In this episode, Nate is joined by biologist and biophysicist Olivier Hamant to explore why living systems prioritize robustness over performance, and what that means for a civilization built almost entirely in the opposite direction.
The Optimization Trap: Why Too Much Efficiency Makes Us Fragile with Olivier Hamant
The Jevons Paradox of AI - Wesley's notes
Why AI can make us more productive but will never save us time
Wisdom in a World in Crisis: The Counterintuitive Need to Slow Down and Find Spaciousness - The Great Simplification
In this episode, Nate is rejoined by philosopher and neuroscientist Iain McGilchrist for discussion on how our left-brain dominance obscures our sense of value, especially for abstract qualities such as truth, goodness, and beauty.
AI's Affordability Crisis
A year ago in The Back Of The AI Envelope I pointed out that the AI platforms were running the drug-dealer's algorithm, "the first one's fr...
Pace Layering: How Complex Systems Learn and Keep Learning · Journal of Design and Science
Pace layers provide many-leveled corrective, stabilizing feedback throughout the system. It is in the contradictions between these layers that civilization finds its surest health. I propose six significant levels of pace and size in a robust and adaptable civilization.
A Drive to Survive
Since 2005, Karl Friston's proposal that the principle of free energy minimization underpins the purposive behavior of living agents has evolved through thou...
Co-Creation: Systems Thinking Beyond the Machine
Complexity thinking is all the rage — in the arts and sciences. Yet, there are two different strands of thinking about complexity, which are often confounded. The first comes from cybernetics, focussing on control in complex situations. The second is ecological, aiming at sustainable participation in a reality beyond control. Their difference rests on a fundamental distinction: is complexity rooted in feedback regulation or collective co-creation? While feedback remains mechanistic, co-creation generates new spaces of possibilities. We need it to understand life and its evolution. And it empowers us to rewrite our future, to escape our mechanistic cage without abandoning scientific rigor. In this paper, we illustrate how we implement these powerful yet abstract principles through our artistic and philosophical practice.
Solipsistic Superintelligence is Unlikely to be Cooperative
AI's central challenge is shifting from capability to coexistence. The dominant paradigm in AI research focuses on developing powerful agents that treat the world as an exogenous and stationary source of feedback. We contend that superintelligence, an extremely capable task solver, born out of such a solipsistic approach to AI design, is unlikely to be cooperative. Deploying AI systems induces endogenous non-stationarity, resulting in a train-test-deploy gap where historical distributions diverge from the deployment context. We refer to this as the self-undermining property of unilateral optimization. Closing this gap requires AI that participates in cooperation: the equilibrium-selection process through which multiple actors navigate their interdependence. We call for a non-solipsistic research paradigm that treats this interdependence as a core design principle rather than approaching cooperation as a task to solve. This entails building dynamic evaluation testbeds involving adaptive counterparties, treating institutions as design primitives, and preserving human agency as a structural feature of the systems we build.
Wisdom in a World in Crisis: The Counterintuitive Need to Slow Down and Find Spaciousness with Iain McGilchrist
</> htmx ~ Working With AI: A Concrete Example
In this essay, Carson Gross walks through a concrete bug fix in hyperscript to show where AI helped, where it fell short, and why keeping a knowledgeable human in the loop is what kept complexity in check.
Cognition all the way down 2.0: neuroscience beyond neurons in the diverse intelligence era
This paper formalizes biological intelligence as search efficiency in multi-scale problem spaces, aiming to resolve epistemic deadlocks in the basal “cognition wars” unfolding in the Diverse Intelligence research program. It extends classical work on symbolic problem-solving to define a novel problem space lexicon and search efficiency metric. Construed as an operationalization of intelligence, this metric is the decimal logarithm of the ratio between the cost of a random walk and that of a biological agent. Thus, the search efficiency measures how many orders of magnitude of dissipative work an agentic policy saves relative to a maximal-entropy search strategy. Empirical models for amoeboid chemotaxis and barium-induced planarian head regeneration show that, under conservative (i.e., intelligence-underestimating) assumptions, even ‘simple’ organisms are from two-hundred- to sextillion-fold more efficient in problem space exploration. In this sense, the deep insights of neuroscience are not about neurons per se, but about the policies and patterns of physics and mathematics that function as a kind of “cognitive glue” binding parts toward higher levels of collective intelligence in wholes of highly diverse composition and origin. Therefore, our synthesis argues that the “mark of the cognitive” is perhaps better sought in the measurable efficiency with which living systems, from single cells to complex organisms, traverse energy and information gradients to tame combinatorial explosions-one problem space at a time.
The Multiple Paths to Multiple Life
We argue for multiple forms of life realized through multiple different historical pathways. From this perspective, there have been multiple origins of life on Earth—life is not a universal homology. By broadening the class of originations, we significantly expand the data set for searching for life. Through a computational analogy, the origin of life describes both the origin of hardware (physical substrate) and software (evolved function). Like all information-processing systems, adaptive systems possess a nested hierarchy of levels, a level of function optimization (e.g., fitness maximization), a level of constraints (e.g., energy requirements), and a level of materials (e.g., DNA or RNA genome and cells). The functions essential to life are realized by different substrates with different efficiencies. The functional level allows us to identify multiple origins of life by searching for key principles of optimization in different material form, including the prebiotic origin of proto-cells, the emergence of culture, economic, and legal institutions, and the reproduction of software agents.
Ecocivilization: making a world that works for all
""One of the greatest thinkers of our age" (The Guardian) presents a new way of living-one modeled on nature's design instead of capitalism's-for fans of Guns, Germs, and Steel and Doughnut Economics It has often been said that it is easier to imagine the end of the world than it is to imagine the end of capitalism-and yet that is what the historical moment urgently calls for. Climate change has reached an emergency state, inequality continues to grow, and, for many, the future has never seemed more bleak. Incremental policy improvements are no longer enough-we need a deep transformation of our current civilization to continue to survive. In Ecocivilization, leading thinker Jeremy Lent reimagines the basis of our civilization, and argues for a new global system of living, one based on life-affirming principles modeled after nature's own design. What enfolds is a robust framework incorporating Lent's own expertise, and the lived experiences of those on the ground already putting ecological civilization's core tenants into practice-justice, mutuality, diversity, and symbiosis. From the global economy to universal housing and income, from infrastructure to agriculture, every major aspect of our society could be redesigned to work together as a coherent whole, setting the conditions for all people to flourish. Ecocivilization shows how this future on a regenerated Earth is not only desirable, but entirely feasible"--
The Creature in the Machine | Frankly 120
The AI Buildout and the Material Trap
Why Strategic Necessity, Physical Bottlenecks, and Unsettled Economics Are Forcing Capital into a Constrained System
