Machine learning still the hype

Science Guide, an international scientific community, has conducted a study on 500 AI companies. Science Guide's mission is to combine science, developers, business and investors with the common goal of creating a revolution in AI technologies in different vital industries. It is necessary to minimize the path from the scientific idea to the finished commercial product.

Analytical map ?500 AI-companies International Report 2018? contains the AI companies based in several countries. Companies are developing or using artificial intelligence in their business processes. Also, the 2018 artificial intelligence ecosystem was studied to make general conclusions about each country’s AI ecosystem.

• We highlight the development of AI in those countries according to several reasons. First, they are not covered as much as others, second they all have in some degree developed business bounds.
• The main goal of the report is to highlight the AI part of each of the presented countries in order to improve relations not only between new technologies and traditional business but also between countries.

Methodology

All data presented in the analytics were collected from various open and closed sources, such as reports from Crunshbase, Deloitte, CBInsights, Asgard, PwC and others. With the help of the following sources, we have created a complete picture of the AI ecosystem.

The report will help to understand what technologies exist on the market today and what businesses need they are made for. It includes all the types of services that AI can provide for business, and focuses attention on the pain of the large and successful companies.

Key characteristics of AI

• BIG DATA: Capable of processing massive amounts of structured and unstructured data which can change constantly.
• LEARNING: Ability to learn based on historical patterns, expert input and feedback loop.
• REASONING: Ability to reason (deductive or inductive) and to draw inference based to the situation. Context driven awareness of the system.
• PROBLEM SOLVING: Capable of analyzing and solving complex problems in special-purpose and general- purpose domain.

The AI technologies covered

• Robotics - The applications of robotics is for instance self-driving or self flying vehicles.
• Computer vision - The applications of it is for instance recognition of persons and other objects, video analytics, description of the contents of images and video, handwriting recognition, Intelligent image processing.
• Machine learning - The applications of it is for instance optimization of traffic flows, forecasting prices, programmatic-advertising and personalization of offers.
• Intelligent Data Analysis – it could be a platform that provides an architecture for business analysis based on automation of several manual tasks.
• Recommender Systems -  for example a tool that gives you recommendation on how to maximize marketing activities.
• Search Engines and Language Processing - The applications of it is for example analysis of user requests, search ranking, machine translate, antifroud and antispam, analysis of the tonality and content of texts.
• Internet of Things – an interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data, for example devices to measure enviromental parametares.

The industries covered

• Marketing and Advertising
• Fintech and Finance
• Entertainment
• Education and Research
• Chatbots and AI Assistans
• Information technology and services
• Computer Software
• Transport and Infrastructure
• Others
• Healthcare
• Security

We decided to take a look into those industries to get a picture of how artificial intelligence develops in each of them in different countries.

Machine learning most popular

Globally, among AI technology systems, machine learning attracts almost 60 percent of external investment. This is most likely because it is an enabler for so many other technologies and applications, such as robotics and speech recognition. In addition, investors are drawn to machine learning because, as has long been the case, it is quicker and easier to install new code than to rebuild a robot or other machine that runs the software.

In our analysis the picture is the same; machine learning is still the hype.

Information technology and services, and Computer Software are those industries towards  AI companies most develop their services, follow by others and marketing and advertising.

General observations

As we have seen, AI companies usually appear in city capitals, at tech hubs or at places where an ecosystem consisting of supporting community and expertise exists. In such cases we see a flourishing startup scene.

In societies where uncommonness of new technologies prevails, the organizations tend to be more sceptic to them, compare to societies where new technologies are cherished.

A national strategy plays a crucial role for the development of AI industry, given the eagerness to move on.

The report will be out during the presentation on the conference AIONE on December the 14th.