Technology
How Many Millions of Lines of Code Does It Take?
How Many Millions of Lines of Code Does It Take?
Today’s data visualization comes from David McCandless from Information is Beautiful. Buy their awesome book called Knowledge is Beautiful – we own the physical version, and it’s full of great data visualizations.
How many millions of lines of code does it take to make the modern program, web service, car, or airplane possible?
The range is extraordinary: the average iPhone app has less than 50,000 lines of code, while Google’s entire code base is two billion lines for all services. And interestingly, the code behind machines such as fighter jets, popular video game engines, and even the Large Hadron Collider fall somewhere in between these two extremes.
Increasing Complexity
A million lines of code, if printed, would be about 18,000 pages of text. That’s 14x the length of War and Peace.
It’s more than what was needed to run old technologies like the Space Shuttle, a pacemaker, or even the game engine of Quake 3 – but it’s not enough to be the driving force behind the modern software that’s used in everyday life today.
- The control software to run a U.S. military drone uses 3.5 million lines of code.
- A Boeing 787 has 6.5 million lines behind its avionics and online support systems.
- Google Chrome (browser) runs on 6.7 million lines of code (upper estimate).
- A Chevy Volt uses 10 million lines.
- The Android operating system runs on 12-15 million lines.
- The Large Hadron Collider uses 50 million lines.
- Not including backend code, Facebook runs on 62 million lines of code.
- With the advent of sophisticated, cloud-connected infotainment systems, the car software in a modern vehicle apparently uses 100 million lines of code. This is according to Wired magazine.
- All Google services combine for a whopping 2 billion lines.
Applying the math above – that means it would take 36,000,000 pages to “print out” all of the code behind all Google services. That would be a stack of paper 2.2 mi (3.6 km) high!
Digital Transformation
Mapped: The Number of AI Startups By Country
Over the past decade, thousands of AI startups have been funded worldwide. See which countries are leading the charge in this map graphic.
Mapped: The Number of AI Startups By Country
This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.
Amidst the recent expansion of artificial intelligence (AI), we’ve visualized data from Quid (accessed via Stanford’s 2024 AI Index Report) to highlight the top 15 countries which have seen the most AI startup activity over the past decade.
The figures in this graphic represent the number of newly funded AI startups within that country, in the time period of 2013 to 2023. Only companies that received over $1.5 million in private investment were considered.
Data and Highlights
The following table lists all of the numbers featured in the above graphic.
| Rank | Geographic area | Number of newly funded AI startups (2013-2023) |
|---|---|---|
| 1 | 🇺🇸 United States | 5,509 |
| 2 | 🇨🇳 China | 1,446 |
| 3 | 🇬🇧 United Kingdom | 727 |
| 4 | 🇮🇱 Israel | 442 |
| 5 | 🇨🇦 Canada | 397 |
| 6 | 🇫🇷 France | 391 |
| 7 | 🇮🇳 India | 338 |
| 8 | 🇯🇵 Japan | 333 |
| 9 | 🇩🇪 Germany | 319 |
| 10 | 🇸🇬 Singapore | 193 |
| 11 | 🇰🇷 South Korea | 189 |
| 12 | 🇦🇺 Australia | 147 |
| 13 | 🇨🇭 Switzerland | 123 |
| 14 | 🇸🇪 Sweden | 94 |
| 15 | 🇪🇸 Spain | 94 |
From this data, we can see that the U.S., China, and UK have established themselves as major hotbeds for AI innovation.
In terms of funding, the U.S. is massively ahead, with private AI investment totaling $335 billion between 2013 to 2023. AI startups in China raised $104 billion over the same timeframe, while those in the UK raised $22 billion.
Further analysis reveals that the U.S. is widening this gap even more. In 2023, for example, private investment in the U.S. grew by 22% from 2022 levels. Meanwhile, investment fell in China (-44%) and the UK (-14.1%) over the same time span.
Where is All This Money Flowing To?
Quid also breaks down total private AI investment by focus area, providing insight into which sectors are receiving the most funding.
| Focus Area | Global Investment in 2023 (USD billions) |
|---|---|
| 🤖 AI infrastructure, research, and governance | $18.3 |
| 🗣️ Natural language processing | $8.1 |
| 📊 Data management | $5.5 |
| ⚕️ Healthcare | $4.2 |
| 🚗 Autonomous vehicles | $2.7 |
| 💰 Fintech | $2.1 |
| ⚛️ Quantum computing | $2.0 |
| 🔌 Semiconductor | $1.7 |
| ⚡ Energy, oil, and gas | $1.5 |
| 🎨 Creative content | $1.3 |
| 📚 Education | $1.2 |
| 📈 Marketing | $1.1 |
| 🛸 Drones | $1.0 |
| 🔒 Cybersecurity | $0.9 |
| 🏭 Manufacturing | $0.9 |
| 🛒 Retail | $0.7 |
| 🕶️ AR/VR | $0.7 |
| 🛡️ Insurtech | $0.6 |
| 🎬 Entertainment | $0.5 |
| 💼 VC | $0.5 |
| 🌾 Agritech | $0.5 |
| ⚖️ Legal tech | $0.4 |
| 👤 Facial recognition | $0.3 |
| 🌐 Geospatial | $0.2 |
| 💪 Fitness and wellness | $0.2 |
Attracting the most money is AI infrastructure, research, and governance, which refers to startups that are building AI applications (like OpenAI’s ChatGPT).
The second biggest focus area is natural language processing (NLP), which is a type of AI that enables computers to understand and interpret human language. This technology has numerous use cases for businesses, particularly in financial services, where NLP can power customer support chatbots and automated wealth advisors.
With $8 billion invested into NLP-focused startups during 2023, investors appear keenly aware of this technology’s transformative potential.
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