Artificial intelligence

Artificial intelligence, shortened AI, first appeared in 1955 in research with the purpose of finding a way to learn machines to speak, shape thoughts, concepts and solve problems that previously demanded a person’s involvement. In short, Artificial intelligence AI is about simulating human intelligence on computers by learning, drawing conclusions and self-correcting. We’ll immediately go deeper into it.

Artificial intelligence can give you a customer service on 72 languages?

Uses for Artificial intelligence AI are many and new ones all appear. Actually, only the imagination sets the limits. Here are a number of examples. Customer service is an area where AI Artificial Intelligence and Machine Learning start to take a lot of space and is not rarely used for e-commerce and services recommendations. Zalando uses Artificial intelligence AI to help customers find the right size. Netflix recommends movies and comics you want to watch and Amazon uses it to show you new items you may be interested in based on what you’ve been shopping before. Similarly, the AI is behind Spotify’s tailor-made playlists that extend to users every week. Even Google and Microsoft use AI in their voice and image recognition algorithms.

AWS Artificial intelligence

A US company has developed what they call a digital colleague who, with AI Artificial Intelligence, is going to increase productivity. Amelia, as she is called, speaks 72 languages fluently and teaches in principle any job in 60 days. If she is placed in a customer service, she listens at the beginning of the conversation and learns from their questions. She reads mail and learns what to answer and over time she takes over the conversation. The conversation she cannot handle herself, she takes the help of a human colleague. However, she is listening to the conversation to answer that question the next time. None of this would be possible without AI Artificial Intelligence and Machine Learning.

There are many examples of highly qualified tasks that Artificial intelligence AI can perform. In medical care, it is used in patient diagnoses, for example, when IBM’s AI computer “Watson” was loading 20 million pages of the latest cancer research and 10,000 anonymous records to help Japanese doctors with a hard-hitting case. In eight minutes, Watson “a diagnosis, some doctors did not manage in two months. The AI computer provided just the right diagnosis for a very unusual form of leukemia. It also provided a recommendation for a treatment that the physicians could confirm and who have also helped. is a study using Computer Assisted Diagnosis (CAD) to review early mammography images of women who later developed breast cancer. The computer detected 52% of cancer cases over a year before an official diagnosis was established.

AI can also detect deviations in production in the manufacturing industry, create forecasts for the transport industry as well as optimize warehouses in trade and logistics. It is also used in careless cars and robots. That said, it’s just the imagination that sets the limits. Machines are also not tired and do not have a bad day so the quality is maintained.

What is AI Artificial Intelligence, Machine Learning and Deep Learning?

As research has progressed and our technical possibilities have evolved, AI has done the same and there are several different concepts. We’ll figure them out.

When computers are equipped with the ability to learn from the experiences they do, so called Artificial Intelligence. AI is the theory and development of computer systems that can perform tasks that require human intelligence, such as visual perception, voice recognition, decision making and translation of languages. Machine learning is when AI Artificial intelligence is used for systems to automatically learn and improve from experience, rather than programming. That is, to develop computer skills to independently understand and handle large amounts of data. In order to achieve independence, algorithms are used that allow computers to interpret and learn from data to create an opinion or prediction about something. With the help of Machine learning, the computers learn more and more as they process and analyze new information. Therefore, they become smarter with time.

Machine learning is often used to predict future results based on past data. These results enable the company to make better business decisions ahead. Another term that you probably encountered is Deep learning. Deep Learning has emerged from Machine Learning and focuses on selected tools and methods to enable the implementation of Machine learning. After that, the machine can solve essentially any problem that requires human or artificial thought courses. The concept then builds on the idea of creating and using artificial networks as a method of processing and deciding on given data. Research on Deep Learning focuses on constantly developing these networks, to handle data sets as big as, for example, Google’s image bank or all tweets ever written on Twitter.

AWS Machine Learning

AI Artificial Intelligence and Machine Learning – Amazon Web Services (AWS): As you previously read in the blog, Amazon Web Services comes to Sweden this fall, which creates great opportunities for Swedish companies. With AWS, companies not only get cost-effective and flexible IT solutions, but also the ability of AI in the company easily.

E-commerce giant Amazon has invested in Artificial intelligence AI for a long time and many of AWS’s services in the area are used in different ways. One example is their virtual assistant Amazon Alexa or complete API-driven services like Amazon Recognition. This is used for analysis of images and video and can recognize people or objects. Amazon Comprehend recognizes languages, keywords, people, places, events, etc. Amazon Transcribe converts voice into text and can even recognize different voices and separate them. Amazon Polly instead converts text to speech in many different languages and with several different voices. Amazon Translate translates text between different languages through Deep Learning models to get more accurate and natural translation, compared to more traditional translation services. With Amazon Lex we can build chat bots to have direct contact with customers or users. Furthermore, Machine Learning services like Amazon SageMaker are available to build, train, and distribute models.

As a rule, the AWS services are designed for their specific purposes and remove complexity in managing underlying infrastructure and systems. You only pay for what you consume and when you spend it.