With generation tools like ChatGPT and Stable Diffusion everyone is talking about artificial intelligence (AI), but where is AI going next?
The Future of Generative AI Beyond ChatGPT
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It is already clear that this exciting technology will have a profound impact on how we live and work. UK energy provider Octopus Energy has announced that 44% of customer service emails are now answered by AI. Also, the CEO of software company Freshworks said that as a result of introducing AI tools into its workflow, tasks that previously took eight to 10 weeks can now be completed in days.
But we are just the beginning. In the coming weeks, months and years, the pace of development of new forms of generative AI will accelerate. They will be able to perform an ever-increasing number of tasks and enhance our skills in every possible way. Some of them may seem as incredible to us today as the rise of ChatGPT and similar tools seemed incredible just a few months ago.
So let’s take a look at some of the ways we expect generative AI to evolve in the near future, and some of the tasks generative AI will help us with in the near future.
Beyond ChatGPT
Text-based generative AI is already pretty good, especially in research, drafting, and planning. You may have enjoyed writing stories and poems, but you may have noticed that you are still not up to Stephen King or Shakespeare, especially when it comes to generating original ideas. Next-generation language models beyond GPT-4 will provide a deeper understanding of factors such as psychology and the human creative process, allowing you to create deeper and more engaging copy. There will also be a model that replicates the progress made by tools like AutoGPT that allow text-based generative AI applications to create their own prompts and perform more complex tasks.
Generated Visual AI
In addition to text, current generative AI technology is also very good at creating images based on natural language prompts, and there are even some tools that use it to generate videos. However, there are some limitations due to the intensive data processing required. As this area of ​​generative AI becomes more sophisticated, it may become easier to create images and videos of just about anything, until it becomes difficult to distinguish between generative AI content and reality. In that case, deep fakes will become a problem, and fake news and disinformation may spread.
Generative AI in the Metaverse
There are many predictions about how we interact with information in the digital realm. Many of these focus on immersive 3D environments and experiences that can be explored through virtual reality (VR/AR). Generative AI speeds up the design and development of these environments, a time- and resource-intensive process. Meta (formerly Facebook) suggests this could be part of the future of his 3D world platform. Additionally, generative AI can be used to bring these environments to life, creating more lifelike avatars capable of more dynamic actions and interactions with other users.
Generative Audio, Music, Speech AI
AI models are already very good at generating music and mimicking human voices. In music, generative AI will become an increasingly valuable tool for songwriters and composers, with the potential to create novel compositions that can serve as inspiration or encourage musicians to approach the creative process in new ways. there is. It will also likely be used to create real-time adaptive soundtracks. For example, when accompanying live footage of video games or real-world events such as sports. AI text-to-speech has also improved, bringing computer-generated speech closer to the level of expression, inflection, and emotion conveyed by the human voice. This opens up new possibilities for real-time translation, audio dubbing, automated real-time narration and narration.
generative design
Designers can use AI to help them prototype and create new products of all shapes and sizes. Generative design is a term that describes the process of using AI tools to do this. Tools are emerging that allow designers to create step-by-step instructions for an algorithm to design a finished product, simply by entering the details of the materials to be used and the properties the finished product should have. An Airbus engineer used tools like this to design the internal partitions of his A320 airliner, resulting in a 45% weight reduction for him over the human-designed version. In the future, we can expect more designers to adopt these processes and involve his AI in creating increasingly complex objects and systems.
Generative AI in video games
Generative AI can have a profound impact on how video games are designed, built, and played. Designers use it to help conceptualize and build the immersive environments that the game uses to challenge the player. AI algorithms can be trained to generate landscapes, terrain, and buildings, giving designers time to work on compelling stories, puzzles, and gameplay mechanics. Also, non-player characters (NPCs, etc.) that behave in a realistic way and communicate with the player as if they were humans (or orcs or aliens), rather than being restricted to following a script. You can also create unique content. As game designers become more familiar with implementing generative AI into their workflows, the need for scripted scenarios and challenges will decrease, and we can expect games and simulations that react to player interactions on the fly. This could lead to games that are far more immersive and realistic than most advanced games available today.
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