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Decentralized AI: A Solution to Centralization and Soaring Model Costs
Decentralized AI: A Solution to Centralization and Soaring Model Costs
 ### 0xSammy@0xSammy
> train a model for $5M
> next one costs $100M
> next one costs $1B
> 5 companies own all the AI
> rest of the world rents access at their margins
> crypto says “we can fix this”
> launches 128 subnets competing to produce intelligence
> miners earn TAO based on output quality
> one subnet hits $5.5M annualized revenue
> another signs Reading FC and 3,000 petrol stations
> another gets research accepted at NeurIPS
> another is discovering drug compounds 24/7
> largest permissionless pre-training run ever conducted
> grayscale files an ETF
> a state VC fund backs the ecosystem
> OpenAI valued at $500B
> the decentralized alternative: $4B
> you mass-allocated to Nvidia
> the Intelligence Olympics were running the whole time Show More
00:16
#### Khala Research
@KhalaResearch · 4w ago
Training a frontier AI model cost $5M in 2020. Today it costs $1B+
The gap keeps compounding, in favour of the same five companies
A decade ago, nobody believed open-source could compete with enterprise software. But then it did
Bittensor (TAO) is a global open market where subnets compete to produce AI services, getting paid based on quality output
This is what crypto is good at - coordinating users with shared incentives
Over the past 12 months, significant progress has been made in the ecosystem; recurring fiat revenue, enterprise contracts, decentralized research and more
In our TAO report, we:
1) Profile 5 subnets generating revenue across inference, computer vision, compliance, and drug discovery
2) Show how token incentive mechanics create advantages centralized companies cannot replicate
3) Breakdown catalysts and risk factors of subnets and Bittensor
The link to the full report is in the next post below:Show More
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Mar 17, 2026, 9:39 PM View on X
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33.4K Views  0xSammy @0xSammy
One Sentence Summary
This tweet contrasts the escalating costs and centralization of frontier AI development with the potential of decentralized AI networks like Bittensor (TAO) to foster diverse, quality-driven intelligence production.
Summary
The tweet uses a 'greentext' narrative to highlight the rapid increase in AI model training costs (from $5M to $1B) and the resulting centralization of AI ownership among a few companies. It then introduces decentralized alternatives, specifically Bittensor (TAO), where 128 subnets compete to produce intelligence, earning rewards based on output quality. The quoted tweet provides further context, detailing how Bittensor acts as a global open market for AI services, with examples of subnets generating revenue, conducting research, and discovering drug compounds, positioning it as a viable, decentralized alternative to the current centralized AI paradigm.
AI Score
82
Influence Score 54
Published At 03-17
Language
English
Tags
Decentralized AI
Bittensor
TAO
AI Centralization
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