<div dir="auto">Hi Russell and everyone,<div dir="auto"><br></div><div dir="auto">Here is a recording of my presentation and some follow up Q&A for these slides:</div><div dir="auto"><br></div><div dir="auto"><a href="https://youtu.be/KUPTtraCK-g">https://youtu.be/KUPTtraCK-g</a></div><div dir="auto"><br></div><div dir="auto">Jason </div></div><br><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Fri, Sep 18, 2026, 9:20 AM Jason Resch <<a href="mailto:jasonresch@gmail.com">jasonresch@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="auto"><div>Hi Russell,</div><div dir="auto"><br></div><div dir="auto">I appreciate the feedback. I have a lot of important context in the slide notes, and I deal with the population expectation divergence there. I just made a recording of myself giving this presentation yesterday, so when I have that I can share it.</div><div dir="auto"><br></div><div dir="auto">In the meantime I will share my slide notes (which can be seen more easily if you access the slides from a desktop or laptop computer) for the slide on human population not reaching infinity this year, as well as the notes for the slide immediately before it:</div><div dir="auto"><br></div><div dir="auto">Slide with models pointing to 2027:</div><div dir="auto"><br></div><div dir="auto">Researchers who have studied these trends have found that extremely simple hyperbolic models account for over 99% of demographic, societal, and economic macrodynamics across millennia of human history.</div><div dir="auto"><br></div><div dir="auto">Here we’ll look at two examples of simple models which accurately account for human population trends as well as the pace of historic change. </div><div dir="auto"><br></div><div dir="auto">(animate)</div><div dir="auto">The first model was proposed by Heinz von Foerster in 1960, using only data about human population growth. Which gave this simple formula here. Note it is a hyperbolic function, and its accuracy in terms of the coefficient of determination is 99.6%</div><div dir="auto"><br></div><div dir="auto">This degree of fit is astonishing, implying that things we consider as pivotal in shaping history, like the fall of Rome, the black death, the discovery of New World, the invention of agriculture and the printing press – are unnoticed blips against the backdrop of these much greater, ever-present macro trends.</div><div dir="auto"><br></div><div dir="auto">(animate)</div><div dir="auto">The second model is based on a list of major historic events compiled by Alexander Panov, it yielded an even simpler model, shown here, which is even more accurate, with a coefficient of determination of 99.91%!</div><div dir="auto"><br></div><div dir="auto">What is fascinating about this, is that someone in ancient times or the middle ages, didn’t need to know about Moore’s law to have performed this same population or historic event extrapolation. Merely using the population or historical data available in their time, they could have made this same prediction: that something interesting would happen early in the 21st century.</div><div dir="auto"><br></div><div dir="auto">What is notable is that both of these models were based on entirely different data sets composed by, and reported by different people in different times.</div><div dir="auto"><br></div><div dir="auto">Another thing, which you may have already noticed, which is somewhat alarming, is how both of these have a nearly identical singularity point (animate) t=2026.87 for Foerster and t=2027 for Panov. (animate) This is where a “divide by zero” happens in the equation.. What could this mean for us?</div><div dir="auto"><br></div><div dir="auto"><br></div><div dir="auto">Slide on human population growth rate:</div><div dir="auto"><br></div><div dir="auto">But we also note that the rate of world population growth peaked in 1963, just a few years after Foerster’s 1960 paper was published. Does that invalidate his prediction?</div><div dir="auto"><br></div><div dir="auto">Despite the slowdown in population, the pace of technological development and the pace of history has not slowed. How could this be?</div><div dir="auto"><br></div><div dir="auto">What I think can explain it, is that at this time, humans began to offload more and more of their decisions and processing to computers, in effect, making human thinking faster. The world's first computer, the ENIAC, in its 10 years of operation, performed more calculations in those ten years than had all humans that came before it. And with the rise of personal computers, office workers (which include engineers, technologists, and inventors) became far more productive.</div><div dir="auto"><br></div><div dir="auto">So it's not just the population of human inventors that matters, but also their productivity. Today, one human using AI can have the productivity of 10 or 100 inventors.</div><div dir="auto"><br></div><div dir="auto">We may soon see the rise of AI agent inventors shoot unbounded upward, unconstrained by normal limits on human population growth.</div><div dir="auto"><br></div><div dir="auto">Perhaps it will be Seth's technology that triggers this by cloning human innovators.</div><div dir="auto">Then we will see an unlimited number of personal AI agents replicating human engineers, technologists, and inventors. We will then have reached the zenith of ingenuity, part human – part machine.</div><div dir="auto"><br></div><div dir="auto">---------------</div><div dir="auto"><br></div><div dir="auto">(New email commentary from me to the extropy list)</div><div dir="auto"><br></div><div dir="auto">I think we're starting to see this now with agent swarms of ever increasing size. We still won't hit infinity since there are physical limits, but I think agent swarms mark a plausible point of identifying the recursive self improvement necessary to qualify as an ultraintelligent machine, and where human ingenuity departs from the control loop -- a new paradigm between the past few million years of the homo genus will have begun.</div><div dir="auto"><br></div><div dir="auto">Jason </div><div dir="auto"><br></div><div dir="auto"><br></div><div dir="auto"><br><div class="gmail_quote" dir="auto"><div dir="ltr" class="gmail_attr">On Fri, Sep 18, 2026, 5:07 AM Russell Standish <<a href="mailto:lists@hpcoders.com.au" target="_blank" rel="noreferrer">lists@hpcoders.com.au</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">On Wed, Sep 09, 2026 at 10:25:01AM -0400, Jason Resch via extropy-chat wrote:<br>
> <br>
> We appear to remain on track to reach the singularity between most November of<br>
> 2026 to the end of December 2026:<br>
> <br>
> <a href="https://docs.google.com/presentation/d/" rel="noreferrer noreferrer noreferrer" target="_blank">https://docs.google.com/presentation/d/</a><br>
> 1bITq1_XCNY4sEmZhbkcRUr77PtWawP3rpLxNYZxDTBY/edit?usp=drivesdk<br>
<br>
Some things are wrong with this presentation - I can't believe we will<br>
hit infinite population next year (or in any year, for that<br>
matter). The hyperbolic curve fit seems definitely ad absurdum. It<br>
also contradicts a later slide showing that we have passed the<br>
inflection point in population growth, so definitely not hyperbolic then.<br>
<br>
<br>
> <br>
> As was predicted 60 years ago, and again about 20 years ago, using two entirely<br>
> distinct data sets. See the slide notes for each slide as they give important<br>
> context for what each slide shows.<br>
> <br>
> Jason<br>
> <br>
> <br>
> <br>
> <br>
> AI Has Solved One of Math’s $1 Million Millennium Prize Problems<br>
> <br>
> John K Clark See what's on my list at Extropolis<br>
> <br>
> 4y9<br>
> _______________________________________________<br>
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> <br>
<br>
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<br>
<br>
-- <br>
<br>
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