[ExI] The AI Wake-Up Call Everyone Needs Right Now!

[Jason Resch]

On Thu, Feb 12, 2026, 5:57 PM Adrian Tymes via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> > Gemini 3 -
>
> > The "February 5th" Shift: Shumer points to the recent release of models
> like GPT-5.3 Codex and Anthropic’s Opus 4.6 as a turning point. He claims
> these models no longer just assist with work but can execute complex,
> multi-day technical projects autonomously, demonstrating "judgment" and
> "taste" that were previously thought to be uniquely human.
>
> Which has literally been said of prior releases.
>

The lastest AI from anthropic was used to program a 100,000-lines-of+code C
compiler that can compile the Linux kernel on 3 platforms, without one line
of code being written by a human. This is a paradigm shift in capability.


> Including running multi-day technical projects autonomously (to take a
> recent but running-since-before-Feb-5 example, Moltbook; I am
> personally aware of capability that could be described that way going
> back to at least 2023), and demonstrations of taste and judgment that
> were previously thought to be uniquely human.
>
> > Recursive Self-Improvement: A critical development is that AI is now
> instrumental in building its own next generation. By automating the coding
> and debugging of its own training runs, the "feedback loop" of intelligence
> is accelerating at an exponential rate.
>
> The thing about accelerating at an exponential rate is, at any given
> time the acceleration is faster than it has ever been before...and
> it's still not "the" moment, because future acceleration is even
> faster.
>

I learned recently that technological growth doesn't follow an exponential
curve, but rather a hyperbolic one.

For an exponential curve, the slope doubles for each fixed unit of time.
For a hyperbolic curve, the time between each doubling halves. One shoots
towards infinity in finite time, the other takes infinite time to reach
infinity.

Using the observed rates of historic change (even using data from the many
decades ago), showed we would reach a singularity point in 2027.

What will the trigger be? AI improving its own software? Robots building
robots? Hard to say, but the 2027 timing seems accurate.


> > The End of Knowledge Work as We Know It: Shumer warns that white-collar
> sectors—law, finance, medicine, and engineering—are at the precipice of
> massive disruption. He cites Anthropic CEO Dario Amodei’s prediction that
> 50% of entry-level white-collar jobs could vanish within 1 to 5 years.
>
> People will find other things to do, not remain unemployed forever.
> See the history of every such disruption ever.
>

Consider the history of horses after the automobile.

If intelligence and ingenuity is what allowed us to adapt in the last, how
do we adapt when artificial intelligence surpasses humans, and can work
cheaper, more reliably, with fewer errors, and complaints, etc.?

Humans may still trade their time with other humans human and track that
using human currencies, but humans will represent an ever diminishing
fraction of the productive economy.

If we're lucky we can look forward to a future like that in the Culture
Series, where humans were free to pursue hobbies and interests to their
content, but no one needs to work to survive.


> > The "Capability Gap": There is a dangerous divide between those using
> free/outdated AI models and those using the latest paid versions. Those who
> dismiss AI usually do so based on 2024-era experiences, failing to realize
> how much the technology has evolved in just the last few months.
>
> See also the gap between those using even free/outdated AI models, and
> those who've yet to seriously start using AI.
>
> > Immediate Advice: He urges readers to "be early" by integrating the most
> powerful models into their daily workflows now. His stance is that the
> window to gain a competitive advantage is closing, and the only path
> forward is radical adaptation and financial caution.
>
> It is true that, even today, AI can give a boost to many careers,
> particularly white collar/knowledge work.  For blue collar jobs,
> useful tools are emerging: they might be better off learning and using
> said tools, rather than "learning AI" in and of itself.
>
> TL;DR: can the hype, cancel the alarm.  Do study up on AI or
> AI-powered tools, depending on what's more applicable to your career,
> like how learning how to use the Web and email became new priorities
> about 30 years ago.
>

The summary reads like hype, but the full article backs everything up with
real world examples and data (which the summary doesn't include). Given
these data, it's not hype but justified alarm.

Jason
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