Exploring the AI Revolution
Artificial intelligence is the current trend in every aspect of daily life. It is a revolution that significantly changes how we learn, create, and organise our lives. It can perform routine tasks in a fraction of a second, leaving more time for creative endeavours.
AI has also entered the music and audio industry at every level. From management and organisation to composition, audio editing, processing, and mixing. Additionally, it can help remove any artistic blockage we might have.
Like any other revolution, this new technology also has fears and misgivings. But what is AI exactly? How does it work? How far can it go? And most importantly, will it take over our jobs in the music industry?
In this article, alumnus and freelance writer Carlos Bricio explores the above step-by-step. Delving into the basic mechanics of AI and how it can be a beneficial tool in the music industry.
What is AI?
Artificial intelligence is a field of science that studies how machines and computers can reason, learn, and act based on data. It groups disciplines like computer science, data analytics, engineering, neuroscience and even philosophy. It tries to learn how to mimic human decision-making processes. This process, known as Deep Learning, involves faster processing, thanks to the power of modern computers.
It does this by using data as the main ingredient. Thanks to modern technology and the internet, we can turn everything into data. Our heart rate, diet routine, and the music we listen to… can all potentially be used to train an algorithm and create the rules for a specific task.
Ultimately, AI is a set of rules and instructions (algorithms or models) that guide the machine in making decisions.
Based on this, it’s easy to see what AI offers, from automating tasks to reducing repetitive processes and, in some cases, human error in addition to accelerating research and development. As long as there is data to feed the algorithm, there will always be ways to improve AI.
Image source: The Motley Fool
Different types of AI
There are two types of AI models. The classic model analyses big data and can find and recognise patterns in massive amounts of information. It is used by online markets or streaming services to suggest your next purchase or music based on your habits.
The second AI is the generative assisting or creative algorithm, which can create images, sounds and music from a given prompt. These models can translate a human language (written or spoken) to orders that the machine can interpret. This returns something meaningful to the user. This type of AI also relies on data, but the resulting algorithm can generate something similar to the previously provided trained information.
The most popular AI technology currently in the market is based on predictions, forecasts and categorisation. However, generative AI has grown substantially in the last few years.
Music and Audio applications
AI models have many advantages in the audio world. They have enabled engineers and producers to move from “traditional” digital workflows to data-driven work. This makes it easier to perform applications like audio enhancement, speech synthesis, and music generation, in addition to sound classification and sound source localisation.
AI has automated feature extraction processes that allow one to learn and extract specific audio characteristics from audio data. This might be separating instruments from a mix or finding similar-sounding mixes. These methods offer substantial improvements over the classic approaches. It has also improved accuracy, versatility, and real-time application in digital audio tools like noise reduction software.
Challenges & Possibilities of AI in Music
The use of AI in the music industry goes beyond a simple tool for the creative community. It represents challenges and opportunities at every level of the business. One of the industry’s concerns is reducing diversity in the music industry. This is due to the creation of music with models and the bias in the algorithms. This information is collected from the data used for training. Another concern, and perhaps the most important one, is the ownership of AI-generated music.
Who is the owner and is responsible for the music being created by the models? What music can be used for training algorithms? AI is a controversial topic, and every country is having conversations and regulations about it. For example, the EU has started
legislating AI, placing humans at the centre of the creative process. At the same time, independent USA groups like writers and actors have shown their concerns by going on strike. Some have done this for several months to protect their rights from the generative AI models.
Despite the negatives, there is equally a lot of optimism around AI. Many artists and engineers see a bright future ahead. Thanks to trend analytical algorithms, we can now reach more of the public than ever before. In addition to bringing music to a broader audience via recommendations. The development of AI has democratised technology further by allowing communication with machines using plain language. Most importantly, it puts the artist’s creative process and ideas first. Thus helping reduce what some may see as ‘tedious’ work and letting the talent focus on what they do best: making music.
The Future of AI
Right now, the music industry is experiencing a paradigm shift. Similar to the introduction of digital music and streaming services. This shift is shaking the industry at many levels. Much work remains, but with every revolution, new opportunities arise. AI is here to stay, so we better get ahead and take advantage of this new technology.
We hope this article helped you get a broader view of the current state of AI (which might change quickly). If you enjoyed this article, check out our previous feature, ‘Producing Music for AI with Humtap.’ Keen to start a career in the music industry? Check out our Advanced Diploma in Music Production and Sound Engineering and the topics covered each term.
Stay tuned for more content on how AI can help your music creation process. PS: No generative AI was used for this article 😉.
