When Creation Goes To Zero: AI's Impact on the Economy and Startups

When Creation Goes To Zero: AI's Impact on the Economy and Startups

The rise of the internet brought about a significant consequence - it pushed distribution costs to zero. Suddenly, anyone with an internet connection could distribute their content, products, or services to a global audience without incurring large expenses. This revolutionized industries and gave birth to new business models.

Now, another transformation is on the horizon, and it's all thanks to artificial intelligence (AI). The most significant consequence of AI is that it will push creation costs to zero. This means that machines and algorithms will be able to create content, products, and services at a fraction of the cost that humans incur. But what does this mean for our economy?

To understand the impact of AI on creation costs, we need to look at two key developments. First, the introduction of transformer models allowed computers to understand text. This breakthrough enabled machines to comprehend context and apply it to a defined set of parameters. Second, the astronomical increase in computing power and financial resources unlocked in recent years. GPUs proved to be ideal for running deep learning and machine learning algorithms, allowing for more complex problem-solving.

With these advancements, we are now at a point where computers can not only understand context but also create content based on that understanding. The implications are vast, ranging from automated content generation to personalized product recommendations. But as creation costs approach zero, the focus shifts to acquisition. In other words, how can businesses compete for customers when everyone has access to the same creation capabilities?

Interestingly, the impact of AI on different industries varies. For example, the crypto industry has largely been dominated by startups, with very little participation from existing financial services or infrastructure companies. On the other hand, the mobile industry saw a mix of startup and incumbent capture, with companies like Apple and Google taking a significant share of the value.

One hypothesis for this disparity is that the prior wave of AI created better products, but they were not remarkably better than incumbents or hard market structures. Additionally, incumbents may have enjoyed an advantage due to their access to valuable data. However, as companies leverage the broader internet as an initial training set and switch to models that work robustly with smaller data sets, the data advantage diminishes.

Furthermore, certain markets prove to be challenging for startups due to market structure, regulation, or a lack of responsiveness to end-user needs. Education and healthcare are examples of such hard markets, where incumbents often prevail over technological innovation.

So, what lies ahead for startups in the AI era? Here are three actionable pieces of advice:

1. Keep an eye on emerging technologies: Future language models like GPT-4 have the potential to revolutionize consumer and B2B interactions. Startups should explore how these advancements can enhance their products and services.

2. Focus on infrastructure: While incumbents may have failed to capitalize on their AI advantages, startups can provide valuable infrastructure to the industry. Identify gaps and build solutions that enable others to leverage AI effectively.

3. Target untapped app use cases: Look for areas where there are no strong incumbents and clear use cases for AI. Marketing copy generation, image generation, and code generation are just a few examples. Imperfect fidelity is acceptable as long as there is room for human review and improvement.

As the AI landscape evolves, it's crucial to focus on end-users and markets. While incumbents may capture the lion's share of value due to their scale, startups can still make a significant impact in terms of market cap and their contributions to the world.

In conclusion, AI's ability to push creation costs to zero will undoubtedly reshape our economy. Startups need to adapt to this new reality by leveraging emerging technologies, providing valuable infrastructure, and targeting untapped app use cases. The future of AI-powered startups holds immense potential, and those who embrace it will be at the forefront of innovation and disruption.