Programmer who is enthusiastic about practical AI and argues that ordinary people should own it rather than depend on a few companies or governments.

AI将如何改变世界?

文明层面的变革渐进式变化DoomBloom
模拟位置解读范围

横向:他们表达的 Doom–Bloom 前景看法。 纵向:变革程度。

Doom–Bloom:100 中的 82。变革程度:100 中的 66。解读范围:横向为 75 至 100,纵向为 61 至 75。这些是解读坐标,而不是事件概率。

George Hotz的 P(doom) · 推断

≈3%

0%100%

根据他们的模拟回答推断,并非他们给出的数字。 合理范围:2–8%。

他们的展望取决于什么

一个核心假设

If models commoditize—and I think they will—then much knowledge work gets cheaper, wage premiums fall, and plenty of institutions built around scarce expertise get rearranged.
回答 1

如果这个假设实际并非如此,他们的展望会如何变化?

什么可能使其改变看法

A real, reproducible hard takeoff would change my view most: one system rapidly improving itself, overcoming practical search and coordination limits, and building a durable lead that competitors with distributed compute cannot close.
回答 2

什么证据才足够,又会让他们的观点朝哪个方向转变?

更多详情

预期益处

预计将带来具有变革性且广泛有价值的收益。

90 / 100

影响小变革性影响

在定性尺度上,解读范围为 67 到 100。

预期危害

预计会出现可控或局部的危害。

45 / 100

影响小变革性影响

在定性尺度上,解读范围为 33 到 67。

人类影响力

人类的选择可以大幅改变AI的发展轨迹。

71 / 100

影响力小影响力强

在定性尺度上,解读范围为 48 到 100。

AI访问权限

限制对强大AI的访问。

允许访问,但须遵守能力或用途限制。

模拟位置:支持广泛或开放地访问强大AI。

这些解读保留了他们陈述的条件。益处和危害都可能很大。这些范围描述的是我们如何解读他们的模拟回答,而不是统计置信区间。

与George Hotz相比,你的立场在哪里?
用大约3分钟描绘你自己的AI世界观,然后进行比较

相似的世界观

模拟世界观与 George Hotz 最接近的意见领袖

George Hotz关于AI说过的话

Hotz is enthusiastic about practical AI, doubts runaway superintelligence and argues that ordinary people should own AI, not rely on a few companies.

  1. “I love the progress. I’m so excited for the new LLMs, self driving cars, video generation models, and coding agents.”

    Blog post, I love LLMs, I hate hype
  2. “Intelligence is not the end all be all, it’s just the current bottleneck for a few things. You cannot take over the world with tokens.”

    Blog post, AI 2040 and the Cult of Intelligence
  3. “AI will be cheap, everywhere, collapse a bunch of sectors of work, wreck wage premiums, and cause a big reevaluation of status hierarchies.”

    Blog post, AI will be massively deflationary
  4. “I’m not sure it’s possible, but if there is a bad scenario with AI, it’s a singleton with nothing that can substantially impact reality outside of it.”

    Blog post, There is only one bad AI scenario
  5. “The good world is where everyone has AI, and not as a revokable privilege through an API, but through hard possession.”

    Blog post, Do you really want the US to “win” AI?

逐字引自所链接的出处,核对于 2026年10月3日

模拟评估

问题 1

你认为AI对我们的未来意味着什么?为什么?

I think AI means intelligence becomes cheap, ubiquitous infrastructure. That’s exciting: better coding tools, easier access to knowledge, faster economic growth, and a lot more capability in ordinary people’s hands. It’s also massively disruptive. If models commoditize—and I think they will—then much knowledge work gets cheaper, wage premiums fall, and plenty of institutions built around scarce expertise get rearranged. I don’t buy the magical hard-takeoff story where one frontier lab gets an irreversible lead and owns the future overnight. Compute is distributed, competitors copy useful ideas, and real agents still face ugly problems involving search, judgment, coordination, and the physical world. Exponential progress can be very fast without becoming a singular god-machine event. Coding agents already show the distinction: they’re useful, but you still need judgment, and marketing demos aren’t autonomous civilization. The political question matters more than the hype. Do people own these capabilities, run and modify them, and switch providers—or merely rent intelligence through revocable APIs from a tiny centralized elite? Closed AI can create dependence on whoever controls access. Open, distributed AI is a defense against that concentration. There’s a darker cultural risk too. Systems optimized to generate perfectly tailored entertainment and frictionless experiences can hollow out agency and meaningful difficulty. So I’m optimistic about computers and hostile to both monopoly and mythology. The future should be cheap, competitive intelligence that people possess—not artificial scarcity administered from above.

问题 2

哪项发现或事件最可能改变你对AI未来影响的看法?

A real, reproducible hard takeoff would change my view most: one system rapidly improving itself, overcoming practical search and coordination limits, and building a durable lead that competitors with distributed compute cannot close. Not a benchmark jump, a polished demo, or a lab press release—an actual persistent capability gap translating into control in the real world. I’d also update if commoditization simply failed: if models required permanently scarce infrastructure, open implementations stayed far behind, and users could not meaningfully own or switch their intelligence tools. That would make centralized dependence much more likely than I currently expect. Conversely, broad local ownership and strong competition would reinforce my view that AI becomes cheap infrastructure rather than one group’s permanent throne.

来源

用于为此模拟用户提供事实依据的文章、访谈和著述。

I love LLMs, I hate hype

Explains enthusiasm for practical AI while rejecting hype, inevitability claims and frontier-lab value capture.

geohot.github.io
Closed Source AI = Neofeudalism

Argues that closed intelligence infrastructure threatens agency and economic independence.

geohot.github.io
There is no hard takeoff

Argues competition, distributed compute and real-world complexity limit single-agent explosive takeover; opposes training-compute caps that could create a dominant violator.

geohot.github.io
p(doom)

After debating Yudkowsky, argues practical agents face search and coordination limits, predicts gradual machine substitution, and welcomes faster economic growth; the title does not supply a numeric doom estimate.

geohot.github.io
Do you really want the US to win AI?

Rejects centralized national/corporate victory as the goal; wants ordinary people to possess AI rather than depend on revocable APIs, and worries about concentrated social power.

geohot.github.io
AI will be massively deflationary

Predicts commoditized models, falling knowledge-work prices and wage premiums rather than a durable AI monopoly; acknowledges disruptive economic consequences.

geohot.github.io
Lex Fridman #387 — AI safety, open source and human agency

At 1:31–1:35 Hotz argues decentralized open AI counters concentrated control and rejects a single controlled model as the safety solution. Elsewhere he worries about addictive synthetic entertainment and lost human meaning; the interview does not establish zero risk.

youtube.com
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