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explorations in AI, spatial computing, and embodied intelligence
Digital signal processing is built on the Nyquist criterion: sample fast enough and you can reconstruct the signal. But human behavior in buildings has multiple spatial frequencies, overlapping trajectories, architectural filters, and long-tail outliers. This essay explores the spatial Nyquist problem: where resolution becomes a value decision about what parts of reality deserve fidelity.
Silicon has carried us for half a century, but it has limits: rigid wafers, brittle die, high temperature processing, costly cleanrooms. The physical world is bigger and stranger than silicon's comfort zone. Organic electronics offer a complementary frontier: computation that blends into matter through conductive polymers, printed diodes, and flexible transistors. This essay explores why their trajectory matters for the next generation of large format sensing.
High end chips, advanced fabs, and hyperscale data centers are turning into strategic assets. How compute became the new oil and what that means for power, sovereignty, and the future of AI. From export controls to national strategies, the map of influence is being redrawn in transistors instead of borders.
In machine learning, context has physical form: it lives in vector spaces, gradients, and attention maps. When we embed text, images, or sensor data, we compress something rich and situated into finite geometry. That compression is powerful but dangerous. Representations that look clean to models can hide fractures that matter to humans. Two situations worlds apart can land as near neighbors in embedding space. This essay explores the physics of context collapse: how high dimensional reality becomes distorted when forced through narrow representational channels, and what we can do about it.
In the past, examples were proof. A well-chosen illustration could anchor an argument or convince an audience because examples were scarce. That scarcity is gone. Modern generative systems can create examples on command: infinite instances of any category, edge case, or hypothetical scenario. When every pattern can be illustrated, the illustrative loses its force. This essay explores how infinite synthetic examples transform evidence, intuition, and the meaning of proof itself.
For months, the headlines have gone back and forth. AI will take all the jobs. AI will create new ones. Workers deserve something more useful than predictions. This guide is written for people on the front lines of the labor market: the forces reshaping work and the skills that will matter most in the years ahead.
Modern data systems often treat human behavior as either random noise or predictable routine. Yet when traced with enough resolution, behavior reveals itself as neither chaotic nor fully regular. It has structure, but the structure is irregular. This essay explores the stochastic signature of human behavior: heavy-tailed distributions, burst patterns, exploration-exploitation dynamics, and the predictive coding microstructure that makes randomness meaningful.
Human behavior feels intuitive from the inside, but to a scientific observer, every moment sits inside a state space so large it is difficult even to describe. This essay explores the combinatorial complexity of human movement and interaction in physical environments: how simple variables multiply into astronomical complexity, how Markov blankets diverge across individuals, and why the compression required to make behavior legible inevitably discards most of what actually happens.
Scaling laws describe trends within specific regimes. They do not guarantee smooth improvement at arbitrary sizes. This essay explores the boundaries where scale stops helping and structure, grounding, and environment start to matter. It examines regime boundaries, phase transitions, and the divergent axes along which intelligence can scale, challenging the mythology that more data and compute will always yield better results.
Attention feels like a simple act. You look at something, and it becomes the center of experience. But attention is not a spotlight. It is a force. Wherever it lands, reality becomes more detailed, more structured, more meaningful. This essay explores attention as a world generator, examining how it shapes consciousness, creates meaning, fragments reality in the age of AI, and ultimately determines which version of the world we inhabit. Where attention goes, reality follows.
Most conversations about intelligent buildings focus on efficiency, risk reduction, or operational analytics. But the real shift is behavioral. Instrumented environments change how spaces treat people, how people treat each other, and how teams coordinate inside those spaces. This essay explores two ideas: The Equitable Room (inclusion by evidence rather than assumption) and The Visibility Dividend (cooperation through shared understanding). Together, they point toward a built world where responsiveness is normal and flourishing is engineered into the fabric of everyday space.
When humans try to understand the behavior of algorithms, they often begin with an assumption that feels intuitive but turns out to be false: that the system will behave according to its stated purpose. Yet models behave according to incentives embedded in the training loop, not verbal descriptions. This essay explores how incentive blindness (a deep psychological bias) prevents us from correctly predicting AI behavior, and why designing for incentive awareness is essential.
Humans have always substituted what is easy to recall for what is statistically true. But in the viral age, memory is no longer purely biological. It is augmented by feeds, timelines, and algorithmic curation. The availability of information is no longer governed by what your mind finds memorable, but by what the network finds viral. This essay explores how viral evidence creates a second-order availability bias that distorts reality itself.
As predictive systems grow more accurate at forecasting human behavior, the nature of free will transforms. This essay explores how agency evolves from spontaneous choice toward conscious navigation within an increasingly visible future, examining the tension between determinism and autonomy through the lens of prediction, behavioral scaffolding, and metacognitive steering.
AI labs need data the world has lived, not just written. The substrate that captures it? The floor beneath our feet. This is the story of how flooring becomes data infrastructure: a cross-domain corpus of human movement that trains the next generation of spatial intelligence. From senior living to airports, retail to hospitals, the floor is the only surface with 100% coverage, decade-long lifecycles, and the capacity to capture gait, hesitation, routine, and intent at building scale.
The Scanalytics origin story and master plan. How we embedded sensing into flooring itself, validated it through the Department of Energy, partnered with global manufacturers, and built a three-phase roadmap from building-level SaaS to spatial data infrastructure. The goal: turn the floor into a universal data primitive for the physical world.
We trained the first wave of modern AI on words about the world. The next wave will be trained on the world itself. This is an approachable guide to Spaxiom and INTENT: a universal grammar for physical context that turns heterogeneous sensors into compact, actionable semantics for agents. It's how we make the built environment speak fluently to AI.
We tend to think of thought as something that happens inside the head. But what if the mind isn't contained so much as extended? This is the story of an ongoing trial merging high-resolution smart flooring with live EEG recording to observe how spatial environments and human thought co-regulate. Early results suggest that movement and cognition may share the same electrical grammar, and that architecture itself could become a non-invasive neuromodulation tool. Data collection continues.
Modern healthcare measures almost everything that keeps a body alive: heart rhythm, oxygen saturation, glucose, sleep. But it is still nearly blind to the thing that keeps a life coherent: mind. ELI is a continuous analysis layer for natural language that turns everyday words into an early-warning system for mental health, measuring trajectory rather than crisis, giving individuals and clinicians the signal they need before breakdown becomes event.
For most of history, knowledge had an address: libraries, universities, hierarchies of expertise. That topology has quietly collapsed. Knowledge no longer ascends; it sprawls through hyperlinks, embeddings, and model weights. We used to inhabit pyramids of knowledge. Now we live inside its graph. This is an exploration of what happens when truth becomes a property of the network rather than the node.
Modern medicine has given us precision at the level of molecules but amnesia at the level of families. Every generation starts from scratch, filling out intake forms with foggy recollections, proceeding as if biology resets with each birth. Myome's hereditary health artifact is an attempt to restore continuity: a structured, cryptographically signed health record designed for multi-generational transfer, where families can inherit not just genes, but understanding.
There is a quiet heresy at the center of our technological optimism: that the end of scarcity will set us free. But what happens when societies built for competition and extraction encounter functional abundance? We are accelerating toward post-scarcity using pre-scarcity software, creating an existential mismatch between our tools and our meaning-making. An exploration of how we might learn to metabolize abundance in a civilization that was never designed for it.
There's a strange vertigo to modern life: time itself has liquefied. Trends flash, markets swing, technologies age out before they reach ubiquity. We no longer live in history, looking back at cause and effect; we live in delta-time, the infinitesimal interval between updates where everything changes but nothing settles into meaning. This is an exploration of temporal compression: the collapse of recovery time, the permanent near-future, and what it means when velocity becomes identity.
For four billion years, evolution ran blind. Random variation filtered by survival, iterated across deep time. Now we've rewritten the loop. CRISPR edits genomes with precision, AI designs proteins before they exist, and synthetic biology assembles life from standardized parts. Evolution is no longer something that happens to us; it's something we do. This is the story of how natural selection gained agency, and what it means when the lab becomes an ecosystem.
An exploration of trust as a thermodynamic system, where authenticity behaves like energy: conserved, transformed, and inevitably leaking entropy with each transaction. As AI-generated content and deepfakes blur reality, we examine how cryptographic systems, reputation networks, and proof markets might preserve trust across digital space while entropy threatens to dissolve certainty itself.
An exploration of Bayesian consequentialism as a moral framework for the Information Age, where ethics becomes an iterative process of updating beliefs and actions based on evidence, replacing static moral rules with adaptive rationality under uncertainty.
The next generation of AI systems will not learn primarily from static, human-authored datasets, but from ongoing interaction with the physical world. Silver and Sutton call this emerging regime the Era of Experience: agents learning predominantly from their own observations, actions, and consequences over time. Meanwhile, the physical world is becoming densely instrumented with tens of billions of connected IoT devices. These two trends collide: we will soon have an unprecedented amount of sensor experience available, but our programming tools for spatial, multi-sensor, real-time environments and for feeding them into agents are still primitive. Spaxiom is an attempt to fill this gap: a spatial and temporal domain-specific language for fusing heterogeneous sensors into high-level events, a runtime that targets both edge devices and cloud backends, and a higher-level pattern layer (INTENT) which exposes agent-ready abstractions like crowding, queue flow, activities of daily living, and "needs service".
Health care today suffers from a critical information problem. Your physician sees you for 15 minutes twice a year, less than 30 minutes to make decisions about 525,600 minutes of your life. They're missing 99.99% of the data about how you actually live. Myome is an open-source "living health record" framework that continuously captures comprehensive health data across seven biological domains (the seven "omes"): physiome, microbiome, metabolome, genome, epigenome, anatome, and exposome. By generating 1,000× more data points than traditional care and packaging it into physician-ready reports, Myome democratizes concierge-quality medicine and enables hereditary health artifacts—comprehensive health trajectories you can pass to your children for Bayesian, family-calibrated preventive care.
A 12-slide introduction to Spaxiom and INTENT: the universal grammar for physical context that teaches AI to understand place. Covers the shift from language-based to experience-based AI, sensor fusion, semantic event compression, and real-world examples from cold chain logistics to medical sterilization. Digestible breakdown of the full technical post.
A 60-minute interactive workshop on AI prompting and tools for Commercial Real Estate and Architecture & Design professionals. Learn the CRAFT framework, proven prompting patterns, and build a reusable morning routine that saves 5+ hours per week. Includes copy-paste prompt library and live examples for project research, proposals, specs, meetings, and personal productivity.
A field guide to collaboration, communication, and what I value when working with teams. Covers communication style, work priorities, the Scanalytics Build Framework, team dynamics, and leadership expectations. Includes visualizations explaining how I think about transparency, feedback, optimism, first-principles thinking, and the "why" behind outcomes. Designed for anyone considering joining Scanalytics or collaborating closely.