{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "(life)=\n", "# Life ⚓️ \n", "\n", "\n", "\n", "
\n", " + Expand\n", " \n", "
\n", " \n", "
\n", " \n", "
\n", " \n", "
    \n", "
  • What makes for a suitable problem for AI (Demis Hassabis, Nobel Lecture)?\n", "
      \n", "
    • Space: Massive combinatorial search space
    • \n", "
    • Function: Clear objective function (metric) to optimize against
    • \n", "
    • Time: Either lots of data and/or an accurate and efficient simulator
    • \n", "
    \n", "
  • \n", "
  • Guess what else fits the bill (Yours truly, amateur philosopher)?\n", "
      \n", "
    • Space\n", "
        \n", "
      1. Intestines/villi
      2. \n", "
      3. Lungs/bronchioles
      4. \n", "
      5. Capillary trees
      6. \n", "
      7. Network of lymphatics
      8. \n", "
      9. Dendrites in neurons
      10. \n", "
      11. Tree branches
      12. \n", "
      \n", "
    • \n", "
    • Function\n", "
        \n", "
      1. Energy
      2. \n", "
      3. Aerobic respiration
      4. \n", "
      5. Delivery to \"last mile\" (minimize distance)
      6. \n", "
      7. Response time (minimize)
      8. \n", "
      9. Information
      10. \n", "
      11. Exposure to sunlight for photosynthesis
      12. \n", "
      \n", "
    • \n", "
    • Time\n", "
        \n", "
      1. Nourishment
      2. \n", "
      3. Gaseous exchange
      4. \n", "
      5. Oxygen & Nutrients (Carbon dioxide & \"Waste\")
      6. \n", "
      7. Surveillance for antigens
      8. \n", "
      9. Coherence of functions
      10. \n", "
      11. Water and nutrients from soil
      12. \n", "
      \n", "
    • \n", "
    \n", "
  • \n", "
\n", "
\n", "
\n", "
\n", "
\n", "

-- Nobel Prize in Chemistry, 2024

\n", "\n", "
\n", "
\n", "\n", "\n", "\n", "

\n", "

\n", "\n", "Ukubona, at its core, is a philosophy disguised as a company. It is a theology of visibility—of seeing—and not just any seeing, but a layered, intentional gaze upon risk, survival, and epistemology itself. Its architecture is not random. It draws upon the deep, recursive intelligence of layered metaphor, where each layer bears not only technical function but mythic resonance. At the first tier lies the sea—the servers and ecosystem—our oceanic substrate of information, entropy, and potential energy. Ukubona drinks from this ocean but does not drown in it. Like any worthy mariner, it knows the difference between vastness and guidance.\n", "\n", "The sea of servers is not neutral. Every ping and packet is embedded with decisions, histories, and exclusions. Ecosystem here means not just digital infrastructure, but ecological insight—datasets with bodies behind them, with diagnoses and deaths and donations and deserts. Ukubona’s servers hum with the residues of thousands of lives, particularly those at risk: renal patients, potential donors, those forced into medical trade-offs with neither transparency nor peace. This is the sea that must be navigated: vast, real, and fundamentally unstable.\n", "\n", " \n", "```{raw} html\n", "\n", "\n", "
\n", " \n", "

CG-BEST: Karl Marx remains surprisingly relevant 200 years after his birth. He rightly predicted some of the pitfalls of capitalism, but his solution was far worse than the disease. Source: The Economist

\n", "
\n", "\n", "```\n", "\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The platform—the ship—is built with intention. It floats above the sea but depends on it. Ukubona’s platform is coded, yes, but it is also curated. JavaScript, HTML, Cox regression—these are the rigging, the sails, the deck. The platform does not pretend to be the sea; it is a tool for surviving it. It takes the chaos of raw clinical data and renders it into comparative curves, into paths that can be chosen with knowledge. This ship does not claim omniscience, but it offers orientation.\n", "\n", "Every ship has a doctrine. Ukubona’s is not neutrality. Its code carries a politics of care. It believes in the right of patients to see—really see—the trade-offs they are asked to make. The curves it draws are not decorations but compasses. They point toward futures that can be survived or futures that cannot. Ukubona is not afraid to say that some choices are better than others, that some risks are unjust.\n", "\n", "But every ship, inevitably, faces pirates. Decision-support is not a sterile affair. It is riddled with power: Who gets to decide? Who holds the wrench, and who waves the flag? In Ukubona’s world, the pirate represents the hijacker of intent—those who would use data to obscure rather than illuminate. These are institutions, incentives, protocols that reify asymmetry under the guise of “objective metrics.” Against this, Ukubona wields its screwdriver.\n", "\n", "The screwdriver is not romantic. It is not glamorous. It is the symbol of maintenance, of refusal to mythologize sabotage. Where pirates want to reroute the ship for profit or ideology, the screwdriver insists on the daily labor of repair. Ukubona takes the side of the technician, the analyst, the nurse who knows what it means to recalibrate. This is not about perfection but fidelity: to truth, to safety, to the fragile contract between patient and system.\n", "\n", "Still, even with a screwdriver in hand, one must face the storm. Layer four of Ukubona’s model brings us into the territory of interactivity and personalization—where the stakes grow teeth. Here, the shark lurks. It is the algorithmic bias that devours without acknowledgment, the unspoken assumptions embedded in “default” models. The shark is uncurated machine learning, indifferent to individual context.\n", "\n", "In the face of the shark, Ukubona offers the scissors. Not blunt resistance, but precision—tools to cut away irrelevance, to trim the model to fit the body it purports to serve. Scissors represent the courage to challenge even statistical authority, to say: this model, this cohort, does not capture me. Ukubona lets users engage with their data actively, not passively. They snip, revise, reshape.\n", "\n", "But what of those too weary or too busy to cut? Ukubona offers the life-raft. This is default configuration done with care. The life-raft is not as precise as the scissors, but it is honest and protective. It is a ready-to-use visualization for those who must decide now. It floats. It keeps people from drowning in abstraction. Ukubona respects urgency.\n", "\n", "\n", "\n", "\n", " \n", "```{raw} html\n", "\n", "\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import networkx as nx\n", "\n", "# Define the neural network layers\n", "def define_layers():\n", " return {\n", " 'Tragedy (Pattern Recognition)': ['Cosmology', 'Geology', 'Biology', 'Ecology', \"Symbiotology\", 'Teleology'],\n", " 'History (Resources)': ['Resources'], \n", " 'Epic (Negotiated Identity)': ['Faustian Bargain', 'Islamic Finance'], \n", " 'Drama (Self vs. Non-Self)': ['Darabah', 'Sharakah', 'Takaful'], \n", " \"Comedy (Resolution)\": ['Cacophony', 'Outside', 'Ukhuwah', 'Inside', 'Symphony'] \n", " }\n", "\n", "# Assign colors to nodes\n", "def assign_colors():\n", " color_map = {\n", " 'yellow': ['Resources'], \n", " 'paleturquoise': ['Teleology', 'Islamic Finance', 'Takaful', 'Symphony'], \n", " 'lightgreen': [\"Symbiotology\", 'Sharakah', 'Outside', 'Inside', 'Ukhuwah'], \n", " 'lightsalmon': ['Biology', 'Ecology', 'Faustian Bargain', 'Darabah', 'Cacophony'],\n", " }\n", " return {node: color for color, nodes in color_map.items() for node in nodes}\n", "\n", "# Define edges\n", "def define_edges():\n", " return [\n", " ('Cosmology', 'Resources'),\n", " ('Geology', 'Resources'),\n", " ('Biology', 'Resources'),\n", " ('Ecology', 'Resources'),\n", " (\"Symbiotology\", 'Resources'),\n", " ('Teleology', 'Resources'),\n", " ('Resources', 'Faustian Bargain'),\n", " ('Resources', 'Islamic Finance'),\n", " ('Faustian Bargain', 'Darabah'),\n", " ('Faustian Bargain', 'Sharakah'),\n", " ('Faustian Bargain', 'Takaful'),\n", " ('Islamic Finance', 'Darabah'),\n", " ('Islamic Finance', 'Sharakah'),\n", " ('Islamic Finance', 'Takaful'),\n", " ('Darabah', 'Cacophony'),\n", " ('Darabah', 'Outside'),\n", " ('Darabah', 'Ukhuwah'),\n", " ('Darabah', 'Inside'),\n", " ('Darabah', 'Symphony'),\n", " ('Sharakah', 'Cacophony'),\n", " ('Sharakah', 'Outside'),\n", " ('Sharakah', 'Ukhuwah'),\n", " ('Sharakah', 'Inside'),\n", " ('Sharakah', 'Symphony'),\n", " ('Takaful', 'Cacophony'),\n", " ('Takaful', 'Outside'),\n", " ('Takaful', 'Ukhuwah'),\n", " ('Takaful', 'Inside'),\n", " ('Takaful', 'Symphony')\n", " ]\n", "\n", "# Define black edges (1 → 7 → 9 → 11 → [13-17])\n", "black_edges = [\n", " (4, 7), (7, 9), (9, 11), (11, 13), (11, 14), (11, 15), (11, 16), (11, 17)\n", "]\n", "\n", "# Calculate node positions\n", "def calculate_positions(layer, x_offset):\n", " y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))\n", " return [(x_offset, y) for y in y_positions]\n", "\n", "# Create and visualize the neural network graph with correctly assigned black edges\n", "def visualize_nn():\n", " layers = define_layers()\n", " colors = assign_colors()\n", " edges = define_edges()\n", "\n", " G = nx.DiGraph()\n", " pos = {}\n", " node_colors = []\n", "\n", " # Create mapping from original node names to numbered labels\n", " mapping = {}\n", " counter = 1\n", " for layer in layers.values():\n", " for node in layer:\n", " mapping[node] = f\"{counter}. {node}\"\n", " counter += 1\n", "\n", " # Add nodes with new numbered labels and assign positions\n", " for i, (layer_name, nodes) in enumerate(layers.items()):\n", " positions = calculate_positions(nodes, x_offset=i * 2)\n", " for node, position in zip(nodes, positions):\n", " new_node = mapping[node]\n", " G.add_node(new_node, layer=layer_name)\n", " pos[new_node] = position\n", " node_colors.append(colors.get(node, 'lightgray'))\n", "\n", " # Add edges with updated node labels\n", " edge_colors = {}\n", " for source, target in edges:\n", " if source in mapping and target in mapping:\n", " new_source = mapping[source]\n", " new_target = mapping[target]\n", " G.add_edge(new_source, new_target)\n", " edge_colors[(new_source, new_target)] = 'lightgrey'\n", "\n", " # Define and add black edges manually with correct node names\n", " numbered_nodes = list(mapping.values())\n", " black_edge_list = [\n", " (numbered_nodes[3], numbered_nodes[6]), # 4 -> 7\n", " (numbered_nodes[6], numbered_nodes[8]), # 7 -> 9\n", " (numbered_nodes[8], numbered_nodes[10]), # 9 -> 11\n", " (numbered_nodes[10], numbered_nodes[12]), # 11 -> 13\n", " (numbered_nodes[10], numbered_nodes[13]), # 11 -> 14\n", " (numbered_nodes[10], numbered_nodes[14]), # 11 -> 15\n", " (numbered_nodes[10], numbered_nodes[15]), # 11 -> 16\n", " (numbered_nodes[10], numbered_nodes[16]) # 11 -> 17\n", " ]\n", "\n", " for src, tgt in black_edge_list:\n", " G.add_edge(src, tgt)\n", " edge_colors[(src, tgt)] = 'black'\n", "\n", " # Draw the graph\n", " plt.figure(figsize=(12, 8))\n", " nx.draw(\n", " G, pos, with_labels=True, node_color=node_colors, \n", " edge_color=[edge_colors.get(edge, 'lightgrey') for edge in G.edges],\n", " node_size=3000, font_size=9, connectionstyle=\"arc3,rad=0.2\"\n", " )\n", " \n", " plt.title(\"Self-Similar Micro-Decisions\", fontsize=18)\n", " plt.show()\n", "\n", "# Run the visualization\n", "visualize_nn()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{figure} https://www.ledr.com/colours/white.jpg\n", "---\n", "width: 1\n", "height: 1\n", "---\n", "_Innovation: Veni-Vidi, Veni-Vidi-Vici_. If you're protesting then you're not running fast enough. Thus spake the Red Queens\n", "```\n", "\n", "
\n", "\n", "\n", "Through sharks, scissors, and rafts, Ukubona arrives at the island—its final layer: the visualization of risk and uncertainty. The island is not certainty, but a place where uncertainty can be understood, lived with, even planned for. The island is not utopia. It is realism with contour. It says: you might not survive, but now you know the shape of the sea. Now you choose knowingly.\n", "\n", "Risk, when visualized poorly, induces panic or passivity. Ukubona’s gift is metaphor made interactive: a Kaplan-Meier curve that feels like a compass. It shows divergence—donor vs. non-donor, transplant vs. dialysis—not as abstract stats but as journeys with emotional and temporal weight. These curves are maps of potential futures. They are cartographies of consequence.\n", "\n", "The island is not always welcoming. Sometimes it is harsh: a display of just how short a projected life might be. But even then, it grants dignity. There is a quiet honor in knowing. In a system where so much is obscured, Ukubona believes that clarity—even painful clarity—is a form of respect.\n", "\n", "The name Ukubona, from Zulu, means “to see.” But to see, in this model, is not passive reception. It is epistemic labor. It is political. Ukubona’s architecture demands that we revisit what it means to see risk. Not as mere numbers, but as lived forecasts. Not as punishment, but as possibility.\n", "\n", "The servers that feed Ukubona’s curves are not disembodied. They rely on public trust, clinical honesty, and federal access. These are resources, yes, but they are also responsibilities. Ukubona does not leech from datasets; it gives back meaning. It loops the system back toward its human origin.\n", "\n", "
\n", " Resources: Data 📉; Pretext, 95/5 (deconstructed)
\n", " Bequest: Filter 🌴; Subtext, 80/20 (project 2025)
\n", " Strategic: Choice 🪵; Text, 50/50 (low-propensity voters)
\n", " Motive: Scaling 🪡 🐫 ; Context, 20/80 (once-in-a-lifetime)
\n", " Distributed: Canopy 🌿; Metatext, 5/95 (symphony)
\n", " — Yours Truly\n", "
\n", "\n", "This looping is essential. Ukubona believes in feedback—not just statistical, but moral. If a model suggests disproportionate risk to a population, that is not just data—it’s indictment. It is signal that something is wrong, not with the patient, but with the structure around them. The sea is biased. Ukubona doesn’t pretend otherwise.\n", "\n", "The platform, in this regard, becomes more than code—it becomes protest. Against opaque risk scores, against unjust eligibility criteria, against the flattening of human variety into actuarial tables. Ukubona’s ship is navigated not by captains alone, but by all who ride it. Patients, clinicians, families—they all get to steer.\n", "\n", "This ethos makes Ukubona dangerous to systems that prefer silence. Where other tools prioritize [efficiency](https://en.wikipedia.org/wiki/Department_of_Government_Efficiency), Ukubona dares to [prioritize](https://www.nobelprize.org/uploads/2024/12/hassabis-lecture.pdf) understanding. It does not believe that care must be fast to be just. Sometimes slowness—reflection, customization, hesitation—is the more ethical stance.\n", "\n", "But that stance requires tools. Ukubona’s screwdriver, its most humble icon, is also its most radical. It affirms that models must be maintained, adjusted, localized. That no model is final. That even truth, once seen, must be tuned. This is what separates Ukubona from static dashboards and inert PDFs.\n", "\n", "The screwdriver, too, protects against the pirate. It is not enough to resist once. Maintenance is ongoing. Pirates, whether in finance, insurance, or ideology, reemerge. Ukubona builds systems that expect attack—not in paranoia, but in wisdom. It assumes the ship will be tested.\n", "\n", "And so it trains its users. Not with lectures, but with interface. Ukubona teaches through interaction. When a user tweaks a curve, it is not mere aesthetics—it is education. It says: you have agency. You can intervene. Even in statistics, your story matters.\n", "\n", "That story is not singular. Ukubona's visualizations allow for overlay—multiple lives, multiple paths. It is a comparative theology. Not in a religious sense, but in a metaphysical one: which future shall I serve? This or that? The curve becomes sacred, a scrying mirror for the soul.\n", "\n", "But the mirror reflects only what is fed into it. This is why Ukubona insists on open data pathways—why it allows CSV uploads, API inputs, voice entries. If the platform is to serve the many, it must listen to the many. Its ears are open.\n", "\n", "It listens not just to patients, but to analysts. Ukubona’s back-end is transparent. The Cox regression is not a black box; it is documented, modifiable, inspectable. The platform respects those who question it. This, too, is moral: no model should be above critique.\n", "\n", "\n", " \n", "\n", "```{raw} html\n", "\n", "\n", "
\n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", " \"Eco-Green\n", "\n", "\n", "\n", "
\n", "
\n", "
\n", "\n", "```{figure} https://www.ledr.com/colours/white.jpg\n", "---\n", "width: 1\n", "height: 1\n", "name: figures/cgbest\n", "---\n", "We just might have figured out how to number non-python images. This is exciting\n", "```\n", "\n", "
\n", "\n", "Even the life-raft, which might seem passive, is built on this ethic. It is a default made by people who care. It is a best-guess, constantly updated. It floats not by luck, but by repeated testing. It is born of humility: sometimes people can’t engage deeply—and that’s okay.\n", "\n", "But for those who can, the scissors await. A beautiful tool. Delicate, sharp. The curve can be trimmed to fit gender, race, lab value, comorbidity. These aren’t tweaks for show—they change the shape of the risk. They reshape fate. Ukubona makes that visible.\n", "\n", "The shark, meanwhile, circles. Ukubona does not pretend it can be defeated entirely. The shark is the cost of automation. The risk of scale. It is always there. Ukubona’s courage is not in ignoring it, but in naming it. That, too, is visibility.\n", "\n", "Visibility is not enough. Ukubona believes in accountability. Every curve it draws is tied to sources. Data provenance matters. If a curve misleads, the platform takes responsibility. It is not infallible—but it is answerable.\n", "\n", "Answerability extends to its developers. Ukubona does not hide its team. It humanizes them. It shows who made the models, who tested them, who maintains them. This breaks the myth of AI as godlike. It restores personhood to the process.\n", "\n", "That personhood ripples outward. Patients using Ukubona do not just “see” risk—they reclaim some of their story. They no longer submit to clinical fate passively. They narrate. They ask: what if I wait? What if I proceed? What does that curve mean for my child?\n", "\n", "And still, the island beckons. Not as salvation, but as orientation. A place to rest, briefly, before setting sail again. Ukubona never pretends the journey ends. It simply gives you the means to continue, eyes open, map in hand, and truth underfoot.\n", " " ] } ], "metadata": { "kernelspec": { "display_name": "myenv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.11" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 4 }