Dawson Preethi | වචන ටැක්සි

  1) What “crest level design” must satisfy at FEED Crest elevation is not “one formula”. It is the highest of several controlling requirements : Hydraulic performance limit mean overtopping discharge q  (and/or individual overtopping volumes) for the asset function limit run-up exceedance and freeboard under design sea state Structural/geotechnical robustness allowance for settlement / consolidation / rock rearrangement allowance for construction tolerance (as-built variability) allowance for sea-level rise (project life) Operational / functional crest used as access road? utilities corridor? emergency access? allowable “green water” / spray conditions for people/vehicles/equipment Guidance commonly used for this methodology is EurOtop (overtopping/run-up) and the Rock Manual / rubble mound design practice . 2) FEED inputs you must define (minimum set) A. Design water levels (vertical components) You need a Design Still Wa...

  A Linear Algebraic Reframing of Mental Imagery Traditionally, the debate about mental imagery splits into familiar camps: Imagery as inner pictures. Imagery as generative simulation (à la rendering software). Imagery as propositional encoding (structured symbolic relations). Aphantasia complicates all three. A person with aphantasia may report no internal visual phenomenology — no inner cinema — yet can answer spatial questions flawlessly: “In your bedroom, where is the window relative to the door?” “To my left.” No image. Still structure. This suggests something crucial: The core competence may not be pictorial at all. In this essay, I propose a mathematically structured reframing: Mental imagery may be better understood as relational geometry in high-dimensional state space rather than internal pictures. 1. The Vector Space Hypothesis Let us begin minimally. Assume a cognitive state can be modeled abstractly as: x ∈ R n \mathbf{x} \in \mathbb{R}^n...

  On Empty Walls, Empty Pedestals, and the Enjoyment of Lack In May 2021, the Italian conceptual artist Salvatore Garau sold an “immaterial” sculpture titled Io Sono (“I Am”) through Art-Rite in Milan. It fetched €15,000 (about $18,000 USD). There was no object. No material. No form. The buyer received a certificate of authenticity and instructions to display the work in a 1.5 × 1.5 meter empty space in a private home. Garau described it as composed of “air and spirit,” invoking even quantum language—reminding us that what we call “empty” space is not truly empty. Predictably, social media responded with ridicule: “$18,000 for nothing?” “Art has lost its mind.” But what if this is not absurdity—what if it is structure? When the Mona Lisa Disappeared—and the Crowd Grew In 1911, the Mona Lisa was stolen from the Louvre. For two years, the painting was missing. Yet something remarkable happened: people flocked to the museum—not to see the painting, but to see the empty sp...

In control theory, there is a beautiful idea: if you want to stabilize a system, let it descend along the gradient of a potential function. For a simple system like a single integrator 𝑥 ˙ = 𝑢 , we can choose a potential 𝑉 ( 𝑥 ) V ( x ) and define the control law 𝑢 = − ∇ 𝑉 ( 𝑥 ) . The system then flows “downhill” toward a minimum of 𝑉 . Under standard assumptions (compact level sets, unique minimizer), convergence can be proven using Lyapunov arguments or LaSalle’s invariance principle . It is elegant. It is deterministic. It works. But then something remarkable happens. When we move to nonlinear driftless systems — systems whose dynamics are constrained by geometry — this strategy can fail completely. Even if the system is globally controllable, it may be impossible to smoothly stabilize it with time-invariant feedback. This impossibility is formalized in the work of Roger Brockett , who showed that certain nonholonomic systems cannot be smoothly stabilized to a point. The ...

  AI Did Not “Do Physics.” It Located a Structural Gap. The OpenAI preprint on single-minus gluon amplitudes is being framed as “AI discovering new physics.” That framing misses what actually happened. The interesting part is not that GPT-5.2 proposed a formula. The interesting part is that a symbolic system detected a structural regularity inside a recursion landscape that humans had already built — and that conjecture survived formal proof and consistency checks. The amplitude was long assumed to vanish. It turns out it does not — in a constrained half-collinear regime. And in that region, it collapses to a remarkably simple piecewise-constant structure. The paper explicitly notes that the key formula was first conjectured by GPT-5.2 and later proven and verified 2602.12176v1 OpenAI preprint on. But here is the Left-AI reading Notes: 1️⃣ Spinor Helicity Formalism A computational framework used to describe massless particles (like gluons and gravitons) in terms of spinors inste...