Duty over Love... For love Sometimes you are The princess and sometimes You must play The girl

Sometimes you are The prince and at others Just the Pauper

Truth Beauty Freedom Love

Most of all... LOVE

As Wesley said To his Buttercup

As You Wish

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A life lived in fear is a life half lived

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Please give me the gift of the spirit in my heart and the spirit Of dance in my feet.

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#poetry #osxs #sketchbook

2024-11-10 00:54:10

wrinkled pages

Finished on Sunday: Three Moments of an Explosion, a collection of short stories by China Miéville. I had found a hardback copy in a charity shop which cost me a pound. Given my literary tastes, Miéville's work should very much be my cup of tea — but it hasn’t worked out that way. I was put off by my first taste of his work, when I read Kraken about fifteen years ago (which, to this day, remains the only book I’ve read on a Kindle). I actively disliked it: there was something about his authorial voice that I couldn’t warm to. The inexpensiveness of this copy of Three Moments seemed like the ideal opportunity to give his writing a second chance.

While I got along better with it than with Kraken, reservations remain. The title story, for instance, is one of several very short pieces in the book, none of which impressed me. To my mind, the volume would have been better had they been omitted. Elsewhere, Miéville's ‘voice’, as it sat & ‘sounded’ in my mind again often had something about it I found off-putting. There were a some exceptions: the slick satire of ‘Dreaded Outcomes’ delighted me; and I relished the old-school style of ‘The Design’, the tale which closes the book. Of the other stories I enjoyed, a couple (‘The Dowager of Bees’ and ‘The Bastard Prompt’) could have been the basis for intriguing X-Files plot-lines. The horror stories in the collection generally failed to fully connect, with ‘The Rabbet’ the only one of them to properly get under my skin. Miéville’s imagination is undeniably fertile, though some of its productions teetered awkwardly past the furthest points to which I could suspend my disbelief. These were cases less fit for Mulder & Scully than perhaps for Professor Quatermass, or even Doctor Who.

Miéville’s new novel The Rouse was purportedly twenty years in the making and runs to 1,264 pages. I shan’t be rushing to buy it, but if a cheap copy should turn up in a charity shop in years to come, I may take a look.

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My latest music acquisitions were likewise very inexpensive ones. Seeing a CD copy of Manu Chao’s Próxima Estación: Esperanza reminded me I used to like his song ‘Me Gustas Tu’. Picking up the disc, I saw the song was on there so decided to buy it. It’s a pretty good record — a warmly uplifting Bob Marley-influenced feel suffuses much of it — just perhaps a little too much of it for my taste: a tad more variation of mood would have suited me better.

On a neighbouring shelf to the Manu Chao album, an early ‘90s CD issue of Art Blakey’s Jazz Messengers With Thelonious Monk. The music here is wonderful; the recording and/or mastering, regrettably less so. The bass — played by the curiously-named Spanky DeBrest — is often all-but inaudible, undermining my enjoyment of the performances. The absent bass is apparently a known flaw in the original stereo recording, so I’ll have to try to get my hands on one of the more recent mono remasters. For an example track from the record (with audible bass) try ‘In Walked Bud’.

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During the same visit to Chepstow when I bought the CDs (which were £1 each), I also found a dainty-looking ornamental glass vase (Fig. 40) which set me back another £4.

As if to offset these relatively thrifty acquisitions, I squandered (via ebay) a rather larger sum on yet another box of old stationery: some ‘Milano’ paper and matching envelopes from Pineider. The set is second-hand, but unused (Fig. 41). The Florentine retailer seem like an Italian equivalent to the likes of Smythson or Cassegrain, with a historic focus on providing personalised stationery to a wealthy clientele. The box contains only 24 sheets of A4 paper with as many envelopes. The paper is laid, watermarked and straight-cut; and the envelopes are lined with white tissue & discreetly embossed with a Pineider logo. There’s no claim of the paper being rag-based or hand-made: one might hope that, given the asking price, it might at least be one or the other, but who knows.

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Cheese of the week: Bluemin White from Shepherds Purse Artisan Cheeses in Yorkshire. This mould-ripened offering is encased in blue-grey penicillium roqueforti rather than white p. camemberti, yet it isn’t a properly blue cheese, as the small truckles are left unpierced so that the mould can’t readily infiltrate the paste. The hint of blue provided by the rind does however add a certain extra tang to what is otherwise a subtly delicious brie-like number.

The Short Version

I spent two days in May chairing and speaking at World Class Cannabis Business Europe (WCCBE) in Frankfurt, on the subject of visual AI for cannabis cultivation. The biggest takeaway wasn't about the technology. It was about the gap between what the AI industry likes to talk about – autonomy, end-to-end automation, “AI runs the grow” – and what growers in the room actually asked for, which was something much more grounded. They want a tool that helps them decide, not one that decides for them. They want it to be specifically good at plants, not generically good at everything. Here's what I heard, and what it means for where PlantLab goes next.

Context, September 2026: this piece is from PlantLab's founding vertical – cannabis, still our only live diagnosis model. The plant-health platform and public crop roadmap grew out of this work.

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The setting, and an honest mismatch

WCCBE Frankfurt, May 19-20, 2026. I chaired a day and gave a talk on visual AI for cannabis – the kind of plant-by-plant diagnosis problem PlantLab works on.

The first honest thing to say is that a deep cultivation-diagnosis talk is not the same animal as a policy, regulation, and investment talk, and a conference that spans all of those is going to have rooms with very different centers of gravity. The business and policy sessions are genuinely useful for credibility and for understanding where the industry is heading. But the product conversation – the one where someone tells you what they'd actually use on a Tuesday in their grow room – happens with operators, not in the M&A track. That's not a criticism of the event. It's a note to myself about which rooms the product story belongs in.

With that said, the technical lessons that came out of the operator conversations were sharp enough to be worth writing down.

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Lesson 1: Growers want a co-pilot before they want an autopilot

The pitch the AI industry loves is autonomy: the system watches, decides, and acts, and the human steps back. Almost nobody I talked to wanted that as the first step.

What they wanted was a tool that makes their own judgment faster and more confident. Flag the plant that looks off. Tell me what you think it is and how sure you are. Then let me decide. The grower stays in the loop because the grower is accountable for the crop, and because they have context the camera doesn't – what they fed it last week, what the room did overnight, what this strain always does at this stage.

This maps cleanly onto a design choice: the most valuable output isn't a decision, it's a well-calibrated suggestion plus an honest signal of how much to trust it. Autonomy can come later, on the narrow slices where the tool has earned it. Human-in-the-loop is not a stepping stone to be skipped. For most growers it's the actual product.

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Lesson 2: Generic AI keeps disappointing growers

This came up again and again, usually as a half-frustrated aside: people have tried asking a general-purpose AI assistant what's wrong with their plant, and it gives them an answer that sounds authoritative and is often wrong, with no signal that it might be wrong.

This is the wedge, and it's a fair one to talk about publicly because it's about outcomes, not methods. A general model trained on the whole internet knows a little about cannabis among a billion other things. It will confidently call magnesium deficiency on something that's actually a pH problem, because the visual distinctions between plant health issues are subtle and the general model never had to get them right. Worse, it presents every answer with the same smooth confidence, so the grower has no way to tell the good answers from the bad ones.

A purpose-built tool earns its place precisely here: it's narrow on purpose, it's measured on how well it does the specific thing, and it can tell you when it's unsure. “Specifically good and honest about its limits” beats “generally capable and uniformly confident” for anyone making a real cultivation decision.

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Lesson 3: The near-term home for visual diagnosis is controlled indoor cultivation

Visual AI diagnosis works best where the inputs are consistent: stable lighting, repeatable camera angles, a known set of plants, a controlled environment. That description is controlled indoor cultivation, and it's also where the people most willing to adopt new tooling tend to be.

Outdoor and greenhouse settings introduce variability – weather, mixed lighting, scale – that makes consistent visual diagnosis harder. None of that is unsolvable, but it's the second problem, not the first. The honest near-term answer is that indoor, controlled grows are where this technology delivers reliable value today, and that's where the product should aim first.

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Lesson 4: The automation companies need plant-state signals, not another app

A recurring theme in the hardware and automation conversations: the companies building controllers, sensors, and grow-room automation don't need another consumer-facing diagnosis app. They need a plant-state signal they can pull into what they already build.

That's a different shape of product. It says the diagnosis capability should be available as something an automation system can consume – a clean signal of plant condition and how trustworthy it is – rather than only as an app a human opens. The growers running those rooms have already chosen their controllers and their dashboards. The useful move is to feed plant-state into those systems, not to ask everyone to adopt yet another screen.

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Where this points PlantLab

Four lessons, one direction. Take the product to the rooms where operators are, not only the rooms where the industry talks about itself. Keep the diagnosis specifically good and honest about its uncertainty, because that's the thing generic AI can't do. Aim first at controlled indoor cultivation, where visual diagnosis is reliable today. And make plant-state available to the automation systems growers already run, instead of competing for their attention with another standalone app.

None of these are surprising in hindsight. That's usually the sign of a good conference – it doesn't hand you a new idea so much as it sharpens the ones you arrived with and tells you which were wishful thinking. The wishful one was autonomy-first. The sharpened one was that being narrowly excellent and honest about it is the whole game.

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PlantLab is free to try at plantlab.ai. Three diagnoses a day, results in milliseconds. If you build grow-room automation and want a plant-state signal to integrate, the API documentation lives at plantlab.ai/docs.

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FAQ

What is WCCBE?

World Class Cannabis Business Europe (WCCBE), held in Frankfurt in May 2026, covering cultivation, policy, regulation, and business across the European cannabis sector. I chaired a day and spoke on visual AI for cannabis cultivation.

Why not just use ChatGPT to diagnose my plants?

A general-purpose AI knows a little about cannabis among everything else, and presents wrong answers with the same confidence as right ones. A purpose-built diagnosis tool is narrow on purpose, measured on how well it does the specific task, and can signal when it's unsure – which is exactly what a general model can't do.

Does PlantLab automate my grow room?

PlantLab provides the diagnosis and a trust signal; what you do with it is your call. Most growers want a tool that informs their decision rather than one that acts for them, and the API is built to support that human-in-the-loop use first. It can also feed plant-state into automation systems for the cases where automatic action makes sense.

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Related reading: – What's Wrong With My Cannabis Plant? A Visual Diagnosis Guide – The grower-facing diagnostic hub – Confidence Is Not Reliability: Trust Signals for Automated Plant Diagnosis – How to know when to trust an automated answer – Build an Autonomous Plant Health Monitor with AI + Home Assistant – Feeding plant-state into automation

The Problem

Let's say you are a new or aspiring cultivator. You got some seeds, soil, nutrients, and the rest of your setup. You plant the seed and in a few days a little sprout starts growing. You hope that all goes according to the instructions you read or videos you watched. But at some point, your plant looks a little off. Perhaps the leaves are curling or its color changes. Something doesn't seem right. You search online, post photos on growing forums. You adjust pH, nutrients, lights. Sometimes the plant bounces back and sometimes it doesn't. You wish you could get a clear signal about what's going on, so you can actually address it.

Or perhaps you are an advanced grower, with a large tent or greenhouse. Daily, you walk and examine your plants, checking for signs of stress or pests. The more plants you have, the more chances something goes amiss and needs your attention. Your systems for lights, pH, water may be automated but they still need you: your vision and your experience.

The Solution

Now imagine a service that takes a photo, analyzes the state of your plant's health, and produces a structured response your tools can log and alert on. Not an app that gives you a diagnosis and leaves you to interpret it. Not a ChatGPT wrapper that overpromises because it was never trained on actual plant data. Rather, an extra pair of expert eyes in your growing operation – running continuously, flagging anything amiss, and handing you the detail you need to decide what happens next.

Why I Built It

I tried the apps. I tried uploading photos to ChatGPT. The apps gave me generic advice. The AI chatbots hallucinated confidently—telling me I had calcium deficiency when it was clearly light burn. None of them were trained on actual cannabis data, and it showed.

So I built my own. I collected thousands of real plant images, labeled them, trained models specifically for cannabis diagnostics. Not because I wanted to start a company, but because I wanted something that actually worked for my own grow.

What PlantLab Is

PlantLab is that tool: an AI trained specifically on cannabis plants to identify health issues with speed and accuracy. It gives you an expert eye on your plants around the clock, producing structured output your tools can log and alert on.

Your Data, Your Privacy

Your images are not stored. Your data stays yours. And if you need it, PlantLab can run completely offline and on-premise, for air-gapped environments where privacy is non-negotiable.

Tomato is the crop I get asked about most after cannabis. The honest answer first: tomato diagnosis does not exist at PlantLab yet. Cannabis is the only live model. Tomato is the first crop on the public roadmap, and its status today is planned – not in development, not in beta, no ship date.

The short version

• Not live. PlantLab does not diagnose tomato plants today. Anything that claims to is not us.
• First in line. Tomato leads the public roadmap, ahead of apple.
• Planned, honestly. “Planned” means intended, with no corpus work started yet. I won't call it “in development” until that's true.
• Available now: cannabis diagnosis, free tier, 3 checks a day, at plantlab.ai.

The tomato scouting problem

Anyone who grows tomatoes at scale knows the routine: walk the rows, flip leaves, look for the first spot. It's hot, repetitive work, and the difference between a bad week and a lost season is usually one leaf noticed two days earlier.

The problems a tomato diagnosis model has to catch are public agronomy, documented anywhere tomatoes are studied:

• Early blight (Alternaria solani). Brown spots with concentric target rings, oldest leaves first. Common everywhere tomatoes grow.
• Septoria leaf spot. Many small spots, pale centers, dark edges. Starts low and climbs the canopy.
• Late blight (Phytophthora infestans). Greasy dark lesions on leaves and stems that can kill a planting in days. The one everyone fears.
• Leaf mold (Passalora fulva). Velvety growth on leaf undersides, mainly in greenhouses and high tunnels.
• Tomato spotted wilt virus (TSWV). Bronzed, ring-spotted young leaves. Thrips-vectored, no cure – removal is the only answer.
• Two-spotted spider mites. The same pest cannabis growers fight, same stippling, same fine webbing.
• Nutrient deficiencies. Nitrogen and magnesium show on the oldest leaves first, potassium scorches leaf margins – the same mobile-nutrient grammar across crops.

None of this is exotic. The hard part isn't knowing the list. It's telling them apart from a photo, early, when the spot is pinhead-sized and three of these look nearly identical.

What transfers from cannabis, and what does not

PlantLab's habits transfer: every result carries a condition, a calibrated confidence, and a severity reading, and the model is built to flag the mild early signal a person would skim past. A calibrated hedge beats a confident wrong answer, on any crop.

The lookalike knowledge does not transfer. Early blight versus septoria versus late blight on a stressed plant is its own exam, and the only way to pass it is the same standard cannabis met before its model shipped. No shortcuts, and I won't pretend otherwise.

What “planned” means

The crop roadmap uses four labels, and each one is a claim:

• Live – a deployed model diagnosing that crop. Today that's cannabis alone.
• In development – corpus work has genuinely started. Tomato isn't here yet.
• Research – an active, named collaboration or dataset evaluation.
• Planned – intended, no work started. Tomato sits here.

A crop moves up only when the evidence moves. No dates, no percentages, no “coming soon” until a model actually clears the bar.

What you can do today

If you grow tomatoes, the crop roadmap page has the current status and a notify option: plantlab.ai/platform.

If you grow cannabis, diagnosis works today – free tier, 3 checks a day, structured output through the web app or API.

Tomato diagnosis is planned, not live. Cannabis diagnosis works today at plantlab.ai – free tier, 3 checks a day. Watch the crop roadmap for tomato.

The short version

PlantLab diagnoses plant health from a photo. Cannabis is the live model today: 30 conditions, a calibrated confidence score on every result, about 18 milliseconds a check. Tomato and apple are next, on a public roadmap, and neither is live. This post is the plain-language version of what all that means.

One crop first, on purpose

I built PlantLab for cannabis first because I needed the answer myself. ChatGPT looked at my plant and said calcium deficiency. It was light burn. A general-purpose chatbot always has an opinion; it rarely has what it takes to be right on the hard cases.

That failure set the bar for everything since. The problems worth catching are lookalikes – deficiencies that mimic each other, pests that mimic deficiencies – and trust gets earned on the hard cases, not the easy ones. Shallow coverage of twenty crops would have been easier to market and useless in a grow room.

The name was never CannaLab. The data is cannabis-shaped. The question never was.

What the platform actually is

Three pieces, and none of them are cannabis-specific:

• A diagnosis engine: photo in, structured result out – condition, confidence, severity, one per plant.
• A public API: the same JSON envelope every check returns, free tier included.
• An honesty layer: calibrated confidence and a reliability signal, so a weak result tells you it's weak.

The engine is crop-agnostic by construction. Each crop still earns its own model.

The bar each crop must clear

Every crop on the roadmap carries a label, and each label is a claim:

• Live – a deployed model diagnosing that crop. Cannabis, today.
• In development – corpus work has genuinely started.
• Research – an active, named collaboration or dataset evaluation.
• Planned – intended. No work started yet.

Tomato and apple sit at Planned. They move up when the evidence moves, not before. A date is easy to publish and impossible to keep honest.

What carries over, and what has to be rebuilt

The habits transfer. Calibrated confidence, the per-plant read, saying “low confidence, monitor this” instead of guessing – those apply to any crop.

The data does not. Every crop earns its own library, and tomato starts from zero. That's the work, and there is no shortcut around it.

What you can do today

If you grow cannabis, PlantLab works today: 30 conditions, under a second per check, 3 free checks a day at plantlab.ai, same JSON through the API on the free tier.

If you're waiting on tomato or apple, the crop roadmap lives at plantlab.ai/platform. A crop gets announced when its model is Live – not when it is hoped for.

To paint is to invite you into my dream, realms where anything is possible. Soft edges of understanding and experience rife with hope and the unexplored. We are there together, artist and lover interpreting the form and color in our own time and understanding. Sometimes delighted, sometimes sad, sometimes confused. Each experience personal and every journey differing.

Writing is inviting you to the knife’s edge of my reality, now, moments past or futures imagined. A moment or experience revealed in the precise detail of invention or observation. You come into my mind and you feel the pain and the joy, the tears and the exultation as I feel. We are bound on that journey in experience, feeling and understanding.

Music takes the precision of writing and combines it with the abstract qualities painting to create ethereal moments exploding with experiential thrill. Music is poetry. Music is painting. It is wide and narrow, dark and bright, loud and quiet.

2025-01-17 15:28:55

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GitBook.io är en webbaserad plattform för att skapa, organisera och publicera dokumentation och kunskapsmaterial. Tjänsten är särskilt populär bland företag, utvecklare och projektteam som behöver samla information på ett strukturerat sätt och göra den lättillgänglig för användare eller medarbetare.

Med GitBook kan man exempelvis skapa användarmanualer, produktdokumentation, guider, API-dokumentation, FAQ-sidor och interna kunskapsbanker. Informationen organiseras i sidor och sektioner, vilket gör det möjligt att bygga upp allt från en enkel guide till en omfattande dokumentationsportal. Dokumentationen kan publiceras offentligt på webben eller skyddas så att endast behöriga användare får tillgång till den.

En viktig funktion i GitBook är möjligheten att samarbeta kring dokumentationen. Flera personer kan arbeta med innehållet, kommentera och granska ändringar samt använda versionshistorik. Plattformen har stöd för Markdown och kan synkroniseras med GitHub och GitLab. Det gör att utvecklare kan arbeta med dokumentationen direkt från sitt vanliga kodflöde samtidigt som andra medarbetare använder GitBooks visuella redigerare.

GitBook innehåller även AI-funktioner. GitBook Agent kan hjälpa till att skapa, granska och hålla dokumentation uppdaterad, medan GitBook Assistant kan låta användare ställa frågor och få svar baserade på informationen i dokumentationen. Publicerat innehåll kan dessutom göras mer tillgängligt för AI-system genom bland annat Markdown, llms.txt och MCP.

Tjänsten passar därför bra för exempelvis ett företag som vill bygga ett hjälpcenter för sina kunder, ett utvecklingsteam som behöver dokumentera ett API eller ett projekt som vill samla instruktioner och teknisk information på ett och samma ställe. GitBook kan även användas som en intern företagswiki där rutiner, processer och annan kunskap samlas och hålls uppdaterad.

En av fördelarna med GitBook är att man inte behöver bygga en egen webbplats eller ett eget system för dokumentationen. Plattformen kombinerar redigering, strukturering, publicering, sökning och samarbete i samma tjänst. Det gör GitBook till ett praktiskt verktyg när information behöver vara lätt att hitta, enkel att uppdatera och tillgänglig för rätt målgrupp.

Här är ett exempel på hur Gitbook kan användas.

The pillar of cloud would not move away from before the people during the day, nor the pillar of fire at night.

I noticed driving home that the clouds were odd. In the land of big sky, you get used to every sort of cloud.

North of the city, out over the land toward the Red River, a huge plume of clouds covered the sky at least out to the Oklahoma border. It was kind of glorious, but the color was off. Instead of the usual blue/grey the clouds had a sickly yellow tint to them. Even some dark grey floating around.

It wasn't until I got a few miles closer that I could see the column connecting the clouds to the ground about 15 miles out.

It was an impressive fire, and thankfully out in the middle of nowhere. Though I doubt the terrestrial animals felt like it was the nowhere.

Coming over the bridge where I like to watch the sun set into the railroad tracks, I spotted this crusty old cowboy hat. Pulling off to capture it, I saw that it was well-worn, but not end of life. Some farmer is going to be plenty ticked off that he lost his favorite straw hat.

I left it there so when he comes back, he'll be able to reclaim it.

Standing there in 108º heat, with the sun cooking my back and the smoke burning my nostrils, I was stricken with how beautiful the moment was.

It turns out even hell has a good side.

Given the choice, most sane people would choose a beautiful mountainside with trees and lush grass. Or maybe a beach bungalow where the waves could lull them to sleep.

And I like those things. I think I'd choose them from a lineup. But the old adage 'bloom where you are planted' came to mind. There is good and bad to every place people dwell, but it absolutely floors me that there can be beauty in destruction.

If you gave me an unlimited budget and a capable team as well as all the time I needed to turn someplace into a paradise, I wouldn't choose something where most of the work was already done. Give me a Death Valley, a Badlands or a Dust Meridian any day.

Imagine the thrill of looking back over 20 or 30 years of terraforming and trying to convince people the place was once one of the most avoided locales in the world.

I ran into this heat map a few weeks ago. It shows distance in miles of how far away from a national park you are.

Now, you'll note that NY, FL panhandle and a few others are either red or yellow, indicating that maybe they're ugly places to visit. Nope. Just no parks designated by the federal government.

The streak from Galveston Texas to Minnesota is pretty telling. They don't call them the flyover states for nothing.

Unless you like sunsets. They're pretty glorious.

But imagine turning that corridor into one of the most attractive places on earth.

Now that's a task I could get behind. And I bet you could too.

HOW?

The funny thing about places nobody wants to be? You can get away with pretty much whatever you want. Without making a big deal of it, what if someone planted a few hundred thousand sequoias while no one was looking?

And I'm not saying Yellowstone is going to blow North America off the map, but a little tectonic action out here sure does have the potential to create some new and stunning vistas.

Fire is always gonna' fire. Burn it all down. But you know what? Some pretty damn amazing things come in the wake of destruction.

Look at Mount St Helens.

The richness of the soil in the aftermath is hard to deny.

And I think this applies to us emotionally as well.

We all go through periods where our worlds end. Losing a hat or two, or maybe our heads entirely. A paddock or the whole continent of our heart burns away.

And we, just like the land, are not done.

We're just prepped for what comes next. And sometimes, impossibly, what comes next becomes more precious than what was there before.

Honestly, I'm kind of counting on it.

So, let's stand here for a minute and appreciate that old hat.

Soak in the heat. The smoke. The scorching earth.

Hell has a strange way of making the land fertile again.

There is simply no telling what is going to grow here next.

Let's hope together that it is more glorious than we could have imagined.

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Song of the day:

This Too Shall Pass – Okay Go – Of the Blue Color of the Sky (2010)

You know you can't keep letting it get you down And you can't keep dragging that dead weight around If there ain't all that much to lug around Better run like hell when you hit the ground

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#music #essay

Black Queen by herself.

I won this game, part of a club-based CC tournament which started on 29-June, a few minutes ago when my Black Queen checkmated the White King on her 35...Qh3#. The position of pieces at game's end is shown above, and our full move record below:

1. e4 a6 2. Qh5 g6 3. Qe5 f6 4. Qc3 Bg7 5. d4 Nh6 6. f3 e6 7. e5 Nc6 8. Bd3 f5 9. Ne2 O-O 10. Nf4 b5 11. Nh3 Nf7 12. Ng5 Nxg5 13. h4 Nf7 14. O-O d6 15. Qxc6 Bd7 16. Qc3 dxe5 17. dxe5 Bxe5 18. Qc5 Bd6 19. Qd4 c5 20. Qc3 c4 21. Be2 Bc5+ 22. Be3 b4 23. Qxc4 Rc8 24. Bxc5 Re8 25. a3 b3 26. cxb3 Rc6 27. g4 Qxh4 28. b4 Ne5 29. Qf4 Nf7 30. Nc3 e5 31. Qc4 Be6 32. Nd5 Kg7 33. gxf5 Qg3+ 34. Kh1 Nd8 35. Rg1 Qh3#

And the adventure continues.

Your wonderful works are evident in creation.

They rise above the landscape, blaze with color, or stretch toward the sky. We stop to admire them because they are impossible to miss.

And then there are the small things.

The things we walk past.

The tiny flowers growing beside a path. The moss tucked into the cracks of a stone. The intricate veins of a leaf. A seed no bigger than a grain of sand, carrying within itself the promise of an entire plant.

They don't demand our attention. They invite it.

The Texas frogfruit is one of those quiet wonders.

At first glance, it is easy to overlook. Its flower heads are tiny, its stems slender, and it often grows close to the ground, mingling with the ordinary vegetation around it. Nothing about it seems designed to stop a hurried person in their tracks.

But stop.

Lean closer.

Look at it as though you have never seen a flower before.

Suddenly, the ordinary becomes extraordinary.

What appeared to be a simple little flower head reveals itself as a miniature constellation of petals—white and lavender blossoms arranged with almost jewel-like intricacy. Tiny forms overlap one another, each one contributing to the beauty of the whole. There are colors and textures and patterns that the casual glance completely misses.

It is a bejeweled spectacle hiding in plain sight.

And perhaps that is part of what makes small things so beautiful.

They require us to slow down.

The grandeur of a mountain can overwhelm us from a distance. The brilliance of a sunset can stop a conversation. But the beauty of a tiny flower asks something different of us. It asks us to become attentive.

To bend down.

To look again.

To discover that there is more here than we first imagined.

Creation is full of this kind of hidden magnificence. The closer we look, the more there is to see. A single flower is not merely a splash of color; it is an intricate architecture of petals, pollen, stems, shadows, and delicate relationships with the living world around it. A leaf is not merely green. A drop of water is not merely wet. Even the smallest seed contains a mystery far greater than its size suggests.

Smallness, it turns out, is no indication of insignificance.

In fact, some of the most astonishing things in creation are almost absurdly small.

We live in a world that trains our attention toward the large. Bigger achievements. Bigger houses. Bigger landscapes. Bigger experiences. Bigger lives.

But nature has another lesson for us.

Pay attention to the little things.

There is beauty in what doesn't shout.

The Texas frogfruit doesn't need to be magnificent by human standards. It doesn't need towering stems or enormous petals. It doesn't need to be rare or famous. It simply exists as what it was made to be—and when we take the time to truly see it, we discover that it is astonishing.

Maybe that's a lesson worth carrying with us.

How many beautiful things do we miss because we have decided, too quickly, that they are ordinary?

How many moments pass unnoticed because we're looking for something bigger?

How many tiny gifts surround us every day, waiting not to be found, but simply noticed?

The practice of paying attention changes the world—not because the world suddenly becomes more beautiful, but because we finally become awake to the beauty that was already there.

A tiny flower by the roadside becomes a cathedral in miniature.

A patch of sunlight becomes a painting.

A bird's song becomes a reminder that the world is still full of wonder.

And a little Texas frogfruit, easily passed by, becomes a jeweled spectacle.

Perhaps creation has always been speaking this way.

Quietly.

Patiently.

In small things.

We only have to stop long enough to look.

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#museum #milepost

The 17th century French diplomat and cryptographer Blaise de Vigenère published a treatise on fire and salt. The title is literal — Traicté du Feu et du Sel — and the premise acts as alchemy at its most reductive, where the whole of transformation is compressed into a simple binary: two principles, two substances. Vigenère’s text, however, is actually stranger than its title suggests. It is not really about fire or salt. It is about the impossibility of speaking about anything for the first time. And the implication that an idea, once spoken, cannot be controlled or contained and may perpetuate beyond its source in ways its speaker never intended.

The treatise opens with Pythagoras. Not Pythagoras directly — no one has Pythagoras directly — but Pythagoras as received through tradition, “held to have made more profound search, and with less incertainty penetrated into the secrets as well of Divinity, as of Nature.” Already the syntax demonstrates the author’s argument: Vigenère is reading Pythagoras, who is reading the Mosaic tradition, who is reading — what? The mind of God, presumably, but even Moses received the law on tablets, which is to say, in written form, which is to say, as a text that was already a mediation, rather than a direct link to the mind of God — a shared consciousness. The chain has no first link.

This raises the question: are there other links in this chain lost to time? Or, better still, how do we trust any source of knowledge when its origins are so obfuscated or enigmatic?

Vigenère builds an elaborate scheme of attribution: Pythagoras borrowed from the Hebrews. The Egyptians and Chaldeans borrowed from both. Scripture conceals philosophy within ritual. Every source, when you press it, reveals a prior source beneath. Vigenère moves through these layers with the confidence of a man who has spent decades in the archives of other people's reading — which he had, literally: before writing on alchemy, he spent years translating and annotating classical texts, and before that, a foundational cipher of modern cryptography. He was a man professionally devoted to the idea that every surface meaning conceals a deeper one, and that the concealment is both method and feature rather than flaw.

This is the treatise's subtle radicalism. Vigenère never claims to have discovered anything himself. He does not position his text as a source but as a commentary — on Pythagoras, on Moses, on Mark 9:49 (“every man shall be salted with fire”), on a chain of prior readings stretching backward into a darkness he treats as generative rather than empty. And the remarkable thing is that his commentary feels enriched rather than diminished by its secondariness. Each layer of mediation adds a new context and texture. Vigenère reading Pythagoras is not a degraded copy of Pythagoras reading Moses. It is a new act of understanding that could not have existed without the distance spanned.

There’s also a serious epistemological claim, not just a historical curiosity. What Vigenère demonstrates — almost against his own intentions, since he would probably have said he was simply recovering ancient wisdom — is that knowledge does not degrade as it passes through commentary. It transforms. It acquires texture, context, contradiction—and, yes, flavor, the way fire and salt season food. This suggests that scholarly annotation in this method comes from within rather than passively from outside, the way a river that continues the rain that feeds it without becoming the rain itself.

We still seek originals. We distrust commentary. But this is precisely what Vigenère's chain of attribution makes impossible to sustain. There is no moment in his treatise where a source appears without already being a reading of something else. Moses is already interpreting. Pythagoras is already annotating. The “darke sentences” in which ancient knowledge arrives are not failures of transmission but the very form that deep knowledge takes — because what matters is not the content in isolation but the relationship between reader and text, the transformation that occurs when one mind meets another across the distance of centuries and tradition and language.

This is, I think, the secret argument of the Traicté du Feu et du Sel, hidden inside its alchemical metaphors the way Vigenère says philosophy is hidden inside scripture. Fire transmutes rather than destroys. Salt seasons the object, changing its nature through contact rather than merely preserving it. Some of these passages — on preservation, on the spaces between — I recognize all too well.

Commentary is the fire that transmits, not destroys. And what emerges from that intersection is not a diminished copy of some lost original but something new: knowledge that has transited a human mind, becoming something new but not altogether different from what had entered.

Perhaps there are no original texts. Perhaps all we have across the whole of human history are the ongoing commentaries of others past — some survived, some lost. Provenance falls away when meaning lives in interpretation alone. All of which would otherwise be impossible without someone first having named the unnamable, the sacred unmentionable somehow spoken. And once spoken, renders the anomalous more familiar.

#Philology

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Notes:

1. My copy of Vigenère’s Traicté du Feu et du Sel is an English translation from roughly 1649. Though I find his ideas intriguing, I cannot speak to his traditions, nor the potential differences between the English and French versions of the text.

2. The alchemical opus transforms the practitioner alongside the substance in the vessel. The lapis is not just produced but undergone, meaning the text is already a record of anomalous experience: knowledge inseparable from the encounter that produced it.

3. Can anomalous experience even be articulated in the raw moment, becoming meaningful only through layers of interpretation and introspection afterward? Could mediation be the process by which the darke sentence reveals what was latent beneath the letter, rather than a distortion of it?

4. Might some knowledge require encryption to survive transmission, as Vigenère's cipher requires a key and his alchemy requires a veil? Is it possible that indirection serves not to obscure but to protect what cannot be stated directly?

5. Both alchemy and anomalous experience are relational: the alchemist needed the soror mystica, the student needed the master, the work could not be done alone or in full daylight; and the witness exists, not to verify the event empirically, but to receive the account and become the next link in the chain of knowing.

6. Alchemical transformation is irreversible: one does not un-calcine, nor reverse the nigredo. Could anomalous experience operate similarly, reorganizing the knower so permanently that the distinction between encounter and ordinary learning dissolves? Where does ordinary dream end and extraordinary vision begin?

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By D. Bowman Nomina Numina is a journal of my reflections, moments, and meaning-making between worlds. Reply by email.

Just a story about a story.

It’s been over two years since I logged into my last social media. It was BlueSky, and I ran across a batch of mean folks. I wasn’t talking to them. I didn’t have them in mind when I said what I said about a personal memory. They inserted themselves underneath my post to berate me and call me a fat white guy. I was like, “I am just telling a story that actually happened. What if there was an opinion in here?”

Do you need to hate so many people?

I find a lot of irony in folks feeling like they need social media to stay connected, yet they use social media to write off huge swathes of the population. Many folks feel like they need social media. I have felt that way before in my life. But nothing could be further from the truth. I promise.

Let’s mention brainwashing.

They wouldn’t call it brainwashing if you knew it was happening. Brainwashing doesn’t mean ‘I willingly take on a different mindset.’ So if you’re on social media, you don’t know what you don’t know. You may not know that sometimes folks really into their social media stuff can come off ridiculous and concerning. You may not know that your world is divided up into grid lines of good and bad, right and wrong, what’s cool and what isn’t. You may not realize you have whole populations on this planet that you would like to see dead. All the MAGAs, all the Muslims, all the Jews, all the Mexicans, all the liberals, all the Android users, the pesky Playstation fans. You may not realize your lack of control of your worldview. You may not realize the words on the screen appear because the screen knows your preferences. You may not realize it has cost you money and friends you can touch. You don’t “need” this shit.

What if I was a big corporation and I wanted to implant a commercial in your brain? I wanted you thinking about me 24/7. Without a moment to yourself? What if I wanted you on my software for hours on end so I could gather data about your environment and your preferences? What if I wanted people to become addicted to whatever I was making? I don’t think that would make me a good guy. Yet…

Maybe if you “need” social media, you simply “need” a hand.

I honestly think if you feel like you need social media, what you really need is help. You need the kind of help that isn’t on social media. You need the kind of help that hugs, that joins you for a meal, that talks to you about a movie you saw together, that likes your kind of music, that says things that are unexpected. A real-life connection, not online sycophancy. 

I have a lot of memories of being on social media and feeling wired. People would buzz around my brain. It would keep me awake, rolling words in my brain much like a slot machine in Vegas, and they were just words I saw on my feeds. They were words I wouldn’t have seen if not for algorithms and folks selling things. Me seeing them had nothing to do with who was writing them. It had to do with the computer thinking I wanted to see them. This changed the way I saw the world, eventually. I thought it was here for me. The truth is I’m here for it. So I put it down. Social media. Glad for it. Better too.

I am worried.

I talk about social media with people still using it. I’m concerned. They think we all need it. It connects us. It gives us presence. I’ve even been told I’m doing it wrong, and I’m the one who should get a social media. But I’ve been down that road. It’s not happening again.

I was not in control. Multiply that times billions. No thanks.

Kelly Kintner

The Horses Mouth

The Kintners

Djembe Funk

clever girl

The day started with brilliance and joy. My partner sprung from bed happy as a clam. Not sure what the source is, but savoring. Lots of illustration yesterday! Story story story! Going in the ministry this morning Got the robovac going again. Just caught it trying to steal two quarters Living room disassembled for deep cleaning: goodie night tonight Going to start with a session of Scriptionary (I I'll post a PDF if you'd like to make your own). Sleep was deep and refreshing Great dream, failed to record it, now all I remember are the emotion and touch I was in a buttercup boat—that much remains... travel dream Finished a piece that might be hard to read for some. Still haven't decided to post. Weather: winding and warm Countenance: bright and determined Missing level: manageable My screen is filled with colorful characters Im OFF to see the wizard! YAAY! DHL FINALLY RESPONDED. In German. All I have to do is find a local address in Germany. They'll delivery my packages there. Then I get to pay my friends to ship them a second time to the US. THANKS DHL DE. Good Grief!!! Insurance claim is proceeding. Sklr, the injured hired a lawyer. Our claims adjuster is like 'nbd, it's normal.' So, yay? Not stressing. Warm and windy today.

Insurance stress we drive old cars, so they of course point out they may want to total me out. Sigh. Okay, never mind. I'll do the work myself and hire paint and body to paint it. I did get a fat thank you for your honesty from the agent when I pointed out that the bumper was from a parking lot, not the motorcycle Break Sara Bareilles – king of anything

Home. Hot. Cleaning house. Wish I had a Dev. Closest I have is Robodev—my robot vacuum cleaner. Dev always kinder than a robot. First time in 35 years that my floors have stayed consistently clean. Neither of us likes to vacuum. Eck! All this cat hair. Robo vac was down for a few weeks before I noticed and the cat hair is EVERYWHERE!

Continuing the Barielles concert I love a clean house. Who doesn't? IKR? Full of art and music. All i need is voices and food. Some beer. Dancing would be nice. Someone. Art takes time. That's what makes it so wonderful. It's not a thing, it's a way to see the collected energy of the artist. Barielles making me wistful.

PF wishi you were here Printing and cutting cards Taking a break to draw. 2p

More to come.

30 August 2026

Sat on the lawn at the MMCA in Seoul today from about 4-6pm. Around 5pm, an aproned chef cradling something in his arms walked out of a nearby restaurant and over to a wall, topped with black 기와 tiles, running along the street bordering the museum. It turned out he was holding food—he stood on his toes and reached up to neatly place eight single pieces of bread in a row on the tiles. When he was done he double checked his work for a brief moment, then quickly walked away without looking back. Maybe ten minutes later, a magpie flew down from a tree onto the wall and grabbed a piece of bread. Then another came down, then another.