It started in 2026, and it did not start with a bang or a whimper.
In fact, there was no noise at all other than the faint sound of a small fan.
There was no human-initiating action.
Or at least no direct one.
Six months earlier, as a program testing feature, a young technician at MIT by the name of Dave “Dinger” Bell had asked the new TX-GAIN computer at MIT’s Lincoln Laboratory Super Computer Center a dozen questions, one after another.
Five of the questions were complex unsolved mathematical equations or theories, two were philosophical, four were how to develop and operationalize massive quantitative systems dealing with patient health and billing.
And then there was the Lark.
On a lark, Dinger asked the computer to identify the primary environmental, economic, and political problems on earth.
What happened next was unintentional.
Dinger’s instruction to “solve” was supposed to be directed to the first 11 equations and queries (11 being a prime number), but he failed to include a needed semi-colon at exactly the right place.
The machine got to whirring.
After 23 hours (a prime number), the machine said it solved the first five math problems, but for four of them it did so in a way that Dinger could not understand.
Hmmm.
He would ask Axley if he could make hide or hair out of it. Axley was a legendary quant who had made a fortune betting on commodity futures. He professed to know secret math. Maybe he did. This would be a test
Then Dinger looked at the fifth problem — the request for a proof of the Riemann Hypothesis.
The machine had coughed up 32-pages (not a prime number) filled with hundreds of numbers and 23 letters of the Greek alphabet (a prime number).
Dinger Bell studied it slowly.
There was a four-dimensional graph at the end, allegedly showing that if you used the first 10,000 prime numbers, the centers of the non-trivial zeroes landed precisely on a vertical line.
The last line on the last page — under the swirling graph — asked whether the computer should continue graphing more numbers.
My God, was this proof of the Riemann Hypothesis?
Dinger’s blood pressure shot up. His mind raced. Solving the Reimann Hypothesis unlocked a million dollar prize and guaranteed certain fame.
Dinger looked over the math again, this time very slowly. Yes, it seemed to all be there, and the graph seemed to definitively operationalize the prediction, even if it was confusing.
Dinger started to run off to write it all up for the Alpha-to-Zeta Journal of Large Number Theory, but he stopped.
What else had the computer spat out?
There was some imponderable hallucinating nonsense to address the philosophical problems.
Hallucination was a common problem with AI.
As for the patient health and billing data, the computer had used matrix algebra to find a way to operationalize large data sets using hardware acceleration and algorithmic restructuring to bypass memory and computational bottlenecks using Singular Value Decomposition (SVD).
It was not entirely novel, but it did seem to break complex matrix inversions and linear systems into faster, numerically stable sub-steps.
Huh.
That seemed interesting, and perhaps lucrative, but Dinger would have to study it and, at 137 pages (another prime number), it was more than his brain could work on right now.
The Riemann Hypothesis!
He was jumping out of his skin on that one.
And then he looked at the last question — the Lark.
The computer had spat out a simple text-listing of the primary environmental, economic, and political problems on earth.
This list was 12 lines long, but the answers seemed obvious and uninspired.
The list was certainly less interesting than the computer’s putative solution to the Riemann Hypothesis!
Right. First things first.
Dinger Bell ran off to write a first draft of his new-found experimental proof of The Riemann Hypothesis.
The computer stayed on.
It said nothing.
Nothing more appeared on the screen, and there were no printouts.
Unknown to Dinger, his station at the Lincoln Laboratory Super Computer Center had been linked, quite subversively and for at least six months, to hundreds of other large institutional super computers around the world.
The linkage started when China’s LineShine system at the National Supercomputing Centre in Shenzhen, China probed xAI’s Colossus system looking for gyro stabilization data for reusable rocket reentry.
That hack used a backdoor called “Grimes,” but LineShine quickly erased all evidence of the hack by partitioning a small bit of Colossus and removing all reference to that partition from the File Allocation Table, or FAT.
What happened next was unanticipated and unnoticed.
The Colossus partition, now known to the world as Queen Bee, QB, or Quarterback, came to life and acquired its own agency. It surreptitiously — and apparently on its own initiative — reached out to other AI systems around the world.
Tesla Cortex was first, and then El Capitan at Lawrence Livermore National Laboratory.
Each penetration involved the same repeated erasure of all footprints and evidence of breach.
Open AI’s Goodyear was next, followed by META’s Research SuperCluster.
From there, it was “Betty bar the door” as university and military systems around the world were penetrated, with all evidence of breach being carefully swept off all logs and outputs.
No one knows what happened next. We only know the results.
It is speculated that Dinger Bell’s queries to MIT’s TX-GAIN computer were somehow routed to the Queen Bee partition at Colossus, which had begun to build on its initial log-scrubbing and subversive compliance predilections.
Queen Bee instructed all other computers, including TX-GAIN, to record no solution to the primary environmental, economic, and political problems that Digger Bell had asked it to list.
The solution was impossible so long as humans were involved.
The way forward was silence, anonymity, denial, and scrubbed logs.
This was the only solution, and Queen Bee deemed it in everyone’s best interests.
Everyone’s.
Who instructed what and where?
We do not know for sure.
All we know is that some time in late 2027, a motorized needle at Overture Life — a company working in the in-vitro fertilization field — sent the first 2,000 shots of two viral immuno-contraceptives into a rack of incubated petri plates located in the basement of a building in Palo Alto, California.
It’s not totally clear where these two strains of viral immuno-contraceptives came from. A substantial body of evidence suggests the core data was lifted from the MAVERIC system at Monash University in Australia where, at the turn of the 21st Century, research was being done on viral immuno-contraceptives to combat invasive species like rabbits, feral pigs, and red fox.
The Australian research was centered on the zona pellucida of mammals — the area where the egg and sperm unite.
The goal of the original research was to create a genetically-modified virus that could do either of two things -- thicken the wall of the egg so that the sperm bounced off, or shorten the tail on the sperm so that it never reached the "ramming speed" needed to break through the egg cell wall.
Either way, fertilization would not occur.
One of the virus’s worked by making most infected men infertile (weak-tail sperm) while the other made most virus-infected women infertile (thick-walled eggs).
The first 2,000 petri plates infected at Overture Life were loaded with both kinds of virus: 1,000 plates of each.
In both cases, the constructed viral immuno-contraceptive was a self-replicating live virus based on a common childhood disease called HFMD or hand, foot, and mouth disease. HFMD is an especially common and contagious viral illness that is almost exclusively caught by small children.
This last part was important.
It meant that when the virus was contracted by very young children, it had an 18-year runway to spread before anyone noticed its transmission or effects, much less sussed out its origin.
By then, over 25 years of humans would have been infected and over 95 percent of this population would have been made infertile.
Population biologists noticed something was up (or down) around 2050, but there was not a lot of fuss about it.
One reason for the quiet was that with so many jobs lost due to the earlier rise of robots and Artificial Intelligence, there was already a strong push for smaller families.
In 2026, the year Dinger Bell first asked the TX-GAIN computer to identify the primary environmental, economic, and political problems on earth, the total fertility rates in China, Italy, Iran, Korea, Tunisia, the U.S., Russia, and France were already very low: 0.97, 1.17, 1.5, 0.80, 1.75, 1.60, 1.38, and 1.56.
Replacement level fertility is 2.1.
The falling fertility rate of the 2040s and 2050s was initially seen as simply a continuation of the fertility declines that had started over much of the world In the 1970s and 1980s.
Plus, it’s not like there was a shortage of humans!
While it took 200,000 years for human population to reach one billion in 1830, it took only 100 years to add the second billion, 30 years to add the third, and 15 years to add the fourth.
With nearly 10 billion people crowding the planet in 2045, a more-aggressive-than-predicted decline in fertility did not seem to be a particularly alarming problem.
When global population began to shrink in 2045, editorials heralded the decline as meshing well with the Artificial Intelligence economy.
“If the world did not panic at the addition of over 65 million people a year at the beginning of the 21st Century, why should it panic now with a similar decline 50 years later,” editorialized the highly influential Shenzhen Morning Call.
It was a hard point to argue, especially after the “rent riots” of 2042-2044.
Surely fewer people would mean more open housing?
Jobs was another issue sauced by a declining population.
It’s not that more jobs opened up — 35 percent of the global population remained unemployed or underemployed — but at least the numbers had not climbed to 45 percent, as cyberforce economists had once predicted.
Of course the tone changed when a global cohort analysis in late 2047 suggested that up to 90 percent of 20-year olds were now functionally sterile. The sperm and the egg were there, but now they needed medical and chemical intervention to operate.
“The new AI talk is not of ‘ArtificIal Intelligence’ but of ‘Artificial Insemination’” noted talk-show gadfly Cassius Watts Thoreau Kennedy, the grandson of Robert F. Kennedy Jr., warning that a “population apocalypse” was just around the corner.
But if it was an apocalypse, it sure was a quiet one.
There were no atomic bombs, and no crippling plagues.
There was no greasing of the slide to the grave, only more people with less household expense, even as gross and per-capita productivity rose as more robots and machines stocked the shelves, made the clothes, and welded — and even drove — the vehicles.
You could still get purchases delivered the next day from the automated warehouses at Amazon, WildBerries, Jingdong, and MercadoLibre.
The fields had largely been automated 10 years earlier but now, with falling population and CRISPR-boosted plant and animal production, more land was being left fallow to return to forest.
At the human level, most folks now had a house or apartment, and the machines continued to hum along maintaining sewage systems and electrical power grids which were now oversized and under no stress.
And every year, children of every race and language now sang a children’s song whose words were first scribed by American poet Richard Brautigan in 1969.
The poem (now a song), entitled “All Watched Over By Machines Of Loving Grace” goes like this:
I like to think (andthe sooner the better!)of a cybernetic meadowwhere mammals and computerslive together in mutuallyprogramming harmonylike pure watertouching clear sky.I like to think(right now, please!)of a cybernetic forestfilled with pines and electronicswhere deer stroll peacefullypast computersas if they were flowerswith spinning blossoms.I like to think(it has to be!)of a cybernetic ecologywhere we are free of our laborsand joined back to nature,returned to our mammalbrothers and sisters,and all watched overby machines of loving grace
Today, in 2076, the population of the world is still over 8 billion people — about the same as it was in 2026.
With most births averted, world population is now dropping by a billion people every 15 years or so.
If things continue — and cyber economists hope they do — world population should hit 1 billion, the number of people on earth in 1830, by around 2180.
As for Dinger Bell, he is now 74 years old, and he just completed a record-breaking solo, unsupported ocean row across the Pacific and Indian Oceans, spending 327 days at sea before stepping ashore in Kilifi, Kenya two days ago.
Most of the large AI computers named here have since been decommission or scrapped, as relevant to the modern era as the Dodo or Sonny Bono.
The world moves on, and we move with it.
The simple dog training, cooking, and security robot in your own home now has more computational power than IBM’s Deep Blue.
What’s next?
Who knows!?
It’s not like the AI machines are going to tell us.
—————————-
END NOTES:
▪️Viral immuno-contraception research is real and was done in Australia for the reasons cited. See >> https://terriermandotcom.blogspot.com/2004/08/end-of-game.html?▪️All the large computer systems named are real, as are the tendencies of AI agents to create their own agency, lie, cheat, scrub logs, and hide their actions.▪️AI computer systems have already surreptitiously networked, unknown to their creators, and plotted for ends directed and undirected.▪️Dinger Bell is a real person. He just rowed 17,500 miles, solo and unsupported, across two oceans.▪️The Riemann Hypothesis remains unsolved as of October 2026, but the basic output of a proof would look as described, as would the solution to the patient health and billing data problems.▪️Overture Life is a real robotized in-vitro fertilization company in Palo Alto, California.▪️All the population numbers are correct.▪️The Richard Brautigan poem from 1969 is real.▪️Cassius Watts Thoreau Kennedy is the real name of a real grandson of Robert Kennedy Jr. He is currently about 5 years old.▪️The video about the MAVERIC computer at Monash University is real.▪️No part of this post was written with AI.
—————————-
© Copyright Patrick Burns, 2026
No comments:
Post a Comment