mugenpower78 🦇🔊

[Jim Liu @jiahanjimliu]

Neoclouds: The Kimi K3 Scare

Kimi K3 caused a large scare in the AI trade as this Chinese open source model matched frontier models on benchmarks. Let me unpack what's actually going on.

Chinese Labs have much less GPUs than American Labs and yet are able to train "just as good" of a model. This implies that Chinese Labs have huge efficiencies that allow them to use much less GPUs in training. This is would imply less HBM, less datacenters, less cloud bills - the whole capex heavy buildout that the AI trade is predicated upon.

Now here's the big hole in all this logic. MoonshotAI, the Lab that made Kimi K3, is supposedly a magnitude more efficient in training than American Labs yet their inference compute consumption is the same or less efficient! Kimi K3 cost exactly the same as GPT 5.5 and slightly less than Claude 4.8 Opus High.

Some people are misunderstanding what expensive tokens mean. Yes the cost of the open source weights/topology is 0 but the amount of the compute/GPUs that you need to run the model is a metric of a efficient your inference is. Compute/GPU time is very expensive and cost of open source inference is very not free.

Now, it makes absolutely zero sense that MoonshotAI Kimi is so much more efficient in training but slightly less efficient in inference. Why? Training is a the forward pass plus backward pass and inference is the forward pass. This means that training efficiency improvements lead to inference efficiency improvements.

You know why MoonshotAI training and inference efficiencies are asymmetric? Because their "training efficiencies" come from distilling American models. If MoonshotAI had true training efficiencies they would also show inference efficiencies but they have no advantage in inference efficiencies!

AI Capex will still continue because:
1. If American Labs stop training capex, then Chinese models will also stop improving. AI progress will have stopped. American companies have never given up just because Chinese are trying to copy them.
2. Chinese model still consume alot of compute/GPUs for inference. Inference demand will outstrip training demand anyways.

[Samantha LaDuc @SamanthaLaDuc]

This parabolic Korean margin loan chart is from June 6th -
Over a month before Korea's Financial Supervisory Service reported that 1.2 million leveraged retail accounts triggered margin calls July 13.

Result: 320K- 360K accounts were fully liquidated.

See why I say:

PARABOLAS ARE TRAPPED LONGS WHO TRIGGER VOLATILITY AND LIQUIDATION EVENTS

So let’s talk about US finra margin debt chart… 💣

[zerohedge @zerohedge]

Morgan Stanley also expects 80GW in new compute coming online from now until 2028. That translates to $4-$8TN in capex spending in just 3 years, all of which has to be funded with debt and equity (no more positive FCF).

[mugenpower78 🦇🔊 @limkw78]

@tatthang Solana will be his 15th failed attempt

[Richard Gage, AIA, Architect @RichardGage_911]

[RG911Team] This fact alone proves 9/11 was a false flag.

The Twin Towers were designed with the lightest, thinnest steel on the top floors, and each lower section used thicker, heavier and stronger steel than the one above it. This made a progressive collapse IMPOSSIBLE.

The idea that a thin, light steel beam would collapse and then crush thick, strong steel below it… and that would in turn crush the even thicker and stronger steel below it… all through the path of GREATEST resistance… all in less than 12 seconds… violates the laws of physics.

This is why FDNY sent hundreds of their best firefighters in those buildings. They knew the planes and fires could not completely collapse the towers because the extremely robust design would easily withstand it.

343 firefighters died on 9/11 because they were caught off guard by something no one expected - every single column being ripped apart and blown in every direction.

And the only force that can do that requires explosives.

[Dr Teck Khong @DrTeckKhong]

We have already started seedless humans.

[NIK @ns123abc]

>be Chang Liu
>senior system electrical engineer at Apple
>8 years working on iphone
>january 2026: leave Apple to join OpenAI
>apple asks for laptop back
>ignore them
>lmao it’s my laptop now
>within HOURS of leaving
>message Yu-Ting “Alyssa” Peng, friend at Apple:

Liu: “I still have another computer”

>uses it to access Apple secret info
>within weeks, use HER Apple work laptop
>february 9: try Apple’s network storage
>cloud repo of confidential engineering files
>authentication bug. still works!
>message Peng: “LOL, I found out I can access the [network storage], so funny”

Peng: “I’m ready”

>while developing hardware for OpenAI
>download DOZENS of confidential files
>including a thousand-plus-page compilation of technical files
>including MLB (main logic board) manufacturing + testing presentations

>send Peng links to Apple’s proprietary folders
>point her to specific project data
>coach her how to copy files “to avoid trouble with the security team”
>tell her which confidential Apple materials to study before her OpenAI interview
>warn her another guy “fumbled” Tang Tan’s questions about a secret Apple project
>“download some info” for her to review

>tell her: switch to LINE Messenger so nobody sees this
>she gets the OpenAI offer, leaves Apple April 16
>meanwhile every message was left on APPLE-ISSUED WORK LAPTOPS

>july 10: Apple Inc. v. Chang Liu
>named first. before OpenAI. before Tang Tan

LOL
so funny

[Visegrád 24 @visegrad24]

BREAKING:

The EU today introduced the new requirement for all new cars registered in Europe to have installed cameras filming the driver’s face.

The system is called Advanced Driver Distraction Warning, ADDW, and is part of the EU’s General Safety Regulation.

The camera tracks the driver’s gaze, head movements and attention.

According to the regulations, the system must be active from 20 kilometers per hour. At lower speeds, it should be able to warn if the driver looks away for too long, while the requirements become stricter at higher speeds.

The requirement does not yet mean any obligation to record the driver for the authorities.

Critics warn that the technology could pave the way for more extensive monitoring and recording in the car once the cameras, sensors and software are installed.

[Dr. Maalouf ‏ @realMaalouf]

Historian Bill Federer: "By 2030, there will be a majority Muslim population in Europe, and they will just flat out vote in Sharia law.

People forget Egypt was completely Christian for 6 centuries. It's not anymore. All of North Africa was completely Christian for 6 centuries. It is not anymore.

Constantinople was the largest Christian city in the world, and the largest Christian church in the world for hundreds of years was the Hagia Sophia. And it was turned into a mosque.

They want to do the same thing with the Vatican."

Pay attention to what he’s saying!

[Tulsi Gabbard 🌺 @TulsiGabbard]

Yesterday was my final day as Director of National Intelligence. I declassified and released never-before-seen documents exposing the truth about Fauci directing millions of US taxpayer dollars to fund dangerous gain-of-function research at the Wuhan lab, worked with the Intelligence Community to suppress the truth about his actions and hide the virus’ lab-leak origins, and lied to Congress while under oath in 2024. It’s time you know the truth. Go to https://t.co/tVwWp0TxZ4 to see for yourself.

[mugenpower78 🦇🔊 @limkw78]

@CryptoKaleo REKT

[mugenpower78 🦇🔊 @limkw78]

@Zac_labs Dude 20% of global semi equipment is manufactured in SG. And is increasing yoy

[Milk Road AI @MilkRoadAI]

This is WILD!

Something very large is happening in global bond markets, and most people are completely missing it (Save this).

The hyperscalers, Amazon, Google, Microsoft, and Meta have collectively committed $725 billion in capital expenditure for 2026 alone, up 77% from the $410 billion record set in 2025, and Goldman Sachs projects total combined capex from 2026 through 2031 reaching $7.6 trillion.

Those numbers are so large they have broken the American bond market's ability to absorb them.

In 2024, not a single dollar of hyperscaler bond issuance was in a non-USD currency.

In 2025, 100% of new non-USD issuance was new meaning the category barely existed the year before.

By 2026, non-USD currencies already account for 48% of hyperscaler bond funding, with the euro at 52% of that slice, JPY at 15%, CAD at 14%, GBP at 12%, and CHF at 7%.

Bank of America confirmed the shift, hyperscalers have doubled the non-dollar share of their bond funding to 30% of total issuance in 2026.

The individual deal sizes tell the story of how fast this is moving.

In May, Alphabet issued ¥576.5 billion approximately $3.6 billion in yen denominated bonds, the largest yen bond ever sold by any non-Japanese company in history, surpassing the previous record set by Berkshire Hathaway in 2019.

Then Amazon came in June and issued C$14 billion in Canadian dollar bonds, the largest corporate bond ever sold in the Canadian market, attracting over C$28 billion in investor orders, nearly double the amount ultimately sold.

Amazon's single Canadian deal surpassed Alphabet's previous record Canadian issuance of C$8.5 billion set just weeks earlier in May.

Alphabet has now set borrowing records in yen, Canadian dollars, Swiss francs, and sterling in a single calendar year.

Morgan Stanley projects euro borrowing by hyperscalers will hit €50 billion in 2026 potentially making the United States the single largest source of corporate debt issuance in the entire eurozone, ahead of France.

Global AI-related debt issuance is projected to reach $570 billion for the full year 2026, according to Morgan Stanley more than double the pace of the same period last year and nearly four times the 2022 level.

The AI infrastructure buildout is so capital-intensive that even the most cash-rich companies in human history, Apple, Microsoft, Alphabet, Amazon, and Meta collectively hold over a trillion dollars in cash and near-cash assets have concluded they cannot self-fund it.

And they are barely started.

Come join Milk Road Pro for our full breakdown, what $7.6 trillion in hyperscaler capex means for global credit markets over the next five years and our entire Ai thesis.

Link below!

[mugenpower78 🦇🔊 @limkw78]

@saylor The ticker symbol is $ETH

[JustDario @DarioCpx]

To go out publicly and say what he is saying, @edzitron has balls the size of the Las Vegas sphere

[Hedgie @HedgieMarkets]

🦔GitHub Copilot switched to token-based billing this morning and users are already out of credits. Pro+ subscribers paying $39 a month are reporting 60% of their credits gone in two hours of normal use. One user lost 20% of their allowance from a single file review with no code changes. Another hit their monthly cap before the calendar even flipped to June.
Orgs with shared token pools have no way to see individual usage, so entire teams get cut off when one person runs a heavy prompt. Users are canceling and moving to Claude Code and Codex. GitHub community forums are on fire.

My Take
Flat-rate AI subscriptions were always subsidized. Everyone in the industry knew it. Today the subsidy ran out for a few million developers at once. The problem is a lot of companies already restructured around these tools. They cut headcount and told remaining engineers to lean on Copilot instead of building skills internally. Those companies now depend on a tool whose cost just became unpredictable and whose usefulness completely changes when you have to ration prompts to stay under budget.

The developers moving to Claude Code and Codex will hit the same wall eventually. Every AI provider faces the same unit economics. Anthropic filed its S-1 this morning, and the durability of its revenue depends on whether customers stick around once real pricing kicks in everywhere. If a $39 subscriber cancels after one day because the tool became unusable, multiply that across millions of seats and the churn risk becomes very real.

Today showed what happens when AI pricing meets reality. The companies that built their workflows around cheap tokens just discovered the tokens aren't cheap anymore and the people who knew how to do the work without them are already gone.

Hedgie🤗

[mugenpower78 🦇🔊 @limkw78]

@zerohedge Michael "I will never sell bitcoin" Saylor

[Data Driven Stocks @stockdatamarket]

@michaeljburry Had a similar conclusion last month

[Bull Theory @BullTheoryio]

🚨Michael Burry just said Elon Musk and Nvidia's deal is built on fake numbers.

Burry published a detailed breakdown calling the entire structure "Fugazi", his word for fake.

He is alleging that billions of dollars in Nvidia chips are being hidden off balance sheets, and that American retirees are unknowingly funding the whole thing.

Nvidia, the world's largest AI chip company sold $5.4 billion worth of its most advanced GPUs, the GB200, to a company called Valor.

Valor is not a real operating business. It is a special purpose vehicle, a shell company created specifically to hold these chips and nothing else. Nvidia also invested $1.9 billion of its own money directly into Valor on top of the sale.

Those 100,000+ chips are now physically inside xAI's data center. xAI is Elon Musk's artificial intelligence company, the one that builds Grok. xAI is using every single one of those chips right now to run its AI models.

But here is what Burry is flagging.

Neither Nvidia nor xAI owns those chips on paper. Valor, the shell company holds legal title. That means $5.4 billion in GPU assets do not show up on Nvidia's balance sheet as inventory.

They do not show up on xAI's balance sheet as assets. They are legally invisible to both companies.

Nvidia gets to book the $5.4 billion as a completed sale and record it as revenue. xAI gets full use of the chips without owning them. And the risk disappears into a shell company in the middle.

Now here is where American retirees enter the picture.

Valor needed $3.5 billion in debt to fund this structure. Apollo provided it. Apollo is one of the largest asset managers on earth with $1.03 trillion under management and $834 billion specifically in private credit.

Apollo raised the $3.5 billion, packaged it into debt securities, and sold those securities to Athene.

Athene is Apollo's own insurance company. It sells fixed and indexed annuities, retirement savings products, to ordinary Americans.

When a retiree buys an Athene annuity, they believe their money is sitting in safe, stable investments. That money is now inside a structure funding Elon Musk's AI data center.

The numbers inside Athene are most alarming.

Athene holds $74.2 billion in reserves. It has moved $217 billion in assets into a captive insurer based in Bermuda, meaning those assets sit outside normal US insurance regulation and oversight.

Of the entire portfolio, 34.7%, equal to $103 billion, is classified as Level 3 assets.

Level 3 is an accounting classification that means there is no observable market price for these assets. No outside party can independently verify what they are actually worth.

The leverage sitting on top of those unpriced assets is 16 times.

Burry's says:
Every step of this structure is technically legal and publicly disclosed. But the entire thing was deliberately engineered across 8 to 12 steps to move credit risk off balance sheets and away from any market pricing.

- Nvidia books the revenue.
- Apollo collects the fees.
- xAI gets the computing power.
- And retirees sitting at the bottom of a 16x leveraged Bermuda insurance structure, holding $103 billion in assets with no market price carry the risk without knowing it exists.