The internet was the last big change, and now it's maturing into what we call cloud computing, simplifying user devices while increasing complexity in the network.

Investors today are focusing on building physical infrastructure like data centers, similar to how they invested in fiber infrastructure during the internet boom.

The demand for computing power is growing rapidly, and we can't ramp up spending fast enough to keep up with use cases.

The capabilities of AI are rapidly evolving, leading to increased demand for data centers and chips, contrary to expectations that efficiency would reduce these needs.

I realized that if you have a source of time in a network, you can build a more efficient system that utilizes the entire bandwidth allocated to it, unlike traditional protocols that suffer from inefficiencies.

The shift from scaling up to scaling out in technology means moving towards more distributed computing, which allows for greater accessibility and lower costs.

The current high inference costs resemble an iceberg, where reducing these costs can enable applications to scale into sustainable businesses.

Cloud computing is a branding evolution of the internet, which has been continuously developing for over a decade, not something entirely new.

We need to rethink traditional algorithmic analysis to account for network and memory bandwidth, as these factors are crucial in modern machine learning computing.