Skip to main content

AI Business: Framework and Maturity Model

 Methods and Technologies

In the following, the various methods and technologies are briefly outlined

and explained.

Symbolic AI

Since the conference at Dartmouth College in 1956, a variety of different

methods and technologies have been developed for the construction of intel-

ligent systems.

Even if neuronal networks and thus the approach of sub-symbolic AI

dominates today, the field of research was dominated by the symbolic

approach for a long time. This “classical” approach by John Haugeland

called “Good Old-Fashioned Artificial Intelligence” (GOFAI) used defined

rules to come to intelligent conclusions depending on the input. Up to the

AI winter of the 1990s, “artificial intelligences” were developed by program-

ming and filling control equipment and standards and databases to then be

able to access them in practice. To this day, a large number of search, plan-

ning or optimisation algorithms and methods from the times of symbolic

artificial intelligence are applied in modern systems, which today are simply

regarded as excellent algorithms of informatics.

Natural Language Processing (NLP)

Computer linguistics covers the understanding, processing and generating

of languages. “Natural language processing” describes the ability comput-

ers have to work with spoken or written text by extracting the meaning

from the text or even generating text that is readable, stylistically natu-

ral and grammatically correct. With the help of NLP systems, computers

are put in a position of not only reacting to formalised computer lan-

guages such as Java or C, but also to natural languages such as German or

English.

Rule-Based Expert Systems

ule-based expert systems belong to one of the first profitable implementa-

tions of AI that are applied to this day. The fields of use are multifaceted and range from planning in logistics and air traffic over the production of con-

sumer and capital goods down to medical diagnostics systems.

They are distinguished by the fact that the knowledge represented inside

of them originates from experts (individual fields of expertise) in its nature

and origin. Depending on the input variables, automatic conclusions are

then derived from this knowledge. To this end, the knowledge (in the spirit

of symbolic AI) must be codified, i.e. furnished with rules, and be linked to

a derivation system to solve the challenges.

Sub-symbolic AI

The approach of symbolic AI to systematically capture and codify knowl-

edge was considered very promising for a long time. In a world that is being

digitalised further and further, in which knowledge implicitly lies in the

amounts of data, AI should be able to do something that knowledge-based

expert systems inherently find difficult: Self-learning. Deep Blue, for exam-

ple, was in fact able to beat Garry Kasparow in 1996 without the use of

artificial neuronal networks, but only because the chess game had been for-

malised by humans and because the computer was able to compute up to

200 million moves per second from which the most promising one was then

chosen.



Comments

Popular posts from this blog

Customer Engagement with Chatbots and Collaboration Bots: Methods, Chances and Risks of the Use of Bots in Service and Marketing

 Relevance and Potential of Bots for Customer  Obtaining information, flight check-ins or keeping a diary of one’s own diet—all of this is possible in dialogue today. Customers can ask questions via Messenger or WhatsApp or initiate processes. This service is comfortable for the customer, available at all times via mobile and promises fast answers or smooth problem-solving. A meanwhile strongly increasing number of companies is already relying on this means of contact and the figures on chat usage speak in favour of this means supplementing or even replacing many apps and web offers in the future. The reasons for this are manifold. Figures of the online magazine Business Insider 1 reveal a clear develop- ment away from the public post to the use of private messaging services such as Facebook Messenger or WhatsApp. Facebook meanwhile has a user base of around 1.7 billion people worldwide; 1.1 billion people use WhatsApp, and Twitter can nevertheless still record 310 million us...

Robot Journalism Is Becoming Creative

 Algorithms are able to automatically search the Web for information, pool it and create a readable piece of writing. In addition, data-based reports in the area of sport, the weather or finances are already frequently created automat- ically today. Recently, for example, merely a few minutes after Apple had announced their latest quarterly figures, there was a report by the news agency Associated Press (AP): “Apple tops Street 1Q forecasts”. The financial report deals solely with the mere financial figures, without any human assistance whatsoever. Yet, AP was able to publish their report entirely via AI in line with the AP guidelines. For this purpose, AP launched their corresponding platform Wordsmith at the beginning of 2016, which automatically creates more than 3000 of such financial reports every quarter, and which are pub- lished fast and accurately. It is no longer that easy to distinguish between whether an algorithm or a human has written a text. Another exception of rece...

Sales and Marketing Reloaded—Deep Learning Facilitates New Ways of Winning Customers and Markets

 Sales and Marketing 2017 “Data is the new oil” is a saying that is readily quoted today. Although this sentence still describes the current development well, it ides not get down to the real core of the matter; more suitable would be “artificial intelligence empowers a new economy”. The autonomous automation of ever larger fields of tasks in the business world will trigger fundamental economic and social changes. Based on a future world in which unlimited information is available on unlimited computers, ultimate decisions will be generated in real time and processes will be controlled objectively. These decisions are not liable to any subjectivity, information or delays. In many sectors of the economy, e.g. the public health sector or the autonomous control of vehicles, techniques of artificial intelligence (AI) are applied and increase the quality, availability and integrity of the services offered. The same development can be observed in the field of sales and marketing. Today, ...