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How Facebook is Using Machine Learning to Map the World Population

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When it comes to knowing where humans around the world actually live, resources come in varying degrees of accuracy and sophistication.

Heavily urbanized and mature economies generally produce a wealth of up-to-date information on population density and granular demographic data. In rural Africa or fast-growing regions in the developing world, tracking methods cannot always keep up, or in some cases may be non-existent.

This is where new maps, produced by researchers at Facebook, come in. Building upon CIESIN’s Gridded Population of the World project, Facebook is using machine learning models on high-resolution satellite imagery to paint a definitive picture of human settlement around the world. Let’s zoom in.

Connecting the Dots

Will all other details stripped away, human settlement can form some interesting patterns. One of the most compelling examples is Egypt, where 95% of the population lives along the Nile River. Below, we can clearly see where people live, and where they don’t.

View the full-resolution version of this map.

facebook population density egypt map

While it is possible to use a tool like Google Earth to view nearly any location on the globe, the problem is analyzing the imagery at scale. This is where machine learning comes into play.

Finding the People in the Petabytes

High-resolution imagery of the entire globe takes up about 1.5 petabytes of storage, making the task of classifying the data extremely daunting. It’s only very recently that technology was up to the task of correctly identifying buildings within all those images.

To get the results we see today, researchers used process of elimination to discard locations that couldn’t contain a building, then ranked them based on the likelihood they could contain a building.

process of elimination map

Facebook identified structures at scale using a process called weakly supervised learning. After training the model using large batches of photos, then checking over the results, Facebook was able to reach a 99.6% labeling accuracy for positive examples.

Why it Matters

An accurate picture of where people live can be a matter of life and death.

For humanitarian agencies working in Africa, effectively distributing aid or vaccinating populations is still a challenge due to the lack of reliable maps and population density information. Researchers hope that these detailed maps will be used to save lives and improve living conditions in developing regions.

For example, Malawi is one of the world’s least urbanized countries, so finding its 19 million citizens is no easy task for people doing humanitarian work there. These maps clearly show where people live and allow organizations to create accurate population density estimates for specific areas.

rural malawi population pattern map

Visit the project page for a full explanation and to access the full database of country maps.

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Technology

Nvidia is Worth More Than All of These Companies Combined

Gain a unique perspective on the market cap of Nvidia in this simple graphic.

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Putting the Market Cap of Nvidia Into Perspective

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.

Nvidia’s massive rise in the AI era has been well-documented, but did you know that it’s currently the world’s third most valuable company?

To put the massive market cap of Nvidia into perspective, we’ve put it side by side with a collection of other major U.S. tech companies.

All figures were sourced from Companiesmarketcap.com, and are as of May 23, 2024.


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Data and Takeaways

All of the numbers we used to create this graphic are included in the table below.

CompanyMarket Cap
(as of May 23, 2024)
Nvidia$2.5T
Meta$1.2T
Tesla$553B
Netflix$272B
AMD$257B
Intel$128B
IBM$157B

These figures are even more impressive when you consider that at the beginning of 2020, Nvidia was valued at a relatively tiny $145 billion.

Since then, the company has greatly surpassed other American chipmakers like Intel and AMD. This growth is due to several key factors:

  • Expansion into AI and data centers: Nvidia’s chips are highly effective for AI training, making them essential for companies engaged in machine learning and generative AI
  • Advancements in AI software: Nvidia has developed AI software platforms, such as CUDA-X and TensorRT, which are widely used by researchers.
  • Strong financial performance: Nvidia has consistently delivered strong financial results in recent years, with substantial revenue growth.

Closing in on Apple

With Nvidia’s latest stock surge (up 13.5% over the past five days ending May 24, 2024), the company could possibly overtake Apple to become the world’s second most valuable company.

Microsoft, another major player in AI, holds the #1 spot with a market cap of $3.2 trillion.

See More Visuals on Nvidia

If you enjoyed this graphic, be sure to check out this graphic that breaks down Nvidia’s revenue by product line, from 2019 to 2024.


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