Killer Switch: why decentralized AI is needed

AI has discreetly become critical infrastructure – as vital as electricity or the internet. Every business already depends on AI, often without even realizing the extent of that dependence:

• Customer Support: Chatbots handle millions of inquiries – API shutdown = paralysis of support services.
• Code Generation: Developers use Copilot and ChatGPT daily – productivity drops by 30-50% without them.
• Analytics: Models analyze data, generate reports, forecast demand.
• Content: Marketing, SEO texts, translations, design – AI automates routine tasks.

The API of a single company – OpenAI, Google, or Anthropic – becomes a single point of failure (SPOF) for thousands of businesses. OpenAI has experienced global outages multiple times: each one halted hundreds of thousands of applications built on their API. AWS us-east-1 downtimes caused cascading failures across the internet – and AI-dependent services suffered first.

OpenAI's projected losses – $112 billion by 2030 – question the sustainability of its business model. What happens if a company, on which millions of businesses depend, goes bankrupt or radically changes its terms? Dependence on a single AI provider is not just a technical problem; it's an existential business risk.

Centralized AI creates four categories of risk, each of which is already playing out in practice:

Censorship. Every AI company sets its own rules about what a model can and cannot say. Models refuse to discuss certain topics, generate certain content, or answer "inconvenient" questions. For a business, this means you don't control the capabilities of the tool your product is built on. The rules can change at any moment — without warning and with no way to influence the decision.

Kill switch. Russia, Iran, China, North Korea and dozens of other countries are already facing restrictions on access to AI services. One decision by the US government — and OpenAI blocks its API for an entire country. This isn't a hypothetical: it's already happening. For countries building their economies on AI, it's the equivalent of being cut off from the power grid.

Price blackmail. When a business depends entirely on one company's API, the monopolist can raise prices without limit. OpenAI changes its rates regularly, and companies that have invested millions in integration are forced to pay — because switching to an alternative would cost even more. Small businesses suffer first: $2.50—15 per million tokens is an impossible sum for a startup in a developing country.

Data leaks. Every request to centralized AI passes through one company's servers. All your prompts, customer data, business logic, confidential documents — all of it is stored and potentially analyzed. Corporate secrets shared through ChatGPT are effectively under OpenAI's control — with all the attendant leak risks.

Decentralization eliminates each of these risks at the architectural level — not through management promises, but through protocol mathematics.

No single point of failure. Requests are processed by independent MLNodes around the world (GPUs in the network: 584, MLNodes: 121). If one node goes offline, the Transfer Agent instantly redirects the request to another. The failure of 10%, 50%, or even 90% of nodes does not stop the network — it continues to operate as long as there is at least one active node. This is the same principle that makes the internet resilient: a network, not a server.

No censorship. No single company controls what AI can answer. Models in Gonka operate without corporate "guardrails" — the network is open. This does not mean a lack of responsibility — it means the decision about content suitability is made by the user, not a board of directors in San Francisco.

Prices are determined by the market. Competition among independent hosts ensures market pricing. The cost of an AI request via Gonka is $0.0069 per million tokens, ~720 times cheaper than OpenAI GPT-5.5. A monopolist cannot raise prices because there is no monopolist.

Privacy. Requests are not stored on the servers of a single corporation. They are processed in a distributed manner: the Transfer Agent directs the request to an MLNode, the node processes it, and returns the result. Your data is not accumulated in one place, which radically reduces the risk of leaks. This is analogous to the difference between an intranet (one owner) and the internet (a distributed network): the latter is resilient by definition.

Decentralized AI isn't just a technical solution — it's a geopolitical tool. AI is called "the new oil" — and control over AI compute is becoming a matter of national security. A country without access to AI finds itself in the same position as a country without oil in the 20th century — dependent and vulnerable.

Bhutan became the world's third mining state (after El Salvador and the CAR), leveraging cheap hydropower. A small Himalayan country with a population of under a million has made a strategic bet on crypto — and is showing interest in DePIN projects like Gonka.

Uzbekistan is considering integrating state data centers into the Gonka network. For a country that can't buy millions of GPUs from NVIDIA (quotas are limited, with priority given to the US and its allies), connecting existing capacity to an open network is the only realistic path to AI sovereignty.

This pattern scales: dozens of "second-tier" countries — from Kazakhstan to Nigeria, from Vietnam to Argentina — have GPU capacity but no access to cutting-edge AI models. Gonka gives them infrastructure: connect your GPUs, earn GNK for the work, use AI without intermediaries. Digital sovereignty isn't a slogan — it's a concrete architectural possibility: countries, companies, and developers gain access to AI without dependence on Big Tech and without the risk of a kill switch.