<aside> 💡 Summary: Over the next decade, AI investment is expected to surge, with companies like Microsoft and Meta leading massive datacenter expansions. This could lead to a 100 to 10,000-fold increase in compute power for AI training. Performance per dollar is projected to improve significantly, although risks like monopolies and technological limits could impede progress. Algorithmic advancements will further enhance AI capabilities, potentially unlocking new functionalities such as reasoning and planning. <removed Integral strategy bit>
</aside>
In the last decade, from 2014 to 2024, AI capabilities such as text generation, knowledge retrieval, and multimodal understanding (voice, text, image, video), have rapidly improved. These and future advancements are opening many new possibilities for AI applications. For example, a fast, high-quality voice-enabled AI could be used to create a voice-enabled AI leadership coach.
To accurately assess where Integral should focus its products & technology investments, it’s essential to predict where the technology will be in 3-5 years and beyond, enabling us to skate to where the puck is going, not where it is.
This memo explores the historical advancements in AI, identifies the key "building blocks" for improved AI capabilities, and assesses the likelihood of enhancements in these areas. I then discuss how these improvements could expand AI capabilities, such as increased knowledge, speed, and memory, and explores potential new use cases for Integral.
In summary, I will explore these four questions:
To get a sense of improvement of AI, here are some examples of real-world capabilities of AI. Showing AI is improving in areas such: