Friday, October 31, 2025

History

 

All Hallows by Cecily Fox Smith

All Hallows
by Cecily Fox Smith (1882-1954)

All on the autumn woods the mist lay white and chill;
And I heard the rising wind come piping down the hill,
    And the stream sigh o'er the shallows
    On the Eve of All Hallows
        When the house was still.

I did not set the door wide, no meal did I spread,
Neither a cup of water nor a platter of bread,
    They came without my calling
    When the night was falling,
        From the days that are dead.

No dogs barked at their passing from the silent fold;
There was no step on the doorsill nor print on the damp mould
    To tell the world to-morrow
    I supped with love and sorrow
        Ere the hearth grew cold.

Dear dreams of years departed, kind ghosts of vanished days,
Slipped in then to the firelight, stretched their hands to the blaze,
    Lost voices whispered nigh me,
    Loved footsteps lingered by me
        Ere they went their ways.

I heard a bird crying along the lonely hill,
I heard the stream sighing and the wind piping shrill
    Across the frosty fallows . . .
    On the eve of All Hallows
        When the house was still.

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Battle in the Heavens, 1912 by Nicholas Roerich

Battle in the Heavens, 1912 by Nicholas Roerich (Russia, 1874-1947)

















Click to enlarge.

Thursday, October 30, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

The Soup Cutter, 1933 by François Barraud

The Soup Cutter, 1933 by François Barraud (Switzerland, 1899–1934)
























Click to enlarge.

Wednesday, October 29, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Clouds in the Valley by Ed Sandoval

Clouds in the Valley by Ed Sandoval (America, 1945 - )

























Click to enlarge.

Tuesday, October 28, 2025

What a delight to experience the future as it emerges.

This afternoon/evening I dropped off my car at the auto service center for its routine checkup and service.  Pulled up the Uber app to get a ride home.  There's a ride seven minutes out, but if I am willing to wait ten minutes for a Waymow, it will be available at the same rate.

Fantastic.  I have been watching them all around Altanta over the past six months or so.  Even had to wait behind one a month ago in traffic.  A couple of guys had ordered one.  It was clearly their first ride cause they were grinning and carrying on, filming themselves getting in.

Now it is my turn.  I say yes, send me the Waymo.  

As soon I hit the confirm button, I am full of doubts.  I don't know how this works.  Will it find me?  How do I get in?  How does it know its me?  

There's an extra step that I don't recognize at first.  As with a regular Uber ride, you confirm your pickup address.  But with Waymo, you need to confirm one of, in my case, three locations for pickup.  They are all within twenty feet of each other.

No problem.

I spot the car after nine minutes and it pulls into the area where I am to be picked up.  The Waymo system connects with my iPhone Bluetooth.  The door handles are recessed into the doors of the car.  Once the Waymo stops beside me and recognizes me (or my iPhone) it pops open the door handles for me to open the door and enter.

It won't start until I am buckled in.  It gives me a couple of orientation messages and instructions and then we are off.

I film part of the journey to share with friends and family.

It goes a slightly different way home than I would have but it is rush hour and it has actual knowledge of traffic conditions compared to my rule of thumb heuristics.  We get home as quickly as I might have based on my best guesses.  

The Waymo handled Atlanta traffic, Atlanta drivers, a roundabout, speed bumps, a geriatric pedestrian walking in the street, electric scooters going the wrong way, rush-hour traffic, narrow residential streets with oncoming traffic etc..  

I’m grinning from ear to ear. I feel like I’m 25 years old and installing the first five meg hard drive in the Arthur Young offices some forty years ago. Sure, it crashed 20 times a day, but it was so much better than the floppy discs.   

I cannot say just how emotionally and intellectually invigorating this journey was.  As William Gibson said, "The future is already here, it's just not very evenly distributed."  

What a delight to experience the future as it emerges.




History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Light, c. 1905 by Frans Van Holder

Light, c. 1905 by Frans Van Holder (Belgium, 1881-1919)































Click to enlarge.

Monday, October 27, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Life's Circumnavigators By Louis MacNeice

Life's Circumnavigators
By Louis MacNeice (Ireland, 1907-1963)

Here, where the taut wave hangs
Its tented tons, we steer
Through rocking arch of eye
And creaking reach of ear,
Anchored to flying sky,
And chained to changing fear.

O when shall we, all spent,
Row in to some far strand,
And find, to our content,
The original land
From which our boat once went,
Though not the one we planned.

Us on that happy day
This fierce sea will release,
On our rough face of clay,
The final glaze of peace.
Our oars we all will lay
Down, and desire will cease. 

Data Talks

 

Undercurrent by Richard Claremont

Undercurrent by Richard Claremont (Australia, 1965 - ) 

























Click to enlarge.

Sunday, October 26, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Forest by Józef Wilkoń

Forest by Józef Wilkoń (Poland, 1930 - )























Click to enlarge.

Saturday, October 25, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Oak, 1963 by S. R. Badmin

Oak, 1963 by S. R. Badmin (England, 1906-1989)
































Click to enlarge.

Friday, October 24, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

72 hours on the streets of Paris with a fedora

A wonderful and lighthearted illustration of the 72-hour rule.  The 72-hour rule suggests waiting three days from some MSM or social media dramatic claim before reacting.  The probability is that the initial claim will be either debunked or materially changed in the first three days.  

In this instance, there is an epic theft of crown jewels from the Louvre in France.  

I saw the headlines about three days ago.  Soon after, I saw this post (without the community note.)

Chen's full message is:

Actual shot (not AI!) of a French detective working the case of the French Crown Jewels that were stolen from the Louvre in a brazen daylight robbery. 

Somehow he looks like he’s smoking even without a cigarette in his hand, but surely everything you know about life is screaming at you: this case is officially screwed!

To solve it, we need an unshaven, overweight, washed-out detective who's in the middle of divorce. A functioning alcoholic who the rest of the department hates.

Never gonna crack it with a detective who wears an actual fedora unironically.

Yesterday I see this clarification. 


Yesterday evening we enter the humor phase.


And then this morning, a slightly slyer wit:

That's quite the life-cycle of a piece of "news."  

A variant of the 10 hours walking in New York genre.

The original:

Click to enlarge.

And the spectacular derivative.

Click to enlarge.

Data Talks

 

Spring Twilight, St Margarets, 2021 by Ian Archie Beck

Spring Twilight, St Margarets, 2021 by Ian Archie Beck (England, 1947 - )





















Click to enlarge.

Thursday, October 23, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

The Yellow Gate by Marc Gooderham

The Yellow Gate by Marc Gooderham (England, 1977 - )


































Click to enlarge.

Wednesday, October 22, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Winter Dusk in London, 2013 by Nessie Ramm

Winter Dusk in London, 2013 by Nessie Ramm (England)


 




















Click to enlarge.

Tuesday, October 21, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Dawn in London, 2008 by Stefan Bleekrode

Dawn in London, 2008 by Stefan Bleekrode (Netherlands, 1986 - )



















Click to enlarge.

Monday, October 20, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Evening Light, 1942 by Oakley Richey

Evening Light, 1942 by Oakley Richey (America, 1902-1971) 














Click to enlarge.

Sunday, October 19, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Morning Tempest II by Edward Gordon

Morning Tempest II by Edward Gordon (America, 1940–2023)



























Click to enlarge.

Saturday, October 18, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

East River, 1920 by Edward Hopper

East River, 1920 by Edward Hopper (America, 1882-1967)


















Click to enlarge.

Friday, October 17, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Messaging, 2016 by Leonard Koscianski

Messaging, 2016 by Leonard Koscianski (America, 1952 - ) 
 


















Click to enlarge.

Thursday, October 16, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Reflecting on St Stan's by Bill Vrscak

Reflecting on St Stan's by Bill Vrscak (America, 1946 - )



































Click to enlarge.

Wednesday, October 15, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Canal Boat, 1992 Reg Cartwright

Canal Boat, 1992 Reg Cartwright (England, 1938 - ) 

























Click to enlarge.

Tuesday, October 14, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Big Sur Shimmering Coast by Jeff Daniel Smith

Big Sur Shimmering Coast by Jeff Daniel Smith (America, 1956-2023) 



















Click to enlarge.

Monday, October 13, 2025

History

 

An Insight

 

I see wonderful things

 

Offbeat Humor

 

Data Talks

 

Data Talks

 

Data Talks

 

She Leaves the Light on for Him, 2017 by Tim Kelly

She Leaves the Light on for Him, 2017 by Tim Kelly (America, 1966 - ) 




















Click to enlarge.

Sunday, October 12, 2025

They give answers which are evasive and tautological

From Lanzarote by Michel Houellebecq

The same cannot be said of the English, nor of the more general mystery of the English holiday maker. There's no such mystery to the Germans (who will go anywhere there's sun), still less to the Italians (who will go anywhere there's a cute ass); as for the French, let's not even go there. Alone among Europeans in the middle- and higher-income brackets, the English are notable by their absence from mainstream holiday destinations. Nevertheless, meticulous and systematic research, supported by considerable data makes it possible to map their movements during summer pasturing. They gather in small groups and head for unlikely islands absent from Continental holiday brochures—Malta, Madeira or, indeed Lanzarote. Once there, they duplicate the principal elements of their home environment right there. When asked to explain their choice of destination, they give answers which are evasive and tautological: 'I came because I came here last year.' It is apparent that the Englishman is not motivated by a keen appetite for discovery. Indeed, one may observe that he is not interested in architecture, landscapes, in anything whatsoever. In the early evening, after a short trip to the beach, he is to be found drinking bizarre cocktails. The presence of the English at a resort, therefore, is no guide to the intrinsic interest of the destination, its splendour or its possible tourist potential. The Englishman goes to a particular tourist destination purely because he certain that the will meet other Englishmen there. In this, he is diametrically opposed to the Frenchman, a vain creature, so enamored of himself that the mere sight of a compatriot abroad is anathema to him. For this reason, Lanzarote is a destination to be recommended to the French.

No Enemies by Charles Mackay

No Enemies
by Charles Mackay (England, 1814–1889)

You have no enemies, you say?
Alas! my friend, the boast is poor;
He who has mingled in the fray
Of duty, that the brave endure,
Must have made foes! If you have none,
Small is the work that you have done.
You’ve hit no traitor on the hip,
You’ve dashed no cup from perjured lip,
You’ve never turned the wrong to right,
You’ve been a coward in the fight.

In all cases, the most common (modal) age for women is in their 20s, whereas in images from IMDb and Google, the most common ages for men are 40 years and 50 years, respectively

One of those research papers which raise more questions than it answers but is interesting none-the-less.  From Age and gender distortion in online media and large language models by Douglas Guilbeault, Solène Delecourt & Bhargav Srinivasa Desikan.  All sorts of reasons to dismiss this (essentially related to the inherent possible quality issures of the input data rather than the methodology per se.)  But it is a good college try.  From the Abstract.

Are widespread stereotypes accurate or socially distorted? This continuing debate is limited by the lack of large-scale multimodal data on stereotypical associations and the inability to compare these to ground truth indicators. Here we overcame these challenges in the analysis of age-related gender bias, for which age provides an objective anchor for evaluating stereotype accuracy. Despite there being no systematic age differences between women and men in the workforce according to the US Census, we found that women are represented as younger than men across occupations and social roles in nearly 1.4 million images and videos from Google, Wikipedia, IMDb, Flickr and YouTube, as well as in nine language models trained on billions of words from the internet. This age gap is the starkest for content depicting occupations with higher status and earnings. We demonstrate how mainstream algorithms amplify this bias. A nationally representative pre-registered experiment (n = 459) found that Googling images of occupations amplifies age-related gender bias in participants’ beliefs and hiring preferences. Furthermore, when generating and evaluating resumes, ChatGPT assumes that women are younger and less experienced, rating older male applicants as of higher quality. Our study shows how gender and age are jointly distorted throughout the internet and its mediating algorithms, thereby revealing critical challenges and opportunities in the fight against inequality.

As usual, I get very suspicious when research does not report absolute measures.  How many years younger?  Why isn't that in the abstract?  

The researchers get distracted by the ideological goal of stamping out inequality.  But the research findings stand, independent of the ideological interpretation of those findings.  So what are the actual findings which aren't in the abstract?  

The Abstract does not mention by how much younger are women depicted than men which seems to me a crucial omission.  If it's six months then that is probably within margin or error.  If it is six years, then there might be something interesting.

The report itself gives the answer for celebrities:

Next, we analysed the 2018 IMDb–Wiki dataset43 and the 2014 Cross-Age Celebrity Dataset (CACD)44 consisting of Google Images, each of which provides the true gender and age of the celebrities depicted using their public bio pages and time-stamped photographs. Figure 1 shows that female celebrities are, on average, 6.5 years younger than men on IMDb (t = −169.9; P = 2.2 × 10−16; n = 451,562 images; Fig. 1d), 3.27 years younger on Wikipedia (t = 10.64; P = 2.2 × 10−16; n = 57,972 images; Fig. 1e) and 5.35 years younger in Google Images (t = −90.92; P = 2.2 × 10−16; n = 149,889 images; Fig. 1f). In all cases, the most common (modal) age for women is in their 20s, whereas in images from IMDb and Google, the most common ages for men are 40 years and 50 years, respectively. These analyses show that age-related gender bias online is not an artefact of human perceptions of gender and age, because it is replicated using verified objective information about the age and gender of those depicted. That age-based gender bias replicates strongly in the context of celebrities is concerning, given the salient role that celebrities play in reinforcing stereotypes.

6.5 years is in the interesting category.  

However, the media industry is by repute notorious for favoring young starlets while providing more roles for older men.  So maybe 6 years gap isn't surprising.  What about other occupations and categories.

From the bowels of the report it appears that their other approaches (aside from IMDb) don't have nearly the gap. One or two years seem the modal gap depending on the different methods used.  Certainly within the margin of error given questions about data integrity and methodological sensitivity.  

From potentially interesting research, this now begins to look like cognitive pollution.  They wanted to find a discriminatory bias and they were able to play with the data to get one.  But mostly by building a house of cards, likely to collapse at the slightest breath of inquisition.  

Christian Rudder had far better evidence some fifteen years ago, see One data set can have multiple truths.



History

 

An Insight

 

An Insight

 

I see wonderful things