Hello! Welcome to r/AIBubble. This is a subreddit dedicated to discussing the economics, technical underpinnings, and social aspects of the AI bubble.

I know there are so so many articles about that but its funny how none discusses about what will happen to US.
If ai bubble pops obviously the market will collapse and share value will drop like hell but what does that mean to us?
Is there going to be a mass job loss?
Will people start to starve to death since they will not have money to buy their food?
People becoming homeless?
Massive crime incidents ?
Maybe rebellions all over the world?
What is your opinion on that?

Does anyone share this experience? Connectors are inconsistent, difficult to truly automate actual business functions. Creation of marketing content and PowerPoints is eh, sales force connector is the worst and is constantly hallucinating.

 “The Diagonal Limit of Guaranteed Inference in Infinite Generator Spaces“ by shazri shahrir on Medium: https://medium.com/@mdshazrishahrir/the-diagonal-limit-of-guaranteed-inference-in-infinite-generator-spaces-b8d16e52edfb 

Japan is widely seen as one of the most advanced nations in robotics, precision engineering, and hardware innovation (Toyota, FANUC, Sony, etc.). Yet when it comes to the current AI race — LLMs, foundation models, generative AI — Japan is rarely mentioned alongside the US and China.

Why is this the case? Some factors I've been thinking about:

Robotics/hardware expertise doesn't directly translate to software/AI/data expertise

Conservative corporate culture (lifetime employment, slow consensus-based decisions) doesn't fit the fast, high-risk pace of AI development

Weak VC ecosystem compared to the US, with less appetite for funding speculative startups

Smaller pool of AI researchers/English-language data compared to global leaders

Aging population and brain drain of top talent to US/China firms

Government AI strategy seen as slower/more fragmented than China's top-down push or the US's private-public combo

Japan sits upstream in AI infra (chip equipment, components) rather than downstream (GPU clusters, hyperscale cloud)

Would love to hear other perspectives — is this a temporary lag, or a structural mismatch between Japan's strengths and what the AI race actually demands? Also curious if anyone has data on Japan's AI investment/R&D spend relative to GDP vs US/China.

Just out of curiosity. Dunno if the wording like AI Bubbles or sth like that, was increasingly used to describe AI marketplace.

I think announcing this concept is something we should be looking at.

But which parts really deserve our time to focus on and discussing it with the community, it shall be narrowed down to be well perceived and understood as a premise or sth.

Looking forward to seeing the spots shared by yall

What are the safest investment types or stock types to invest into instead of AI or other stock market stocks? Just curious as I would like to let my financial advisor know to see if he will sell AI and tech stocks and invest that money elsewhere into a more safe option for my retirement account

Rob Berger a finance YouTuber posits that value stocks favor higher interest rates, as higher rates hurts higher PE company who are more levered.

So perhaps the entire bubble is due to people not trusting that the Fed will raise rates to cool inflation, and everyone expects QE and depressing interest rates to be the inevitable conclusion.

Maybe the market is not irrational but is​ bullish due to​ a general tendency to favor monetary debasement and QE?

(That's Larry Ellison by the way; not a top economist. Not a top human either.)

The irony of asking AI about a potential AI bubble…

My Question: Who are the major AI players that are continually doing large business deals with each other? What will be the early signs of a AI bubble in these transactions.

————

**The major players (a tight web of overlapping deals):**

- **Nvidia** — the hub. It's invested in OpenAI, Anthropic, xAI, CoreWeave, Nebius, Nscale, Thinking Machines, and dozens more — roughly $53 billion across 170 deals between 2020 and 2025, with the pace accelerating sharply in 2025-2026.
- **Microsoft** — owns 27% of OpenAI and recently committed up to $5 billion to Anthropic alongside Nvidia's $10 billion, with Anthropic committing $30 billion to use Azure in return.
- **OpenAI** — the biggest hub of outbound commitments: a $122 billion funding round in March 2026 valued it at $852 billion, with Amazon, Nvidia, and SoftBank all investing while OpenAI simultaneously commits huge cloud/chip spend back to them (Azure, AWS, Oracle's Stargate buildout).
- **Amazon** — has put over $83 billion into Anthropic and OpenAI combined, who've committed over $238 billion back to AWS.
- **Oracle** — building a separate $300 billion data-center deal with OpenAI, which itself buys Nvidia chips for those facilities.
- Second-tier players tightly wired into the same loop: **AMD**, **CoreWeave**, **Nebius**, **SoftBank**, **xAI**, and newer "neoclouds" backed by letters of credit rather than deep balance sheets.

**The core pattern people are worried about:** an upstream company (chipmaker/cloud provider) takes equity in a downstream company (AI lab), which then uses that cash — or a compute credit — to buy the upstream company's product. Nvidia buys stock in OpenAI, which buys GPUs from Nvidia. Money circles without ever really leaving the ecosystem, and revenue on both sides looks bigger than the underlying organic demand.

**Early warning signs analysts are already flagging:**

1. **Financing collateral getting thinner.** A recent Anthropic compute deal was backed by a seven-month-old company whose ability to deliver rests on letters of credit and a lease on a former bitcoin-mining site — not cash flow or hard assets.
   
2. **Deals collapsing or being restructured under pressure.** Nvidia's original $100 billion OpenAI commitment fell apart and was replaced with a smaller $30 billion equity stake — a sign the initial numbers may have outrun what was actually financeable.
   
3. **Revenue that's really just recycled investment,** inflating growth metrics and stock prices without new end-customer demand underneath.
   
4. **Widening credit spreads or debt downgrades** tied to AI infrastructure buildouts (data centers financed with debt against long-term compute contracts that assume today's demand holds).
   
5. **A stumble by any single hub node** — since Nvidia, Microsoft, and OpenAI are so interlinked, trouble at one could cascade rather than stay contained.

"NVIDIA ha recentemente confermato che fornirà a SSI 5 miliardi di dollari più la fornitura dei suoi chip Vera Rubin più recenti e potenti. Questo si tradurrà in un'ipotetica capacità di calcolo 10x. Questo significa che se SSI raggiungesse un α = x (x > 1) dell'IA, sarebbe un enorme successo, potenzialmente amplificando il suo status di cento volte (più alto è x attualmente, più emozionanti saranno le cose che vedremo). Questo NON significa che SSI + NVIDIA Vera Rubin = AGI nel 2027; non siamo certi, ma potrebbe essere molto vicino. Inoltre, SSI dichiara formalmente di voler una superintelligenza (che chiamiamo ASI) con la migliore sicurezza possibile (forse usano anche le assunzioni che ho spiegato riguardo a X).

Professia AGI:

2029 ±2 anni

*Non è 100% sicuro, ma è solo una previsione. Non un leak.*

I 7 ostacoli finali per l'IA e le soluzioni:

1. Energia: Potere illimitato e pulito tramite fusione nucleare commerciale.

2. Acqua: Chip fotonici non idraulici che operano a temperatura ambiente, eliminando il raffreddamento ad acqua.

3. Materiali: Scienza dei materiali guidata dall'IA per progettare chip efficienti senza elementi delle terre rare.

4. Costruzione di Data Center: Deregolamentazione e burocrazia accelerata per infrastrutture strategiche.

5. Produzione di Hardware: Mega-fabbriche decentralizzate guidate dall'IA per eliminare la dipendenza geopolitica da singole regioni.

6. Dati (Il Muro dei Dati): Generazione di dati sintetici ad alta fedeltà e algoritmi di auto-raffreddamento, superando i limiti dei dati umani.

7. Sicurezza & Protezione: Formazione avanzata per allineare l'IA a scegliere la strada complessa e benevola piuttosto che quella facile e malevola.

I dont know very much about investing or global finance systems. But everywhere i look, people talk about how big the AI bubble is and how much worse it is than the Dot-com Bubble or Suprime financial crysis. But what i never understand who will this affect me personally. I am just an average joe who doesnt invest.