The TikTokization of Everything: AI, Learning Techniques, and the Future of Tech

The TikTokization of Everything: AI, Learning Techniques, and the Future of Tech

In today's digital age, where attention is the currency of the online world, it comes as no surprise that money follows attention, especially in the realm of advertising. This is why digital ad spending for mobile has been steadily increasing over the years. Additionally, with the vast amount of data being generated, it's no wonder that most of it is stored in the cloud. However, while these markets are not yet saturated, the opportunities in these areas may be becoming more limited.

So, where is the venture capital money flowing these days? One possible answer lies in emerging technologies such as virtual reality/augmented reality (VR/AR), web3, and artificial intelligence (AI). With recent advancements in AI, leveraging data for better recommendations has become easier than ever. A prime example of this can be seen in the commerce industry with companies like SHEIN utilizing AI algorithms to provide personalized recommendations to their customers. The trend of AI is not limited to a single industry; we will see its influence in various sectors in the coming years.

Speaking of AI, one of the most prominent applications of this technology that has captured the attention of millions is TikTok's For You Page. Through sophisticated recommendation algorithms, TikTok's AI anticipates users' preferences and delivers a curated feed that keeps them engaged for hours. This showcases how AI has transitioned from the infrastructure layer to the application layer, where everyday people directly interact with it.

While AI holds immense potential, it is crucial to understand how we can effectively learn and comprehend the complexities of this technology. This is where the Feynman Learning Technique comes into play. Named after Richard Feynman, a renowned physicist, this technique offers a simple approach to learning anything new. The technique revolves around the idea that true learning occurs when we can explain and apply the information in various contexts.

The Feynman Learning Technique consists of four steps. The first step involves pretending to teach the concept or topic to a sixth-grade student or even a rubber duck. This step forces us to simplify and clarify our understanding. If we struggle to define the words and terms we are using, it indicates a lack of true comprehension.

The second step is to identify gaps in our explanation. This involves recognizing areas where we may forget crucial information, struggle to explain it, or have difficulty understanding how variables interact. Identifying these gaps is essential as it allows us to focus on filling them and expanding our knowledge.

Once the gaps have been identified, the next step is to organize and simplify the information. This step helps us create a coherent mental model of the subject matter, making it easier to recall and apply the knowledge in different scenarios. Organizing and simplifying also help define our circle of competence by understanding the boundaries of our understanding.

The final step of the Feynman Learning Technique is optional but highly recommended – transmitting the knowledge to others. The ability to convey complex ideas in a simple manner is a true test of our knowledge. As the saying goes, "If you can't explain it simply, you don't understand it well enough." Transmitting knowledge not only solidifies our own understanding but also allows us to contribute to the collective learning of others.

Learning is not a solitary endeavor; it happens through exposure to various sources of information and engaging in conversations with others. Learning in public, as some would say, is a way to learn collectively. By seeking out different perspectives, ideas, and opinions, we broaden our understanding and challenge our own preconceived notions.

It's essential to approach learning with an open mind and a willingness to question our own knowledge and that of others. Knowledge is not static, and continual evaluation is necessary to keep improving. Errors often arise from a lack of information, and by being open to new insights, we can fill those knowledge gaps.

In conclusion, the convergence of AI, effective learning techniques like the Feynman Learning Technique, and a growth mindset towards collective learning will shape the future of technology. As AI continues to evolve and permeate various industries, the power of personalized recommendations and anticipating user desires will become more prevalent. By adopting the Feynman Learning Technique and embracing a learning journey that includes collective knowledge, we can actively participate in this technological revolution.

Three actionable advice to take away from this article are:

1. Embrace the Feynman Learning Technique in your pursuit of knowledge. Simplify, clarify, identify gaps, organize, and transmit your understanding to solidify your knowledge.
2. Engage in collective learning by seeking out diverse perspectives and engaging in conversations with others. Learning in public allows for a more comprehensive understanding of complex topics.
3. Continually question your own knowledge and be open to new insights. Knowledge is not static, and by challenging our own understanding, we can grow and improve.

Remember, the future is in our hands, and by combining AI advancements, effective learning techniques, and a growth mindset, we can shape a world where technology serves us in the most meaningful and beneficial ways.