Artificial intelligence is a topic on everyone's lips and is becoming increasingly important for our future. Since its emergence, artificial intelligence has developed enormously, especially in recent times. The potential of AI is immense and it's currently a major topic in discussions about the future in many companies.
A classic example of AI that has already integrated itself into our everyday lives is voice recognition - Alexa or Siri have become the norm in many households. Chatbots are also becoming increasingly popular on websites, increasing the efficiency of customer communication. Software is used that can access databases, linguistic knowledge, and full-text search engines, and can thus conduct an intelligent conversation with customers.

In the field of intelligent chatbots, exciting competition is brewing
Microsoft has supported a startup in creating a chatbot called ChatGPT (GPT stands for "Generative Pre-training Transformer"). This type of AI is used to generate text that reads as if it has been formulated by a human. ChatGPT was developed by OpenAI and uses a neural network to process texts and answer questions. It can also create text based on given templates.
ChatGPT can be used for customer service portals, social media platforms, search engine enhancement as well as translation and news generation.
GPT can be used to improve translation services or to create machine translations of websites and other online content. It can also assist journalists in researching and writing articles. Which can make their work a lot easier and more effective in the future.
But a competitor to ChatGPT wasn’t long in coming. Google is also on board: its answer to ChatGPT, Google Bard is supported by the language model Lamda. Bard draws its information from the internet in order to be able to provide a high-quality answer to all questions.
What’s the difference between Bard and ChatGPT?
Google Bard pulls its information from the Internet and can thus also answer questions that relate to current topics that have just happened. ChatGPT can only access information up to 2021.
However, ChatGPT is available for free (upgrading to Plus costs money). Google's AI is only available to a small group of testers so far.

Artificial intelligence is revolutionizing the translation market
AI is also becoming increasingly important in the field of translation and is the most current type of machine translation. At first glance, it’s often not even noticeable that an AI is behind it. This is possible because a neural network can process huge amounts of data and thus link information together in a meaningful way. With this, AI can imitate our thinking and learn from inputs. This is also known as Deep Learning, which allows an AI translator to teach itself how to translate best.
Already today, machines translate billions of words every day. A remarkable achievement that would be impossible for translators to accomplish.
Google Translator and DeepL are probably the best-known AI translators.
Best practice for AI translation
AI translation can be used wherever the quality of the text is not the most important factor. However, even though AI has continuously improved in recent years, it still can’t quite hold a candle to human translation.
AI translators can process huge amounts of data very quickly, technologies are always translated in the same way, and an AI does not make any escape errors. However, it also does not recognize cultural differences and does not know which idioms are used in a specific country, for example.
Also, an AI can't adapt the translations to a target group and can't necessarily transmit emotions. If you want to have a high-quality translation, it makes sense to have the text checked by a translator to give it the final touch. This way you can be sure that the text is translated correctly. However, you still save time and money with the combination as opposed to just working with a translator.

The human in the loop
The phrase “the human in the loop” certainly sounds familiar to fans of science fiction novels. In the context of artificial intelligence, the human in the loop acts like a teacher, because the AI needs instructions.
The principle works like in school. If the student makes a mistake, the teacher corrects it and the student learns from it. In this way, similar mistakes are avoided in the future. This is exactly how it works with artificial intelligence.
So what is the advantage of a human in the loop?
The right human already has a lot of experience and can recognize errors. The machine naturally translates much faster than a translator could and has access to large amounts of data. The combination of both optimizes the translations and gives the best possible result. The translator does the fine-tuning and the AI gets a higher accuracy due to the human factor. The translator evaluates the output data and adjusts or corrects it. Through these interactions, the program continues to learn and evolve, making future translations more effective and speeding up the process.
Having a “human in the loop” contributes immensely to the improvement of Artificial Intelligence. The biggest problem in the development of AI systems is often the lack of training data. This is the point where humans can intervene, by feeding the algorithm with correct results based on natural intelligence.
This can compensate (to a limited extent) for the lack of data. Gradually, the system learns from this and adjusts the algorithms, contributing significantly to the quality of artificial intelligence.
What can and can’t AI do right now?
AI can be used well for things that are predictable and solve a particular problem. As soon as AI can access data sets, it works very efficiently.
For situations that aren’t predictable, however, it’s a different story. A good example is autonomous driving. Driving on the highway, keeping your distance, and changing lanes, all no problem for an AI. However, if you are in city traffic where every situation is different, the data sets fail. This is because the systems only know statistics.
Regardless, AI will become increasingly important in the coming years and decades.
Conclusion
But this is only a small sample of what’s possible with AI.
Especially in marketing, a lot will happen with AI in the near future because it can be used effectively with simple methods. AI is used to analyze existing customer data with the help of algorithms to find out what future customer behavior and buying patterns will look like. These predictions can then be used in a targeted manner, which not only saves costs but also generates more sales.
Ultimately, what are the advantages of AI in marketing?
Customer needs along the life cycle are better understood and marketing can be more targeted. This creates the opportunity for better and at the same time stronger customer loyalty. Buying behavior can be predicted and campaigns can be launched at the right time.
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