質問1
Yann LeCun
x.com/ylecunAI researcher and AMI Labs founder who is optimistic about intelligent machines and argues they need world models, not just bigger language models.
AIは世界をどのように変えるでしょうか?
横軸:彼が表明したDoom–Bloomの見通し。 縦軸:変革の規模。
Doom–Bloom:100点中89。変革の規模:100点中73。解釈範囲:横方向は75から100、縦方向は50から78。これらは解釈上の座標であり、事象の確率ではありません。
≈0%
“p(doom) is smaller than the probability of an extinction-level asteroid hitting the earth”
Undefined “p(doom)”; he benchmarks it against an extinction-level asteroid impact and says it is far less likely than a nuclear holocaust
I didn't say p(doom) was zero · 2026年4月
中心的な前提
An intelligent system must solve new problems it was not explicitly trained on, anticipate the consequences of actions, and plan in unfamiliar situations.回答1
この前提が実際には異なると判明した場合、彼の見通しはどう変わりますか?
考えを変え得るもの
The biggest change would be evidence that the world-model program is fundamentally insufficient—that systems cannot learn useful abstractions, plan reliably, and generalize to unfamiliar situations without impractical amounts of supervision or data.回答5
どのような証拠なら十分で、それによって彼の見解はどちらの方向に変わりますか?
詳細
変革をもたらし、広く価値のある恩恵が予想されています。
97 / 100
質的尺度での解釈範囲は100から100です。
対処可能、または局所的な害が予想されています。
31 / 100
質的尺度での解釈範囲は33から33です。
人間の選択によって、AIの軌道を大幅に変えることができます。
75 / 100
質的尺度での解釈範囲は50から100です。
AIは、限定的なツールにとどまると予想されています。
AIは、ほとんどの認知作業において人間と同等になると予想されています。
シミュレーション上の位置:AIは、認知作業全般において人間を大幅に上回ると予想されています。
これらの解釈では、彼が示した条件が維持されています。恩恵と害は、どちらも大きくなり得ます。この範囲は、統計的な信頼区間ではなく、彼のシミュレーションされた回答をどのように読み取ったかを示すものです。
似ている世界観
シミュレーションされた世界観がYann LeCunの世界観に最も近いオピニオンリーダー
Yann LeCunがAIについて語ったこと
LeCun argues that AI can be designed to stay safe and useful, and that systems trained only on text won’t reach human-level intelligence.
“Ultimately, the goal is to amplify human intelligence and bring those benefits to humanity, which I think is intrinsically good.”
Nebius Science interview “We’re never going to get to human-level AI by just training on text. It’s just not going to happen.”
Mixture of Experts interview “It makes little sense to attribute a probability to an event on which we have agency.”
Post on X “The nice thing about an AI system is that you can design it in such a way that it cannot escape its guardrails.”
Newsweek interview “The desire to dominate is not correlated with intelligence at all.”
TIME interview
リンク先の出典から原文どおりに引用(2026年10月2日に確認)
シミュレーション評価
出典
このシミュレーション対象者の根拠として使用された記事、インタビュー、著作です。
Distinguishes useful LLM symbol manipulation from learning the physical world and planning in unfamiliar situations. Advocates predictive representations and world models; discusses difficult, unfinished research rather than a solved replacement.

Expects applications in physical systems and control, with much longer timelines for versatile household robots. Scientific applications have great potential. Supports open foundational research, and expects human judgment and education to remain important. The interviewer is affiliated with a compute supplier to his lab.

Older grounding for his rejection of intelligence automatically implying a desire for dominance, preference for controllable objectives and open AI, and optimism about widely available intelligent assistance. Treat these as conceptual positions, not fresh 2026 capability measurements.

Coauthored research reports a compact world model learning from pixels and planning across selected control tasks. The abstract supports a concrete alternative to language-only learning and a focus on useful physical representations. It does not demonstrate general human-level intelligence; the source was reviewed at abstract level.

Coauthored theoretical work links representation learning to recovery of latent world structure and planning under specified distributional assumptions. Adds technical content to the world-model program while making clear that a conditional mathematical result is not a universal guarantee. Summary is limited to the authors’ abstract.

In Axios’s interview, LeCun criticizes hype-driven career advice, defends the value of education and predicts that capable tools expand people’s ability to direct work. Adds his confident social optimism to the architectural critique; these are his forecasts rather than settled labor-market findings.

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