Demis Hassabis and John Jumper, the Nobel winners in chemistry, have helped crack complex protein structures using an AI model they developed. Even though the field wasn’t related, AI helped researchers achieve a solution to the 50-year-old study regarding protein structures.
Not only this, but AI’s impact on creative industries is huge as can be seen with the generation of AI images, videos, voiceovers, and more. It only makes sense to keep an eye out for automated content generation tools to understand how AI can help innovate creative industries. Let us explore this and the ways AI is being integrated for producing content in today’s world:
AI in Content Creation
To understand how AI creates content based on user input, it’s important to understand the mechanics behind AI’s workability first. The foundation lies in the term ‘Machine Learning’ which encompasses an algorithm consisting of three main participles:
- Decision Process: this process is aligned with classifying the data that will be used for constructing a model.
- Error Function: the AI compares the existing model with known and unknown error constants. This allows to assess and improve the accuracy of the model developed.
- Model Optimization Process: the processes of decision and error functions are repeated until the model is optimized or in computational words, a specific accuracy threshold is met.
In addition, we need to understand how machine learning is different from ‘Deep Learning’. Let’s check it out:
Deep learning, also known as scalable machine learning, is a process where the machine can come up with applicable models without even having a structured dataset. It can distinguish between sorted and unsorted datasets, and process unstructured, raw data to produce the results required as needed without much human intervention.
Deep learning, combined with machine learning, enables assessment of the provided information as well as mimicking human behavior to produce the desired content.
Let’s consider an example: Xfinity, one of the largest US internet providers, is harnessing AI to transform customer experiences. From Xfinity bundle deals to mobile services, personalized TV options, and more, the brand is excelling in terms of recommendations and user experience without needing any human input.
This way, deep learning can boost the overall performance of the content and services provided by any organization.
AI-Generated Content – Types and Examples
Now that we know how AI-generated digital art and animation work, it’s time to look at various examples of AI-generated content in the market:
· Video Production & Editing
With the help of AI, users can create videos from just text inputs. One of the perks of using AI video creation tools is that it reduces the need for tedious editing. The final product is already processed and any further improvement required can simply be made by giving another input.
In addition, the video production process is streamlined as AI tools help churn videos faster than regular production tools.
· Music Composition
Music composition has never been easy and it’s a skill that not everyone can achieve. However, with AI, getting things done from one place is easier than ever. Users can compose music without having to input numerous elements.
Using machine learning and neural networks, artists can help identify musical patterns from existing songs as well as get suggestions for improvements. In addition, AI music production tools can help generate more sounds, sounds that are difficult to replicate or take time to produce.
Plus, AI tools can also identify instrument sounds, harmonies, and music of all sorts, fetching data that can be used later to produce a symphony. This is done in three steps:
- Data Input: data of music samples added in the tool.
- Pattern Recognition: the tool reads and recognizes rhythmic structures from the data added.
- Output Generation: generates creative mixes from the structures identified.
· Scriptwriting & Storytelling
From writing blogs to creating scripts for a video, AI tools can help churn a good amount of content without any delay. Tools like Jasper, ChatGPT, etc. are excellent examples that produce an immense amount of content according to the given prompts .
The only reasonable argument here is that the amount of content generated lacks the emotional touch to it. Content creators using AI for scriptwriting ensure that a copywriter goes through the missing ‘human element’ while minimizing ‘robotic tone’.
Most AI assessment tools can pick AI-generated content by assessing its tone, which is why it’s important to add a human touch to the content.
When it comes to voiceovers, artists can generate human-like voices for the script provided. Again, the voice generated would sound robotic; however, AI tools are innovating their production to make these voices more human-like.
However, with the ability to produce results quickly and the versatility of voiceovers available (we have various artists’ voiceovers for the songs they didn’t sing), producers have a plethora of voices to play with.
· Visual Effects, Digital Art & Animation
While this domain is based on creativity, there are a lot of elements where AI tools step in:
With an extended set of features, including scene detection, automatic trimming, motion detection, etc. AI tools can make VFX processes more streamlined than ever!
Entertainment Personalization through AI
Not only is AI allowing users from various industries to produce amazing content without making much effort, it is also generating some exceptional benefits; benefits that are focused upon the following:
· Content Recommendation
One of the best things that AI has provided to marketers is smoothening the process of recommending relevant content, products, and services. For e-commerce, AI-integrated tools recommend similar products to what a user has been searching for.
In terms of viewing content, AI tools do the same; recommending similar content that the user can watch. Just like Netflix’s ‘Since you watched (name of the movie/drama)’ and then recommends related shows/movies.
· Audience Segmentation
With AI, users can easily work on large data and carry out operations as needed. Doing so helps them produce effective results such as in-depth audience segmentation or personalized segmentation.
Factors such as browsing history, purchases, social media interactions, etc. are taken into account by the AI tools. This allows the marketers to work with the audience’s preferences with a deeper connection.
Instead of targeting just the basic demographics, marketers can use AI to target a ‘highly specified’ audience pool. Marketers can use this to promote their products and services to targeted audiences better than before.
· Interactive Entertainment
AI in video games allows producers to make the games more interactive. From improving NPC (non-playable character) logic and actions to improving the mechanics of the game, AI does it all.
Ethical Implications of AI in Creative Industries
While AI has been quite helpful when it comes to streamlining the processes for almost every field, there are some ethical boundaries that are concerning its use.
- Copyright and Ownership: this has always been an issue with the use of AI, termed the ‘intellectual property problem’. Since AI is using prompts to find patterns online and then generate the content, it results in infringement of property or content.
- AI processes such as deepfakes can enable users to use any image, voice, or video and exchange with any content (face, voice, etc.) they want. This is dangerous on a whole different level, particularly associated with cybercrime, identity theft, and spread of false information, and more.
- Companies using AI reported more than 30% of employees losing their jobs due to its application. This only indicates that the use of AI is creating unrest and job displacements for existing employees.
The Future of AI-Driven Content Production
With the rapid use of AI, we’re using numerous forms of content production. However, one thing’s for sure; the bar for producing quality content is higher than ever! Since AI is already churning out immense content, AI detectors must operate effectively to identify content that actually produces value.
