Have you also come in contact with the latest buzzwords artificial intelligence (AI) and machine learning (ML)?
Maybe think about what it is and what it can be used for within a company?
I did so and took the opportunity to try to learn more about what it is and how it can be used.
Table of Contents
Maybe you’ll be disappointed…
But artificial intelligence originated in the 1950s by the American computer scientist and researcher John McCarthy. Who then described artificial intelligence as a machine that can think just like a human. Since then, the development has continued with some “notches” in the curve for interest in the area.
But in the mid-90s, for example, Deep Blue became the first chess-playing computer system (IBM) to beat world chess champion, Garry Kasparov.
One factor that affects the increased interest in artificial intelligence is that today there is great access to large amounts of data. It facilitates the creation of various AI solutions. Other factors that affect interest and development are:
– Cheap cloud services make it possible to create AI solutions at a reasonable cost.
– Today there are frameworks and tools that simplify the work of developing AI solutions.
– Computer power in the form of fast processors adapted to AI.
– A lot of interest in AI breeds even more interest in AI and in developing new AI solutions.
Nothing is new under the sun, it’s usually hot. What makes AI more difficult today is that there are differences from “before”.
OCR (optical character recognition), ie text interpretation, is no longer perceived as an example of “artificial intelligence”, as it has become a routine technology for a long time.
The difference today compared to before is that current OCR applications integrated with AI technology, provide enormously improved accuracy and speed because it uses machine learning technology.
You can divide the area of artificial Intelligence into different areas of application. A few examples are:
Reasoning functions
In this area, there are various solutions for data analysis (data science) for forecasting and probability-based solutions.
An example is being able to predict how many items of a certain type need to be purchased for a company or warehouse. Where the data is based on historical information or real-time information from various sources.
AI and machine learning are around you today in real-time.
Just take, for example, Facebook’s face recognition, the best way suggestions in Google Maps, or the personalized recommendations on Amazon (more on these later in the text).
An important parameter to follow up for all companies is customer loss (Customer Churn Rate). This is due to the fact that it is cheaper to retain current customers than to acquire new ones. Loss of customers is simply a lost value for the company. In this area, AI can be used to predict which customers are considering leaving the company so that they can be contacted.
Do you want more areas where AI is used in CRM? Take a look at the video below about Salesforce Einstein, an AI tool that helps companies get a data-driven sales culture.
Many manufacturing companies already collect large amounts of data from various plant sensors during its production. Information that is a perfect basis for AI. Where the information can be used for fault detection and quality control without human intervention.
Another area in production where AI is used is planning and schedule optimization. By being able to quickly predict when different machines are available, it leads to more efficient and optimized manufacturing. In the video below you can see how BMW uses AI to handle deviations in real-time.
AI is an excellent tool for preventive maintenance, needs planning, and aftermarket activities. That is, to continuously check when parts in a machine or engine must be replaced, even before something has broken.
AI can be used to individually customize e-commerce and web pages. Using algorithms, AI can predict what each customer and visitor wants and display the most relevant products and recommendations automatically.
We are also changing the way we consume content on, for example, an e-commerce site. Today we search by writing. But more and more people are being introduced to search using pictures, videos, or speech.
With analysis of large amounts, for example, traffic data from websites, e-mail, or other network data.
All to find deviations from the normal that involve some form of security threat. Where the changes take place so quickly and the amounts of data are so enormous from both own and other sources that it is difficult to draw the right conclusions. There is AI logic that gives you information about what changes you should act on.
Few areas are better suited for AI and machine learning than the economics area. This is in view of the fact that these are often large volumes of data. Today, AI and algorithms are used in stock trading, lending, and insurance to assess risks. But also in follow-up and analysis.
AI and machine learning algorithms can prioritize and automate your decisions. They can also alert you to immediate action. AI can also process both historical data and input data in real-time. Which means you can react to what’s happening right now.
AI can analyze large, complex amounts of data and from these reach its own insights in a way and at a speed that is beyond our human ability.
With AI, the company’s efficiency can be significantly improved in, for example, scheduling and planning, automation of tasks, or quality control.
Mastering the fundamentals of software engineering is crucial for building a strong foundation in the…
In present Online market Online Shopping with offers are the most common thing for these…
Have you heard about BCPS Schoology? Do you want to know about the term clearly?…
Clevo NH70 is one of the best and powerful Gaming laptops with top notch features…
If you are using the Facebook application on your android mobile phone then you are…
In this telecommunication era social media platforms and communication tools are very important for the…