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When was the last time you read a book outside of university? Nowadays it’s not easy to take a moment to read with all the distractions around us. And when you are trying to get back to it, where do you even begin? How can you choose something that might engage you enough to convince you to get through the book? We have all been there, spending hours in the bookstore trying to read blurbs and blindly choosing something that often ends up covered in dust inside our drawer. What if we told you we have a solution to encourage people to read again?

With Bookbuster, all you need to do is download our app, scan a book you think you may be interested in, and our AI-powered text-to-video technology will show a trailer of the book for you to decide whether you want to read it, increasing your chances to dive into the book and finish it. In a world where we are constantly on our phones and looking to engage with content through social media and other platforms, this innovation will provide you with a real multisensory experience to improve your decision-making and increase your enthusiasm for reading.

Bookbuster is not only beneficial for readers. It will revolutionize the way books are promoted, allowing authors to create a memorable experience for readers without having to face high production costs to create promotion content. A lot of costs can be saved, and new authors who don’t have the resources to hire a video editing team also get the opportunity to promote their book to a bigger audience. By adding an algorithmic-based recommendation system, Bookbuster can introduce other books and authors to the reader to expand their horizons.

With this solution, value is generated for both parties, creating a virtuous circle of advantages. This positive feedback loop is activated by leveraging network effects. The participation of one side of the network is what creates value for the other side, and vice versa. To start this circle of reciprocal benefit, readers should join Bookbuster first. When more readers join, the app becomes more attractive to authors and publishing houses looking to promote their books, increasing the amount of available books in the app. Therefore, pricing strategies will be aimed at attracting readers first, by employing discounts or free trials, with adjustments over time to also incentivize authors to not delay their participation. With a two-sided network connecting readers, authors, and publishers, Bookbuster is aiming to become a platform for literary discovery.

But how can Bookbuster realise this? Its business model creates two revenue streams, from both sides of the platform. For readers, Bookbuster could offer a subscription model or pay-per-use options for accessing specific trailers. A license fee could be asked for the other side to convert their books into trailers.

With Generative AI at its core, Bookbuster will be a game-changer in the book marketing industry, providing an affordable and accessible platform for all stakeholders in the world of literacy.

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In ten years, the landscape of graphic design will probably be entirely different. Generative AI (GenAI) and advanced image creation tools will take on a crucial role in transforming this industry. These technologies are already changing how graphical designers envision their craft, but imagine the potential influence it can have on the future of graphical designing.

Personally, I had never used an image creation tool until a couple of weeks ago. Since I am not a designer myself, I had already learned how to optimize the use of Canva, another designing tool. However, the big difference between Canva and Image creation tools is that with Canva you just use templates or recommendations, but bringing together different aspects to your own personal preferences is something you have to do yourself. With image creation tools, this entire creative thinking process can be skipped, which complete shook my mind. I used to create personalised menu cards, logos or invitations via Canva, but now I first saw the possibilities of creating images with Generative AI.

The first time I used ChatGPT for creating an image. I wanted to create a photo that I could use for my first blog post, so I uploaded my blog and told ChatGPT to create a suitable image for me. I was not entirely satisfied with the result, so I gave some feedback and it gave me an adjusted version. However, I still was unsatisfied but could not put my feedback in words to tell ChatGPT what I wanted to change exactly. Thus, I did not use the self created picture after all, but the future possibilities caught my attention.

It got me thinking about how we could use this feature, and what skills we needed to make optimal use of it. One challenge in particular, is that it is really hard to create an exact description of what the image needs to have, because the tool just guesses what you want. You have to be very specific if you want to create the perfect picture, and know what aspects need to be different. However, this tool can come in very handy for the idea generation. It can provide you with some examples to start your thinking process, and from here you can adjust anything based on your personal preferences.

So what could this mean for professional graphical designers? As these image creation tools become more advanced, they will smooth the fine line between human creativity and GenAI creativity. The role of the professional graphical designer may shift from hands-on creation to the case where the capability of selecting the best generated concepts becomes a key element for the skillset of a graphical designer Designers will need to develop from being makers to strategists who must understand not only aesthetics but also know how to align AI capabilities with brand identity, market trends and user experiences. They have to keep the overview, without losing their creativity or becoming lazy because they think they do not need to think for theirselves anymore.

Furthermore, as more businesses choose to use AI-generated designing techniques, differentiation will become essential. The capacity to combine personal or brand style, human intuition, and emotional depth with AI-driven workflows will be how you can tell designers apart. Rather than being replaced by Generative AI, future graphical designers will work together with these tools, using them as a creative partner to extend their own unique vision.

In 10 years, being a successful graphic designer will be less about mastering software and more about embracing innovation. I am curious how this will look like in the future and how these image creation tools will find their way to professional designers, as well as to lucrative users.

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More than 1 million people in the Netherlands play football under the Royal Dutch Football Association (KNVB), while only 26 men and 23 women make it to the national team. Scouting the right talent in the early stages of their career is an art itself, and professionals are trained to find the few players that grow out to be one of the successful ones. These scouts use data such as speed, goals, completed passes among others, but also review the role a player has in a team outside of these metrics. Is talent quantifiable in every aspect? Or do we need the human skills of a football scout to find the needle in the haystack?

Nnamdi Emefo, CEO of Afriskaut, spoke to the Global Business Report about using Artificial Intelligence to scout for young African sports talent. He talks about the model he built over the course of five years, where he now is able to extract all statistics from a video of a football match within 24 hours, for all 22 players on the field. He created a platform where all this data is available for the whole world to see (against payment). You might think, what is new about that and why can big professional football clubs not generate this theirselves? Nnamdi’s platform is so valuable that even the big clubs like Bayern use his platform. And it is not just football, other sports like tennis or basketball can also be converted into statistics by Nnamdi’s model.

And it appears to be successful in scouting talents. Right now African basketbal players are scouted using this model. These players were successfully matched with clubs in higher divisions. His model is not only able to generate a personal file of performance statistics, but is also able to see if there would be a match with a possible transfer team, taking all data of current players in that team into account.

Another success story besides in basketball can be found in football again, young African boys are also scouted for the youth teams of professional European clubs. His data base is used to find the optimal match that is a fit for both the player, as the team as the club. This way he gives young African boys the opportunity to be taken serious by European clubs, by providing them to prove their worth with data. He believes his model had the ability to mitigate racism in the scouting process, and thrives to be the key player in the scouting proces in the sports industry in Africa in the next couple of years.

See interview here: https://www.youtube.com/watch?v=74pzE6AofG4