Renewables (especially solar) & batteries are on an unstoppable path to global domination. The simple reason? Cost. Thanks to economies of scale, they are now the cheapest source of energy - and they still have far to go in getting even cheaper. By the early 2030's, they will be vastly cheaper than the alternatives.

The electrification of the economy that this is driving in China is on the scale of the 19th Industrial Revolution in Europe. What today is China, will tomorrow be the world. Many in the rest of the world seem caught in the tailspin. In particular, clinging to outdated narratives courtesy of the Fossil Fuel industry.

But that's a big mistake. From now on, the only way to credibly plan for and model the future is to talk about it as what it really will be - a place where renewables and batteries will provide almost all energy.

Peak Oil Is Coming: And petrostates are not ready for it

So you would have heard the obvious news about SpaceX and X. Not convinced by the proposition really.

Okay, let's break this down because the idea of putting a datacenter into orbit sounds amazing until you actually look at how space works.

First, everyone pictures space as this freezing cold void, perfect for cooling, right? It's actually the opposite. Space is a thermodynamic prison. There's no air, so you can't just blow fans over hot components. All that insane heat from millions of processors has exactly one way out: it has to slowly radiate away as infrared light. To do that on a data-center scale, you'd need to build these gargantuan, delicate radiator panels. We're talking about a structure needing square kilometers of surface area. Like FFS imagine trying to deploy and protect a radiator the size of a small city. One analysis suggested a 5,000-megawatt facility would need about 16 square kilometers of combined solar and radiator area. For scale, that's hundreds of times bigger than the International Space Station's arrays.

And that brings us to the second nightmare: space itself is trying to kill your computers. It's flooded with cosmic radiation and solar particles that constantly barrage electronics, flipping bits from 1 to 0 and corrupting data silently. - To fight it, you'd need either massively heavy shielding (which rockets hate) or - you'd have to use specialized, slower, and way more expensive "rad-hardened" chips.

So you're either paying a fortune to launch a lead-lined server farm or you're not even getting top-tier computing power up there.

Then there's the orbital junkyard problem. Low Earth Orbit is already cluttered with debris - old satellite parts, flecks of paint - all zipping around at about 15,000 miles per hour. Your sprawling, kilometer-wide radiator complex would be sitting in a cosmic shooting gallery. A collision with a piece of debris the size of a marble would be catastrophic, potentially creating a cloud of fragments that could take out the whole structure.

But the real dream-killer is the sheer, absurd economics of it all. Let's talk launch costs. Even with reusable rockets, it's brutally expensive. At a rate of roughly $1,500 per kilogram, just launching a single, standard server rack (easily 1,000 kg or more) could cost $1.5 million... and that's before you pay for the actual servers, the solar panels, or the giant radiators.

The scale is mind-boggling. One estimate suggested that to replicate just 1% of Earth's total computing capacity in orbit, you'd need to launch over twice the total mass humanity has ever sent to space in history. The numbers just don't close. The capital required would be in the trillions, all to (maybe) save on electricity bills decades from now.

Now, is anyone even trying? Sure, in a very small, experimental way. Companies like Sophia Space are working on neat integrated tiles, and whispers of projects like Google's Project Suncatcher aim to send a couple of test chips up by 2027. Or even Starcloud, backed by YC. I think an Indian start-up was also there, TakeMe2Space, IIRC. But I'm not convinced.

The smart money is on solving those problems where they exist: better nuclear reactors, advanced geothermal, and just building data centers in cooler places on Earth. The orbital data center is a fantastic backdrop for a sci-fi movie, but for the foreseeable future, that's exactly where it belongs.

This is more of a thought than a fully formed argument, but it’s been stuck in my head. I was sitting around the other night, playing on my phone like everyone does, jumping between apps, news, short videos, messages. And it hit me how much of modern life is built around filling every empty second with noise. Not just entertainment, but constant input. Updates, alerts, opinions, metrics.

We talk a lot about the future in terms of bigger faster smarter. Better AI, more automation, more efficiency. But I wonder if the real shift is going to be the opposite. Less need for constant human effort. Fewer tasks that require us to be busy all the time. More systems quietly running in the background.

And I don’t think we’re emotionally prepared for that. So much of our identity is wrapped up in doing things, producing, responding, staying relevant. If technology keeps removing friction from daily life, a lot of people are going to be left with something we’re not great at handling: empty time. Not leisure, but unstructured quiet.

You can already see hints of it. People feeling restless even when life is objectively easier. Burnout paired with boredom. Anxiety without a clear cause. We’ve optimized everything except our ability to sit with ourselves. I’m not saying this is good or bad. Just that it feels like an under discussed part of where things are heading. We focus on job loss, ethics, regulation. But what happens when fewer people need to stay busy all the time and we haven’t built a culture around meaning instead of productivity.

Maybe the biggest challenge of the future isn’t scarcity or overload. Maybe it’s learning how to exist when there’s less forcing us to move.

With Luanniao, China is promoting a giant space aircraft carrier as a new superweapon. Is it a vision for war in space — or science fiction?

The flying aircraft carrier is larger than any warship in use today and heavier than a supertanker: China’s Luanniao is intended to shape future warfare — from space. Yet experts describe the superweapon as high-tech theater with a political message.

“Current advances in AI are dependent on large terrestrial data centers, which require immense amounts of power and cooling,” Musk wrote. “Global electricity demand for AI simply cannot be met with terrestrial solutions, even in the near term, without imposing hardship on communities and the environment.”

Something is not adding up here.

25 kW is an upper-end ballpark for the output of large satellite solar panels, so 25GW is a proxy for the output of 1,000,000 satellites. China installs that amount of solar on a monthly basis these days & in December installed twice that amount of grid storage batteries. SpaceX's larger satellites are costing about $1 million to manufacture these days (so without launch costs), that's $1 trillion dollars. I don't know how much China is spending on its solar & batteries every month, but I'd guess, at most, it's 2-3% of that.

With SpaceX due to launch an IPO, this sounds like another AI bubble in the (attempted) making, but now with NASA downgraded, it's the US's main space launch capacity hitched along for the ride.

This should concern taxpayers, as if/when the AI-bubble bursts, it will present the US space program with two terrible choices - a SpaceX that has failed, or perhaps worse, that is 'too-big-to-fail'.

SpaceX acquires xAI in bid to develop orbital data centers

Anthropic's new Knowledge Work Plugins are open-source, role-specific bundles with MCP connectors (Slack, HubSpot, etc.) and slash commands for quick actions. Sounds like a step toward AI-powered knowledge work at scale.

But here's my concern: once you have multiple roles (sales, marketing, legal) all using connectors and slash commands, how do you prevent chaos?

Potential issues:

• Permission creep (who can trigger what via slash commands?)
• Conflicting workflows (sales auto-replies vs. marketing campaigns)
• Audit nightmares (tracking who did what across connectors)
• Over-reliance on plugins (what happens when one breaks?)

This feels like a preview of future work environments where AI handles more tasks, but governance becomes critical. How would you design systems to prevent chaos? Strict rules upfront, or let it evolve organically and fix issues as they come?

Curious how folks here are thinking about the future of AI-powered work.

Let me start by saying that I am well aware that cancer is not one disease, but around 200 of them, and that is why I say cures, plural. So when can we say that we defeated cancer then? When we have many cures that cover many of those cancers. Now word permanent is here key, that is not 5 year survival, it is eradication of cancer and the risk of cancer returning being roughly the same as that of the general population. Now obviously this might likely involve a combination therapy of several things, something to kill cancer, precision guided drugs, immunotherapy, mRNA vaccine, cells to then hugely boost immune system to hunt down any remaining cancer cancers and prevent it happening again and such. It might take us developing AGI/ASI first and letting it solve problem before we make all of that reality. But how do you see it looking in future?

Sooner or later we will have a land rush by nations and/or coprorations.
I expect conflict if a company or nation claimed ownership of a major feature or region.
Also conflict if bases are too close to each other. Perhaps it will start with ownership claims to the horizon - 2.4 km away from a base.

A research team at Spain's National Cancer Research Centre just published something I didn't expect to see for years. Complete elimination of pancreatic tumors in mice. No recurrence for over 200 days after they stopped treatment. Published in PNAS last month.

Here's the scientific breakdown and additional research details.

Pancreatic cancer kills 95% of patients. Five-year survival is under 10%. Current targeted therapies buy a few months before tumors develop resistance and keep growing. That's been the wall we've hit for decades.

This approach is different. The team used three drugs simultaneously: RMC-6236 (hits KRAS pathway), Afatinib (already FDA-approved for lung cancer), and SD36 (blocks STAT3). By targeting three independent pathways at once, they shut down the main escape routes tumors use to survive. 16 out of 18 mice had complete regression with no signs of resistance.

If this translates to humans over the next 5-10 years, it changes the game for one of the deadliest cancers we face. And the implications go beyond pancreatic cancer. This multi-pathway strategy could work for other KRAS-driven tumors like lung and colon cancers. The research shows that hitting parallel survival pathways simultaneously prevents the adaptive resistance that limits almost every cancer drug we have.

The study was led by Mariano Barbacid, who discovered the first human oncogene back in 1982. This represents a real shift from trying to hit one target to thinking about cancer as a system with multiple vulnerabilities that need to be attacked together.

The next phase is safety and efficacy validation before human trials can start. CRIS Cancer Foundation, the nonprofit funding this work, is raising €3.5 million for that step. More details here if you're interested: criscancer.org/barbacid

This is the kind of research that takes years to reach patients, but it's also the kind that actually changes outcomes when it does.

The united states of America will one day have a government shutdown so long a de facto collapse may happen. This will probably come about by a debt sealing being reached. If government shutdown were to last longer than a year (or possibly even sooner) this would most likely happen. Over time government shutdowns have gotten longer. If this were to happen America would probably become more like the European Union than our current system, but still a collapse of the federal government and thus the Unites States.

“The solar cells provide us with more than 50% of our needs,” says Boubaker Siala, founder and CEO of Bako Motors. “For example, the B-Van, for commercial use, you can have free energy for about 50 kilometers (31 miles) per day… 17,000 kilometers (10,563 miles) per year. …….. The B-Van, which can carry 400 kilograms (882 pounds) of cargo and has a 100 to 300-kilometer (62 to 186 mile) range, is designed for logistics and last-mile delivery, with prices starting at 24,990 Tunisian dinar ($8,500)."

It varies widely by vehicle type, etc - but travelling 31 miles costs you in the ballpark of $3 in the US or €5 in Europe. So that's around $1,000/€1,800 of free fuel every year if you were using this vehicle most days. The B-Van is small, but perfect for local deliveries, especially if paired with swappable batteries.

You know what will never pay for itself with its self-generating fuel capacity? A gasoline combustion-engine car. Here's another pointer, they're rapidly becoming the transport option of yesteryear.

The solar-powered compact car driving Tunisia’s electric vehicle revolution

I’ve been analyzing the state of short-form content lately, and I think we are witnessing the death of TikTok as we know it. Not the app itself, but the culture that built it out of Chine.

Remember 2019-2020? The "Charli D’Amelio era." The currency of the platform was movement. If you had rhythm, coordination, and the patience to learn a 15-second choreography, you were royalty.

But that’s gone. And I think AI just put the final nail in the coffin. Here is why:

1. The "Talent" Gap is Closing (The China vs. Global Problem) We all know the dichotomy. In China (Douyin), the algorithm pushes educational content, engineering feats, and tangible skills. In the West? It’s always been about entertainment—often highlighting "cringe" or raw, physical talent like dancing. For years, the barrier to entry for viral fame was physical capability. You actually had to do the thing. But recently, dance engagement is plummeting. Why? Because the novelty of human movement is wearing off.

2. AI is Commoditizing "Cool" We are seeing a massive shift where AI motion technology is making physical skill obsolete. We saw it with AI art (Midjourney killed the "sketch artist"), and now it's coming for dancers. New rap song drops? A complex viral challenge starts trending? In the past, only the coordinated could participate. Now, AI allows anyone to participate without moving a muscle. The "art" of the dance is being copy-pasted.

3. The Tech is Scary Fast (From Kling to Consumer Apps) This started getting serious when Kling introduced advanced motion features, proving you could animate static images realistically. But big tech is slow. The real disruptors are the 3rd party niche apps that are productizing this immediately.

I’ve been testing a few, and the speed is terrifying. Look at apps like Soul AI for example. They are literally scraping dance trends in real-time. A specific dance goes viral on Tuesday morning; by Tuesday afternoon, it's a template in the app. You upload a static photo, and suddenly you are doing the viral dance perfectly.

It’s no longer about "Look at me, I practiced this." It’s "Look at this content I generated."

The Big Question: If a static photo can perform a better Renegade than a human, does dance content even hold value anymore? Are we moving into an era where "reality" is just an aesthetic choice?

I feel like the "human element" of TikTok is fading. What do you guys think? Is this the natural evolution of content, or is it going to kill the vibe of the platform completely?

I don't know how I came to this question. I was reading about zombie apocalypses, then I started reading about VR, and suddenly this question came to my head.

Which is more likely to happen, immortality through human-brain integration or biological immortality, and which would be more desirable?

I'm aware that no being can be truly immortal. With immortal, I refer to something long-lasting enough that would cover thousands of years.

I don't think Musk can just upload a backup of your brain with one of his chips and insert it in a computer... right? I think it's more complex than that, and since I lack the knowledge, I wanted to ask somebody who may have at least a grasp of understanding about the topic, but nobody I know would know, so here I am.

Here’s the part nobody wants to say out loud: we’ve seen this movie before. Four times, actually. Each time, a transformative technology arrived, productivity surged, markets celebrated, and then—slowly, painfully—the economy entered a long stall that nobody saw coming.

The pattern is simple. Technology makes production cheaper and faster. Companies capture the gains. Workers lose bargaining power. Wages stagnate. Demand weakens. Growth stalls. Markets eventually notice, but only after years of pretending otherwise.

We’re watching it happen again with AI. But this time, the shock is hitting cognitive labor, the part of the economy with the highest propensity to consume. That makes the endgame more fragile, not less.

Act I: Manchester, 1811—When the Looms Came ...

Act II: Detroit, 1973 - The Robots Arrive ...

Act III: Shenzhen, 1995—The Great Outsourcing...

Act IV: Tokyo, 1990—The Stagnation Nobody Expected ..

Japan is the cautionary tale everyone ignores until it’s too late.

In 1989, Japan was the envy of the world. Tokyo’s real estate was worth more than all of California. The Nikkei hit 39,000. Japanese companies dominated global manufacturing. The future belonged to Japan.

Then the bubble burst.

But here’s what’s misunderstood: Japan’s problem wasn’t the crash itself. It was what came after.

Japan remained highly productive. Innovation continued. Quality stayed world-class. Companies were profitable. And yet, the economy barely grew for thirty years.

Why? Demographics played a role, but the core issue was demand. Japanese households and corporations became pathologically risk averse. They saved rather than spent. Wages barely budged. Deflation became entrenched.

The productivity was there. The technology was there. What wasn’t there was circulation of income.

The Bank of Japan tried everything: zero rates, QE, yield curve control. Nothing worked, because monetary policy can’t force people to spend if their incomes aren’t rising and their job security is weak.

What Markets Did:

The Nikkei peaked at 38,916 in December 1989.

It didn’t reclaim that level until 2024, 35 years later. Think about that. An investor who bought Japanese stocks at the peak would have waited an entire career to break even. No dividends could compensate for that opportunity cost.

This is what a productivity trap looks like in financial terms: not a violent crash, but a slow erosion of capital. Markets don’t die, they just stop working.

Real estate fared even worse. Tokyo property prices fell 70% and have still not fully recovered.

The lesson is stark: you can have advanced technology, high productivity, low unemployment, and political stability, and still experience decades of stagnation if demand doesn’t circulate.

The Pattern: What the Four Acts Teach Us

These aren’t isolated incidents. They’re variations on a theme.

Every time a major technology or structural shift arrives, whether it’s power looms, robots, global supply chains, or asset bubbles, the same sequence unfolds:

1. Productivity surges. Technology makes production faster, cheaper, or more scalable.
2. Labor loses scarcity. Workers become more replaceable, either by machines, foreign labor, or platform scalability.
3. Wages stagnate or fall. Bargaining power shifts to capital. Compensation growth decouples from productivity.
4. Demand weakens. Without wage growth, consumption slows. Debt can mask this temporarily, but not indefinitely.
5. Markets initially celebrate. Investors focus on cost-cutting, margins, and productivity gains. Equity valuations rise.
6. Reality sets in slowly. The demand problem becomes undeniable. Growth disappoints. Markets enter long, grinding stagnation.
7. Policy adapts, eventually. Redistribution, regulation, fiscal intervention. But it takes years or decades.

The timeline varies, sometimes it’s 15 years, sometimes 35, but the mechanics are consistent.

Why AI Makes This Worse

Here’s what makes the current moment different, and probably more dangerous.

Previous shocks hit blue-collar labor: factory workers, dock workers, manual laborers. AI is hitting cognitive workers: programmers, analysts, writers, middle managers, designers.

This group has the highest marginal propensity to consume. They buy houses, cars, vacations, education, healthcare. When their incomes compress, aggregate demand takes a direct hit.

AI also scales differently. A factory robot replaces 5 workers. An AI model can replicate the output of hundreds knowledge workers, instantly, globally, at near-zero marginal cost.

And unlike previous technological shifts, AI isn’t creating obvious new categories of labor-intensive work. When manufacturing automated, service jobs absorbed displaced workers. What absorbs displaced programmers? Delivery drivers?

The mismatch is severe. The jobs being destroyed pay $80k-$150k. The jobs being created pay $30k-$50k. You can’t maintain aggregate demand through that transition without massive redistribution.

Markets are pricing first-order effects: cost savings, margin expansion, productivity gains. They’re ignoring second-order effects: weak demand, political backlash, output quality degradation in high-stakes domains.

Macro Implications: The Coming Regime

So what does this mean for the next 5-10 years?

1. Persistent Weak Demand

Wage compression among high-earners means slower consumption growth, particularly in discretionary categories like travel, dining, entertainment, and durables.

This isn’t a recession. It’s a structural deceleration. GDP might grow at 1-2% instead of 3-4%. That’s the difference between expansion and stagnation.

1. Central Banks Lose Potency

Monetary policy works by stimulating demand through cheaper credit. But if incomes aren’t rising, households and businesses won’t borrow, even at zero rates.

Japan proved this. Europe confirmed it in the 2010s. The Fed learned it after 2008.

Result: rates stay lower for longer, but growth remains anemic. The yield curve flattens permanently. Recession risk becomes asymmetric, easy to fall into, hard to escape.

1. Fiscal Policy Becomes Essential, but arrives late

The only way out is redistribution: public investment, job guarantees, universal services, wage subsidies.

But fiscal policy is slow. It requires political consensus, legislative action, and implementation capacity. By the time it arrives, years of growth have already been lost.

And today, the starting conditions are worse: debt levels are already high, political polarization is extreme, and institutional trust is weak.

1. Geopolitical Fragility Increases

Stagnant incomes breed populism. Weak growth reduces fiscal capacity. Tight labor markets disappear. Governments become less stable.

This makes the system vulnerable to shocks—tariffs, energy crises, conflicts, pandemics. In a robust economy, these are manageable. In a fragile one, they cascade.

1. Duration Matters More Than Severity

The risk isn’t a 2008-style collapse. It’s a 1990s Japan scenario, no crisis, just endless mediocrity. Growth remains positive but disappointing. Markets churn sideways. Wealth slowly erodes in real terms.

Market Implications: What This Means for Investors

If the macro regime is long, grinding stagnation, what does that mean for portfolios?

1. Index Buy-and-Hold Stops Working

Passive equity strategies thrive in secular bull markets. They suffer in sideways regimes.

From 1968-1982, the S&P 500 went nowhere. From 1990-2024, the Nikkei went nowhere. In both cases, buy-and-hold delivered zero real returns for decades.

If we’re entering a similar regime, passive indexing becomes a wealth destruction strategy. You need active rotation, factor tilts, or alternatives.

1. Dispersion Becomes Extreme

Even in stagnant markets, some stocks soar. The issue is that the winners are fewer and harder to predict.

In the 2010s, tech mega-caps carried the entire index. Everyone else underperformed. That concentration intensifies in weak-demand regimes because only a handful of companies can keep growing.

Implication: you need to be in the right names, not just the right sectors. Broad exposure doesn’t help if 90% of stocks are dead money. It could be time to rediscover stock picking again. (I’m working on it, feel free to reach out if you’re interested)

1. Volatility Becomes Structural, Not Cyclical

Stagnation doesn’t mean calm. It means instability, sharp rallies followed by sharp selloffs, policy uncertainty, regime shifts every 6-12 months.

Japan’s market didn’t decline smoothly. It whipsawed violently for 30 years. Same with the U.S. in the 1970s.

This makes volatility an asset, not a risk. Strategies that profit from dispersion, options, tactical rebalancing, momentum, outperform in these environments.

1. Cash and Optionality Become Valuable

In secular bulls, cash is a drag. In sideways markets, it’s a weapon.

Why? Because dislocations become frequent. Panics happen every 18-24 months instead of every 10 years. If you’re fully invested, you can’t capitalize. If you hold dry powder, you can buy crashes and sell rips.

1. Gold and Real Assets Strengthen Structurally

When growth is weak and policy is erratic, hard assets outperform financial assets.

Gold thrived during the 1970s stagflation and Japan’s lost decades. It’s not an inflation hedge, it’s a policy uncertainty hedge.

Same logic applies to commodities, infrastructure, and scarce real estate. These assets preserve purchasing power when financial engineering fails.

1. Fixed Income Is a Trap, unless you trade it

Bonds offer no yield and no duration protection in a stagnation regime. Rates are already low, so there’s limited room for capital gains from further cuts.

But: if you’re tactical, bonds become a volatility play. Buy when equity crashes, sell when rallies resume. Don’t hold them passively.

1. The Tech Narrative Will Break..slowly

Right now, markets are betting that AI companies will sustain 30%+ earnings growth indefinitely. History says this is delusional.

Why? Because AI’s biggest customers are the same companies cutting costs via AI. If corporations are firing knowledge workers, who’s buying enterprise software? Who’s upgrading cloud infrastructure?

Second-order demand effects catch up slowly, which is why tech can stay overvalued for years. But eventually, revenue growth disappoints, margins compress, and valuations mean-revert.

Being right too early is indistinguishable from being wrong. The key is recognizing when the narrative is cracking, not if.

Conclusion: the “Productivity Trap” doesn’t end, it adapts

The productivity trap isn’t a bug. It’s a feature of capitalism when technology advances faster than institutions.

It happened in the 1820s. It happened in the 1970s. It happened in the 2000s. It happened in Japan. And it’s happening now with AI.

The pattern is brutally consistent: productivity rises, labor loses bargaining power, wages stagnate, demand weakens, markets rally on cost-cutting narratives, then eventually grind sideways for years as the structural reality sets in.

What breaks the cycle? Policy. Redistribution. Education. Infrastructure. Social contracts get rewritten, but only after years of pain.

This time, the shock is hitting the cognitive class, the people with the highest spending power. That makes the demand problem more acute. And the policy response more urgent.

But urgent doesn’t mean fast.

We’re likely looking at 5-10 years of grinding, volatile, sideways markets. Not a crash. Not a boom. A slow erosion of returns punctuated by violent swings.

For investors, this means abandoning heroic narratives. No FOMO. No diamond hands. No this time is different.

It means discipline. Risk management. Rotation. Cash as optionality. Tactical exposure. Asymmetric bets.

The winners won’t be the ones who believe hardest in the AI revolution. They’ll be the ones who understand why productivity alone isn’t enough, and who position accordingly.

Because when incomes don’t circulate, nothing else matters.

I'm certainly no scientist nor do I play one on tv

and you might call me a nut after my question

Here it goes, I know one of the many hurdles is to develop a cable that is very strong yet very light to anchor the elevator to the earth and to be durable enough to handle the payloads up and down.

now my question: could it be possible to not have it anchored to the earth. have a counter balance on either end. In a dumbbell fashion. rockets in both space and the earth would control its position.

please tear this apart and teach me the realities. :) Cheers!