The fundamental driver of AI advancement has been the incredible increase in computing power and breakthroughs in algorithms, which will continue to grow, allowing us to approach human-level intelligence in the next decade.

Current AI models are increasingly capable of solving a growing set of problems year-over-year due to algorithmic improvements and better hardware scaling.

The exponential increase in computational power is driving advancements in AI, leading to significant improvements in technology and capabilities, and the law of accelerating returns indicates that technological progress, including AI, continues to advance exponentially, as evidenced by a chart I found 45 years ago.

We're currently experiencing a Cambrian explosion in AI, with advancements in processing text, pixels, videos, and audio, leading to new applications and models.

The pace of AI improvement is unprecedented, outpacing previous technological advancements like cloud computing and processors, surprising even those within the tech industry.

Both algorithmic improvements and computational advancements, such as better chips and larger data centers, are essential for progress in AI.

There's a significant gap between the current compute capabilities and what could be achieved with ten to a hundred times more compute, which would allow for much greater AI services.

Despite expectations of a slowdown, AI advancements have continued to accelerate over the past three years.

The next decade will see profound changes in computing, driven by advancements in AI and the transition from traditional software to AI-driven solutions.