The brief history of artificial intelligence: The world has changed fast – what might be next? Just 10 years ago, no machine could reliably provide language or image recognition at a human level. But, as the chart shows, AI systems have become steadily more capable and are now beating humans in tests in all these domains. This rapid progress can be attributed to three fundamental factors: training computation, algorithms, and input data.

The brief history of artificial intelligence: The world has changed fast – what might be next? Just 10 years ago, no machine could reliably provide language or image recognition at a human level. But, as the chart shows, AI systems have become steadily more capable and are now beating humans in tests in all these domains. This rapid progress can be attributed to three fundamental factors: training computation, algorithms, and input data.

Training computation is measured in floating point operations, or FLOP for short. One FLOP is equivalent to one addition, subtraction, multiplication, or division of two decimal numbers. All AI systems that rely on machine learning need to be trained, and in these systems, training computation plays a crucial role in driving the capabilities of the system. For the first six decades, training computation increased in line with Moore’s Law, doubling roughly every 20 months. However, since 2010, there has been an exponential growth in training computation, with a doubling time of just about 6 months.

This exponential growth in training computation has led to the development of more powerful AI systems. In fact, according to a report, there is a 50% probability that "transformative AI" will be developed by 2040. This means that human-level artificial intelligence could become a reality within the next two decades, or possibly even sooner.

Now, let's shift our focus to the world of newsletters. Email newsletters have been around longer than the web itself, and paid newsletters have been around longer than the internet. In the past, there were always two constraints when it came to one-writer businesses. First, generating meaningful ad revenue on the web required more traffic and more writing than a single person could produce. Second, creating a mass-market paid blog model proved to be challenging.

However, the rise of platforms like Substack has changed the game. Substack made publishing and charging for newsletters easy by providing an all-in-one solution. With Substack, you can easily create a website, manage memberships, send emails, and process payments. This simplicity has attracted many writers to monetize their content through paid newsletters.

Substack also offers a user-facing brand that provides a platform for recommendations and discovery. In the early stages of a new platform, the first creators to offer something valuable have the opportunity to thrive and become influential. However, as more creators join the platform, the dynamics change, and the question of "what happens when there is more stuff on your platform than anyone can look at?" becomes essential. This question defines the true meaning of a product and its role in the network.