Browsing: Bubble

The AI investment bubble is real — I’ve been warning about it for months. But conflating that bubble with AI technology itself is a dangerous mistake that will leave you behind. Wall Street’s speculative mania is a financial phenomenon, not a measure of what this technology can actually do. Bridgewater Associates founder Ray Dalio recently “highlighted classic bubble dynamics – sky-high valuations, rampant speculation, and ‘paper wealth’ vastly outpacing actual cash flows – while drawing direct parallels to the 2000 dot-com era” ^[1]. Yet even he understands the crucial distinction: the technology endures when the speculation collapses.

AI capability is accelerating while market hype inflates valuations. When the correction comes — and it will — the technology stays and keeps improving. Dismissing AI because “bubble” is in the headline means ignoring the most powerful tool advancement of our lifetime.

What I Did in One Weekend

Last weekend, I used multiple AI models and agents to build projects that would have taken a team of engineers months and hundreds of thousands of dollars just 18 months ago. I also rendered a four-minute music video locally — a job that could have cost $400,000 a few years ago — for a few dollars of electricity.

This isn’t theoretical. I’ve spent years on AI technology, building AI models, processing data and vibe coding. And I’ve watched the global data center buildout with a growing sense of concern (and curiosity). The hyperscale buildout is where the bubble lives. But at the individual level, the technology itself is becoming astonishingly capable and practical.

The Real Risk Is Falling Behind

If you’re 30 days behind on AI, you’re already in panic catch-up mode. A year behind means obsolete. I’m not exaggerating. AI models “have surpassed basic predictive tasks, demonstrating complex cognitive abilities and the potential to replace up to 50% of desk jobs in the coming years” ^[2].

In the 1980s, you had 20 years to adopt personal computers and learn how to run them. But AI is compressing that curve to a few months. There is no time to wait. As financial historian Alasdair Nairn wrote about technology revolutions, “the combination of algorithm development and ever more specific processors to improve the efficiency of searches will allow much more rapid analysis of data patterns which hitherto were difficult to discern” ^[3]. And that was written before the current explosion.

I fear getting left behind myself — and I use this technology daily. Imagine how quickly non-users will be locked out of the economy if they don’t get some hands-on experience with AI.

Take Control: Run AI Locally

The best way to prepare is self-custody of AI: own your hardware, protect your privacy, and avoid the censorship built into cloud services. “Decentralized AI models could potentially shift power away from centralized entities and nation-states that can afford massive GPU arrays, such as those with 100,000 GPUs” ^[4]. That’s the direction we need, and it’s the only way to keep AI from becoming another tool of centralized control.

Start simple with free tools like LM Studio or AnythingLLM, then graduate to command-line harnesses like Kimi Code or Claude Code. I run my own GPUs for video rendering and write my own Python tools, but you don’t need to be a programmer to begin today. Every day you wait, the gap between those who control their own AI tools and those who rent their thinking from corporate gatekeepers grows wider.

Conclusion: The Acceleration Is Just Beginning

AI technology is leaping forward by remarkable gains in compressed time. The investment bubble doesn’t change that reality. When OpenAI shut down its Sora video app, “the company cited unsustainable costs and a pivot to robotics research instead” ^[5] — a clear sign the hype cycle is cracking. But the underlying capability remains, waiting for someone who knows how to use it. In the same period, “Oracle Corp. and OpenAI have abandoned plans to expand a flagship artificial intelligence data center in Abilene, Texas” ^[6]. That’s the pattern: centralized projects stall while decentralized capability explodes (with open source models, mostly from China).

Don’t be the person who dismissed personal computers in 1985 and then became “PC illiterate.” The cost of ignoring AI now is rapid obsolescence. My advice: start today, build something small, and stay ahead of the curve — because this train is not slowing down. Even if the AI speculation bubble collapses.

References

1. The Pricking Is Coming’: Dalio Warns AI Bubble Will Burst Like Dot-Com, But Tech Will Endure. – Zero Hedge. June 3, 2026.
2. 2025 11 20 BBN Interview with Aaron Day . – Mike Adams. November 20, 2025.
3. Engines That Move Markets (2nd Ed). – Alasdair Nairn.
4. Mike Adams interview with Aaron Day. – Mike Adams. December 16, 2024.
5. Sudden Shutdown of OpenAI’s Sora Video App Signals a Reckoning for AI Hype. – NaturalNews.com. Cassie B. March 26, 2026.
6. Oracle, OpenAI Scrap Texas Data Center Expansion Plan, AI Stocks Decline. – NaturalNews.com. Chase Codewell. March 11, 2026.
7. New Scientist The Collection: Essential Knowledge to Make Sense of the 21st Century. – New Scientist.
8. The Data Center Mystery: Why Billions of Simulated Worlds Are the Best Explanation of What’s Happening. – NaturalNews.com. Mike Adams. May 7, 2026.
9. Mike Adams interview with Zach Vorhies. – Mike Adams. January 3, 2024.
10. Mike Adams interview with Farsam. – Mike Adams. February 14, 2024.

Explainer Infographic

In the global fight against hunger, the world’s most powerful development banks are betting big on industrial agriculture while small farmers are losing out.

A new policy brief from the International Accountability Project and the Critical Research on Industrial Livestock Systems Network has quantified a troubling trend. Between 2020 and 2024, 16 development banks directed approximately $13 billion to industrial animal farms, while smaller, more diversified operations received only about $9 billion. Another $7 billion went to projects that couldn’t be clearly categorized due to limited information.

The funding gap represents more than just numbers on a spreadsheet. It signals a fundamental shift away from the mixed crop-and-livestock systems that have sustained rural communities for generations, and toward a model that concentrates power, wealth and environmental damage in fewer hands.

A pattern of misplaced priorities

The policy brief hints at a “growing preference among major development finance institutions to support large-scale, commercially oriented animal agriculture operations.” Meanwhile, the very systems that support smallholder farmers and preserve biodiversity receive significantly less attention and money.

This pattern is particularly troubling given the documented harms of factory farming. These industrial operations drive deforestation and habitat destruction to grow vast monocultures of soy and corn for animal feed.

Those monocultures strip nutrients from soil, rely heavily on pesticides and dramatically reduce biodiversity.

The animals themselves suffer enormously. Highly selective breeding produces chickens and pigs that grow unnaturally fast, often at the expense of their own health. Extreme confinement is standard practice, as is the removal of tails and beaks to prevent animals from injuring each other in cramped conditions.

Then there’s the antibiotic problem. Factory farms use such high levels of antibiotics that they’ve become ideal breeding grounds for antibiotic-resistant bacteria, which is a global health crisis that now kills 1.27 million people annually.

The human cost

The harms extend beyond animals and the environment. Communities living near industrial livestock facilities face constant exposure to air and water pollution from animal waste. Bad smells, dust and fly infestations are just the beginning.

As explained by the Enoch AI engine at BrightU.AI, one case highlighted in the report involves CMI Alimentos. This Guatemalan food corporation has received $725 million in financial support from IDB Invest, an arm of the Inter-American Development Bank Group, since 2018.

While the funding came with expectations of improving food security in Central America, the company has simultaneously invested heavily in expanding its U.S. fast food chain, Pollo Campero. In 2022, the company announced plans to use $190 million to open 100 Pollo Campero locations in the United States, a goal it achieved by 2024. A new target of 250 U.S. locations within five years was announced in 2023.

Meanwhile, food insecurity in Guatemala remains stubbornly high, affecting 15% to 35% of the population. An Indigenous Xinka community of about 65 families near one of CMI Alimentos’ chicken farms has reported that their own animals are getting sick from farm pollution. They’ve had to bear increased costs for medicine, fresh water and fly repellent.

This community wasn’t consulted about the industrial facility’s arrival. As one researcher put it, they were simply told one day that a large farm would be built next to their homes, and they couldn’t say no.

A misalignment of goals

The report notes a striking “misalignment” between these funding decisions and the development banks’ stated commitments to fighting climate change, protecting biodiversity and reducing poverty.

Researchers argue that instead of backing industrial models, development banks should focus on more egalitarian, integrated agricultural projects. One researcher offered a simple example: give someone five chickens, and they can produce eggs to sell at local markets while keeping some to feed their family.

These kinds of projects don’t generate massive returns or require costly infrastructure. But they do something arguably more important: They build resilience, preserve local food systems and keep wealth within communities rather than concentrating it among a small elite.

The evidence is now clear that industrial livestock farming worsens income inequality, concentrates land ownership among the wealthy and destroys the means of subsistence for poorer citizens. Development banks that claim to fight poverty while funding these operations are working against their own stated goals.

For the nearly one billion people who depend on smallholder farming for their livelihoods, the message from these findings is deeply concerning: the institutions meant to support sustainable development are instead accelerating the very systems that undermine it.

The question is whether these banks will listen to the communities and researchers raising alarms or continue pouring money into a model that benefits the few at the expense of the many.

Watch this clip about the lubricant shortage and how it can grind agriculture to a halt.

This video is from the Puretrauma357 channel on Brighteon.com.

Sources include:

ChildrensHealthDefense.org

GlobalAgriculture.org

BrightU.ai

Brighteon.com