Machine Intelligence 2.0 in charts and graphs

Google is doing it. So is Microsoft. And Facebook, too. So are Apple, IBM, and Amazon.

In fact, every major technology company is investing in machine intelligence to improve their existing products or to develop entirely new ones.

This transformative technology is poised to affect just about every industry out there. VB Profiles partnered with Shivon Zilis to better understand its impact and to present the Machine Intelligence 2.0 landscape.

Above: This chart is part of VB Profiles Machine Intelligence Series. (Disclosure: VB Profiles is a cooperative effort between VentureBeat and Spoke Intelligence.)

You can download a high-resolution version of the Machine Intelligence 2.0 landscape here.

Here are a few key takeaways from the Machine Intelligence landscape:

• 247 companies
• 50,000 employees
• $23 billion in funding
• 7 companies with valuations greater than $1 billion
• A collective valuation of $107 billion

Conclusion: For every dollar invested in machine intelligence companies, the average projected return is 4.6x.

A concentrated geographical distribution

The chart reveals that 216 machine intelligence companies, or 87 percent, are based in the U.S. That leaves just 31 firms operating in other countries. Canada, Israel, and the U.K. hold the most promise of becoming additional hubs of innovation.

A very recent phenomenon

Almost half of these machine intelligence companies didn’t exist a few years ago, which suggests that the space will be inundated with new companies in the next few years.

Looking one layer deeper, one of the most exciting spaces in terms of new entrants is the Air Autonomous system — or unmanned aerial system for drones — which includes the likes of Dji and Airware. Other hot spaces are machine learning tech data tools, which include IBM Watson, and professional agents, which include Fusemachines and x.ai.

Size doesn’t matter

More than 50 percent of these machine intelligence companies have under 50 employees, and almost one-third have 10 or fewer employees. Just 10 companies have over 2,500 employees.

This post is part of the Machine Intelligence Landscape series. You can track this landscape and get all the latest news here.