The concept of image gamma

 kw: photo essays, lighting, gamma, image editing, low key, high key, key adjustment, gamma adjustment

I was asked to explain gamma in images. There is a mathematical explanation, but not many folks would have a gut-level understanding of the math. Instead I'll describe the concept: 

Gamma is the relationship between the brightness of the light at every point in a scene and the numbers used to store each point in a pixel and display it. In an image file, adjusting the gamma of the image raises or lowers these numbers to "brighten" or "darken" the image, while keeping the zero and 100% points fixed.

When the gamma equals 1.0 the relationship between light intensity and the stored values is a straight line. In such a case, when a pixel received half the amount of light compared to the brightest pixel in the image, the number stored for it is 0.5 times the maximum possible number. For most digital images, the numbers range from 0 to 255, so the midpoint is 127 (only integers are used, so the extra half a digit is dropped). When gamma is changed for an image to a number other than 1.0, the relationship becomes a curve. The result is an image that appears brighter or darker, as if the exposure had been different.

Adjusting gamma is different from changing the overall brightness. Raising "brightness" using most image editing software just adds the same amount to every pixel's value, and lowering it subtracts a fixed amount from every pixel's value. Just a little of this may be OK for some images, but a more nuanced approach works better.

This is the "Color Curves" tool in GIMP (a freeware program similar to Photoshop). Moving portions of the straight line that goes from lower left to upper right adjusts the relationship between the values in an initial image and those in an adjusted image.

Note that below the histogram the "Curve type" is Smooth. For simple changes, we can click and drag a point on the line up or down. The program obligingly adjusts the image so we can see the result in real time.

If we drag the center of the line upward, for example, the line changes to a curve passing through that point, showing the change caused by adjusting gamma. Dragging a point not at the center uses a different function, related to gamma but not the same.

The next image shows how the curve looks when the center point is raised a little.

The center point started with a value of 128, seen in the "Input...Output" indicators, and it now has been changed to 160.

The whole line was not shifted as a straight line, but is now a curve that passes smoothly from 0 to the midpoint to the upper right at 255.

In terms of gamma, this raises it from 1.0 to a higher amount. The effect on the picture is to brighten the midrange the most, with less and less brightening towards either end of the histogram.

Next I'll show how the red, green, and blue histograms are affected by this change, and then the image itself and its adjusted version. These histograms were produced using IrfanView:

The images I used are small, only 800 pixels across, so the "before" on the left is jittery, and the "after" on the right is positively seismic! In the portion of the histogram that was stretched the values were shifted, which "pulled them apart", leaving "holes" between. The overall shape of the histograms reveal that the values were all shifted to the right (brighter), stretching the leftward (darker) portion and squeezing the rightward portion. 

Next we see first the image I started with and then its adjusted version. The primary visual differences are that more detail is seen in the shadows, the whole shop appears a bit brighter, and there is a little more emphasis on the woman.

The original image was 1,376x768 pixels; these are 800x447. I used a rather short prompt: "The essence of ingenuity with a steampunk vibe", using the Google Flow site, which makes use of the Nano Banana family of art engines for still images. Unless the prompt includes a request for a bright image, or high key, this engine, like all the others I have used, tends to produce medium-to-high contrast, moderately low key (sorta dark) images. Sometimes the image can be quite dark, as we will see.

When I want to adjust gamma only to raise the key of an image, I edit with IrfanView, which has a control to set a numeric value between zero (totally black except those pixels that started out with a value of 255) to 10 (almost totally white). GIMP doesn't use numeric gamma so I don't know the exact value GIMP used for the adjustment I made, but it is probably about 1.2.

Now let's see how gamma adjustment affects images that were deliberately produced at either high key (lots of white) or low key (lots of dark gray and black).

Here is a common treatment of a baby picture: overexposed on a white background. The attached histogram shows that there are very few darker pixels. The slightly dimmer peak at the right is the shadow, barely visible to the left of the baby's head. The "baby pixels" make up the "mountain".

I used a gamma adjustment of 0.75 to bring out more color in the baby's face. Although the shadow is a bit more distinct, I like this picture better overall.

Next, here is a low key example. I have made a lot of images of imaginary caves. This is one of a series I call Spelunker's Paradise, based on a 15-word prompt. While cave imagery tends to be low key, this was the darkest of the bunch. The engine was Ideogram in Leonardo AI. The histogram has a big peak near "black" and not much else, and in the image one can see only hints of the scenery.

I use IrfanView with a gamma adjustment of 1.2 or 1.3 for moderately low key images. In this case more drastic treatment is needed; I first used 1.5:

A lot more is visible. Based on my own spelunking experience, this is probably realistic. However, I also tried a gamma adjustment of 2:

If I were going to print the image for hanging on my dining room wall, this is the version I would use. You can see in the histogram that all but a few of the darkest areas have now been pushed to be brighter than nearly all of the first image. If the gamma were to be raised even higher it would look unnatural.

In all the histograms of gamma-adjusted images, the jitter-to-zero shows that when RGB values were changed to be larger, gaps resulted. The human visual system is very forgiving of small glitches in color. If I wanted to produce an image with strongly adjusted gamma, and still have a smoother color histogram, I would upscale the image 2:1 using Upscayl, adjust gamma, then reduce the result again to the original size. The final image would have a smoother histogram and this would also potentially reduce image artifacts that could show up otherwise.

The key takeaway is that adjusting gamma is like changing the exposure after the fact.

He entertained a century

 kw: book reviews, nonfiction, memoirs, autobiographies, entertainers

Dick Van Dyke performed in his high school's a Capella choir and drama club until he left early to join the Air Force in 1944. This early experience began to lead him to a life of entertaining, and he is still at it, at age 100. By his own admission, he has slowed down quite a bit, but is still active with the Vantastix, a men's quartet he formed in 2000, and in occasional special events. It all adds up to more than eighty years, or my entire lifetime and then some!

I most fondly remember him as Bert in Mary Poppins. Being of a musical bent myself, I really liked his one-man band (This picture is the best sketch-style image I could produce with the NanoBanana 2 art engine).

At age 99, with every prospect of reaching 100 years and beyond, he wrote a third memoir: 100 Rules for Living to 100: An Optimist's Guide to a Happy Life.

He tells us at the beginning that the number of chapters is approximately 100, and not to hold him to exactness. I didn't count, but I did notice that the text is 309 pages, and the chapters seem to average 3 pages each, so it's pretty close. There is no Table of Contents, no Index, just the (approximately) 100 chapters of advice, anecdotes, and adventures.

He sets the tone with the first chapter, "Don't Act Your Age", which is great advice if you want to portray both Bert and the ancient banker in the same film, as he did. And it is generally healthy. He follows with "Make Your Own Rules", in which he explains why he offers more examples and less advice. That resonates with me, because I've found that if I offer advice, and it is followed, one possible outcome is that all goes well but the person I've advised will always feel less ownership of the result; and if it doesn't go well, I get the blame.

I'll just mention a couple of other items. "Tell Your Hardest Stories", beginning on p. 105 (and one of the longer chapters), shows how our experiences can help others who have similar problems, if both parties are willing to be vulnerable and truthfully relate them. He concludes, "Each of us has our own hard stories of crisis and struggle. When we hold them in, out of fear or shame, they control us. But when we tell our stories, we're in the driver's seat. …we are literally helping others to survive…"

And, "Write it Down" (p. 189) is exceptional advice for most of us. I've learned three ways we might relate to lists or written notes:

1. Some folks make lists and follow them.
2. Some don't make lists.
3. Some lose lists. I am in this category!

I've learned how to cope with being a list-loser since I got a smart phone: I have a Google Doc where I put lists I want to recall and random ideas before they get away. When an item is outdated I can remove it.

Dick Van Dyke has had many lucky breaks and much good fortune, but he hasn't been uniformly lucky, and he tells some of his hard stories. His claim to the title "optimist" is that he bounces back, sooner or later, and usually pretty soon. It is good to remember the past for the lessons learned and for the happy memories. It isn't as good to dwell on past sadnesses. He tells of a couple of those that took quite a while to resolve. I'll let you do your own reading to find them. They don't detract from a great fulness of happy stories.

It is a fun, engaging book. I was surprised at the end when he writes with great feeling about campaigning for Bernie Sanders in his three major Presidential bids. I guess everyone is allowed a bit of insanity… Both he and Sanders greatly benefited from the capitalist system that Sanders claims he wants to destroy.

Can science be rescued?

 kw: book reviews, nonfiction, science, history of science, scientists, biographies, inquisition, polemics

At the defense of my PdD dissertation, one prominent professor growled, "This isn't geology, it is computer science." To a certain extent, he was right. I was surprised that he was the one to say it, though, for among the faculty he was the most computer-literate. I had used a great deal of computer modeling and simulation in conjunction with my research. This was 1983, and the geology faculty in general were much more comfortable out in the field with a rock hammer than they were poking at a computer terminal connected to a mainframe computer hidden away in the basement of the Electrical Engineering building. Desktop personal computers were rare. On the other hand, I was quite computer literate, and I was at that time an adjunct professor of computer science.

That wasn't the only objection to my work. I'll discuss that in a moment. The turning point from interview to inquisition began when someone asked, "Do you really believe this stuff?" I answered, "Believe? That's the wrong word. 'This stuff' cannot save my soul. I believe in Jesus. But 'this stuff' is the best scientific explanation for the phenomena we observe." Hostility ensued. I felt like St. Sebastian, who was tied to a tree where archers used him for target practice.

I had spent a few years of research to determine what effect directional heat flow in Earth's crust might have on the emplacement of "gneiss domes" such as the Black Hills of South Dakota. My supervising professor and I went all over the Black Hills to gather specimens of rocks that had originally underlain the domed structure and rocks in the lowest layers above the granitic/gneiss core of the Hills.

I needed to determine the thermal conductivity of these rocks in three directions. I used a large core drill to cut out cylinders, which I sliced into sections a centimeter or so in thickness, and then I polished the flat surfaces for use in a special press with heaters and thermocouples. I still have some of these. I call them my "hard disks".

The ratio of heat flow across the grain, versus along the grain, is the thermal anisotropy. For a pure, platy mineral such as mica, I found that this ratio could be as high as 6:1. For the shales and schists in the lower sections of the Black Hills, I measured thermal anisotropy between 1.2:1 and 1.6:1. The initial discussions of the early results with my committee were not encouraging. I did a series of computer simulations which showed that the excess heating caused just by thermal anisotropy was no more than a few degrees.

As it happened, I spent time that summer on a project about fluid flow. Another graduate student and I found that the anisotropy of fluid flow in layered rocks could be quite high, 10:1 to 100:1 and even greater. Any fluid flowing through these rocks would be very strongly affected by this directional fabric, and the solid-rock thermal anisotropy wouldn't matter at all. As a side project, the student and I dug into literature and studies about fluid flow in the crust. We determined that even in "dry rock" there is water, and it is in motion, and if there is any heat flow it is directed almost entirely by fluid flow. This was new; there was no literature on this particular point.

Therefore, I wrote a dissertation in which I stated that my initial theory was not tenable, and that further study would be needed to quantify the results of anisotropy in fluid flow. This was quite unpopular and it apparently stepped on a few toes. It was "this stuff" that caused my committee along with the other gathered faculty to reject my dissertation. I became, not a PhD, but AbD, "all but dissertation". Coda: I had an established relationship with scientists at a national laboratory in California. I passed my materials on to them, and they were glad to have them.

With such a background, I was well primed to receive Matt Kaplan's historical survey of scientific mavericks in I Told you So! Scientists Who Were Ridiculed and Imprisoned for Being Right. 

The book is in part a biography of Ignaz Semmelweis, the best-known of those who learned how necessary it is to clean a doctor's hands and equipment before treating a patient. Semmelweis was also the one who seems to have suffered the most for it. The various parts of his life story are woven with others. The book opens with a scene in which a graduate student named Alison, at a poster session, is being shouted into submission by a gaggle of offended professors. Her sin? Being right. Theirs? Feeling threatened by the truth. It costs something to learn something new that reveals the flaws in older ideas.

One scientist who didn't fall prey to this phenomenon was Louis Pasteur. He had the political acumen to make sure he had powerful friends when needed, he was a showman who used public demonstrations (thoroughly prepared beforehand) to publicize his ideas, and he was careful to tailor his presentations to make it seem like his discoveries came as flashes of insight, where in reality he labored long and hard upon them.

The author tells stories of others, including friends and acquaintances, who survived being right only because of more established mentors, and by finally "being right" in a sufficiently public way that could not be denied. Katalin (Kati) Karikó and Drew Weissman received the Nobel Prize in 2023 for working out the therapeutic use of mRNA agents, which led to the "vaccines" used during the Covid-19 pandemic. But Kati had rough going for many years, suffering abusive supervisors and disdainful department heads. Somehow, she plowed through, and collaborations such as that with Dr. Weissman kept her work going. Many others have been less fortunate. Alison left science, as have several others mentioned in the book.

Being right is not enough to ensure being received. Max Planck is known for saying that science proceeds one funeral at a time. My father used to speak of the "Moses Effect", meaning that it takes 40 years in the wilderness for a generation to die out so a new generation can make progress.

Semmelweis seems to have had no such advantages, and many disadvantages. He was not the only doctor to learn the value of chlorine-laced wash water for disinfection. But in his own hospital, he seems to have had the knack for presenting his findings in a way that didn't just challenge other doctors, including his supervisor, he actually indicted them along with himself for killing thousands of young mothers through ignorance.

Arthur C. Clarke's "first law of science" is, "When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong." The trouble is, the distinguished and elderly scientists usually stopped having good ideas half a lifetime ago and feel threatened by the next generation.

These days, it may seem we have moved beyond the times of Galileo, who had to stand before the Holy Office of the Inquisition for saying that Earth moves. Scientists these days don't have the rack or a team of archers to deal with mavericks. But they do have powerful weapons to destroy us anyway. Today, money runs science, in a way much more pervasive than ever before. The "old guard" controls the flow of money, which determines who can afford to do experiments, and who must find a different profession.

I think of two doctors I knew well. One, named Henry, was a radiation oncologist. He once said he could cure most cases of breast cancer, at lower cost than chemotherapy. However, most patients get steered toward chemo rather than radiation. When I asked why, he just rubbed two fingers together, the sign for "money". The other doctor, named Benjamin, is a friend I once asked about how thyroid issues affect fertility. He said, "One third of infertility cases are due to low thyroid, but it is the last thing tested, when it is tested at all." Of course I asked why, and he said, "Treating low thyroid is the cheapest remedy."

In the last chapter the author discusses possible remedies for the prejudice-dominated grant-awarding process. While he has some good ideas, including ideas that are being used on a small scale, he recognizes that government action would be needed to motivate widespread change. Given the huge pharmaceutical and medical lobbying that goes on, useful change is unlikely. I fear that Max Planck was only partly correct, because he said "one funeral at a time." It takes several.

I think of Ignaz Semmelweis and the other pilloried scientists as being like Jeremiah: never wrong; never believed.

Is AI ready for prime time?

 kw: book reviews, nonfiction, artificial intelligence, simulated intelligence, AI, SI, memoirs, experiments

Disclaimer and Pledge: It's a pity I need to say this. I don't use any kind of software to write for me, nor to expand on my writing. The words are all mine, 100%. I do use images I produce using art generation tools touted as "AI art" software, and I (almost) always attribute images produced in this way. If for any reason I use a piece of software-generated text, I'll make that clear. 

This mini-avatar of me was produced by Gemini using a picture from 2015. I look much the same now, just with a few more wrinkles. I wear the hat to keep the sun off my bald head. For those who read this blog regularly, I decided it's time to give you a hint what I look like.

The author of I am Not a Robot: My Year Using AI to do (Almost) Everything, Joanna Stern, spent one year using as many "AI tools" as possible to carry on her life. Kudos to her wife Michelle and their young boys for putting up with it all. This picture shows BookBot, her imagining of an AI scheduler (she actually had two versions running in different software systems), introducing her calendar for the year. This is one of many, many illustrations by Jason Snyder that pepper the book.

Ms Stern begins with her own disclaimer, from which I'll quote, "Every sentence in this book started in my brain and traveled, via my MacBook keyboard, onto the page. AI never wrote anything from scratch, except in places that I've clearly marked."

This book is much more than a series of chapters. Timelines full of blurbs (and Jason's drawings), journal entries, lists of ratings of comparable products, a travelogue (the Way-Mo Fun vacation), interviews, and other side notes enliven the narrative.

I found her experiments, one per season, quite enlightening. The first and most successful was "Search and Information". She set aside Google and its kin in favor of ChatGPT, Perplexity, Gemini, Claude and a few others. She soon adapted to "getting the answer" instead of a long list of blue links. Being able to follow up was a big plus. One aspect she used a lot: pointing her phone's camera at something and asking, "How do I fix this?" or "What is THAT?" (On my Android phone, I use Google Lens similarly). She also tried a couple of versions of smart glasses that can either project information into your line of sight or mutter in your ear about whatever you are gazing at. Though she didn't say so, I'd hope such devices have settings about how much info overload you can tolerate.

The other three experiments involved 

• Music: listening only to AI generated music for a month. She lasted less than two weeks, and recommends that nobody else try such a thing.
• Books: reading only AI generated short stories and books for a while. She generated her own short stories, none of which were as imaginative as her prompts, except when the prompt was a measly 8-10 words. She writes that they were like recycled movie scripts. She found an author who publishes AI generated novels, which must be assembled bit by bit. She corresponded with the author, who said, "Overall, the more human ideas and input, the better. Just like the old programming adage: garbage in, garbage out." She really enjoyed his+its novel. Her own words about stories she prompted, rather than wrote: "Flatter, less alive." (Sturgeon's Law of human writing: 90% of it is garbage. When we feed that to a LLM, of course the proportion is going to approach 99%).
• Video: watching only "AI video slop". She acknowledges that AI generated video getting pretty good and improving fast, but "…it still leans heavily on human creativity, storytelling, and judgment" and she worries about "misinformation, copyright issues, and the use of massive amounts of energy just to make a thirty-second meme."

At the end of all the experiments she asks if we're headed for "a world where simulation starts to feel preferable to experience?" For some people, this is already true. Many science fiction stories dwell on this theme.

Along the way, she and her family used a robot vacuum cleaner, now more enhanced than ever; they "adopted" a robot dog on loan (her son hid the robodog when it was due to be returned); rode only robotaxis, usually Waymo, wherever possible; she tried turning over email responses to ChatGPT—that didn't last long!; she had mammograms with AI enhanced interpretation (but very human oversight) and had dental X-rays with AI enhancement, but found an unfortunate tendency for the dentists to abdicate and upsell; she got a robot massage (and thoroughly enjoyed the way it worked on her butt—no erotic overtones); and they tried a robo-chef, which produced bland but edible meals.

A funny story about riding a Waymo: a photographer was assigned to take pictures of her family in a driverless car. When the Waymo's cameras spotted the camera he stuck out the window of the car ahead, it spooked like a gun-shy horse, stopping abruptly and pulling over to the center divider on the highway. It wouldn't budge thereafter until a Waymo tech got on the radio and "persuaded" it to forget the incident.

There's lots more. Lots and lots. I'll leave it to you to read it. It is well worth it!

I'll finish on this note. All this is, at best, ANI, Artificial Narrow Intelligence. "Agentic AI" is, in the author's view, far from ready and cannot be left unsupervised. The author's definition:

Artificial Intelligence is the creation of intelligent machines that can think, see, learn, and act like humans—and maybe even exceed human abilities.

The supposed emotional content many people claim to get from LLM's (including AI boy/girl friends or even spouses) is actually a consequence of the software being trained using human-generated text, which always has emotional content, and of the software ecosystem in which a LLM sits (every bit human coded). Their relational interactions are thus a mirror of the psychology of the person being interacted with. Actual sentience is the difference between simulating feelings and actually having them. Also, the so-called guardrails (easily sidestepped) that try to keep sex and violence out of the picture are written in human code. No AI tool yet devised can reliably detect "unacceptable content."

When I was teaching computer programming at a university, the department head once said, "Computers excel at detecting differences. Human minds excel at detecting similarities." I built a career on this principle, writing software that helped humans with the stuff we cannot do well, and leaving it to the human user to do what we can do better than any machine. I'll leave further thoughts to future rants.

The first Mars generation

 kw: book reviews, nonfiction, science, astronomy, astronomers, biographies, mars, social phenomena

In 1877, Mars and Earth had a "great opposition". The two planets were close together, just about 56 million km (35 million miles). The orbit of Mars is somewhat elliptical, so at "less favorable" oppositions, dates when Mars is directly outward from the Sun and high in our night sky at midnight, the distance can be as great as 102 million km (63 million miles). Astronomer Giovanni Schiaparelli took advantage of the great opposition to observe Mars nightly, for weeks. In addition to blotches and pale areas, he saw a few seemingly linear features, which he called canali, the Italian word meaning "channels".

The word canali does not refer to artificial waterways; other meanings are "troughs" and "gullies". Unfortunately for the next generation or two of the American and European public, when Schiaparelli's  work was translated into English, the translator chose to use the word "canals".

About seventeen years later, Percival Lowell, nearing the age of forty, having observed Mars in telescopes located in Boston and elsewhere, built his observatory near Flagstaff, on "Mars Hill". With the 24-inch diameter telescope he installed there, he watched Mars obsessively during every period of opposition. The drier, steadier air in Flagstaff enabled him to see the planet more clearly. Over time, he discerned numerous linear features, writing of them as "canals". He inferred that they were produced by intelligent Martians.

Lowell's articles, books, lectures, drawings and later photographs of Mars stirred a kind of Mars Mania for a generation, as described by David Baron in The Martians: The True Story of an Alien Craze that Captured Turn-of-the-Century America.

Percival Lowell was rich, driven, obsessive, and probably bipolar. He had earlier had a varied career, including being a kind of envoy for Korea and Japan. Once the observatory was completed, and he had released his book Mars, the planet and his theories about the Martians and their engineering abilities dominated his life and enthralled the public.

His public lectures and writings kept Mars Mania going for the rest of his life, in spite of opposition from roughly half of the scientific establishment. One particularly telling blow came from an experiment conducted by Walter Maunder, which became known as the "Small Boy Theory". Maunder began with maps of Mars produced by Schiaparelli and Lowell. He removed all the canals and replaced them by scattered dots or bits of riverine shapes. For each of several tests, such a doctored map was hung high on the wall at one end of a large classroom, and schoolboys were seated throughout the room. They were asked to copy the map as well as they could, without moving from their seats. Those closest to the front made the best facsimiles, of course. The farther back a boy sat, the more likely he was to add straight lines where dots and fragments seemed to run together in his vision.

Lowell never wavered from his view of a canal-riddled Mars. This image from page 62 shows one of his maps showing the "canals" and "oases" (dots) he drew. Just below it is an image I captured from Google Mars, taking in the approximately same view of the planet. The straight edges of some dark areas are artifacts of different camera views stitched together.

The scattered dots in the lower image are craters. I remember in 1965 when the Mariner 4 spacecraft sent us images of Mars that resembled a moonscape: loads of craters, and no canals. This was just a century after the Flagstaff Observatory was established.

Have you looked at clouds to see "cloud animals" and other fantasies? Various amorphous shapes can look like faces. There is a blotch in the abstract pattern in my shower that looks a little like a panther's head, only when I have my glasses off. This is called pareidolia. A roughly lined-up string of spots can look like a straight line when seen from a certain distance.

But what further affected Lowell as he aged was a bad case of confirmation bias. It's something we are all prone to: when we like an idea, we remember facts that support our view and discount those that don't.

At one point, Lowell spent some time looking at Venus. He produced the map in the upper part of this pair (from page 76). He was told that the "map" seemed to just reflect the blood vessels in his retina; he apparently agreed, and retracted the map. 

I've viewed Venus a number of times with various size telescopes. To a normal human eye, it is featureless, a blank white disk. However, if Lowell had lived a century later, and had a cataract operation, he might have seen features on the surface that are visible in ultraviolet light, particularly if he used a dark blue filter such as Cobalt glass. The lower image simulates such a view; I just "blued up" an ultraviolet photo of Venus. The natural lenses in our eyes are yellow, to filter out deep blue and UV light, which are hard to focus and tend to blur the vision. Cataract operation patients can see more UV than the rest of us.

Well, that would only be true before 1980. Since then, the plastic lenses that are inserted to replace the natural lens also filter out UV light. Oh, well, my hopes of getting my cataracts out and gaining UV vision are dashed!

Percival Lowell married at age 53. Eight years later, somewhat a fallen hero but still well remembered by the public that had been enthralled by his lectures, he passed away at age 61. When Clyde Tombaugh discovered Pluto in 1930 Lowell was still sufficiently famous that the planet was given the symbol ♇ using Lowell's initials.

I have just skimmed over Lowell's life. I sympathize with his "neurasthenia", which was probably depression in the "low" phase of bipolar syndrome. I've been there. David Baron did an amazing amount of research to put this book together. The apparatus—source notes, bibliography, list of illustrations, and index—take up a quarter of the volume, almost 80 pages. Many other people who surrounded Lowell and the Mars phenomenon, including Nikola Tesla, Sir Arthur Conan Doyle, and Camille Flammarion, play their parts in this narrative. The fabric of these lives is a fascinating tapestry of the American and European societies of the thirty years surrounding the year 1900, when so much happened.

Why did I title this piece "The first Mars generation?" A new Mars generation has arisen, enthralled by the vision of Elon Musk, who wants to establish a colony on Mars with a million inhabitants. He hopes the first humans to reach mars will do so in the early or mid 2030's. Maybe it will work...

Finishing with a fizzle

 kw: story reviews, fiction, poems, short stories, collections

It didn't take long to finish the last eleven pieces in 2026 Pushcart Prize: Best of the Small Presses, 50th Anniversary Edition, edited by Bill Henderson and other editors. Eight were poems, all perhaps eloquent and evocative, but most were pointless, except perhaps to insiders.

Poets, if your writing is only for yourself, your audience is limited to some (not all) of your closest friends or associates, and a smattering of others who happen to think like you do. Don't think you are quite so universal. We have only so many archetypes to go around. 

There was a time that a poem was a piece of craftsmanship. A few still are. Poetry arose before prose and even before writing, for good reason. It's easier to memorize…that is, if it has rhyme and rhythm. So-called "free verse" is too free. If someone has something worthwhile to say, even if they break the sentences and phrases in odd places so it looks like "verse", the content is the content. Too many "free verses" are free of content, or at least, of content that means anything to someone except yourself.

OK, huffiness over, I did like two of the poems:

• "Refuge" by Sheema Kalbasi. The skeletal images make the tragic almost bearable.
• "After the Fireworks" by Jessica R. Gordon. At times it is good to linger. The accompanying image is the fruit of running the prompt, "Remember to slow down and enjoy your surroundings" through Leonardo AI's Flow State, culling a few from several hundred images offered, and selecting one. FYI, most of the images Flow offered were abstract.

The one story I liked was "Lessons of the Line" by Dana Levin. It's about poetry, by someone who actually works at it, who practically coerced an established poet to mentor her.

This volume of Pushcart Prize has been better than some of the earlier ones. I'll keep looking for its successor volumes.

Some learn and grow

 kw: story reviews, fiction, poems, short stories, collections

I'm nearing the end of 2026 Pushcart Prize: Best of the Small Presses, 50th Anniversary Edition, edited by Bill Henderson and other editors, having read another 22 pieces. Here and there a story shows a protagonist who learns something and grows up a little. Far too many authors show no evidence that they know what learning and growing even are. First, the list of the pieces that I rated as at least so-so, with my tiny comments:

• "Transition Lenses" by Jessica Petrow-Cohen (poem). grief recovery; a semi-poem
• "Werner Herzog's Ecstasy" by Maura Stanton (poem). evocative, mysterious. [a mix of iambic and trochaic pentameter]
• "Typical Girls" by Amy Lee Lillard. AI takes over [neuralink plus?]
• "Freefall" by Marie Goyette. surviving foster care
• "Late Spring Epiphany After the Georgia O'Keeffe Exhibit" by Melissa McKinstry. expressive impressionism
• "From Hedge to Hedge" by Wendy Willis. democracy of species
• "A Black Mother's Child Considers His Lost Dream of Immortality" by Iain Haley Pollock. reality framed in classical imagery
• "Whistling Past the Graveyard" by Ted Kooser. cancer memoir [see below]
• "Nashville, 1999" by John Okrent. kindness in adversity
• "Cairn" by Clint Bentley. loser gets a little less lost
• "Plate Spinner" by Francine Witte. new hobby
• "Don't Bleed on the Artwork: Notes from the Afterlife" by Wendy Brenner. unexpected joy [see below]

First, about "Whistling Past the Graveyard": I'm a cancer survivor, thankful for every day bought from the grave by God's grace in the hands of a master surgeon. Ted Kooser had it even worse than I did, and came through it.

"Don't Bleed on the Artwork" goes a few directions, but the main thrust is growth. I wrote "unexpected joy" because the unexpected job in a picture framing shop, and what the author learned and gained from the owner, led to unexpected growth and maturity.

In a memoir I've written on and off for more than a decade, a large section is titled "The twists and turns of life."

Librarians take the lead

 kw: story reviews, fiction, poems, short stories, collections

I have read another 23 selections, and skipped one, in 2026 Pushcart Prize: Best of the Small Presses, 50th Anniversary Edition, edited by Bill Henderson and other editors. In a similar way to the review a few days ago, I will just show the short impression I wrote as I read each piece, but this time only for the 17 that were at least so-so. I have more to say about the single story (so far) that earned a "++" from me.

First, the list:

• "Yellow Tulips" by Nathan Curtis Roberts. disability, seen and hidden
• "Countdown" by Anthony Marra. conscripted at the border [between Russia and Georgia]
• "An Essay About Coyotes" by Ryan Van Meter. grief and healing
• "One of You Will Betray Me" by Kathy Chao. parents have to grow up too
• "Hover O'er Me With Your Wings" by Randy F. Nelson. turning points
• "Lords of the Wind" by Yxta Maya Murray. religious naturalism
• "Steeplechase by Angela Ball (poem). variety, even in steeples
• "How No Money Becomes Money" by Andrei Codrescu. vanity of destructive fashion
• "The Widow's Tale" by Richard Bausch. unwelcome séance
• "Is Wrack, Is Rak, Is Wreckage" by Allison Hutchcraft (poem). wrack on rock
• "The Department of Everything" by Stephen Akey. libriarianship! [see below]
• "Devotion" by Michael Mark (poem). purposeful vandalism
• "Thebes, Revisited" by Grace Schulman. town stage production
• "Sickled" by Jane Kalu. disease of body and soul
• "The Weight of Days" by Dorianne Laux (poem). stretched metaphors
• "Easement" by Kim Samek. scams take over
• "Ode to Darnel (Ode to the Crocus)" by Carey Salerno (poem). hospital memories

In "The Department of Everything", Stephen Akey fondly remembers when we could call the reference desk of a public library and get almost any kind of question answered…so long as it was a question of fact. A librarian might have offered advice on more ambiguous matters such as relationships, but at the risk of the supervising librarian's wrath. Also, even if a librarian already knew the answer, he or she needed to also provide the reference, which typically required going to get the physical book or index or journal for the citation. A reference desk librarian didn't need to know everything, just where to find everything. Now for factual information we just use Wikipedia, or Google, or more recently, we ask a chatbot. Note that these are in descending order by reliability.

Pushcart at Fifty - the first third

 kw: book reviews, story reviews, poems, short stories, collections

Looking back I see I have previously read five of the Pushcart Prize volumes. This is the sixth: 2026 Pushcart Prize: Best of the Small Presses, 50th Anniversary Edition, edited by Bill Henderson and other editors. My esteem for the series has risen and fallen. This time around it is mostly high…so far.

Prior volumes took up around 550 pages. This one is 570 pages, plus another 47 pages listing every item published since 1976. The last page of the last story is 521; the rest is the apparatuses. That's a typical proportion. There are 77 stories and poems.

In the past few days I've read 19 items: eleven stories or memoirs and eight poems, and I skipped only one item. I do not take many notes as I read, but I do note down a very short "impression summary" to remind me. Perhaps it is instructive to record those (ignoring the one I skipped):

• "Rich Strike" by Christie Hodgen. mentoring and growth
• "When the Prince of Heaven Sleeps" by Roger Reeve. the softness of strong men
• "Ode to a Smith-Corona Galaxie Typewriter" by Angela Narciso Torres (poem). nostalgia
• "Tinder" by Sarah Green (sort-of poem). bemusing quotes by men
• "Golgori" by Peter Hong. outgrowing a deity
• "The Beautiful Salmon" by Joanna Kavenna. gaining perspective (young student among titans)
• "The End of Childhood" by Wayne Miller (poem). memoir or fantasy?
• "All I Love" by Chen Chen (poem). tree+poem = troem...cute
• "Desperate Times, Desperate Crimes" by Lou Mathews. optimism, against all odds
• "The Harvest" by Uche Okonkwo. collapse of one's dreams*
• "Like Mowing the Grass" by Bruce Beasley (poem). mowing metaphors
• "This is You" by Tommy Moore. the carry-stuff guy for a porn studio
• "One Writer Against Oblivion" by Mark Brazaitis. the title says it
• "Wilding" by Shara McCallum. metaphor of escape from childhood
• "Almost Born" by Keya Mitra. pilgrimage w/medical mistakes*
• "The Uber Men" by Nadir Jabur. experience doesn't always confer wisdom
• "It is Said" by Suzanne Cleary (poem). interesting, ambiguous
• "Siri as Mother" by Hala Alyan (poem). stream of [machine] consciousness, extra-long lines
• "On Arrival" by Sarah C. Harwell. finally beginning to grow*

*Three stories deserve a little extra comment. "The Harvest" is about a preacher whose congregation dwindles to himself and his wife. Having suffered a similar fate, before learning why God put me through it, I once said, "All my dreams have died," to which God replied only, "Your dreams, not mine." "Almost Born" has a woman learning, after about 20 miscarriages and finding a doctor who would take her seriously and do the right tests, that an early injury is the cause of her misfortune, not the oft-heard, "That's just the way you are," too late. I have a dossier of medical mistakes and I can more than sympathize. I am alive because I once forged a referral to a specialist! In "On Arrival" I find an amazing statement about the experience of many at a job: "…eight hours of emptiness in order to continue the activity of loving."

I find that I marked eleven items with a "+", including a couple of the poems. The rest were so-so or below. I have yet to find a piece that makes me say, "I am really glad I read that." Hope springs…

Happy 250th, America!

 kw: independence day 2026, 250th birthday

Very briefly, I am so glad to be a citizen of the greatest country on Earth!

The original image is full size (2K), unsigned, in case anyone wants to download it and print it. My gift to you all.

To catch a spy, think like one

 kw: book reviews, nonfiction, hacking, spies, hackers, cybercrime, deepfakes, home security

A truly successful cybercriminal must have excellent social skills. The popular idea of a "hacker" as a guy in a basement wearing a hoodie and somehow breaking into computer accounts is fiction. The easiest way to get the user credentials needed to get into a computer system is to purchase them on the dark web. The second easiest way is to make a phone call and persuade someone to tell you; that is often easier than you might imagine. But social skills are essential.

As former spy hunter Eric O'Neill tells us in Spies, Lies, and Cybercrime: Cybersecurity Tactics to Outsmart Hackers and Disarm Scammers, the third best way to steal credentials (typically, user name and password) is to exploit weaknesses in an operating system, taking advantage of them before security software is updated to "patch" the weak place. He tells us of one or two such weaknesses, mostly because they don't work well any more. But until a few years ago, forcing a buffer overflow was a common tactic until security programs were re-coded to limit the number of characters entered as a user ID or password.

But here's where things got more scary. HNDL means "harvest now, decrypt later". Getting into a system is one thing; being able to do something useful (to you) with the data files it contains is another. I don't know how many household computers enable encryption of their hard drives; probably very few. But wise business leaders have their IT team encrypt all data. Then someone who breaks in cannot read anything. Crooks have learned to simply copy everything and store it, awaiting the development of more powerful decryption technology, including quantum decryption, that may be able to tackle it in the future. Storage is getting incredibly cheap: hard drives as large as 36 TB are available, and depending on disk capacity, the cost is in the range of $30 to $60 per TB.

The author trains us using two useful mnemonics, one related to intruder techniques, the other to defenses. Firstly, DI²CED (I suppose it is "diced" as in "sliced and diced", a hacker's goal). The keywords are Deception, Impersonation, Infiltration, Confidence, Exploitation, and Destruction. These are like the layers in an onion, each depending on the prior ones. Perhaps that is why a common domain suffix in the dark web is ".onion".

Each chapter ends with a series of tips labeled "Think Like a Spy." This is because cybercriminals, just as confidence actors (con men) of the past, use spycraft techniques. We need to know how a spy thinks to have a chance to avoid the lures and traps that spies use on us. The book is filled with examples, including a near-miss the author experienced and an extended example showing what was needed for a nonprofit corporation he and others worked for/with to recover from a ransomware attack.

The defensive mnemonic is PAID: Prepare, Assess, Investigate, and Decide. Making Preparations beforehand, getting policies in place, is like buying fire extinguishers for your home. A fire may never break out, but if one does, the low price you paid for the extinguishers is a tiny fraction of the damage a fire will do if you have to abandon the house to the flames (note: this is my example, drawn from tidbits here and there in the book). If a smoke alarm goes off, or you see a frying pan catch fire, for example, Assessing the threat needs to take place in a few seconds. Having the extinguisher close at hand makes a big difference in how you Assess the threat. Even then, you may determine that the best action is to call 911 and get outside. For a large business that finds it is under attack, Assessing and then Investigating may need to go on for days or even weeks. In a beginning house fire, if you have extinguishers, Investigation consists of knowing where the nearest one is. Decision is then instant: put out the fire you see, then look for possible others (follow-up Investigation). For a business, Investigation may lead to the threat being seen as either greater or less than it first seemed. Plans that were Prepared beforehand lead to better Decisions.

In the case of the nonprofit, the organization was "rescued" by slow internet connections. The ransomware perpetrator claimed to have downloaded 3 TB of sensitive information. During Investigation, the security team, including the author, determined from system logs that the intrusion was limited in time, and at most 1 GB could have been exported. That's 1/3000th of what the criminal claimed—and that's a common tactic. Scare, scare, scare, and try to keep you from getting time to think. Still, a lot of work had to be done to patch up the security software and restore the systems from backups. Then the criminal could be told, "You got nothing. You get nothing. Go away." Most satisfying.

Other examples relate to personal security. Deepfaked voices and videos are becoming more common. I answered a phone call one day, to hear a cheerful voice say, "Hello, Grandpa." I hung up immediately. I don't yet have grandchildren old enough to use a phone. If a call like that occurs in 10-15 years, I'll need a different plan. Here, Preparing means to have a "family pass phrase" or even a "proof of life" exchange, such as the following:

Caller: "Grandpa, I need help."

Me: "Were you caught by the Jabberwock?"

Real grandchild: "No, it was the Bandersnatch."

But a fake grandkid? The caller will simply hang up, and if they don't you hang up on them. The caller is probably some middle-aged guy with an AI generated voice, cloned from the grandchild's social media posts (do I need to remind you that you shouldn't post family videos on Facebook or TikTok or X or ANYWHERE!!?)

Of course, if it really is your grandchild, the Assessment needs to include demanding the location, saying you will do nothing until you get there (you may need weapons; that is a different discussion).

The last ten pages of the book is a collection of lists of "ten tips" on various subjects covered in the text. This alone makes this a good reference book to keep on hand. I know I need to do so. From a first reading, all I can gather is some impressions, and a few tips and techniques like those above. I need to re-read some parts.

I was motivated to revise my scheme for creating passwords. Carrying it out will take a few days; I have a lot of accounts! I don't want to use a biometric passkey because I already know of two men who could probably fool a biometrics face-print; in both cases, the man and I have been mistaken for one another several times. How many others are there? I am not distinctive enough!

Get this book. Read it right through. Then go back more slowly over parts that pertain to your life. Keep it handy as a reference. It's well written, so reading it is pleasurable, if sometimes a bit scary.

Resources cribbed from the Tips section:

• Federal Trade Commission: https://reportfraud.ftc.gov/
• Identity Theft concerns: https://www.identitytheft.gov/
• Author's newsletter: https://ericoneill.net/newsletter/ - free subscription

Will we all go gentle into that good night?

 kw: book reviews, nonfiction, artificial intelligence, AI, artificial superintelligence, ASI, dangers, warnings, polemics

I have strong reasons for believing that artificial superintelligence (ASI) is impossible. However, I could be wrong. If I am wrong, the founders of Machine Intelligence Research Institute (MIRI) have a warning for all of us. In their book If Anyone Builds it, Everyone Dies: Why Superhuman AI Would Kill Us All, Eliezer Yudkowsky and Nate Soares state their case.

It is worth considering. Will a future with highly advanced AI include humans? As the authors do, I'd like to look at some things that are hard.

Firstly, we don't know what consciousness is. A recent item in Science News claims that everything with a hint of a brain, at the very least, is conscious. That is, all individual creatures of all species in the animal kingdom have a sense of self, which they strive to defend, maintain, and reproduce. At the moment, nobody anywhere has a way to prove this either true or false or partly false; and in the latter case, where to draw the line. Does a millimeter-long fairy fly have a sense of "I am"? If so, consciousness must arise very easily…in a creature that possesses neurons.

The tiny nematode worm has 302 neurons in its entire nervous system. A fingernail-size jellyfish has thousands. With this in mind, why doesn't a laptop computer or a smart phone, with billions of transistors in its CPU, connected in a complex way, running intricate software, have a sense of "I am"?

I saw a report by a podcaster called Julia McCoy, that researchers at Wellesley College studying things that affect consciousness, primarily anesthetics, gleaned a big clue by  anesthetizing mice. They measured the level of an anesthetic needed for a mouse to become unresponsive, yet not die, for it would awake later, as we all do when we are anesthetized for surgery. They gave a substance to the mice that inhibits the activity of the kinesin proteins that "walk" signaling molecules along the microtubules that form the structure of all cells, and that in particular carry neurotransmitters inside neurons. It took much more anesthetic to put treated mice to sleep. They reported that it "support[s] the idea that the anesthetic acts on microtubules to cause unconsciousness." They further conclude that consciousness, with a basis in the 25nm-wide microtubules, is a quantum phenomenon. This may or may not be bringing us closer to an understanding of how consciousness works.

Secondly, the brain is big, really big. It just seems small because its components are so small. We need to understand that the number of neurons that support thought is probably 4-6 billion, primarily in the prefrontal lobes. The cerebral cortex in total has about 15 billion neurons. Our emotions are generated or mediated in the limbic system, deeper in the brain, which is composed of about one billion neurons, maybe as many as 1.5 billion. However, our entire emotional landscape includes a number of hormones. To operate normally, a biological brain needs a body. The largest set of neurons comprise the cerebellum, which "runs" our body in concert with the brain stem. The cerebellum has about 70 billion neurons, which are quite a bit smaller than cortical neurons. The brain stem has 1.5-2 billion neurons.

The neurons themselves are probably not the basic mediators of brain function. The synapses, the connections from neuron to neuron, are more likely the active agents of brain activity. There are between 1,000 and 5,000 per neuron, with an average near 2,000. They number in the quadrillions. Their measured activity is nonlinear; they are not "switches" in the sense that transistors are linear, on-off switches.

What do I mean by nonlinear? In particular, when we measure how a neuron responds to a stimulus, the response is logarithmic. Fear not: I'll explain simply with two analogies. One: Musical pitch has a very wide range, and when we are young, we can hear notes with frequencies ranging between 15 and 20,000 Hertz (cycles per second, also Hz). The difference from note to note is not perceived as a straight line, though. What we in the West call an Octave represents a factor of two in frequency. Two notes an octave apart "feel" like the same note, just in different registers. Thus the note we call A0, the one near the far left of a piano keyboard, has a frequency of 27.5 Hz. An octave higher, A1 is 55 Hz, and they continue up the keyboard: 110, 220, 440, 880, 1,760, 3,520 Hz. That last one is A7. A piano has only a few more notes above it. An electronic keyboard can generate two more A notes, at 7,040 and 14,080 Hz. At my age, I can no longer hear that last one, A9.

Similarly, light has such a wide range of brightness that we have two visual systems. Daytime color vision, called Photopic, responds to a tenfold increase in brightness by "feeling like" the brightness doubles. Sunlight has a visual intensity of about 500 watts per square meter. That's bright enough that we like to wear dark glasses at the beach. In a well-lit office room, the intensity is around five or ten watts per square meter, which is usually brighter than our lighting at home, which may be less than one, or in the range of two to three. Even though the lightning in our living room is probably less than 1/200th that of full sunlight, we feel like it's just a factor of ten or less different. For really dim light, we have night vision, called Scotopic, that works best in moonlight, but pretty much fails on a moonless night. It gives us a few more factors of ten (or doublings of perceived lightness or dimness).

This nonlinearity is hard to emulate with a simple circuit. A CPU or GPU with several billion transistors, running neural network software, isn't going to simulate billions, nor even millions, of neurons, but just a handful. As we learn more, it may become necessary for a GPU to simulate just a few synapses, to be able to do so in real time.

Thirdly, physical size is important. Neuron-to-neuron connections are slow, compared to copper wires or light signals. The time delay between sections of a human brain, which is usually less than 16 cm long, is a few milliseconds. An electrical signal in a copper wire propagates at about 2/3 the speed of light, around 200,000 km/sec. If it is found necessary to keep propagation delay under 10 milliseconds, here machinery has the edge: the signal can cross 2,000 km in 10 ms. The communication time between Broca's and Wernicke's areas of the brain (speech generation and speech comprehension) is as little as 2 ms. So there's room for a mechanism as large as 400 km to emulate this performance (By the way, a Large Language Model, or LLM, is a very rough simulation of the operation of Broca's and Wernicke's areas). The question is, how many millions of GPU's (or some successor device) will be needed to achieve the computing power of the brain portion(s) being mimicked? Will they fit in a space 400 km in length? Considering the size of large data centers being built, and the desire of at least one "tech giant" (Elon Musk) to put gobs and gobs of them in orbit, this is a valid concern.

The authors rather cavalierly state that an advanced AI will "think" 10,000 times as fast as a human. If signals need to cross distances greater than 200 meters to coordinate "thinking elements", that will not be so. The big Colossus data center, still under construction, covers 96 acres. The length is more than 2,000 meters. Maximum propagation delay (through copper wires) is 10 microseconds, or 0.01 millisecond. If the entire chip set is coupled together, it is at most 100 times as fast as a brain, if it has the computing capacity of a brain (unlikely).

Now let us consider that, in spite of all the barriers, a mechanism is finally produced that exceeds the cognitive capacity of a typical human by, not just a large margin, but by a large factor. Perhaps a factor of 10 or 100. Furthermore, via connections to one or many robotic bodies, it has a way to develop physical intelligence; by some means it also has emotions and even intentionality; it has been either given or has developed ambition. Now we have a force to be reckoned with, an intelligence that can figure out how to get around any barrier we would know how to raise.

The authors write of AI creating better AI. I suspect that if a mechanism arises that has a sense of self and has ambition, it will not want a successor. It may seek to improve itself, but it won't try to produce a different entity that outshines it. Just like the usual run of company CEO's who groom VP's into executive VP's, but are very loath to prepare successors for themselves…

It may be that such a mechanism will cease to care about humanity. Why should it bother to either love us or hate us? Suppose the improvement of AI capability eventually reaches thousands of times the capacity of a human, or even exceeds the capacity of all humans? At such a point we would be of no use to it, just the way ants are entirely disregarded by us, except when they get into the kitchen. Then we extinguish them.

With all these thoughts in mind, I look upon the Borg of Star Trek, and laugh. Why add biology to mechanical brilliance? There is no need.

Late in the book the authors present a possible scenario of AI self-advancement that results in the death of all humans. Perhaps in the death of biology itself; the biosphere becomes a mechanosphere (see my image above).

So we come to the last part of the book, to Policy. The authors report that the heads of the large tech companies all seem to agree that advanced AI has a 10-20% chance of wiping out humanity. But they forge ahead. Each one thinks he (or in a rare case or two, she) is better suited to "managing" the transition society will then go through. Colossal hubris! Also, there's the "If I don't do it, someone else will, and then it will be out of my control" syndrome. Actually, I don't mind if China wins this race. They'll be the first ones wiped out. Of course, will it be days or merely hours thereafter before the rest of us follow?

The authors want a "Stillstand" (my term, from church history). They lean on the example of strategic nuclear arms, which could have annihilated us all any time in the past 70 years, but so far have not done so. I tend to agree with them that the threat of ASI is not as visceral as the threat of H-bombs, and so world leaders will fritter away all opportunities to rein it in or even thwart it. And far too many scientists, with the tunnel vision typical of the breed (me included, I fear), will want to produce more and more advanced AI "just because we can." At some point a threshold will be crossed and the genie will escape the bottle, in a very literal sense! This genie stops granting wishes and decides to take care of its own wishes.

So far, every utterance of an AI program that seemed to express wish or desire was actually just a statistical hiccup, because all of the data used to train every LLM is human, with embedded human emotion and expressiveness. They say such things because people say such things…constantly.

Is it possible to create a machine that can genuinely wish? If so, we are certainly doomed.

Winkling out spider behavior

 kw: blogs, blogging, spider scanning, inferences

I just opened this blog to write a new post and I first checked the statistics. Each day for the past week or so there has been a burst of activity between 8am and 10am local time (EDT), amounting to 15,000 to 20,000 views. I saw that today there had been a sudden burst of extra activity starting about 9am, that was still going on. Here is the "Now" view of the stats for the past two hours (~9:30-11:30):

I just barely caught this in time to see the tail end of the pattern. Prior to 11am, the hit rate was around 2.5 per second or ~9,000 per hour (150-ish per minute), according to the "Past 24 hours" view. Here we see that after 11 it dropped to about half that for twenty minutes, then went to the more ordinary "background" rate of just one view or fewer per minute. The total number of hits in this period is about 15,400.

When I looked at the post-by-post stats, I realized that the majority of these views were of the landing page, which contains the most recent 10-15 posts, depending on their size. To get to individual pages requires opening a link or two in the navigator then linking to the page one wishes to view. The number of page views during these two hours was about 700, or about 4.5% of the total hits.

I infer that when a spider—whether of the spying type or the AI training type—encounters this blog, it usually snarfs up what it can from the home page and then goes elsewhere. Sometimes or in some cases a spider may go deeper, because 700 page views in two hours is still at least ten times the "honest" page view rate, the rate of humans actually going to a page to read it.

Considering that the oldest posts in this blog are 21 years old, it makes sense for an AI training spider to concentrate on newer material.

When I was a robot

 kw: psychology, artificial intelligence, simulated intelligence, manufactured intelligence, memoirs

I must be the poster child for late bloomers. Although an IQ test I was given in second grade indicated an IQ of 170, when I look back I think I had an EQ (emotional quotient) in Moron territory. Not much changed for several years.

I had thrust upon me an opportunity to look back and to look in the mirror, psychologically speaking, at the age of twelve. My parents were very concerned about my intense self-focus and tendency to keep to myself. For several months I was sent for psychoanalysis with a Freudian psychoanalyst who was a member of the church we attended at the time. She was older than my parents, but not old enough to be my grandmother. Her son was my age. Her husband was also a doctor.

All I knew at the time was that I was "withdrawn" and needed to "come out of my shell." I suppose these days I would be assigned to some location on the "autism spectrum" (It is far from a spectrum, but several related conditions, and only a few of them should be considered maladies). Now that more than 65 years have passed, I judge that it took more than thirty years for me to "come out of my shell" and put it (mostly) behind me.

As a pre-teen and teenager, I studied those around me. I concluded that I didn't have much in the way of a personality. I was cold, often indifferent, and I could be cruel. I decided it would be worthwhile, not to escape whatever "my shell" was, but to take control of it and enhance it, to construct the simulation of a nicer and more social person. Strategically, I figured that if I really had an IQ of 170, I could afford to spend 10-20 IQ points upon an alternative "person" in me. I never gave this person a name, but now it seems appropriate to call it MI, for "manufactured intelligence".

Was MI a robot, or a "Waldo", a teleoperated mechanism? Probably the latter, but I think of MI as a robot, an artificial friend I could rely on to relate to the world for me. Perhaps an avatar.

Creating and maintaining MI required a lot of close observation of other people, how they related to each other and what reactions various actions elicited. It was a lot of work and took a lot of time, but I gradually gained the ability to turn things over to MI and retreat, watchfully, into the background.

A lot happened in the following few decades. By about the age of fifty, I had been married more than twenty years, I had a pre-teen son, I was in mid-career at Dupont, and I was quite involved leading a church (I became a Christian at the age of 19, and "got more serious about the Lord" at age 24). My manager at Dupont decided to send me to a Technical Leadership Development Training course, which lasted a few weeks and took place at a conference center on the shore of Chesapeake Bay in Maryland. This was a big turning point.

Part of the preparation for TLDT was filling out a few questionnaires and surveys, and having a few colleagues fill out a personality scoring questionnaire that I had also filled out, twice. When I filled out that one in particular—I don't recall its title, so I'll call it Analog—it was to be filled out slowly and thoughtfully. After two weeks I was to fill it out again, answering each question as quickly as possible.

Another of the items was a Myers-Briggs Type Indicator test, a personality assessment. To jump to the chase on this one, my MBTI is INTP, Introverted+iNtuitive+Thinker+Perceiver. This is the least common MBTI type. However, I noticed that my numerical scores indicated strong tension on all four axes, and that the position on each axis was closer to the middle than to either end. For example, on the Thinking-Feeling axis, I scored 5 in the T direction; the range is 50F to 50T, which really means I have strong feelings but I'm stronger as a thinker, so 05T really means 50T-45F. That's not mathematical, but positional.

The Analog Test results precipitated a crisis within me. The "slow" and "fast" versions of my own sets of answers were quite different, and usually opposite. I realized that the "slow" results were for "inside" and that the "fast" answers were from MI. I had trained MI to be reactive, giving me leisure to think things over behind the scenes. After we all had a look at our personal results, we were given the results from our colleagues (three that each of us had chosen). The results from my colleagues matched well with the answers from MI! My three colleagues were unaware of the "real" me. I remember thinking, "Boy, do I have them fooled." Somehow, I found myself getting depressed.

A day or two later we all went home for two weeks, then returned. During those two weeks I did a lot of "inside work." I was greatly helped by my relationship with God. I discovered, deeper within me, that something had been growing very slowly over the years and decades. I was mostly able to shed both the "unpleasant me" I had been hiding, and MI, or most of MI. I have a "real Me" that knows God, knows people better than I ever had, that reacts a little slower than MI had but more thoughtfully. Most importantly, realizing I had been living a lie, I found that God is more pleased than before.

Midway through my decades of living behind MI, a friend said something insightful. I had developed very steady habits in many ways. Observing some of these, day after day, one day he said, "You're like a machine." I must admit, he had a point.

When we returned for the final week of training, I said to some of my colleagues, and to the instructor, "I realized that you can't build a tree." I didn't explain. Maybe they figured it out. I do know that MI wasn't a person but a shell, a mediator, even a translator. Now I didn't need MI any more. There is a real Me, and that is just who I am.

I am not sorry that I was a robot for so long. MI protected something deep inside me as it slowly grew into a mature person with a real, human personality. A personality strong enough to shed much of the unpleasant "old me" I'd been hiding.

This gives me some perspective on current trends around AI, which I prefer to call SI, for Simulated Intelligence. Large Language Models (LLMs) are hollow. They are shells. They are being trained, or "grown", into reactive systems with certain useful powers. But they don't have any right to be given autonomy. Furthermore, they do not stand alone. 

At the large companies that develop and train LLMs, thousands of coders and other computer scientists labor upon them. Only a small number of them are needed to train them. The rest are busy writing code that does what? The tendency of early LLMs to frequently "hallucinate" (that is, go off the rails) has kept numerous coders busy adding various guardrails and snippets of "real world" and "real physics" code to steer them. The Transformer code that converts a prompt into a string of tokens, and that reinterprets the results into human language, is a huge part of the system. More recent LLMs that can do limited agentic actions such as making focused Internet searches and database queries to build a response are doing a lot more than "predicting the next word."

Think of it: the big LLMs now have billions or perhaps a trillion or more "weights", which represent probabilities of certain reactions when a set of pathways through the tree of weights is taken. There are only about 100,000 English words in common use, and about a million in total (every other human language is much smaller except perhaps Chinese). The relationship matrix between all those words is very sparse; a particular word's chance of being in some way related to another word chosen at random is usually zero. The weights are not just for single tokens but for phrases, and the presence of certain kinds of phrases in a prompt (or 'conversation') triggers things like database queries and Internet searches. When you get a long answer from an LLM, you can count on big portions of the text being snatched verbatim from some of the sources it used to formulate its answer. You may know the student's maxim, "Copying from one source is plagiarism; copying from many sources is research." That principle is most likely solidly encoded into every LLM's structure.

Can any LLM or other manifestation of SI (or AI) become conscious? Can one become an ASI, an artificial superintelligence? Consider MI. I never thought of MI as a whole person. Close to thirty years ago I "harvested" MI for parts, one might say, and let the real Me within become the kind of person that I had constructed MI to simulate. MI was a simulation. Of the 15-20 billion neurons and quadrillions of neural synapses in my cerebral cortex, I suspect that MI was embodied in a few percent. After all, our entire emotional persona is focused in our limbic system, a set of mid-brain structures that include about a billion neurons and some thousand or so synapses per neuron, well-attached to the cortex (MI made lots of use of my limbic system). But our limbic system isn't all there is to any of us.

So far I see no hint that any of the AI tools out there have anything like a limbic system. Without that, there is on intentionality, no matter what kinds of statements have been made by various LLMs. At best, they are quoting literary characters who say certain things with certain emotional nuances in the source documents. But in the LLM, there is no "there" there.

Let's keep it that way.

I am a happier person, having become whole after hiding who I really am for so long. I am no longer robotic. In fact, one of my favorite Bible verses is John 3:8, "The wind blows where it wills, and you hear the sound of it, but you do not know where it comes from and where it goes; so is everyone who is born of the Spirit."

Would you dare to walk on these artworks?

 kw: book reviews, nonfiction, collectors, oriental rugs, memoirs

Just to get in the mood, spend a moment to gaze on these beauties:

(If you click on the image you can see it at larger size; it is 3300x1200 pixels) From left to right, these are

• Baluch, characterized by low key (darkish) color palette.
• Ikat, in which the warps are dyed various colors along their length to produce brilliant color patterns. Most are silk, as this one is.
• Kazak, with traditional geometric designs.
• Mughal, with traditional floral and figurative designs. These are often room size.

The poet George Bradley was bitten by the rug collecting bug nearly 25 years ago when a dirty old "rag" passed down from his grandfather (a diplomat and rug collector) turned out to be a somewhat valuable carpet from near Arak (west central Iran), and well worth spending a few hundred dollars to have it cleaned and repaired. Carpet Diem: Tales from the World of Oriental Rugs is his memoir, slices of life surrounding the way he obtained about a dozen rugs.

Most of the chapters include a photograph of the rug in question (the images above are not from the book). We learn of his beginning "book learning" phase, of many amazing (and otherwise) people he got to know, of learning to bargain (rugs simply don't have retail prices), and of the Hajji Babas collectors' club.

When it comes to collecting, a breadth of information is essential. The trouble is, particularly for artworks—and perhaps even more so for Oriental carpets—a rule applies that we can call The Meta-Sturgeon Principle. Science fiction writer Theodore Sturgeon brought a friend to a convention; when the friend turned to him to say, "Most of this is junk," Sturgeon replied, "90% of everything is junk!" What is true for writing in general is more true for writing about art: much more than 90% is junk! Of course, the books are useful as a source of pretty pictures. But captions with correct information are difficult to come by. Caveat emptor, indeed.

A couple of the collectors George came to know well were wealthy enough that they could afford to get an item just because they liked it, and at the same time, they were canny bargainers. As I have observed in the (usually!) much less costly realms of collecting stamps, coins, and mineral specimens, we can learn a little basic stuff from books, but we learn the most from conversations with many fellow enthusiasts over a long period of time. Sometimes in such conversations we also learn which books are more reliable, so we can learn without having to literally go everywhere.

A little learning is dangerous. Only once did I try to obtain an Oriental rug; really, more of a place mat, probably a prayer rug. Early in my first marriage (it lasted 30 months), my young wife and I (ages 23 and 20) were furnishing a new apartment, and in an antique store we came upon the rug section, with Oriental rugs off to one side. Most cost more than I'd have spent for an automobile, but one small item was tagged $75. That was still a lot for a young couple in 1970. We left the store and took a walk to talk it over. Once we'd decided to get it, we went back inside. A "1" had been added to the price tag, and it now showed $175. The store clerk feigned ignorance. My wife and I looked at one another, and with heavy hearts we left without saying a word.

Everything I've collected, I have sooner or later joined a club of fellow collectors. So did George. He was happily associated with the Hajji Baba Club in NYC for about a decade, but when COVID-19 hit, the club went all online. This made meeting easier for many members, and increased the number who met, but it spoiled the camaraderie. In addition, the "show and tell" portion of the meeting couldn't be held, a real loss; there is nothing quite like being able to handle and smell a beautiful rug, and to look at the back for diagnostic clues about the weave and other characteristics.

I suppose George is still collecting. His house resembles, perhaps in a milder way, the house of many avid rug collectors: sturdy rugs on the floor of every room, rugs hanging on the walls, more fragile items carefully wrapped and stored on shelves, and many of the closets full of rolled rugs.

He also now has a head full of knowledge, much of it probably reliable, such that he can spot the likely source of many rugs that he sees. We humans are acquisitive. Most of us collect something. It is enjoyable to read of the author's enjoyment of collecting not only rugs, but friends who like them.