Whoever Controls Compute Implicitly Controls the Future of AI

Training large models requires building or upgrading data centers.

- Anastasia Matveeva Co-Founder Gonka

But centralized infrastructure is now running into hard physical limits. To improve this infrastructure, AI is being implemented to produce abundance and intelligence. However, the control over computing is becoming a critical point of power in the AI industry.

Here Gonka comes to the rescue. Gonka protocol is a permissionless and global network where anyone can join, and requests are routed programmatically across distributed participants.

In this exclusive conversation with Analytics Insight, Anastasia Matveeva, Co-Founder and Senior Product Manager at Gonka, discusses how they are bringing innovation to compute access for a more controlled and safe AI ecosystem.

Much of the public debate around AI focuses on the centralization of models, but far less attention is paid to the centralization of compute. Why is control over compute becoming a critical point of power in the AI industry, and what risks does this concentration pose for innovation and the market as a whole?

Much of the public debate around AI focuses on models because they are visible. But the real locus of power sits one layer below: compute - the substrate that determines who can build, deploy, and scale AI systems.

Control over compute is becoming critical for economic and physical reasons. The main bottleneck in modern AI is no longer algorithms - it is access to GPUs, energy, and data-center capacity. Training large models increasingly requires building or upgrading data centers. But centralized infrastructure is now running into hard physical limits: energy density, cooling constraints, and the maximum power that can be delivered to a single location. The industry is experimenting with extreme solutions – redesigning chips, cooling, and new energy sources.