Charted: Four Decades of U.S. Tech IPOs

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June 19, 2024 Graphics/Design:

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Charting Four Decades of U.S. Tech IPOs

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.

Big technology companies have been enjoying a wave of stock market success, driving much of the growth in the S&P 500 index since the pandemic. Five of the companies currently dubbed the “Magnificent Seven” are behemoths in the tech space, with market capitalizations rivaling the size of entire countries’ GDPs.

We visualize the number of tech IPOs on American exchanges from 1980–2023. Data is sourced from “Initial Public Offerings: Updated Statistics” a database run by economist Jay R. Ritter, from the Warrington College of Business, University of Florida.

ℹ️ Tech stocks are defined as internet-related stocks plus other technology stocks, not including biotech New Tech Listings in 2021 Broke a 20-Year-Record

From the heydays of the Dotcom boom, when more than 350 companies hit the exchanges in 1999, the number of tech IPOs has dropped steeply over the years.

In fact, the Dotcom boom, driven by investor enthusiasm for internet technologies, and subsequent bust, due to a lack of capital and business viability, left a significant impact on the market. Tech IPOs stayed in the double-digits for the next 20 years.

YearU.S. Tech IPOs 198022 198172 198242 1983173 198450 198537 198677 198759 198828 198935 199032 199171 1992115 1993127 1994115 1995205 1996276 1997174 1998113 1999370 2000261 200124 200220 200318 200461 200545 200648 200776 20086 200914 201033 201136 201240 201345 201453 201538 201621 201730 201840 201938 202048 2021126 20226 20239

However, 2021 saw a significant uptick after

Charted: Stock Buybacks by the Magnificent Seven

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June 18, 2024 Graphics/Design:

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Charted: Stock Buybacks of the Magnificent Seven

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.

By 2025, Goldman Sachs predicts that total U.S. stock buybacks will exceed $1 trillion. The bank sees this growth being driven by strong tech earnings growth and lower rates.

But what are buyback amounts like for the largest tech companies today?

This graphic looks at the total value of shares each Magnificent Seven company has repurchased in the last four quarters using data from their latest financial statements.

What is a Stock Buyback?

A stock buyback is when a company buys their own shares to reduce the number of available shares on the market. Companies may choose to buy back stock to return value to shareholders. Having fewer shares available improves earnings per share, and may drive up the stock price.

Buying back stocks can also come with risks, such as using up cash that would otherwise be put toward growing the business.

Stock Buybacks of Tech Titans

We gathered data from company financial statements to see how stock buyback amounts differed among the Magnificent Seven. Each total represents what companies reported from June 1, 2023 to June 1, 2024.

As we can see, the tech companies in the Magnificent Seven have been the ones buying back their stock over the past year.

CompanyTotal Stock BuybacksBuybacks as a % of Market Cap Apple$83B2.8% Alphabet (Google)$63B2.9% Meta$25B2.0% Microsoft$20B0.6% Nvidia$17B0.6% Amazon$0B0.0% Tesla$0B0.0%

Values rounded to the nearest billion. Company market caps are as of June 6, 2024.

Apple had by far the most share repurchases, raising its diluted earnings per share from $1.26 to $1.53. Going forward, Apple authorized an additional $110 billion for share repurchases, a U.S. record. The board says the repurchases are in light of their “confidence in Apple’s future and the value we see in our stock.”

On the flip side, both Amazon and Tesla did not issue stock buybacks in the last four quarters. Amazon’s CFO

Ranked: The 20 Biggest Tech Companies by Market Cap

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June 17, 2024 Graphics/Design:

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Ranked: The 20 Biggest Tech Companies by Market Cap

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.

The world’s 20 biggest tech companies are worth over $20 trillion in total. To put this in perspective, this is nearly 18% of the stock market value globally.

This graphic shows which companies top the ranks, using data from Companiesmarketcap.com.

A Closer Look at The Top 20

Market capitalization (market cap) measures what a company is worth by taking the current share price and multiplying it by the number of shares outstanding. Here are the biggest tech companies according to their market cap on June 13, 2024.

RankCompanyCountry/RegionMarket Cap 1AppleU.S.$3.3T 2MicrosoftU.S.$3.3T 3NvidiaU.S.$3.2T 4AlphabetU.S.$2.2T 5AmazonU.S.$1.9T 6MetaU.S.$1.3T 7TSMCTaiwan$897B 8BroadcomU.S.$778B 9TeslaU.S.$582B 10TencentChina$453B 11ASMLNetherlands$415B 12OracleU.S.$384B 13SamsungSouth Korea$379B 14NetflixU.S.$281B 15AMDU.S.$258B 16QualcommU.S.$243B 17SAPGermany$225B 18SalesforceU.S.$222B 19PDD Holdings (owns Pinduoduo)China$212B 20AdobeU.S.$206B

Note: PDD Holdings says its headquarters remain in Shanghai, China, and Ireland is used for legal registration for its overseas business.

Apple is the largest tech company at the moment, having competed with Microsoft for the top of the leaderboard for many years. The company saw its market cap soar after announcing its generative AI, Apple Intelligence. Analysts believe people will upgrade their devices over the next few years, since the new features are only available on the iPhone 15 Pro or newer.

Microsoft is in second place in the rankings, partly thanks to enthusiasm for its AI software which is already generating revenue. Rising profits also contributed to the company’s value. For the quarter ended March 31, 2024, Microsoft increased its net income by 20% compared to the same quarter last year.

Nvidia follows closely behind with the third-highest market cap, rising more than eight times higher compared to its value at the start of 2023. The company has recently announced higher profits, introduced

Charted: How Many Data Centers do Major Big Tech Companies Have?

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June 4, 2024 Graphics/Design:

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How Many Data Centers do Major Big Tech Companies Have?

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.

The Big Tech companies are often compared against each other in many ways: how much money they make, market capitalization, and the newest flavor, generative AI capabilities.

But in their great strides to capture the digital realm, how many huge data facilities do they need for all their services, analytics, and storage?

Sourcing information from Meta, Google, Microsoft, and some third-party estimates for Apple and Amazon, we find out.

Ranked: Big Tech’s Data Facilities

Cloud computing giants—Microsoft and Amazon—have data centers in the triple-digits to accommodate their customers’ burgeoning business demands.

However, there’s no one standard of how big a data center needs to be, so quantity doesn’t automatically translate into greater capacity.

Big Tech CompanyData Centers Microsoft**300 AWS*215 Google25 Meta24 Apple*10
Note: *Third-party estimates vary depending on the source. AWS is usually listed between 160–220 and Apple from 8–10. **Microsoft lists their count as “300+.”

According to Statista, AWS still maintains the biggest market share in the cloud computing segment (31%) even as Microsoft Azure edges ever closer (25%).

In fact, Amazon is aiming to spend $150 billion on more facilities over the next 15 years. Estimates say 26 data centers are currently under construction. All of this, of course, to chase the AI boom.

Despite dominating our digital lives however, Big Tech aren’t the only players when it comes to data center metrics. For example, Digital Realty, a colocation data center provider, would rank alongside Microsoft with 300+ data facilities.

Learn More about Big Tech and AI from Visual Capitalist

If you enjoyed this post, and you’re wondering which Big Tech players have made their forays into AI, check out Ranked: The Most Popular AI Tools. We visualize the most popular AI tools of 2023 along with recent tech adoption cycles and the software products that defined them.

Visualizing the Training Costs of AI Models Over Time

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June 4, 2024

See this visualization first on the Voronoi app.

Visualizing the Training Costs of AI Models Over Time

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.

Training advanced AI models like OpenAI’s ChatGPT and Google’s Gemini Ultra requires millions of dollars, with costs escalating rapidly.

As computational demands increase, the expenses for the computing power necessary to train them are soaring. In response, AI companies are rethinking how they train generative AI systems. In many cases, these include strategies to reduce computational costs given current growth trajectories.

This graphic shows the surge in training costs for advanced AI models, based on analysis from Stanford University’s 2024 Artificial Intelligence Index Report.

How Training Cost is Determined

The AI Index collaborated with research firm Epoch AI to estimate AI model training costs, which were based on cloud compute rental prices. Key factors that were analyzed include the model’s training duration, the hardware’s utilization rate, and the value of the training hardware.

While many have speculated that training AI models has become increasingly costly, there is a lack of comprehensive data supporting these claims. The AI Index is one of the rare sources for these estimates.

Ballooning Training Costs

Below, we show the training cost of major AI models, adjusted for inflation, since 2017:

YearModel NameModel Creators/ContributorsTraining Cost (USD)
Inflation-adjusted 2017TransformerGoogle$930 2018BERT-LargeGoogle$3,288 2019RoBERTa LargeMeta$160,018 2020GPT-3 175B (davinci)OpenAI$4,324,883 2021Megatron-Turing NLG 530BMicrosoft/NVIDIA$6,405,653 2022LaMDAGoogle$1,319,586 2022PaLM (540B)Google$12,389,056 2023GPT-4OpenAI$78,352,034 2023Llama 2 70BMeta$3,931,897 2023Gemini UltraGoogle$191,400,000

Last year, OpenAI’s GPT-4 cost an estimated $78.4 million to train, a steep rise from Google’s PaLM (540B) model, which cost $12.4 million just a year earlier.

For perspective, the training cost for Transformer, an early AI model developed in 2017, was $930. This model plays a foundational role in shaping the architecture of many large language models used today.

Google’s AI model, Gemini Ultra, costs even more, at a staggering $191 million. As of early 2024, the model outperforms GPT-4 on several metrics, most notably across the Massive Multitask Language Understanding (MMLU) benchmark. This benchmark serves