Interactive: Visualizing Major Tech Acquisitions (1991-2018)
Connect with us

Technology

Visualizing Major Tech Acquisitions (1991-2018)

Published

on

Launch the interactive version below, or go to our story for simpler, static images

Interactive: Visualizing Major Tech Acquisitions (1991-2018)

To stay successful in tech, companies must find a way to walk alongside the cutting edge of innovation.

Companies do this partially by devoting a large portion of their resources towards research and development (R&D) – but to hedge their bets, these companies also are in constant negotiations to gobble up new startups that could be strategic to their futures.

In this giant game of Pac-Man, most of the acquisitions are small and sequential, just like the dots that make up the arcade game’s classic maze. That said, sometimes these tech giants get lucky, such as in Facebook’s acquisition of Instagram, and buyouts turn into power-ups that can change the dynamics of the game entirely.

Tech Acquisitions by Company

Today’s interactive infographic comes to us from IG and it allows you to compare the tech acquisitions made by dominant companies such as Facebook, Apple, IBM, or Cisco.

Acquisitions can be sorted by industry filters (i.e. e-commerce, security, etc.) and different acquiring companies can be switched in. There are also different tabs that show total M&A expenditures by company, M&A activity by CEO, and frequency of acquisitions measured in quantity per year.

The Big Picture

Before we go into specific acquisitions, let’s look at the big picture using images pulled from the interactive version of the graphic.

Here is a comparison of the number of acquisitions made since 1991, for each major company on the list:

Number of tech acquisitions

Google has made the most acquisitions, averaging about 10 to 11 per year. That adds up to a total of 214 since the company was founded.

Tech acquisitions by dollar amount

Interestingly, while Google has had the most acquisitions, it only ranks in 6th out of this group in terms of dollars spent. Giants like Microsoft, Cisco, and IBM may make fewer acquisitions, but the companies they do buy tend to be more established with higher valuations.

As an example of this: Microsoft bought LinkedIn in 2016 for $26.2 billion. That’s more than Amazon has spent on all of its acquisitions (including Whole Foods) combined.

The Big Five

Finally, here’s a comparison of the big five – Amazon, Apple, Microsoft, Facebook, and Google (Alphabet) – which are also the five largest companies by market capitalization in the United States.

The Big Five Tech Companies

On the interactive version, it’s possible to highlight each acquisition to get the deal value and company name.

But, even on the static version above, it’s noticeable that each of the Big Five has made at least one real sizable acquisition. Those are the circles that stand out the most on the timeline:

  • 2011: Google buys Motorola for $12.5 billion
  • 2014: Facebook buys WhatsApp for $19 billion, and Apple buys Beats for $3 billion
  • 2016: Microsoft buys LinkedIn for $26.2 billion
  • 2017: Amazon buys Whole Foods for $13.7 billion

The gobbling activity for these Big Five has continued into 2018, as well.

In fact, just in June 2018, Microsoft announced the acquisition of code repository GitHub for $7.5 billion. The deal is expected to close by the end of the year.

Subscribe to Visual Capitalist
Click for Comments

Technology

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.

Published

on

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.

Continue Reading

Subscribe

Popular