Big Tech just ran out of money building AI and what they're doing to cover it up should be illegal.
Google, Amazon, Microsoft, and Meta are spending a combined $700 BILLION this year on AI infrastructure.
This eats up 94% of their total operating cash flow.
The richest companies in human history are almost broke. And instead of slowing down, they're covering it up with the biggest financial engineering operation since 2008:
Google just sold $80 billion in stock to fund AI infrastructure. That was their first equity raise in 20 YEARS.
The last time Google needed to sell stock, YouTube didn't even exist. Sundar Pichai admitted the thing keeping him up at night is "compute capacity."
The company that prints $100 billion a year in ad revenue just told Wall Street it isn't enough anymore.
Amazon's free cash flow is projected to go NEGATIVE this year for the first time ever. Morgan Stanley estimates a $17 billion deficit and Bank of America says $28 billion.
The most profitable logistics machine on Earth is about to burn more cash than it generates, and they quietly filed with the SEC saying they may need to raise even more debt and equity to keep building.
All four hyperscalers are now borrowing hundreds of billions in bonds to keep the AI buildout alive. These were the most cash-rich companies in human history, and they're leveraging themselves to the teeth to build infrastructure that nobody has proven will generate enough revenue to pay for itself.
And the cracks are already starting to show:
Broadcom makes the custom AI chips that power Google, Meta, OpenAI, and Anthropic. This week their AI revenue TRIPLED year over year, sales grew 48%, and profits smashed every Wall Street estimate.
The reward for all of that was $320 billion in value erased in a single trading session.
Their CEO Hock Tan went on the earnings call and exposed three things about the AI industry:
Google is already shopping for cheaper AI chip alternatives, broadcom abandoned its strategy of selling complete AI systems and is now retreating to selling bare chips at lower margins.
And despite supposedly "unprecedented demand," Tan refused to raise his full-year forecast, which tells you everything about what he's actually seeing behind the curtain.
Wall Street heard all three and hit the sell button so hard it dragged AMD, Intel, and the entire chip sector down with it.
When a company triples its AI revenue and gets punished because tripling isn't fast enough, the expectations have left the atmosphere entirely.
And here's the really scary part...
These companies ARE your retirement account. Apple, Microsoft, Amazon, Google, Meta, and Nvidia make up roughly 30% of the S&P 500. If you have a 401k or an index fund, you are already exposed to this bet whether you chose to be or not.
Every single one of these companies is telling you AI will generate trillions in revenue. But right now the math says they're spending trillions FIRST and hoping the revenue shows up later.
If the revenue catches up, this becomes the greatest infrastructure buildout in human history. Bigger than railroads and bigger than the internet.
If it doesn't, the companies that make up a third of the American stock market just leveraged their balance sheets into the largest write-down cycle since 2000.
And unlike the dot-com crash, this time the bubble companies aren't random startups with no revenue. They're the backbone of the entire global economy.
🚨🔈 BREAKING: UFO DISCLOSURE MOMENT OF TRUTH ON JUNE 9TH! 🔥🛸
James Fox and Leslie Kean are teaming up with UAP whistleblower David Grusch and a bipartisan crew of Congress members (including Reps. Tim Burchett, Anna Paulina Luna, Eric Burlison, and Jared Moskowitz) for an unprecedented press conference on the steps of the U.S. Capitol Tuesday, June 9th at 1:00 PM ET.
They're issuing a direct call to action to the President demanding the release of specific "groundbreaking conclusive files" on UAPs/nonhuman intelligence, crash retrievals, and reverse engineering programs, plus pushing hard for new disclosure legislation.
Major news media are confirmed to attend.
This builds on Grusch’s 2023 sworn testimony about multi decade programs involving non human craft and biologics that he was denied access to. James Fox (The Phenomenon, Moment of Contact) and Leslie Kean (the 2017 NYT Tic Tac bombshell) bring decades of investigative credibility.
If these files drop as demanded, we could finally see hard evidence of NHI tech and bodies that changes humanity forever, ending the decades long coverup, limited hangouts, and gatekeeping.
This timing (right after recent UAP document releases and before more expected drops) feels like the tipping point toward full transparency.
Is the simulation glitching toward truth? Or are we witnessing the biggest paradigm shift in modern history?
The public deserves answers. Reality shouldn't be classified. Stay tuned, June 9th could be legendary!
🚨 OCEAN GATEKEEPERS EXPOSED: NAVY ADMIRAL CONFIRMS USOs & LEGACY PROGRAMS HIDING NHI IN OUR SEAS! 🌊🛸
In a June 4, 2026 Sol Foundation interview, Rear Admiral Tim Gallaudet (Ret.), ex Navy Oceanographer, confirmed credible whistleblower intel on non human craft/biologics recovered in legacy programs.
He highlighted Navy USO data: transmedium objects diving in/out of the sea (e.g. SoCal canyons), 1980s North Atlantic sonar tracks of torpedo speed anomalies, and 70% unexplored ocean as perfect NHI hideout.
If NHI are operating freely in our oceans, transmedium, outperforming our best subs, tied to decades of legacy crash retrievals, this isn't just "anomalies."
It's evidence of a longterm presence on Earth, with governments (US and others) sitting on paradigm shifting tech and knowledge while we map <25-30% of the seas.
Recent momentum (2024-2026 hearings, Sol symposia, whistleblowers) suggests we can expect more ocean focused revelations soon.
🚨1961 Wisconsin UFO encounter: Joe Simonton watches a flying saucer land in his yard.
A 5ft tall alien motions for water, then another hands him a stack of hot pancakes fresh off the grill.
Joe takes a bite… “If that's their food ... God help them... tastes like cardboard.”
A classic example of High Strangeness.
Mira Murati says human-AI collaboration needs models that can listen while they think:
"The types of models that we work with today, they're very turn-based. You talk, they talk, then they go off and think."
"While they're thinking, it's almost like they're deaf and blind. They cannot perceive anything else about what's going on."
"By contrast, our interactions with each other are very rich. There is a lot of information in our interactions when we are silent, when we're thinking, when we're interrupting one another."
"Interaction models are able to capture all of this nuance. They're not turn-based. They're more like time-based interaction, where they're continuously taking in audio, text, video, and continuously providing output."
"This enables you to catch things like interruptions and simultaneous speech, and really create a rich, high bandwidth interaction between humans and machines."
@miramurati at Bloomberg Tech live with @emilychangtv
The progressive, natural occlusion of this spherical object by the clouds is incredible.
(We know this is not a solar lens flare because the camera was pointed 50° below the horizon and moved in ways entirely divorced from the object’s motion.)
Excellent work by @nipponsteel!
When skeptics call a daytime UAP case anomalous, you stop scrolling.
South Korea, 2019.
Two glowing orbs blink, vanish, and seem to “teleport” across the sky.
Whatever they are, they’re beautiful.
#UAP#UFO
@SadlyItsBradley Huh? Meta's investors have had to essentially beg Mark Zuckerberg - the controlling shareholder of the publicly traded company - to stop being proud of it being a VR company.
But this doesn’t mean there isn’t a lot of value to be had now. A lot of people who lived through the “DIY” era of VR are still here
And they are making magical things. That impress me weekly. But those magical things won’t put a glimmer in any of the giant players’ eyes
I feel people expect me to like everything about XR. Including the things that “might” propel it to mainstream
Well that ship has sailed a long time ago for me. I’ve accepted I’ll probably have to wait another 10 years before a publicly traded company is proud to be a VR company
MAJOR UAP NEWS: James Fox and Leslie Kean join forces with members of Congress and whistle blower David Grusch in an unprecedented call to action directly to the President this Tuesday, June 9th. Major news media have committed to attend the Press Conference which will push for the passage of disclosure related legislation and release of ground breaking conclusive files.
#UAP, #UAPX, #UFO, #UFOX, #UFOTWITTER, #OVNI, #disclure, #disclusureday
Google has published a paper that might end the transformer era.
For the last 7 years, every major AI, ChatGPT, Claude, Gemini, has been built on the exact same architecture: The Transformer.
But Transformers have a fatal flaw.
To remember context, they have to process every single word against every other word. It’s called quadratic complexity. As your prompt gets longer, the compute cost explodes.
The alternative is the old-school RNN (Recurrent Neural Network). RNNs are incredibly cheap and fast, but they have a fixed memory size. If you give them a long document, they get amnesia.
Until today.
Google researchers published Memory Caching: RNNs with Growing Memory.
And it fixes the biggest bottleneck in AI.
Instead of an RNN having a fixed, rigid memory that constantly overwrites itself, Google gave it a "save" button.
The technique allows the RNN to cache checkpoints of its hidden states as it reads.
The memory capacity of the RNN can now dynamically grow as the sequence gets longer.
They built four different variants, including sparse selective mechanisms where the AI actively chooses exactly which checkpoints matter most.
The results rewrite the rules of efficiency.
On long-context understanding and recall-intensive tasks, these new Memory-Cached RNNs closed the gap with Transformers.
They achieved competitive accuracy without the explosive, quadratic compute cost. It perfectly bridges the gap between the cheap efficiency of an RNN and the massive capability of a Transformer.
We have spent billions scaling Transformers because we thought they were the only way an AI could remember a long conversation.
But Google just proved we don't need to process the whole history every single time.
We just needed a smarter cache.