Open-source AI glasses by Brilliant Labs AR

AI research is changing very fast. Imagine a world where AI can improve itself. That world might be closer than you think. When AI can do its own research, it can solve problems much faster. This could speed up progress in many fields.

If AI runs research non-stop, it can achieve a lot in a short time. A decade of research might take only a year. This could lead to huge discoveries much sooner than expected.

We have seen big steps with different AI models. GPT-3.5 led to GPT-4. GPT-5 is expected to make another big leap. These models keep improving and becoming more powerful. But growth might slow down after GPT-6 until new supercomputers are ready.

Once these supercomputers are online, the growth could speed up again. Automated AI research could lead to even faster progress. Growth might not be endless because of physical limits. But it could still look very quick for a while.

It's hard to predict exactly how this will happen. Most AI research is private. We don't have all the information. But some experts think we are seeing a pattern. At first, growth looks very fast. Then it slows down. This is called a logistic trend.

Before a breakthrough, growth can seem exponential. This means it looks like it is speeding up all the time. Yet, every fast growth will eventually slow down. To keep growing, we need new innovations. These are called paradigm shifts.

Each new technology builds on the one before it. This makes it look like non-stop rapid progress. But really, it's a series of steps. Each step goes up, then levels off. Then a new step starts. Over time, this creates a pattern of fast progress.

An example is Moore's Law. It predicted that computer power would double every two years. This held true for many years. But even that progress is slowing now. We need new ideas to keep improving.

AI research might follow a similar path. We will see fast growth, then it will slow, then pick up again with new discoveries. These discoveries are hard to predict but are crucial for continued progress.

In summary, the future of AI is exciting. Fast growth with new AI models will continue. But it will also need new breakthroughs to keep moving forward. The pattern of rapid steps followed by pauses will likely continue. This cycle is what drives long-term progress.