Books

A strategic and geopolitical framing of advanced AI systems, institutional adaptation, and civilizational consequences.

A scenario-driven exploration of where AI could plausibly reshape sectors, culture, and geopolitics over the next two decades.

A critical look at hype, power, and the political economy surrounding AI claims.

Useful for separating real capability from overclaim, especially in discussions where AGI talk gets mixed with weak commercial AI.

A narrative history of how machine learning creates real alignment and specification problems across labs, products, and society.

Long-form interviews with major AI researchers and founders about AGI, automation, and strategic outlooks.

The standard AI survey textbook, useful for grounding AGI discourse in the broader field rather than just the current wave.

A political, material, and labor-focused critique of AI systems and the structures that sustain them.

A governance and industrial-structure lens on the companies shaping advanced AI.

A pragmatic book on working with frontier models, useful when you want grounded examples instead of abstract AGI talk.

A builder-operator view on frontier AI, biological engineering, containment, and state capacity in the age of accelerating capability.

The canonical deep learning textbook for the technical foundations behind the current AGI race.

A deeply reported account of the power structures, labor, and geopolitics behind the modern frontier AI buildout.

A more recent strategic treatment of AI, autonomy, and what machine intelligence changes for states and individuals.

The best narrative history of the recent AI boom, key researchers, and the lab rivalries that define the current frontier.

Russell argues that advanced AI should be built around uncertainty over human preferences rather than brittle objective functions.

A scenario-rich tour of AGI futures, governance problems, takeoff dynamics, and civilization-scale consequences.

Useful context for how AI changes firms, coordination, and digital strategy, even if it is not AGI-specific.

A synthetic overview of machine learning traditions and the idea of a unifying learning framework.

A critique of techno-utopian ideology touching AI, longtermism, and the narratives that often accompany AGI discourse.

A careful critique of claims that statistical pattern matching alone straightforwardly leads to general intelligence.

A pre-deep-learning warning about uncontrollable machine intelligence and the strategic failure modes of AGI competition.

A broad anthology of essays from researchers, philosophers, and builders on what advanced AI could become.

An economics lens on where AI changes systems architecture, workflows, and incentives.

Not AI-only, but one of the strongest frameworks for thinking about existential risk in the AGI era.

A heavyweight technical reference that still matters if you want to trace modern AI back to earlier probabilistic traditions.

A skeptical but serious book on the limits of present-day deep learning and what more robust intelligence would require.

Foundational for understanding RL, planning, and many of the ingredients behind agentic AI.

A lucid public-facing history of AI ideas and why human-level intelligence is both difficult and plausible.

A mainstream but useful argument for taking advanced AI alignment and social steering seriously before capabilities compound.

Earlier than the current wave, but still useful for labor, productivity, and economic framing around automation.

Kurzweil's foundational popular case for accelerating returns, whole-brain emulation, and eventual human-machine merger.

Kurzweil updates his singularity thesis with recent progress in machine learning, biotech, and compute.

The canonical modern book on existential risk, machine superintelligence, and strategic questions around an intelligence explosion.

A fast-moving narrative of OpenAI, DeepMind, and the corporate race now structuring public AGI debate.

A sharper fit for accountability, bias, and deployment questions than AGI directly, but still central to serious AI literacy.

A builder memoir that ties computer vision, academic AI, and human-centered framing together.