😋

The sweet part of the newsletter: fun stuff from the crazy world of tech.

Get ready for this:

You reached the end of this edition 😢

I’ll talk to you next week.

Ciao 👋

This post has been sponsored by the Mozilla Foundation.

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