A Few Things I Believe About AI and the Future of the Social Web

A Few Things I Believe About AI and the Future of the Social Web

In the rapidly evolving world of artificial intelligence (AI), there are two essential components of intelligence: reasoning and knowledge. While advancements in reasoning have been significant, the knowledge base of AI models is still limited. This presents a bottleneck in the performance of AI systems, as their ability to reason is dependent on the knowledge they have access to.

This problem, known as knowledge orchestration, is one of the biggest challenges faced by AI builders. It involves the storage, indexing, and retrieval of knowledge to enable AI models to perform complex language tasks. Fortunately, strides are being made in this area. GPT-4, for example, has a 32,000 token context window, which is eight times better than previous models.

Another aspect of knowledge orchestration is the type of knowledge that is most valuable. One type that holds great promise is end-to-end interaction data about the lifecycle of any process. This data allows AI models to understand the entire process from beginning to end, including all iterations and editing steps. With this knowledge, models can be steered using techniques like reinforcement learning through human feedback, fine-tuning, and prompting to automate and improve these processes over time.

The future of the social web is closely tied to the concept of interoperability. Interoperability refers to the ability of multiple products or services to make use of the same information. It is the connecting thread that will shape the social web of tomorrow. Interestingly, interoperability was also a core benefit mentioned during the Web 2.0 era.

However, the social giants of Web 2.0, such as Facebook and Twitter, did not prioritize interoperability. Instead, their business models revolved around capturing and monetizing user data. The next iteration of the internet, often referred to as Web 2.5, emphasizes the importance of creators and their relationships with their audience.

In this new era, creators will have the ability to publish anywhere and have auto-updated profiles. Consumers will be able to follow their favorite creators across various platforms. The success of platforms like Substack and Patreon, which prioritize creator success over consumer engagement, demonstrates the demand for a more creator-centric approach.

Mirror, a platform that focuses on interoperable content graphs and internet-native money in the form of tokens, is a prime example of this shift. It aims to create a dynamic ecosystem where creators can establish complex business relationships with their content, other creators, and their audience. Mirror's core structure, although still evolving, shows a clear vision for the future of the social web.

One of the key features of Mirror is the unique creator ID, which allows creators to connect their content to their identity. This open database of content, combined with open social and economic graphs, enables creators to build their own networks and monetize their work. While owning content may not be the main focus of Mirror's strategic moat, the platform empowers creators to leverage their content in innovative ways.

However, achieving widespread interoperability is not without its challenges. High transaction fees, the complexity of managing crypto wallets, and the scarcity of talent in the space are some of the barriers that need to be overcome. Additionally, privacy, security, and moderation are critical considerations that must be addressed to ensure the responsible use of interoperable systems.

In conclusion, the future of AI lies in improving knowledge orchestration and leveraging end-to-end interaction data to enhance reasoning capabilities. The social web of tomorrow will be driven by interoperability, empowering creators and allowing for more seamless content sharing and monetization. To embrace these future trends, here are three actionable pieces of advice:

1. Emphasize knowledge orchestration: Invest in tools and infrastructure that enable efficient storage, indexing, and retrieval of knowledge to enhance AI reasoning capabilities.

2. Prioritize interoperability: Explore platforms and technologies that promote interoperability, allowing creators to reach wider audiences and establish meaningful connections.

3. Foster a creator-centric approach: Create platforms and business models that prioritize the success of creators, as they are the driving force behind the next iteration of the internet.

By embracing these principles, we can unlock the full potential of AI and build a more interconnected and creator-driven digital landscape.