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Transcript of YouTube Video: How AI Can Help You Turn an Idea Into the Next Great App | Amjad Masad | TED

Transcript of YouTube Video: How AI Can Help You Turn an Idea Into the Next Great App | Amjad Masad | TED

The following is a summary and article by AI based on a transcript of the video "How AI Can Help You Turn an Idea Into the Next Great App | Amjad Masad | TED". Due to the limitations of AI, please be careful to distinguish the correctness of the content.

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00:04

You know, one of my earliest memories

00:07

as a kid growing up in Jordan

00:10

was watching my father,

00:11

who was a government engineer at the time,

00:14

set up a new computer.

00:16

I was just a kid, but that machine really gripped me.

00:21

It felt like it was magic.

00:23

We couldn't really afford it, but my father had a feeling

00:26

that this thing is going to be transformational

00:28

for the world and for our lives.

00:31

At first, like most kids, I started playing video games.

00:35

I figured out how to boot up video games and play them for hours.

00:38

But then I had a radical thought.

00:40

What if I could make my own video games?

00:44

The very notion that I could take a concept in my head

00:48

and make it a reality that I and other people can explore

00:53

was something that was really gripping.

00:56

Now fast-forward to my teenage years

00:59

and the internet has just arrived.

01:01

And I thought it was going to change everything.

01:04

I was bursting with business ideas.

01:07

But there was a problem.

01:08

I didn't know where to start.

01:10

Which language do you use?

01:12

How do you even share your creations with the world?

01:15

And these questions sent me down a rabbit hole.

01:19

The first thing I attempted doing at solving these problems

01:23

is putting a code editor in the browser.

01:26

Can you make it so that you can code anything really easily

01:30

and share it with the world?

01:32

So eventually I had a breakthrough.

01:33

I built the world's first online programming sandbox

01:37

with a lot of different languages,

01:39

and that went viral.

01:41

A bunch of companies in Silicon Valley started using it,

01:44

and they hired me.

01:46

I got a visa to the United States and I came to New York.

01:51

A few years later, I set eyes to go west

01:55

and I came to Silicon Valley to start a company.

01:57

And that was Replit.

02:00

Our dream is to make it so that anyone can turn an idea into software quickly.

02:06

Our vision is to empower a billion software creators.

02:12

But giving people an editor was not going to be enough

02:16

to get a billion people coding on it.

02:18

We've signed up millions of people

02:20

and today we have 25 million developers registered on our site.

02:24

But we need an order of magnitude jump.

02:27

And a couple of years ago I stumbled on this technology.

02:31

That's the reason we're all here.

02:33

Large language models.

02:35

And I thought this was the unlock

02:38

that's going to make it possible for anyone to become a software creator.

02:42

The interesting thing about large language models

02:45

is that you can transform any thought in any language,

02:48

any human language,

02:50

into software.

02:53

And this, I thought, is how we bring a billion software creators online.

02:58

So right now I want you to imagine something.

03:01

Let's say you're traveling in a new city.

03:04

And you're walking around and seeing these magnificent landmarks.

03:10

But you're interested in the stories around these landmarks.

03:13

Now it kind of takes you out of the moment to pull up your phone

03:17

and Google and find a Wikipedia page for that particular landmark.

03:22

Wouldn't it be easier if you had a map

03:25

with the Wikipedia links superimposed on the map?

03:28

Typically, an app idea like that will be just a fleeting thought,

03:33

and maybe you just forget about it and continue with your life.

03:37

Maybe you'll buy a domain.

03:39

And I know I've been guilty of buying tons of domains

03:42

that never turn into anything.

03:44

But in the world that I'm envisioning,

03:47

you could actually do something about it in that moment.

03:50

You pull out your phone and you talk to your AI assistant.

03:55

And the AI assistant is not just a passive listener.

03:59

It's going to start brainstorming with you.

04:01

It's going to make connections.

04:03

It'll find projects you've worked on in the past

04:06

that kind of look like this idea.

04:09

And let's say you want to give a clearer picture.

04:11

Well, pull out a napkin. Draw a mark.

04:14

Snap a picture

04:16

and boom, you send it to your agent.

04:20

Let's start strategizing and thinking of a road map.

04:23

Now you don't have a lot of time to chat with it, you're on the go.

04:26

So you send it a voice note.

04:30

Now you head home.

04:34

And you have a prototype.

04:35

You have a tangible thing that you could actually play with.

04:38

You have a starting point to make an application out of.

04:42

But it's not just a prototype. You also have a plan.

04:46

You have a plan of action that could turn this prototype

04:49

into a production app that you can share with the world.

04:54

Now, apps take time and they take money.

04:57

So we're going to set a budget of how much money we're going to spend

05:00

and how much time we're going to spend on this app.

05:05

To take a look behind the scenes,

05:08

it's not just magic, although it'll feel magical.

05:11

The plan editor becomes a plan source.

05:14

It recursively expands all the different tasks.

05:18

It goes out and assembles the tools.

05:20

And these are tools that, as developers, we use every day.

05:23

There's your code editor, your source control

05:26

and everything that we're used to.

05:28

And you have, of course, the code.

05:32

Now this is not just about coding.

05:33

It's about a new way of communicating with technology.

05:37

Being able to talk and draw and work with AI

05:42

to make your visions reality.

05:45

Let's go back to our plan.

05:47

We're going to run it.

05:49

It has four feature ideas.

05:51

The first one is user auth.

05:54

Every app needs that.

05:56

The second one is a way to collect feedback from users.

06:01

And the third one is a way to like places you've been to.

06:05

And the fourth one is a navigation.

06:08

The first branch is kind of easy.

06:10

The AI has seen login pages a trillion times and knows how to code it.

06:15

We'll take a look at the code. We'll merge it.

06:17

The second one is a little bit hard. Maybe it's a novel task.

06:21

But the AI here is prompting us

06:23

to add more compute.

06:26

So the easiest way to solve this problem

06:28

would be to pump in more compute.

06:31

Maybe that means a larger model,

06:32

or additional contacts or additional tokens

06:34

in order to solve this problem.

06:37

And the problem is solved.

06:38

The third branch is kind of easy.

06:40

Smooth sailing.

06:42

I look at it, it works, I merge it.

06:46

Now the fourth one is kind of difficult.

06:50

The AI seems confident

06:52

that it's not going to be able to solve this problem with more compute.

06:56

So it prompts me with an increased budget.

06:58

Now it's a hefty number,

07:00

and that's because it's not just going to recruit AIs.

07:03

It's going to go out and recruit people. It's going to post a bounty.

07:07

So in this case, we need a human in the loop.

07:09

And until we get AGI,

07:11

today, natural intelligence is going to be really, really important.

07:16

So we go out, we get a human.

07:20

That quota is going to also be assisted by AI,

07:23

and they're going to help me solve the problem.

07:26

I merge everything together

07:28

and it's just a matter of hours and 50-60 dollars or so,

07:33

I have an app I can deploy.

07:35

I deploy it, I share it with the world.

07:38

Now to step back a little bit,

07:40

notice that I didn't write a single line of code.

07:43

I was basically the creative heartbeat of the project.

07:47

I manage the project,

07:48

I manage both AI and people,

07:50

mediated by AI

07:53

in order to build this application.

07:56

And that fleeting thought that you had is suddenly an application.

08:02

So, you know, I can almost hear some of you thinking, like,

08:06

"OK, Amjad, this is this is great and all.

08:09

This is a fascinating vision

08:11

but it kind of looks too fantastic, two futuristic."

08:14

Well, I'm here to tell you it's kind of already happening.

08:18

So just a couple of weeks ago, an entrepreneur on Replit, Yoeri --

08:23

he's a technical recruiter by training, he's not a software engineer --

08:26

he learned enough code to start building his startup.

08:29

And thousands of miles across the world we have Akashdeep.

08:32

Akashdeep, a student in India, he comes from a farming family

08:36

and he can't afford a PC.

08:38

He has never had a PC. All he's had was his Android phone.

08:41

He started learning to code in Replit just a few months ago,

08:46

and then decided to go and start making money on the platform.

08:50

Now he makes more money than his entire family

08:54

and he can afford a lot of different computers, not just one.

08:57

And now he's joined forces with Yoeri to build that startup.

09:01

You know, today we talk about the Fortune 500,

09:04

and it takes a ton of employees to build a big company like that.

09:08

But I think in the future,

09:11

when AI is helping everyone build their dreams,

09:15

we’re going to be talking about the Fortune 5000000.

09:18

And again, this is not just --

09:21

This is not just a fantasy.

09:23

We're already building this.

09:25

Last week we announced that we're open-sourcing our AI models,

09:30

and we're making it free for all our users

09:34

because we think that's a massive step up for all of humanity.

09:39

AI is not just a tool, it's a ladder that equalizes opportunity.

09:43

And that opens up horizons for people that are typically on the sidelines.

09:48

So I'll leave you with this.

09:50

Imagine that

09:52

the American dream,

09:54

not just --

09:56

not just in one place,

09:59

but actually in the cloud.

10:02

Thank you.

10:03

(Applause)