Currently, AI has been mentioned uncountable times as the innovation of contemporary era with the rich material and potential to exploit. As a technology profession, generative AI field is the competitive and fast-paced market with AI trends updated regularly and even unexpectedly sometimes. Furthermore, AI, besides its function as the machine learning tool with tasks like answering question, translation, or creation. It should be perceived beyond this limit with the broader exposure. Thus, generative AI trends matter significantly, which are utilized for the customer experience ecosystem. Its popularity is undeniable by that governments and business spend on AI technology $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? Instead of merely understanding, let's see through with the breakdown of generative AI trends. What is Generative AI? Generative AI algorithms utilize pre-existing data to generate completely novel content that has never before physically existed. The forms are videos, images, sounds, or even computer code. Among AI trends, this one is pretty common with the emergence of chatbot, especially chat GPT and capable of creating text and prose close to being indistinguishable from that created by humans. Similarly, we also have Fliki, Super Creator for making video, or Midjourney, Rocket AI for creating images. It's anticable that its usage will be beyond the scale of individuals or small enterprises to the bigger businesses with a wider range of tasks. In 2023, we can see it used increasingly frequently to create synthetic data that can be used by businesses for all manner of purposes. Using synthetic audio and video data can eliminate the need to film and record speech on video. Workers can simply type what they want the audience to see and hear into your generative tools, and the AI will create it accordingly. Accordingly, here is some generative AI trends worth noticing: Multi-Modal Models Trend If you are working with only one source of information, it is easier to train the AI. However, the results may lack context or supporting information, leading to skewed outcomes. In multimodal AI, two or more streams of information can be processed together. Then, it allows the software to have a better understanding of what it is analyzing. This generative ai trend will help the interaction with AI like human with full sense. Most generative AI tools, algorithms, and language models (LLMs) specialize in simulating one form of expression, such as language, visuals, or sounds. However, there is a growing trend towards "multi-modal" generative AI. The upcoming version of OpenAI's ChatGPT is the example. It will have the ability to understand and interpret images, as well as respond to voice commands. Meta has also demonstrated a model that can combine images, text, audio, depth, and motion data. This approach is expected to become more common in the coming year. Additionally, it will soon be normal to have conversations with AI about pictures or videos. This is similar to how we interact with it about…