This innovative technology lets machines not only analyze data but also generate creative content. OpenAI’s ChatGPT, powered by their latest large language model (LLM), stands as a testament to the remarkable capabilities of generative AI. It can author love poems disguised like Yelp reviews and compose Nick Cave-style song lyrics, blurring the lines between human creativity and machine intelligence.
The application of Generative AI in these creative areas shows that it serves not only as a tool, but also as a innovative partner that stimulates and enriches human creativity.
But how does Generative AI work and what advantages does it offer?
Generative AI: The magic of the creative technology
The journey of generative artificial intelligence (GenAI) began with the advent of deep learning and the development of models such as variational autoencoders (VAEs) in 2013. Using these models, realistic images and speech can be generated by transforming raw data into a compact representation and then converted back to their original form.
In 2017, so-called transformers revolutionized the field of natural language processing. These models combine the encoder-decoder architecture with mechanisms that pay particular attention to relevant content. This makes it possible to train large language models without having to explicitly define specific tasks. Transformers have become fundamental models that can be used with versatility for a variety of tasks – from classification and translation to question-and-answer applications.
Generative AI is used in many different areas. Here are some examples:
GenAI offers a wide range of advantages:
The future of generative AI holds enormous opportunities to create new capabilities and value for companies. However, it may also harbor new risks, whether legal, financial, or reputational. Many generative models, including those powering ChatGPT, can churn out information that might appear to be trustworthly but is in reality either untrue (so-called “hallucinations”), questionable or biased. Generative models can also inadvertently collect personal or copyright-protected information from their training data and later output it, posing unique challenges for privacy and intellectual property rights. Nevertheless, with GenAI’s ability to produce creative output, it will undoubtedly continue to shape the future of science, business, technology, and art. We are only at the beginning of this exciting journey into the world of Generative AI.
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