Chart: How Long Does It Take to Hit 50 Million Users?
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How Long Does It Take to Hit 50 Million Users?

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How Long Does It Take to Hit 50 Million Users?

How Long Does It Take to Hit 50 Million Users?

The Chart of the Week is a weekly Visual Capitalist feature on Fridays.

Imagine it’s the year 1960, and you’re an entrepreneur that’s about to launch the next big thing.

Let’s assume that your product is actually pretty revolutionary, and that you’re going to receive widespread buzz and word-of-mouth traction. How quickly do you think it could be adopted by millions of users?

Before the internet and consumption of digital goods, the use of a product could only spread as fast as you could manufacture the physical good. You would first need many millions of dollars in capital, a plant, a workforce, and inventory. Then, once the product is ready for distribution, you’d need mass advertising, word-of-mouth, sales channels, and press coverage to stand a chance.

Even then, if the product is really revolutionary, you’re looking at a decade or more for it to get widespread adoption.

Atoms Versus Bytes

Automobiles took 62 years to be adopted by 50 million users. The telephone took three years just to be in the homes of 50,000 people.

But these are both physical goods that need raw materials, skilled workers to produce, and economies of scale. They are made of atoms – and atoms must abide by the laws of physics.

In the modern era, you don’t have to produce a physical good. All you need to do is produce a useful piece of code that be replicated or re-used indefinitely at a marginal cost near zero, and it can spread like a wildfire.

Product / TechnologyTime it Took to Hit 50 Million Users
Airlines64 years
Automobiles62 years
Telephone50 years
Electricity46 years
Credit Cards28 years
Television22 years
ATMs18 years
Computers14 years
Mobile Phones12 years
Internet7 years
Facebook4 years
WeChat1 year
Pokemon Go19 days

As you can see, the transition from physical to digital goods has affected adoption rates, but so has the growing power of network effects.

Metcalfe’s Law

Metcalfe’s Law states the effect of a network is proportional to the square of the number of connected users of the system (n2).

Within the context above, it simply means that each additional user of a good or service adds additional value to others in that network. New goods or services in the digital realm can harness this network effect to gain users at unprecedented rates. It’s why social media, apps, and the internet were able to take off so quick.

It’s also why the augmented reality game Pokémon Go was able to reach a mind-blowing 50 million users in just 19 days.

And now, with unparalleled connectivity and more than four billion internet users globally, the next big thing could hit that milestone even faster than Pokémon Go. Instead of almost three weeks, it might do so in a few days – or even a few hours.

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Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

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Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

  • Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
  • Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
  • Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

  • Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
  • Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
  • Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

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