Last Updated on Thursday, 11 April, 2024 at 9:00 am by Andre Camilleri
Many enquire about the impact of Artificial Intelligence on the development of new games within the gaming industry in Malta.
AI is not merely a technological trend in the gaming industry; it’s a transformative force. AI has reshaped game development, improved player experiences and made gaming more accessible and enjoyable than ever before. Another branch of this new technology is Generative Artificial Intelligence (Generative AI).
This is a cutting-edge technology that has revolutionised the landscape of artificial intelligence. Unlike traditional AI models that are designed for specific tasks, generative AI has the remarkable ability to create new content, whether it is images, text or even music. It is important not to underestimate the importance of AI for our economic growth. Many label such developments as fantasy imagery which like the block chain bubble that hit Malta five years ago, it fizzled into nowhere. However, this time entrepreneurs must avoid repeating past mistakes by not disregarding the realm of generative AI. Instead, they should delve into its foundational principles, its applications across diverse industries, ethical considerations and the vast potential it offers for shaping the future of innovation.
It is true that Malta is a laggard in funding innovation. It only funds creativity and research up to one fifth of what Europe does. This mindset of burying our heads in the sand and hoping that multinational companies will come gratuitously to our shores gifting us with their treasured IP is akin to living in a fantasy world like Alice in Wonderland. Therefore, our future in tech education has to be ratcheted upwards, if we want to survive competition.
For the gaming industry in Malta to remain competitive and ahead of the curve, it must increasingly prioritise ethical and inclusive gambling design, creating gaming experiences that cater to a diverse audience while respecting player data privacy.
In fact, AI systems can simulate countless hours of gameplay to uncover bugs, imbalances and other issues in the game. This accelerates the testing process and ensures a smoother gaming experience upon release. It is interesting to introduce artificial neural networks (NN) at this stage. These are structures akin to human brains that can learn various features from training data. Given a large set of data, NNs are capable of modelling very complex real-world and game scenarios.
Furthermore, NNs are self-adaptive and adapt well to game environments that change in real-time. NN-based agents can quickly adapt to the changing tactics of human players and can make sure the game remains challenging even during extended gameplay. Lately, Deep NN (deep learning) has become a more popular choice for game agent design. Deep learning in games utilises multiple layers of neural networks to “progressively” extract features from the input data.
Due to its layered approach and increased architectural complexity, Deep NN can achieve better results when controlling one or several game agents. What is new here? AI-driven tools are used for content creation, such as generating art assets, music and dialog. This reduces development time and allows designers to focus on more complex aspects of the game. AI can analyse player data to fine-tune game balance.
Developers can identify overpowered weapons or underused features, making gameplay more satisfying for all players. Thus, we expect a tactical change in the gaming companies hosted in Malta to keep up with such fast developments. Can we stop the clock? Not really, unless our gaming industry will, by its own accord, migrate to better shores and avail itself of better trained tech workers.
Let us discuss another associated topic. The development of generative AI can be traced back to the early days of NNs and machine learning. Over time, advancements in deep learning, particularly the introduction of Generative Adversarial Networks (GANs). These represent a remarkable breakthrough in the field of artificial intelligence. They have pushed the boundaries of what machines can create and have had a transformative impact on numerous industries.
However, this creative power also comes with ethical responsibilities and challenges that require careful consideration. As GAN technology continues to advance, it will be essential to strike a balance between creative freedom and responsible use.
The future of GANs promises even greater realism and personalisation, making them an invaluable tool in the creative and innovative landscape of future gaming. It is a paradigm shift in how Malta’s business elite can harness the creative potential of AI. They are a testament to human ingenuity, opening doors to new possibilities and reshaping the way Malta’s entrepreneurs view artificial intelligence.
It’s an exciting journey that is only just beginning. Historically, the concept of GANs was introduced by Ian Goodfellow and his colleagues in a seminal paper titled Generative Adversarial Networks published in 2014. Goodfellow’s idea was inspired by the human creative process, which often involves a tension between creation and critique. Briefly, original GAN architecture consisted of a generator network and a discriminator network. The generator network would create data, while the discriminator network would house it. Over time, the generator improved by learning from the discriminator’s feedback. The discriminator, in turn, improved its ability to distinguish real data from generated data.
This adversarial process led to the refinement of both networks, resulting in highly realistic generated data. During training, the generator and discriminator networks engage in a competitive process.
The generator strives to create data that the discriminator cannot distinguish from real data, while the discriminator tries to improve its accuracy in distinguishing between real and generated data.
George M. Mangion is a senior partner at PKF Malta
