Vol.013 RBC Perspectives|Digital Content Is Eating The World


Image Credit: iStock / Metamorworks


The onset of the global pandemic has brought about a transformation that made our daily lives more digital than ever. Shopping online, attending conferences online, and owning digital assets online are just but a fraction of the new world we are living in. As blockchain technology advances at an accelerated pace, our life will further converge with the digital world, ultimately shaping the future of Metaverse and digital asset ownership for humanity. This trend presents challenges and opportunities along the way, especially for web3 and AI startups, as the amassing number of digital content, services and assets must be properly managed.



Shedding Light into the Inequalities in the Creator Economy

While content creation has gained momentum as a thriving economic model, there is a wide gap in the revenue distribution within the industry. One fundamental struggle for digital content creators is the imbalance in the creator economy. As content creators rely heavily on the platform's distribution power, platforms depend on brands to generate advertising revenue and actively seek creators with the greatest number of followers to maximize their profits. Even if content creators understand how to engage the audience and optimize the algorithm to foster a successful business, it may not justify the incomes they receive. Furthermore, the platform’s recommendation engine may direct users to the top content providers rather than individual creators in order to maximize user engagement and profits. With an apparent hierarchical disparity in the content platforms, creators will often have to take distribution into their own hands to yield more favorable returns for their invested time and effort.

To enhance their content and distribution, creators must produce videos with high-quality and high-precision tags, which in turn generate higher conversion, search results and get more recommendations by the platform's system. However, it can get daunting and time-consuming to provide comprehensive and desirable contextual information for the videos due to their repetitive nature. Moreover, given that cookies will one day disappear and consumer data will become completely decentralized belonging to individuals instead of large corporations, it will become even more challenging for anyone to discover the content they are looking for in an infinite space.

In the past, you could consult real people to find the right art piece in a physical store. Who will assist you with scouting the best NFTs online in the future? You might have a good visual sense of what you are looking for, but if you forget the title, you might never find it. Like in the early days of web2, which was primarily text-and-index-based, recommendations and searches were usually noisy.



Empowering Creators to Control their Own Destiny

In a decentralized world where vast digital assets and services are created by individuals, matching the right content to the right people is more crucial than ever. Therefore, the need to contextualize all kinds of data, such as visuals, sounds, text, and user data, with AI or deep learning has exploded. By extracting the entity names from video content and automatically providing optimized titles and tags, AI can create personalized user experiences, boost engagement and better serve consumers in the digital world.


Image Credit: Lucid Inside


That’s when we stumbled upon Lucid, an AI company that contextually understands and personalizes digital content for the right person at the right time. As the leader in building knowledge graphs for combined data interpretation (visuals, sound, text, etc.) with over 6 years of training, scaling, and advancing their AI senses and brain, Lucid transforms visual, auditorial, and user behavior data into a graph representation, similar to the way a brain is structured to make decisions to serve the right digital content to the right audience based on contexts. They initially started processing and personalizing videos but have quickly expanded into all types of digital content, as the web3 market pulled them into solving the endless content problems that will only worsen in the increasingly digitalized world. 

The power of digital content personalization is leveraging AI to generate, recommend and find content for you based on data and analytics. Instead of only showing you how it's performing, Lucid's solutions act on the data and review them while allowing consumers to have control over their own data rather than passing them through to large enterprises.



Adding Intelligence To The Next Stage Of Web3

Source: AdobeStock / JorgeEduardo


This is the perfect example of the next stage we see in web3 and the decentralized digital world. Not only does it create automation and scale through AI and data, but it also delivers the targeted personalization a vast digital world truly needs. The possibilities to realize the 1:1 experience by giving recommendations and helping users navigate their preferences based on contextual understanding mark the dawn of the next stage in the digital world. Since AI is 1000x faster and more precise in identifying and matching content to consumers' needs, you no longer need to feel lost in the vast space of digital offerings while struggling to find balance in the power dynamics among consumers, content creators and platforms. 

One type of digital content in the web3 space that can benefit from AI are NFTs. There are approximately 2.7 million NFTs on the marketplace and half a million collectors holding on average four to five digital assets. One of the biggest challenges for marketplaces is to drive retention and secondary market traction to become more of a sustainable business versus one-time NFT drop sales. Lucid’s AI helps users discover the most suited NFTs by understanding their preferences and shopping behavior while boosting sales and repeated purchases through analytics. If someone acquires an NFT, AI would recommend a few similar NFTs, or an NFT that has “contextual connections” with the acquired NFT. One key example - if a user purchases BAYC, the AI wouldn’t just recommend NFTs that are ape-related, but more options under the Yuga Labs ecosystem. Not only would it suggest NFTs like MAYC, but it also proposes other NFT projects that are affiliated or partnered with it, from a corporate level down to the discord level. Since web3 is built all on digital data, AI-driven solutions that understand the user behavior and contextual data of digital assets are definitely here to stay.