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去中心化 AI:解决中心化与模型成本飙升的方案

📅 2026-03-18 05:39 0xSammy 人工智能 4 分鐘 4877 字 評分: 82
去中心化 AI Bittensor TAO AI 中心化 AI 成本
📌 一句话摘要 这条推文对比了前沿 AI 开发成本的不断攀升和中心化趋势,以及像 Bittensor (TAO) 这样的去中心化 AI 网络在促进多元化、质量驱动型智能生产方面的潜力。 📝 详细摘要 这条推文通过“绿字”叙事风格,强调了 AI 模型训练成本的迅速增长(从 500 万美元增至 10 亿美元),以及由此导致 AI 所有权集中在少数几家公司手中的现象。随后,它介绍了去中心化的替代方案,特别是 Bittensor (TAO),其中 128 个子网竞争生产智能,并根据输出质量获得奖励。引用的推文提供了进一步的背景信息,详细阐述了 Bittensor 如何作为一个全球开放的 AI 服务
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Decentralized AI: A Solution to Centralization and Soaring Model Costs

Decentralized AI: A Solution to Centralization and Soaring Model Costs

![Image 2: 0xSammy](https://www.bestblogs.dev/en/tweets?sourceId=SOURCE_4f9754ed) ### 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

!Image 3: 视频缩略图

00:16

!Image 4: Khala Research

#### 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

!Image 5: Tweet image

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Mar 17, 2026, 9:39 PM View on X

18 Replies

16 Retweets

219 Likes

33.4K Views ![Image 6: 0xSammy](https://www.bestblogs.dev/en/tweets?sourceid=4f9754ed) 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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