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AI Prospects: Understanding Options in a Hypercapable World

AI will transform our world in deep and unexpected ways. We must understand our options to rethink our goals.

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Framework for a Hypercapable World

Steerable superintelligence will enable vast implementation capacity. Our option space is unprecedented. We should backward-chain from positive outcomes. I’ve proposed a framework.

When Ideas Round to False

When concepts shed complexity and gain memetic fitness, they often cross from true to false; the false version spreads faster and replaces the original. Epistemic damage follows

The Resource Frame: What AI Doesn't Inherit From Evolution

The ‘creature frame’ naïvely imports biological intuitions; the ‘resource frame’ reflects how AI actually develops. The differences are consequential.

The Strategic Calculus of AI R&D Automation

When AI automates AI development, the question shifts from ‘What can we build?’ to ‘What should we build first?’ As difficulty declines, differential value dominates.

The Reality of Recursive Improvement: How AI Automates Its Own Progress

We’re in the early stages of systemic recursive improvement through AI-driven acceleration of AI R&D. Here’s how it works.

AI Options, not ‘Optimism’

‘Optimism’ is about odds of success, but odds are for spectators. Participants weigh options, not odds.

MSEP: A Platform for Molecular Systems Engineering

MSEP is a free, open-source platform for designing and simulating atomically precise nanomechanical systems — a tool for exploring the foundations of future physical technologies.

Orchestrating Intelligence: How Comprehensive Specialization Transforms AI

In the emerging AI ecosystem, even being a generalist becomes a specialized role.

Coercive Cooperation: Forcing Win-Win Outcomes in an AI-driven Transition

Strategic pressure can be leveraged, not to force concessions, but to overcome barriers to mutually benefit.

Don’t Bet the Future on Winning an AI Arms Race

Radical uncertainties in AI development and military applications favor security through cooperative stability. (Includes bonus footnotes on recent disruptive research results)

LLMs and Beyond: All Roads Lead to Latent Space

Essential concepts for understanding AI today and prospects for tomorrow. (Bonus footnotes: the maths of exponential orthogonality & updated citations 30 May 2025)

Large Knowledge Models

Navigating the AI transition with AI assistance: Deeply integrated knowledge as a target for differential acceleration

The Bypass Principle: How AI flows around obstacles

AI will drive change, but even obvious obstacles may prove illusory. Expect advances to flow through new channels.

AI Safety Without Trusting AI

To ensure AI safety, we’ll need advanced AI capabilities. But how can we trust entities smarter than us? (Spoiler: We don’t have to.)

AI-Driven Strategic Transformation: Preparing to Pivot

Prospects for deep AI-driven transformation of military and economic affairs call for rethinking national strategies. We must prepare to pivot when emerging realities force change.

Incoherent AI scenarios are a threat

Coherent strategies for a hypercapable world call for coherent scenarios. Incoherence could be lethal.

Paretotopian Goal Alignment

Prospects for greatly expanded resources can reduce incentives for greed and conflict, even when dividing those resources is a zero-sum game.

Security without Dystopia: Structured Transparency

Emerging technologies and innovative governance can reshape the landscape of security, privacy, and international cooperation.

Breaking Software Bottlenecks

What if flawless software could be developed easily, quickly, and at scale?

Toward deep automation

AI and robotics will revolutionize production capacity and reduce costs, but machines making more machines doesn’t mean hordes of robots building more robots.