With AI, anyone can be a coder now | Thomas Dohmke
TED TechJuly 05, 202414:3913.42 MB

With AI, anyone can be a coder now | Thomas Dohmke

What if you could code just by talking out loud? GitHub CEO Thomas Dohmke shows how, thanks to AI, the barrier to entry to coding is rapidly disappearing — and creating software is becoming as simple (and joyful) as building LEGO. In a mind-blowing live demo, he introduces Copilot Workspace: an AI assistant that helps you create code when you speak to it, in any language.

Learn more about our flagship conference happening this April at attend.ted.com/podcast


Hosted on Acast. See acast.com/privacy for more information.

What if you could code just by talking out loud? GitHub CEO Thomas Dohmke shows how, thanks to AI, the barrier to entry to coding is rapidly disappearing — and creating software is becoming as simple (and joyful) as building LEGO. In a mind-blowing live demo, he introduces Copilot Workspace: an AI assistant that helps you create code when you speak to it, in any language.

Learn more about our flagship conference happening this April at attend.ted.com/podcast


Hosted on Acast. See acast.com/privacy for more information.

[00:00:00] TED Audio Collective I was first introduced to the world of coding as a teenager. I joined an after-school program in Seattle called the Technology Access Foundation, where inner-city kids learned the basics of computer programming.

[00:00:21] Twice a week during the academic year, we immersed ourselves in languages like C-sharp, ASP.NET, and JavaScript. Today, however, those are almost all ancient or obsolete languages. We are now in a world where developing software relies less on human knowledge

[00:00:37] and much more on AI tools that can build and develop without code. I'm Sherelle Dorsey, and this is TED Tech. Today, we hear from GitHub CEO Thomas Dohmke. This talk is about his company's efforts to help everyone become a developer

[00:00:56] and create projects that can change the world, all without learning to program. Let's listen in. Imagine this. In 2030, the CFO of a Fortune 100 company is a bot. I'm Paul Meikleman, and on Imagine This, we'll be exploring possible futures and the implications they hold for organizations.

[00:01:27] Joining me will be BCG's top experts as well as my co-host Jean, BCG's conversational Gen AI agent. Blending human creativity with AI innovation, this podcast promises an unmatched listening journey. Join us on Imagine This from BCG.

[00:01:44] Here at Shortwave Space Camp, we escape our everyday lives to explore the mysteries and quirks of the universe. We find weird, fun, interesting stories that explain how the cosmos is partying all around us. From stars to dwarf planets to black holes and beyond, we've got you.

[00:02:02] Listen now to the Shortwave podcast from NPR. You know, I'm one of these adults that actually still loves playing with LEGO. I loved them way back in the 80s in Berlin when I grew up, and I still love them.

[00:02:19] And these days, I build LEGO with my kids on Saturday afternoons. And the reason that my love for LEGO has remained evergreen is quite simply that LEGO is a system for realizing creativity with almost no barrier to entry.

[00:02:35] Now, I'm not only a LEGO dad, I'm also the CEO of GitHub. And if you don't know GitHub, you can think of it as the home of coding. It's where all the software developers, the chief nerds of our society, collaborate together.

[00:02:50] And it's part of our mission to make it as easy as possible for every developer to build small and big ideas with code. But in contrast to LEGO, the process of building software feels daunting to most people.

[00:03:06] This all started to change when Chet Chippity came along in late 2022. Now we live in a world where intelligent machines understand us as much as we understand them. All because of language. And this will forever change the way we create software.

[00:03:24] Up until now, in order to create software, you had to be a professional software developer. You had to understand, speak and interpret the highly complex, sometimes nonsensical language of a machine that we call code. Modern code still looks like hieroglyphics to most people.

[00:03:44] Here's an example from the early 1940s, the world's first computer programming language called Plan-Kalkül. It set the foundation for the modern code that we use today. It's a few numbers, some bubbles and some big-ass brackets. Not much humanity here, right?

[00:04:03] Flash forward about 20 years to the programming language called COBOL. COBOL was invented during the Eisenhower years, but it remains an important language for many of our largest financial institutions. Wall Street, your savings account, your credit cards all run on this today.

[00:04:22] Flash forward another 30 years to 1991 and we saw the birth of Python, one of the most popular programming languages in this era of AI. In 80 years, we went from bubbles to brackets to blips of English, and yet we got nowhere near as close as the intuitiveness of human language.

[00:04:43] But then came June 2020 and we got early access to OpenAI's large language model, then called GPT-3. It was COVID, we were all on lockdown, and I remember we were on a video call together.

[00:04:56] We fed random programming exercises into this raw model and like magic, it solved 93% of them during the first few takes. We at GitHub recognized we had something remarkable in our hands and we quickly turned around a novel developer tool called GitHub Copilot,

[00:05:15] an AI assistant that predicts and completes code for software developers. Copilot is now the most adopted AI developer tool on the planet. The age of programming has been reborn, but the possibilities of the breakthrough went further than just these business results.

[00:05:33] Because the large language models that power ChatGPT and Copilot are trained on a vast library of human information. They understand and interpret nearly every major human language. They seem to get us. We have struck a new fusion between the language of a human and a machine.

[00:05:57] With Copilot, any person can now build software in any human language with a single written prompt. Goodbye to the bubbles and the big S-bracket. This is the most profound breakthrough to technology since the genesis of software development itself. Today, there are over 100 million developers on GitHub.

[00:06:24] That's about 1% of the world's population, plus minus. I think that number is about to explode. We started it all with the original Copilot, or how we say the OG Copilot, and it really just predicted and completed code in the editor.

[00:06:40] You can think of the editor as the Google Docs for developers. When you have an open doc open, you know how it is. Empty page, what do I actually want to do? And I mentioned Lego, so let's build a 3D Lego brick on a web page.

[00:06:54] What developers do, they start typing in the JavaScript file, create a function to create a Lego brick. You can see here this gray text, we call this ghost text. This is coming from the large English model.

[00:07:08] Now I can just press the tab key and press enter, or I can just do function, draw Lego brick. Here again you see ghost text from Copilot right away available for me.

[00:07:18] And if I like what I'm seeing here, so I get into a bit more mode of writing and understanding, I can just accept this. Developers love that, right?

[00:07:27] Because instead of writing 10 lines of code themselves or copy and pasting them from the internet, they get them right in their editor. They can stay in the flow. Now what the OG Copilot didn't offer me is a way to interact with this.

[00:07:39] I cannot ask questions, I cannot instruct it to do different things. Last year we launched a new feature, Copilot Chat. And you can think about it as chat GPT in your editor.

[00:07:49] Now, you know, similar to chat GPT, it streams the response and it gives me not only some code, but it actually gives me an explanation. And so you can kind of see here the idea of this empowering developers and people that want to learn development.

[00:08:01] But I want to show you something else, this little mic icon. So I can use that to speak to Copilot, and I want to ask it in German what that code does that is on the left side in the editor.

[00:08:12] Kannst du mir erklären, was dieser Quellcode macht? And now we know Copilot responds again, but it responds in German to me, right? So it says, if I loosely translate, yes of course, this JavaScript code defines a function named draw Lego brick.

[00:08:26] So you get the idea here, a six year old in Berlin, in Mumbai and Rio can now explore coding without their parents being around or even having a technical background.

[00:08:36] Now what you also see is you still need to kind of figure out how you put that all together, right?

[00:08:44] So I have a lot of technical stuff here, I have code I have to iterate on my machine, I have to figure out how to deploy this to the cloud so I can share it with my friends.

[00:08:52] But here's my Lego brick now, this is what it looks like if I've done all these steps as a developer.

[00:08:57] It's a nicely rotating brick, I can actually use my mouse to turn it around, these are the anti-studs here, the studs, there's nice lighting effects, you can even zoom into this and zoom out of this.

[00:09:06] Now I don't want to do all this developer stuff anymore, I just want to channel my creativity straight into reality. And so for the first time ever on stage, I'm going to show you a new product that we call Copilot Workspace that does exactly that.

[00:09:20] I can just see a task and I can enter a task and so now I have my Lego brick, I want to now expand the Lego brick into a Lego house.

[00:09:27] I can save my task and now what happens is that Copilot Workspace analyzes what I already have and then describes what it proposes to me. Basically, it reframes my ask into a plan or a specification.

[00:09:38] It's all in natural language, it uses some file names of course, but there is no code here, it's all describing it in English and I can actually go into this and edit it.

[00:09:47] And can make changes to this line or can add another item if I feel like the plan is not exactly what I want.

[00:09:52] I can go a step further and generate a plan and now an agent runs through all my files I already have and figures out how do I need to modify those files or do I need to add files to my repository.

[00:10:02] So, it wants to add a create Lego house function and call the create Lego house afterwards. And now Copilot uses my task, my specification, my plan to write code for me. So here's a button that lets me open a live preview.

[00:10:16] Now the bricks fall from the sky and I have a Lego house. And this is the power of streaming my creativity into reality with natural language. Now one last thing, thank you Copilot, you have always to be nice to the AI. Three leaps in three years.

[00:10:36] Three leaps that are more progress to the accessibility of computer programming than we have made in the last 100. Remember how I said that 1% of the world's population is a developer? Now you can see how this will change.

[00:10:50] Copilot Workspace may still be a developer tool right now, but soon enough these kind of developer tools will become mainstream. Because going forward, every person, no matter what language they speak, will also have the power to speak machine.

[00:11:04] Any human language is now the only skill that you need to start computer programming. This will lead to a globalized groundswell of software developers and it will reshape the geography of our global economy.

[00:11:17] And because of this, I think by 2030, maybe even sooner, we will have more than 1 billion software developers on GitHub. Think about that. 10% of the world's population will not only control a computer, but will also be able to create software just as if they were riding a bicycle.

[00:11:37] This will generate a new renaissance of human creativity with software. Now anyone could have a brilliant idea right now. A website, an application, a cool computer game, an amazing song, maybe even a cure for something.

[00:11:52] For example, last year over a couple of weeks I built an app that tracks all the flights I've ever taken in my life. Now I know what you're thinking. What a freaking nerd. And yeah, it's true, I love building stuff like this.

[00:12:08] And with the help of AI, now I can do this in English or in German before I even finish a glass of wine. And soon enough this will be true for everyone here. The floodgates of nerdy tooth have swung wide open.

[00:12:22] Now this doesn't mean that everyone will become a professional software developer, or even that they should. The profession of a professional software developer is not going anywhere. There will always be demand for those that design and maintain the largest software systems in the world.

[00:12:45] We're adding millions of lines of code every single day to ever more complex systems. And we're barely keeping up with maintaining the existing ones. Like any infrastructure in this world out there, we need real experts to preserve and renew it.

[00:13:00] The point here is not a will or a should. It's that anyone can. All because the most powerful system that we have, any human language, is now fused to the language of a machine.

[00:13:16] And very soon, building software will be just as simple and joyful as stacking a Lego. Dankeschön. Gosh, one billion developers makes GitHub sound more like YouTube and TikTok than it is today. Just super exciting. Got to ask you one question, perhaps the elephant in the room.

[00:13:43] Amazing talk. So you said the developer is still in charge. You also said we've had three leaps in three years. Fast forwarding a little bit, do you think humans will still need to be in the loop?

[00:13:56] Or will these AI systems be able to autonomously build and maintain software? The way I always think about that and talk about it is that we call it co-pilot for a reason. We need a pilot. We need a pilot that is creative, that can decide what to do.

[00:14:10] It's kind of like a Lego set. You need to take this big problem and break it down into smaller problems, into small building blocks. And for that, you need a systems thinker. You need a human that can figure out, am I building a point of sale system?

[00:14:22] Am I building an iPhone app? Am I building a cool computer game? Am I building the next Facebook? Those are very different systems. Now, these building blocks, they will grow in size. Today it's a couple of lines of code, maybe a whole file.

[00:14:35] In the future, it might be a whole subsystem. So I get more work taking off my shoulders, but I'm still there covering the large system. And as I mentioned, we're still running Cobol systems from the 60s. So we have lots of work to do. Absolutely.

[00:14:49] So we will be in charge orchestrating these systems at a higher level of abstraction. Thomas Domke, everybody. Thank you very much. NFTs, GPUs, grokking, capacitance. The tech world is full of a lot of lingo. Keep up with the latest acronyms and technology news with TED's new newsletter.

[00:15:16] TED Talks Tech will bring you tech headlines, talks, podcasts, and more on a biweekly basis so you can easily keep up with all things tech and AI. Subscribe now at the link in our show notes. I'm Sherelle Dorsey. Thanks for listening and talk to you again next week.