Generative AI: The Future of Creative Work

In the future, machines will become increasingly capable of writing, coding, drawing, and creating with credible, sometimes superhuman results. This will have dramatic and unforeseen implications for content ownership and intellectual property protection, but mainly for labor market, where humans will be replaced by AI and robots.

What is Generative AI?

Generative AI is a term that sums up all models that are built to enable computers to create new content using previously created content as input. This can include all creative work like text, audio, video, images, and computer code. The aim is to create authentic-looking artifacts that are completely original.

Generative Artificial Intelligence models may know how to generate images that look like faces, dogs or cars given the parameters and the datasets they were trained on. By using generative AI, computers can generate new content by abstracting the underlying patterns associated with input data.

In the near future, machines will become increasingly capable of writing, coding, drawing and creating with credible, sometimes superhuman results, because of a new class of large language models (LLMs) like GPT. However, as the field has evolved, it has become evident that generative models are unreliable when left on their own. Many scientists agree that current deep learning models – no matter how large they are – lack some of the basic components of intelligence, but this will soon change.

The State of Generative AI

The current state of Generative AI in 2023 is booming. 2023 has for the first time really brought Generative AI on everyone’s lip, and there is no going back now. The speed of development in text-to-image models like Dall-E, Midjourney and Stable Diffusion has been mind-blowing. And this visual component has really taken the internet by storm. But hidden in the shadows of these visual prompt based technologies lies perhaps a bigger disruptor, large language models like GPT-4 or the next GPT-5.

This Generative AI technology has, according to the experts, the biggest potential to disrupt almost all we know about communication and language.

The History of Generative AI

Google was one of the earliest companies to use generative AI, using it to create AdWords. In the early 2000s, generative AI was also used to create the first online chatbots. More recently, generative AI has been used to create new types of music, art, and even fashion.

Large language models were first introduced in 2015 by Google with their release of the BERT model. This model revolutionized NLP by training models to jointly learn language representation and task-specific prediction. Two years later, OpenAI released the large language model GPT, which extends BERT’s pre-training by using a Transformer-based architecture and learning from much larger amounts of data.

The original paper on generative pre-training (GPT) was published in 2018 and showed how a generative model can acquire world knowledge and process long-range dependencies. GPT-2, the successor to GPT, was released in 2019. However,the real breakthrough came in 2020 with the release of GPT-3, a model with 175 billion parameters. This model was capable of generating human-like text, making it a game-changer in the field of AI. Currently GPT-4 is the state of art.

The Future of Generative AI

The future of Generative AI is bright and full of potential. As the technology continues to evolve, we can expect to see even more impressive and creative applications. For instance, in the field of architecture, generative AI could be used to design buildings and structures that are not only aesthetically pleasing but also structurally sound and efficient. In the world of gaming, generative AI could be used to create realistic and immersive virtual worlds, in the film industry it will compete with Hollywood movies, potentially replacing them due to dramatically lower costs.

Moreover, as generative AI becomes more advanced, it could also be used to tackle some of the world's most pressing problems. For example, it could be used to develop new drugs and treatments for diseases, or to create sustainable and efficient solutions for energy production and consumption.

However, with these exciting possibilities also come challenges. As machines become more capable of creating content, questions about ownership and intellectual property will become increasingly important. Furthermore, the potential misuse of generative AI for malicious purposes and propaganda, such as creating deep fakes or spreading disinformation, is a serious concern that needs to be addressed immediately.

In conclusion, Generative AI is a rapidly evolving field that holds enormous potential. As we continue to explore and develop this technology, it will undoubtedly transform many aspects of our lives, from the way we work and communicate to the way we create and consume content. AI and robots will produce and people will buy, consume, and work for pleasure. With a universal basic income. The future of Generative AI is here, and it's time for us to embrace it.

Contact us

If you have a question, suggestion, comment, or are interested in collaborating, please use the form below to connect with us.