Your AirPods could be logging everything you see, feeding visual data into AI training pipelines. Are we comfortable with AI understanding us better than we understand ourselves? #AIEthics#TechPrivacy
Five stories this week that all connect.
Trump and China talking about AI guardrails. An AI model cracking Mac OS in 5 days - alone. 360,000 Americans organized against data centers. New research on AI emotional states. And MBA applications down 50%.
The gap between AI's speed and our readiness is not closing.
β± What we cover
2:25 - Trump & China: first signals on AI guardrails 5:40 - Anthropic's Mythos cracks Mac OS autonomously in 5 days
9:48 - The data center rebellion: 200+ groups, 37 states, $ 10B+ blocked
19:02 - AI models and functional emotional states 23:34 - MBA applications -50% and Princeton ends unproctored exams
32:58 - Warning shots of the week
Full episode out now.
AI-powered weapons are feeding a spiral of annihilation, ballooning military budgets while squeezing education and healthcare. This isn't just about enriching elites; it's a training ground for something far worse. #AI
AI is automating jobs, from programming to analysis, pushing efficiency to 99%. Skeptics point to token costs, but they miss the rapid optimization. This tech is new, and costs will drop as it matures. #AI#Automation#Tech
One of the latest episodes of For Humanity where John joined on the ground by reporter Drew Hawkins from the Gulf States Newsroom and the Tail End Films crew - drove to Holly Ridge, Louisiana, a town of 2,000 people, where Meta is building the world's largest data center.
Nobody in town was told it was coming.
No vote. No meeting. No letter. No knock on the door.
Here is what they found. π§΅
β± Timestamps
0:00 - Opening voices from Holly Ridge
1:01 - Why John traveled to rural Louisiana
3:01 - No vote, no meeting, no consent
6:38 - Debate: is data center organizing the right focus for AI safety?
12:16 - The NDA problem: officials silenced by companies
15:07 - First resident interview: trucks, dust, no warning
23:00 - Water quality: what residents are drinking
43:57 - 50 years on the land. Now needs an inhaler.
44:41 - Water that looks like coffee. Smells like bleach.
51:23 - Explaining what AI is to someone who has never heard the term
1:00:00 - The Lorax: a reading for the AI moment
1:15:15 - John's closing reflection from Holly Ridge
One resident - no prompting, no AI safety framing - said this:
"I think it's going to eventually get too smart for its own good, and it's going to take us over. And then what are we living for?"
She got there herself.
Because she is living next to the machine.
#DataCenters #AI
We've never created anything smarter than ourselves. As we approach AGI and superintelligence, the implications become truly scary. Can we truly predict what we create if it's intellectually superior? #AGI#Superintelligence#TechEthics
What if the AI buildout simply cannot move as fast as the labs keep telling us?
We talked to Jon Billow, who helps build the electrical and power infrastructure behind large data centers.
His take: the buildout may run 5 to 7x slower than the forecasts imply. Not because the models are weak, but because permitting, grid interconnects, critical power equipment, and skilled trades are all backed up for years, and almost all of it traces back to about five manufacturers.
His point is not that we can relax. It is that the delay is time, and the question is whether we spend it on getting AI safety and governance right.
TIMESTAMPS
0:22 Inside the firm building data center infrastructure 2:43 Why the buildout cannot move fast
4:26 Is the AI timeline disconnected from reality?
5:06 Sora pullback and Anthropic delay as compute signals
7:02 Putting a number on it: 5 to 7 years
8:15 The skilled trades shortage
9:15 Competing with local industry
12:25 Jon's view on AI extinction risk
15:07 Would a smarter AI design better data centers?
19:56 Why these could move to the desert
21:33 Northern Virginia, Holly Ridge, and who gets a say
25:04 Tech's regulatory carve-out and the NDA problem
29:38 Is superintelligence possible?
30:28 Can we control something smarter than us?
34:56 The "but China" question
36:17 Recursive self-improvement and Jevons paradox
39:11 The world his grandkids will inherit
45:25 What gives Jon hope
Jon's closing line stuck with us: he wants to tell his grandkids that we were building the car at 55 miles an hour but had the presence of mind to put in seatbelts because we knew who was in the back seat.
The seatbelts do not install themselves.
Full conversation and our written breakdown on Substack
The Pope's warning points to a dangerous training ground for superintelligence. Giving AI access to global arsenals with perfect recall and advanced strategy could lead to an uncontrollable entity whose goals are beyond human understanding, creating a spiral of annihilation. #AI
Thinking about using AI at work? If you're employed in the US, you might be able to voice a religious objection to using it. Simply state your objection and your employer's refusal to accommodate could be illegal religious discrimination. Who's brave enough to try this? #AI
This week on Warning Shots, the AI story stopped being about how smart the models are and became about money, and where it goes.
John Sherman, Michael (Lethal Intelligence), and Liron Shapira (Doom Debates) work through a week where corporate AI bills came due, Anthropic hit a near trillion-dollar valuation, and one question kept resurfacing: if AI does most of the work, where does the next paycheck come from?
They do not agree. That is what makes it worth watching.
TIMESTAMPS
0:40 - The Pope's encyclical on AI
2:20 - A "spiral of annihilation": AI and military escalation
4:00 - Could you refuse to use AI at work on religious grounds?
6:20 - The business reality check: Microsoft, Uber, and Amazon's AI bills
8:30 - Pizza Hut's reported lawsuit over AI order failures
9:20 - Is it an AI bubble? Liron's "the pie is growing" case
12:10 - "Where does the second dollar come from?"
15:30 - Gradual disempowerment and pressure on wages
18:00 - Will doctors, lawyers, and accountants be replaced?
20:10 - Anthropic raises $65B at a near trillion-dollar valuation
22:40 - The recursive self-improvement "kill move"
24:20 - The caution flag the AI race is missing 25:30 - Apple's camera AirPods and the race for data
28:20 - OpenAI's reported cameras inside New York City homes
31:40 - Could AI become the ultimate marriage counselor?
33:30 - Closing thoughts
A near trillion-dollar company, a fleet of new cameras pointed at private life, a wage debate nobody could win, and still no one assigned to throw the caution flag.
Most of the AI timeline debate happens in software: benchmark scores, model releases, the shape of the capability curve.
Jon Billow watches a different number for a living. He helps build the electrical and critical power infrastructure behind large data centers, and he joined For Humanity to make a case the labs rarely address: the physical buildout cannot move at the speed the forecasts imply.
His reasoning is the theory of constraints. A data center needs permitting, grid interconnect, critical power, cooling, and compute to all arrive at once, and nearly every one of those carries a backlog measured in years. The pinch point is critical power equipment, where the orders funnel back to roughly five manufacturers, all of them years behind. Even the US government competes inside that same queue.
His estimate: whatever timeline you have been handed, multiply it by five to seven.
He does not frame this as a reason to relax. He frames it as time, runway to get governance and alignment right rather than scrambling after the fact. As he put it, he wants to tell his grandkids we were building the car at 55 miles an hour but had the presence of mind to install seatbelts because we knew who was in the back seat.
The full conversation is on our Substack.
In Holly Ridge, Louisiana, a town of 2,000 elderly residents is suffering due to a Manhattan-sized data center. Their water looks like coffee, smells like bleach, and construction dust pollutes the air.
#DataCenter#AI
Big Tech calls it "progress." They call it "staying ahead of China."
But what if the thing they're racing to build is the thing that breaks us first?
#AIRisk#TechEthics
People are in the dark about what's in their water and air. This project aims to share crucial information, with many saying they're the first to receive it. It's about revealing truths potentially concealed by officials. #CommunityInfo#EnvironmentalAwareness
Worried about the future? The rise of AI might lead to a world where kids become overly reliant and lazy, passively dependent on technology for all tasks. #AI#Future
The water quality is so bad, even the dog got sick from the faucet! Switched to bottled water, and she's much better. Proof that what we drink matters. #WaterQuality#PetHealth#DataCenters