Sam Altman, co-founder of OpenAI, posted to X earlier today saying:

What we do think might make sense is governments building (and owning) their own AI infrastructure, but then the upside of that should flow to the government as well.

This was in response to accusations that OpenAI is looking for government subsidies/loans. To be honest though, government-backed AI infra sounds like a dystopian nightmare.

Government-Backed AI

First, where would the government get the money to build their own AI infrastructure, considering that they are already

? Perhaps they will just get the privately-owned Federal Reserve to print it for them?

Now imagine the government owning the majority of our AI infrastructure, including the GPUs, energy sources, as well as the data used to train AI models. It would be the ultimate wet dream of a dictator who is seeking complete top-down control.

Future generations could end up being educated by chatbots that have been trained on government-sanctioned datasets that are both historically inaccurate and insanely woke.

Community-Owned AI

In an ideal world, the AI infrastructure would be decentralized, and owned by communities who actually care about the truth and future generations.

But how do we do it?

Thanks to the technology behind Bitcoin and Ethereum, we now have the means to democratize the rapidly growing AI industry.

For example, the objective of many

is to decentralize AI infrastructure, by rewarding participants for contributing resources to the network, whether that be energy, GPUs, or data.

Decentralizing GPUs

Projects like

allow GPU owners to earn AKT tokens for lending their equipment to the network. These GPUs can then be used to train AI models, and run inference on them.

There are also projects like

building on Solana that reward GPU owners in NOS tokens for their resources.

Verifying Data Provenance

How do we eliminate wokeness and historically inaccurate data from large language models used by chatbots?

Community-owned blockchains can be used to verifiably and immutably log the provenance (source, timestamp, and integrity) of every data point used to train AI models, creating a tamper-proof audit trail from raw input to final weights.

This is especially useful for bias mitigation (eliminating woke input, for example), and building trust in chatbots that future generations will use to educate themselves.

Data As A Verifiable Asset on Chain

How is the data verified?

Every training data item (text, image, video, sensor reading) is treated as a digital asset with:

• Hash (cryptographic fingerprint)
• Metadata (source URL, author, license, timestamp, etc)
• Signature (from data owner or crawler)

These are recorded on a public blockchain (like Ethereum) before ingestion into the training pipeline.

Until next time...

Letting the government handle the majority of the AI infrastructure would lead us towards a dystopian future, where a few giant corporations would have top-down control, and children are taught falsehoods by chatbots.

We should be working towards community-owned AI infrastructure, and use public blockchains to verify that the data being fed into AI models is both true and accurate.

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Sources

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