Background:
Not only the largest natural gas power plant but the largest power plant, of any sort -- nuclear, coal, natural gas -- in the entire United States.
Wiki: list of largest US power plants.
SoftBank proposal:
AI prompt:
Alan Turing. Development of computers. Things don't happen in a vacuum (no pun intended). Things don't happen overnight. Specifically, 1937 was a pivotal year and not just with Turing. From 1843 (Ada) to 1931, Vannevar Bush, almost a 100 years -- not much happening in those 100 years. Then Tommy Flowers in 1935 -- valves / vacuum tubes. So you look back five to six years before that pivotal year. What was happening -- or better, perhaps -- what major geo-political-economic event happened five to six years earlier. In fact, it was about eight years but one gets the point: the market crash of 1929. I'm sure there are some observations / thoughts about those years ... 1929 to 1937 that brought us to that point. Thoughts?
Google Gemini:
Even without the wealth tax, I would prefer to live in Switzerland rather than in Norway.
The big problem is that the 1.1% wealth tax on net assets over $US 2 million is just part of the overall tax these two-million-dollar (US dollars) millionaires are paying.
Even worse, $US 1 million is no longer all that much wealth in the big scheme of things.
The big question is whether Norway has either a debt problem or a deficit problem:
Norway's wealth tax:
Norwegian wealth tax. Story reported in The Guardian. AI prompt and reply:
*************************
Wealth Tax
If the wealth tax is a detriment to the economy in a country like Norway, one can only imagine how bad the wealth tax would be to a state like California who is at risk of a major deficit in any given year.
My thesis: for the mom-and-pop retail investor, the tipping point for investing "within the fourth industrial revolution" was in 2021 - 2022 -- a year or so after then "end" of the Covid-19 anxiety even though technically the fourth industrial revolution was identified in 2015 - 2016.
ChatGPT:
Yeah—that intuition tracks. The conceptual “Fourth Industrial Revolution” (AI, automation, digital platforms) went mainstream around 2015–2016, but the retail-investor tipping point didn’t really hit until 2021–2022. Different clocks were ticking for institutions vs. everyday investors. A few reasons why your timing feels right:
⸻
Why 2016 ≠ the retail tipping point
2016 was narrative-level adoption.
That’s when AI became a serious boardroom topic (DeepMind/AlphaGo, early cloud AI services, etc.). But for mom-and-pop investors, the story was still abstract: “Cool tech, not sure how to play it.” Public-market exposure was limited to broad tech names and semis.
Retail tends to move when:
• products become visible in daily life, and
• returns become obvious in stock charts.
Neither was true yet in 2016.
⸻
Why 2021–2022 was the tipping point
1. COVID changed investor behavior, not just tech adoption
Lockdowns did three huge things at once:
• Time: people had more time to learn markets
• Access: Robinhood/zero-commission trading went mainstream
• Psychology: markets felt “democratized” (GameStop, AMC, crypto)
This created a brand-new retail cohort that:
• was younger,
• more speculative,
• and much more willing to chase narratives (AI, EVs, space, quantum, etc.).
AI benefited from that same narrative trading energy that fueled meme stocks.
⸻
2. The tech finally crossed from “infrastructure” to “products people could feel”
Before 2021, AI mostly lived behind the scenes:
• ad targeting
• search ranking
• fraud detection
• logistics optimization
After COVID:
• recommendation engines, automation, and bots were suddenly everywhere
• then ChatGPT (late 2022) made AI personally tangible
That’s when retail investors went from:
“AI is a thing companies use”
to
“Oh wow, this changes everything.”
That emotional shift matters a lot in retail flows.
⸻
3. NVIDIA as the retail “AI thermometer”
Retail investors don’t invest in systems—they invest in symbols.
NVIDIA became the symbol:
• clean story
• obvious revenue growth
• simple narrative: “AI runs on GPUs”
Once NVDA started ripping in 2023, it functioned like:
“Proof that AI isn’t just hype—this is how you get paid.”
That feedback loop (price → attention → more retail inflows → price) is classic retail tipping-point behavior.
⸻
4. Post-COVID narrative hunger
After:
• meme stocks cooled,
• crypto crashed,
• EV hype got messy,
retail investors were hungry for a new mega-theme that felt:
• transformative
• understandable
• not already “over” (psychologically)
AI checked all three boxes.
⸻
Why institutions moved earlier than retail (and always will)
Big money started positioning in:
• cloud,
• data centers,
• semis,
• ML tooling
years earlier—quietly. Retail tends to arrive when:
• revenue curves bend upward, and
• products enter culture.
That’s not stupidity—it’s just different incentives:
• institutions invest in capability
• retail invests in visibility
All four together created what feels like an overnight AI boom—but it was actually a slow fuse with a loud detonation.
⸻
Big-picture take (your instinct is strong here)
What you’re really noticing isn’t just “AI became a thing” — it’s:
When the story became tradable for regular people.
That’s the true retail tipping point.
Not when the tech exists.
Not when it’s useful.
But when it becomes:
• narratively simple,
• culturally visible, and
• attached to stocks that go straight up.
If you want, next time we can map this exact same pattern onto:
• the internet (late 90s),
• smartphones (2010–2012),
• cloud computing (2014–2016),
• crypto (2017 / 2021).
The cycles rhyme a lot.
AI prompt:
With the announcement today that SpaceX (and xAI will merge, suddenly, it's gotten very, very interesting. Think about this: the Pentagon (DOD), all branches of the US military, NSA, NASA, SpaceX (Spacelink / Starlink) .... the one software company that connects them all? Palantir.
ChatGPT:
Today Elon Musk announced that SpaceX has merged with his AI company xAI, forming a combined entity with an estimated ~$1.25 trillion valuation — and that this consolidated company is aimed at combining space technology, AI, communications platforms, and data infrastructure into a single vertically integrated powerhouse.
Key points from the merger:
SpaceX acquires xAI and subsumes its AI assets (including the Grok chatbot and social platform X) under the SpaceX umbrella.
A strategically stated goal is to build large-scale AI data centers in space — potentially using solar-powered satellites to provide enormous computing capacity without the terrestrial power and cooling constraints of today’s data centers.
The combined company is positioning itself to compete with major cloud + AI players (like Google, OpenAI, Meta, and others) in both compute and deployment infrastructure.
This blurs the lines between space infrastructure, AI compute, and communications in a way few expected.
You mentioned something insightful: SpaceX + xAI intersects the realms of government/military infrastructure, satellite communications, and AI — a territory where Palantir is deeply embedded.
Here’s how Palantir plays into this:
Palantir’s software (such as Gotham and Vantage) is used extensively across Pentagon, Army, intelligence agencies, and allied defense systems to consolidate, analyze, and operationalize massive data streams. They help users from logistics to battlefield insights and AI-assisted decision-making across departments.
Palantir reported significant increases in U.S. government and military contracts, with revenue and forecasted growth supported by deals with the Department of Defense, Army, Navy, and more.
Palantir’s government business alone has grown substantially — and reporting indicates high-value, multi-billion-dollar defense contracts which tie it directly into U.S. national security infrastructure.
There are reports of coalitions of defense tech companies — Palantir, Anduril, SpaceX, OpenAI, and others — bidding for Pentagon contracts together. While those discussions aren’t necessarily formal mergers, they illustrate how these companies are increasingly grouped strategically from a government procurement perspective.
This suggests Palantir isn’t just a standalone software contractor: its data tooling is part of how the U.S. military integrates and operationalizes AI across sensors, satellites, and ground systems.
Let’s map out the rough landscape:
Infrastructure provider (rockets, satellites, Starlink)
AIMING to become a global AI compute backbone
Platform for distributed communications
Has Pentagon ties (Space Force, military contracts)
Positioned for a huge IPO
Data integration and analytics platform
Deeply used by the Pentagon and intelligence community
Enables decision-level AI and data workflows across agencies
Not selling compute hardware, but valuable software layers that sit atop it
So: they aren’t direct competitors.
Rather, they could be different layers of the same machine — if government and commercial defense buyers want end-to-end systems that run from data capture (satellite or sensor networks) → inference and AI (compute) → analysis and decision support (software like Palantir).
That’s a powerful combo: hardware infrastructure + AI compute + operational software.
This merger isn’t just another corporate play — it speaks to broader strategic trends:
SpaceX’s Starlink already serves military connectivity
xAI’s AI pushes computational boundaries
Palantir’s software stitches disparate data into actionable insights
If you imagine a future battlefield, space surveillance, logistics operations, or intelligence fusion center — all of these capacities are increasingly essential and interconnected.
Beyond consumer or enterprise cloud usage, national strategy (AI used in defense, intelligence, security) is a massive and rapidly growing bucket of spending. Palantir is currently one of the principal commercial providers in that space.
Today’s competition isn’t just “GAFA vs. OpenAI” — it’s platform stacks that intertwine physical infrastructure (satellites, networks), compute, models, and operational AI. SpaceX’s move toward space-based data centers and AI computing is an example of pushing the hardware envelope, which could dramatically reshape competitive economics for hyperscale compute.
In that context, a software integrator like Palantir (which turns raw data into decisions) becomes significantly more relevant.
Your instinct that Palantir is uniquely positioned was on point — but it’s not that Palantir currently “connects all those dots” in a single stack by itself. Rather:
Palantir’s software enables data and AI at scale in defense and intelligence
SpaceX/xAI’s merger is building the physical and compute infrastructure for next-generation AI
Together they map onto different layers of how tomorrow’s strategic systems will actually operate
So yes — systemically, we’re talking about AI, defense, space, and data infrastructure all converging. Palantir sits in the software layer that makes sense of data from satellites, sensors, and networks — and today’s SpaceX-xAI deal dramatically reinforces why those layers matter together, even if the companies themselves are separate entities.
Let’s watch how customers like the Pentagon or NASA begin to think about procurement — that’s where these stacks become real.
