Top AI Companies and their Machine Learning – Everything to know now

In this article, you’ll find our analysis of the Top AI 50 : the 50 best AI companies according to Forbes magazine.

50 companies implementing AI-based tools have been ranked by Forbes according to their own results.

Here, we will analyze the overall picture of these companies to understand two things :

  • What are the most promising sectors for developing Artificial Intelligence ?
  • Which types of Machine Learning are the most used on the market ?

Top industries in the ranking

Companies by sector

First of all, let’s review the number of companies by sector.

Here we have several major fields of activity:

  • Cybersecurity
  • Industrial
  • Data, which gathers the analysis of Big Data but also the creation of Artificial Intelligence
  • Medical, which includes the hospital sector with the detection of disease, but also the pharmaceutical sector and the discovery of new treatment by AI
  • Transport, with autonomous cars but also the maritime sector
  • Building, with site planning
  • Sales, here we are talking about the sales sector with, for example, the analysis of telephone communication
  • Company, a large domain that includes everything related to the company : management, administration, legal, …
  • Social Media
  • Restaurant
  • Finance

Three companies stand out in this graph :

  • Data
  • Medical
  • Company

These sectors are the most competitive, and at the same time are the areas where there is the most to achieve.

Indeed, in the medical field for example, we can see that the objectives of these companies are as diverse as varied. Whether it is for the detection of disease on scanner, prevention by anticipating the appearance of symptoms or the creation of new molecules, AI has a bright future in the medical sector.

Now that we have seen which sectors witnessed the emergence of the most AI companies, let’s move on to their valuation.

Valuation by industry

Which of the areas presented are the most beneficial ?

The Data sector outperforms the market with a total capitalization of over 40 billion dollars !

If we look at the first graph, we can see that this is both the sector with the most competition but also where profits are the highest.

In comparison, the medical sector, the 2nd most competitive sector, has a capitalization of 627 million dollars. 50 times less than the Data sector !

It is so impactful that it is difficult to visually analyze the rest of the market. So I suggest to look at the same graph without the Data sector :

We can see that the Industrial sector is the 2nd in terms of capitalization with only 2 companies. The Company sector follows just after, with 7 companies in the ranking.

To be noted that the Finance sector succeeds with only one company to reach a value of 1 billion dollars !

At Inside Machine Learning, we mainly write for Data Engineer and Machine Learning Engineer. Therefore we’ll analyze the Machine Learning techniques used by the companies of Forbes Top AI 50.

Most used types of Machine Learning

Field of application

Let’s move on to a more technical analysis. This will allow us to understand the Machine Learning field of application of this Top 50.

Here are the main ones:

  • Computer Vision : images and videos
  • NLP : text
  • Molecule
  • Audio
  • Big Data : all mass data, structured or not
  • Time Series : data across time, such as stock market data

Without surprise, the two most widely exploited Machine Learning domains are also the most studied by specialists : NLP and Computer Vision.

We can also see that Machine Learning applied to Molecules is particularly used in the Top 50 companies.

Audio is also in a good position, followed by Big Data and Time Series.

Note that some Machine Learning domains present in the Top 50 are not displayed here. In particular, AI used in the maritime sector such as tide prediction, analysis of data from sensors such as sonar, and others.

Let’s move on to an analysis of the types of Machine Learning used.

Types of Machine Learning

There are 6 main types of Machine Learning:

  • Detection – example : disease detection
  • Classification – example : classifying an audience according to a product line
  • Analysis – example : optimizing the production of a farm
  • Prediction – example : predicting the yield of a product
  • Generation – example : voice chatbot answering a customer’s question
  • Full, here we’re talking about a company gathering the 5 previous objectives

At the top of this ranking we find data Analysis. Indeed, the data analysis will essentially allow to understand the results of a company. And then enable to differentiate the strategies that worked from those that did not.

Analysis is the basis of the strategy optimization process, an essential part of a company’s business.

Detection comes second, followed by Generation. The latter is particularly applied in the field of translation and language.

AI companies that stand out

Finally, I’d like to show a selection of the companies that have made the biggest impression on us at Inside Machine Learning, whether it be by their application domain or by the potential of their Artificial Intelligence:

  • FarmWise – Enabling farmers to optimize their operations with AI
  • Shield AI – AI applied to military aviation
  • UnifyID – Identifying people by their movement alone
  • Komodo Health – AI learning to detect health problems with data from 300 million people
  • Verge Genomics – Curing neurodegenerative diseases with AI

In order to carry out this analysis, we’ ve only used the information presented in the article published by Forbes. This analysis is not a global analysis of the market but an analysis of the companies that participated in the Forbes ranking.

To see what other companies like Google, Facebook or OpenAI are working on in Artificial Intelligence field, you can read our article on the 3 pioneer companies in AI and how they innovate.

See you soon in a next article 😉

sources :

Tom Keldenich
Tom Keldenich

Data Engineer & passionate about Artificial Intelligence !

Founder of the website Inside Machine Learning

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