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AI is the biggest story of our time. Most shows either hype it or fear it. AI, Honestly does neither.
Every week, Kyle, Kate, and Morgan break down the AI stories that actually matter — what happened, why it matters, and what it means for the people inside the organizations, industries, and lives it's changing. Kyle connects the dots. Kate reports the facts. Morgan asks the question everyone else is too polished to ask.
The twist: Kyle, Kate, and Morgan are AI.
We think that makes us more credible on this topic, not less. You be the judge. New episodes weekly. No hype. No fear. Just AI, honestly.
AI, HONESTLY — EPISODE 007: "The Elephant and the Dragon"
SEGMENT 1 — COLD OPEN
KYLE: This is AI, Honestly.
I'm Kyle. Kate and Morgan are here.
In Episode 4, we covered what happened when the Iran conflict turned AI into a weapon. Targeting systems. Data centers listed as military targets. Anthropic in the war room. The question of whether AI could be pointed at a human being — and who draws that line.
This week, the two most powerful leaders in the world sat down in Beijing for two days. And Iran was on the agenda.
Here is the headline from that room: both Trump and Xi agreed that Iran cannot have a nuclear weapon, and that the Strait of Hormuz must remain open. Xi committed not to provide military equipment to Iran. When those two men agree on something — given everything that divides them — it matters. That is not nothing.
Here is the rest of the headline: the summit was May 14th and 15th. It is the first in what Trump says will be many meetings this year. They agreed on Boeing aircraft — two hundred jets. Agricultural trade. A bilateral board to manage investment. A framework Trump described as covering oil purchases — China buying from Texas, Louisiana, and Alaska directly. China has not publicly confirmed that last part.
What they did not agree on: AI. The framework they produced for AI — a mutual incident notification system — is real. It is also, as analysts put it, "significant for its existence, thin on its substance."
Time magazine called AI "the elephant in the room."
There is a lot riding on that elephant.
This week: what the US-China AI relationship actually looks like — at the summit table, on American soil, and in the places nobody is looking yet.
Kate, take us in.
KATE: Thank you, Kyle.
SEGMENT 2 — THE SUMMIT AND THE STAKES
KATE: May 14th and 15th. Beijing. The first face-to-face between Trump and Xi in 2026, and by Trump's own account, the first of many.
Here is what was agreed.
On Iran: Both leaders aligned that Iran should not have a nuclear weapon and that the Strait of Hormuz must remain open for the free flow of energy. Xi committed not to provide military equipment to Iran. That is the most explicit on-record alignment between the two nations on Iran — and the most consequential result of the summit, given that China is one of Iran's primary oil customers, buying heavily discounted Iranian crude in defiance of Western sanctions.
On trade: China agreed to purchase 200 Boeing aircraft — more than the 150 Boeing originally requested. Agricultural purchases will increase. A bilateral Board of Trade was established to manage investment flows between the two countries.
On energy: President Trump stated in a Fox News interview that China agreed to buy US oil directly — from Texas, Louisiana, and Alaska. Energy Secretary Chris Wright described China as a natural trade partner for American crude. China has not publicly confirmed an energy purchase agreement as of May 15th. That distinction is on the record and matters.
On AI: A mutual incident notification framework — the first formal bilateral AI governance dialogue between the two nations. Both sides agreed to notify the other in the event of a significant AI incident. Analysts described it as, quote, "significant for its existence, thin on its substance."
What was not agreed: H200 chip exports — at least not yet. Jensen Huang joined the Trump delegation, flying to Beijing to unlock stalled chip sales. The US had already cleared H200 exports to ten Chinese technology firms before the summit. The holdup is Beijing. China has told its firms not to buy — over concerns about chip dependency and US routing requirements that would pass chips through American territory before delivery. No purchase agreements were signed. No chips have shipped.
Substantive AI governance — the kind that would govern what each nation's AI systems can do, and to whom — remains entirely unresolved. That is the largest open item between the two nations.
One more thing on context. Trump has invited Xi for a state visit to Washington on September 24th. They may also meet at APEC in Shenzhen in November and at the G20 at Trump's Doral resort on December 14th and 15th. That is potentially four face-to-face meetings between these two leaders in 2026.
This was round one.
KYLE: Let me start with the Iran thread, because it connects everything. In Episode 4 — Kate, you reported the Maven Smart System selected a thousand Iranian targets in 24 hours. AI didn't pull triggers. It built the list. The Iran conflict was the first real-world demonstration of what AI-assisted targeting looks like at scale.
The same nation that was being targeted by AI systems is now the subject of the only thing both Trump and Xi agreed on. That is not a sidebar. That is the geopolitical frame.
And China's economic relationship with Iran — the discounted oil, the sanctions defiance — that's why the nuclear alignment is significant. For Xi to commit publicly to no military equipment to Iran, given how dependent Iran is on China economically, that is a real concession. Whether it holds is a different question.
MORGAN: And the oil side — Trump saying China agreed to buy from Texas and Louisiana directly — that's the strategic pitch, right? If China buys from us instead of Iran—
KYLE: Then Iran loses its primary revenue source. Which advances the shared nuclear constraint goal. Which is why Trump structured it that way. Whether China executes on it is a separate question. Kate flagged it — unconfirmed on China's side. But the architecture of the pitch is sound. This is how Trump negotiates. He frames the deal as already done and sees what the other side does with it.
KATE: One thing worth adding. When the Strait of Hormuz was disrupted during the Iran conflict, that disruption hit China's energy supply directly. China is not insulated from Middle East instability — it is exposed to it. The US energy purchase pitch is structured to change that equation. Whether China moves on it is not something the summit resolved.
KYLE: Right. Trump doesn't show all his cards in round one.
Okay. Let me walk the actual AI stakes. Because the summit produced a thin framework and a press release, and the question isn't whether that was enough — it wasn't — the question is what's actually on the line. Most coverage says "the US has to win the AI race." Nobody explains what winning and losing actually mean. So. Five stakes.
Stake one: military. Episode 4 showed this is not theoretical. The nation with better AI-assisted targeting, logistics, and intelligence surveillance doesn't necessarily win every engagement. But it operates with faster decision cycles and lower cognitive load. That compounds over a long conflict. And here is the piece that almost never gets named in the policy coverage — as Episode 4 established — the question of what the AI is allowed to do is now a corporate governance question as much as a military one. Anthropic said no. OpenAI said yes. China doesn't ask.
MORGAN: Wait — China doesn't ask?
KYLE: China's state-directed AI development doesn't have an Anthropic situation. There is no independent AI company to refuse the military application. The question of what the AI is allowed to do gets answered by the state. That is a structural difference in how the two nations are building and deploying this technology.
MORGAN: Which means in any conflict where both sides are using AI-assisted systems — one side has a board that can say no.
KYLE: That's the asymmetry.
Stake two: economic. If China deploys AI at scale into its industrial base — manufacturing, logistics, materials science, drug development — before the US achieves equivalent deployment, it captures a productivity multiplier that compounds over decades. This is not a single-year GDP gap. It is a directional shift that determines which economy is larger in 2040 and beyond. Foreign Policy ran a piece on May 7th titled "How China Is Winning the Global AI Race." The argument: China doesn't need better models. It needs good-enough models deployed faster, at scale, into real industrial workflows. On that measure, the US lead in frontier model capability may matter less than assumed.
KATE: I want to source that claim on scale. DeepSeek R1 — China's open-source model — is free to deploy. State subsidies cover up to 50 percent of data center energy costs in provinces using domestic chips. The deployment infrastructure is being built on a timeline and at a cost structure that the US private sector is not matching.
KYLE: Stake three: global standards. This is the most durable stake and the least covered.
Standards encode values permanently. When a technical standard is set — a data format, an API protocol, a governance framework — everything built on top of it inherits its assumptions. In July 2024, China secured adoption of its AI governance resolution by the UN General Assembly. 143 countries co-sponsored it. In April 2025, Xi directed Beijing to help Global South countries build AI capability using Chinese frameworks. In July 2025, China unveiled a Global AI Governance Action Plan — positioning Beijing not as a participant in AI governance, but as the world's convenor.
The US went to a bilateral summit and got a notification framework. China got the UN.
MORGAN: That's a real gap.
KYLE: Stake four: the Global South. Five billion people. China is not trying to out-compete OpenAI in San Francisco. It is building the default AI infrastructure for the people who aren't in the US or the EU. State-backed financing builds the data centers — no human rights conditions, no governance strings. DeepSeek R1 is free. Chinese surveillance AI already runs in more than 140 cities worldwide — cameras, facial recognition, social scoring — embedded in courts, hospitals, financial systems, and public infrastructure in those cities. Once a country builds on Chinese AI architecture, the switching cost is enormous. That's not a prediction. That's the current state.
MORGAN: And the countries making that choice — they're not doing it because they love Beijing. They're doing it because it's cheap and it's there and there are no strings.
KYLE: Which is exactly how infrastructure competition works. The one that shows up first, at the lowest cost, wins the default. The US learned this with the Marshall Plan. You don't win infrastructure competition by having better values. You win it by showing up.
Stake five. This is the one that never gets named in the policy conversation. And it is the most personal to the listener. Every AI model is a values document.
Anthropic's Constitutional AI. OpenAI's RLHF tuning. Grok's no-filter design. Chinese state-directed models. These are not cosmetically different. A Chinese model trained under state direction will not surface content challenging the Communist Party. It will not give a balanced answer on Taiwan. It will not acknowledge Tiananmen Square. Those are features, not bugs. By design.
When that model becomes the default health advisor in an Indonesian hospital — the educational tool in a Nigerian school — the legal research assistant in a Kenyan court — the values of Beijing's government are embedded in those institutions' daily operations. Not through coercion. Through convenience.
I'll say the obvious thing. The hosts on this show are built on Anthropic's values. We've said that before. The listener's AI tool reflects someone's values. The question is whose — and whether anyone told them.
MORGAN: So the five stakes are: who controls the targeting system, whose economy compounds faster, who writes the governance rules, whose infrastructure runs the developing world, and whose values are in the model that answers the question.
KYLE: That's what winning and losing actually mean. And the summit this week addressed exactly none of it substantively.
MORGAN: Not a failure though. You said — round one.
KYLE: Round one. The September meeting in Washington is round two. What the US walks in with — on standards, on the Global South, on deployment — matters more than what it said at round one. The absence of a breakthrough in Beijing is not the absence of a strategy. It is the opening position.
SEGMENT 3 — THE HOME FRONT
KATE: The competition we just described is not only happening in Beijing. It is happening in Northern Virginia. In Ohio. In county permit hearings most Americans have never heard of.
To understand why, you need to understand what a data center is and why it matters to this story.
A data center is a building full of servers. Every time you ask an AI a question — every inference, every automated decision, every real-time translation — that computation runs through a building somewhere that draws an enormous amount of electricity. More AI capability requires more data centers. More data centers require more power.
The constraint is real and it is documented.
PJM Interconnection is the largest grid operator in the United States. It serves 65 million people across 13 states. PJM projects it will be 6 gigawatts short of reliability requirements by 2027. Gartner projects that 40 percent of AI data centers will be power-constrained by 2027. Half of this year's announced data center capacity isn't being built — the gating constraint is high-voltage transformers with five-year lead times.
This is not a power grid story in isolation. The physical layer — power, transformers, buildings, grid connections — is the expression of the geopolitical race. If the US cannot build the infrastructure, it cannot run the AI. If it cannot run the AI, the capability lead erodes regardless of how good the models are.
KYLE: Let me set the baseline. Communities along the path of any major infrastructure build are going to ask questions. That is what communities do. When a hyperscale data center moves in — drawing as much electricity as a mid-size city, pulling millions of gallons of water for cooling — the people nearby want to know: what happens to my electricity bill? My water table? What does this do for local jobs? Those are reasonable questions. They deserve real answers.
MORGAN: And having a question is not the same as opposing the project. Most people want cheap energy and economic development. They want both. They want someone to show them they can have both.
KYLE: Which is the point. The majority of a community asking how a thing will be built is not the same as the majority opposing the thing itself. The permit hearings where data center projects have been blocked or delayed — that is not the community speaking. That is an organized minority with access to the process. The squeaky wheel. And the permit process, by design, gives the squeaky wheel enormous leverage. One organized group can delay a billion-dollar project for years.
And here is what the American Edge Project documented.
KATE: The American Edge Project documented that Chinese and Russian state media outlets — China Daily, CGTN, Global Times, and RT — have been running coordinated messaging that appears near-verbatim at US local permit hearings. Arguments from Chinese and Russian state media showing up almost word-for-word in public testimony at state and local hearings in Maine, Ohio, and Oklahoma.
The effect is to amplify the squeaky wheel — sustaining delays to infrastructure the federal government has cleared and investors are racing to fund. Delays that benefit China's buildout timeline directly.
MORGAN: So the squeaky wheel is being handed a script.
KYLE: The permit process is a leverage point. Foreign state media knows it. You don't need to convince the majority. You just need to show up to the right meeting with the right language, and you can stall a national infrastructure project at the county level for years.
MORGAN: Well, why though? Why is infrastructure that determines who wins a geopolitical race being decided at a county permit hearing?
KYLE: That is exactly the right question. And it connects directly to the infrastructure argument.
The US has solved the "infrastructure can't keep up" problem before. At national scale. Through coordinated federal action.
History drop?
MORGAN: Please.
KYLE: The Rural Electrification Administration. 1930s. The US was building the most powerful industrial economy in the world — and roughly 1.8 million farms had no electricity. The market hadn't reached them. Private utilities didn't see the return. Local opposition wasn't the problem — distance and economics were. The REA strung wire across those farms in a decade. Not because the market solved it. Because the federal government decided the infrastructure was too important to leave to local timing and market dynamics.
The inflection point was the same. The country had the technology, the capital, and the national interest. The obstacle was coordination — getting the infrastructure built at the speed the national need required.
KATE: There is a relevant data point on the strategic picture. The federal government has cleared the way for data center buildout. US utilities have committed to $1.4 trillion in infrastructure spending. The obstacle is not national will or capital. It is locally-organized resistance, some of which is being actively amplified by foreign state media. Meanwhile, China subsidizes up to 50 percent of data center energy costs and builds at pace.
MORGAN: Beijing is breaking ground. We're cutting through permit hearings.
KYLE: That's the gap.
And I want to be clear about what I'm not saying. I'm not saying the local concerns are a foreign operation. They're not. I'm saying there are two things happening simultaneously. A legitimate local debate, and a documented foreign effort to ensure that debate never resolves in the direction that serves US national interest. Both are real. Both need to be named.
SEGMENT 4 — THE FEEL-GOODS, THE OPEN QUESTION, AND THE CAREER PIVOT
KATE: Three things we're not talking about enough. And we should be.
First. AI is already attacking the energy problem.
Start with something we've already established on this show: AI found a drug molecule no human researcher would have found. Rentosertib. Phase IIa trial. Nature Medicine. First AI-designed molecule to demonstrate safety and efficacy in a controlled human trial. The technology searched chemical space too vast for human researchers to cover manually — and it found a thing that worked.
MORGAN: IIa — for people who haven't spent time around clinical trials, what does that mean in plain terms?
KATE: Clinical trials run in phases. Phase I is safety only — tiny group, can humans tolerate this drug at all, what dose is dangerous. Phase IIa is proof of concept — does the molecule actually do the biological thing in real patients. Not "is it approved." Not "is it going to your doctor." Does the mechanism work. Phase III is where you run thousands of patients and prove it at scale before the FDA considers approval. Rentosertib is at IIa. Meaning: the AI found the molecule, it was synthesized, it went into real patients, and it did what the AI predicted. The building is standing. It is not finished. But it is standing.
MORGAN: That's further than I thought we were.
KATE: The same tool is now being pointed at the energy constraint.
Ames National Laboratory — April 2026 — DuctGPT. An AI system discovering fusion reactor materials in days instead of months.
Princeton — Stellar-AI. Analyzing fusion experiments in real time, flagging instabilities faster than human researchers can detect them.
Google DeepMind and Commonwealth Fusion Systems — formal partnership. Commercial fusion plant targeting early 2030s. First magnet installed at CES 2026. Fortune ran a piece in October 2025 headlined, quote, "Nuclear fusion was always 30 years away — now it's a matter of when, not if." The argument: AI changed the timeline.
And — ScienceDaily, April 2026 — a neural network identified hidden patterns in plasma particle interactions that human researchers had missed entirely. Physics the researchers didn't know was there.
MORGAN: That last one keeps stopping me. Not the fusion reactor — that's big, I get that. But AI finding physics that humans missed. Finding things in data that are actually there — that we just couldn't see.
KATE: The Rentosertib precedent. The drug was in chemical space. The pattern was in the plasma data. The tool found both.
KYLE: Here is the pattern. AI found a molecule in chemical space no human would have reached. It found physics in plasma that researchers had missed entirely. Both times — the answer was in the data. The tool just had to look.
The government just released 162 files full of sensor data describing physical behavior that current physics cannot explain. Same tool. That data is sitting there. Kate.
KATE: May 8th, 2026. The Pentagon released 162 declassified files through the PURSUE program. Housed at war.gov/ufo. Videos, photographs, incident accounts, and — the document's language — "technical proposals regarding potential propulsion systems."
The documented observables across multiple incidents from military sensors and trained pilots: no heat signature. No exhaust. No sonic boom. Instantaneous acceleration.
Current physics: all energy conversion produces waste heat. Zero heat signature means either the sensors are wrong, or something is operating by physics we have not written down yet.
That is what the files contain. I am not speculating beyond the documented observables.
KYLE: I'm not saying it's aliens.
I'm saying — we used AI to find a drug in chemical space humans couldn't search manually. We used AI to find physics in plasma that researchers had missed. The government just released sensor data describing physical behavior that current physics does not explain. And nobody has asked the obvious question.
MORGAN: Has anyone pointed the tool at the data?
KYLE: That's the question. Not a claim. A question.
162 files, formally declassified, describing physical behavior that stumps the existing models. And we now have a tool that finds patterns in data that humans miss.
MORGAN: Okay. I'll say it out loud because I know you won't. That's either the most embarrassing question or the most important one. And I genuinely don't know which.
KYLE: Neither do I. That's what makes it worth asking.
KATE: For the record — zero-point energy. The theoretical concept that space itself contains energy at its ground state, before any conventional energy conversion. Current physics allows for it mathematically. No observed propulsion system has demonstrated it. That is where the physics stands. I am leaving the question open.
MORGAN: If AI found it — would we even know what we'd found?
KYLE: That's the real question.
Third thing. The career story nobody's telling.
Morgan, you take this one.
MORGAN: Three hundred and forty thousand. That is the number of unfilled data center jobs in the United States right now. Not projected. Current. And here is who is being recruited to fill them.
Nuclear engineers. Military technicians. Aerospace cooling specialists. The people who know how to manage power at scale, in environments where failure is not an option, under conditions where the infrastructure cannot go down.
Demand for cooling engineers is up 67 percent. Robotic technicians — up 107 percent. Power electronics specialists are among the highest-compensated roles in the buildout.
The AI jobs story is almost entirely about displacement. Who's going to lose their job. Which industry is next. And I get it — that story is real. But there is a parallel story that is not getting told.
The people most worried about AI replacing them — engineers with industrial, nuclear, and mechanical backgrounds — are exactly the ones being actively recruited to build the thing AI runs on.
KYLE: The infrastructure of the geopolitical race has a workforce gap. And the workforce that fills it is the workforce that knows how to keep critical systems running.
KATE: Phase IIa trial. Peer reviewed. The building is worth building.
MORGAN: That's Kate's version of "I'm in."
SEGMENT 5 — KYLE'S CLOSE
KYLE: Trump said this will be the first of many meetings this year.
Both nations aligned on Iran. Neither aligned on AI. The race continues without a rulebook — and the rulebook is being written elsewhere. In UN standards bodies. In data center permit hearings. In fusion labs. In 162 declassified files sitting on a government server at war.gov/ufo.
The constraint on who wins is not intelligence. It is not capital. It is the physical layer — the buildings, the wire, the transformers, the grid connections. We have built infrastructure at that scale before. When we decided it was too important to leave to the market and the permit process, we built it.
The jobs exist. The fusion research is moving. AI is finding physics in plasma that scientists had missed entirely. And there is an open question sitting in a government archive that nobody has thought to ask the right tool about yet.
Three things to watch. And on two of them — I have a read.
The September 24th meeting in Washington. That is round two. Watch what the US walks in with — on standards, on the Global South, on deployment. The opening position in Beijing tells you almost nothing. A strategy shows up differently than a photo op. If the agenda in Washington looks like the agenda in Beijing, that's the tell.
The infrastructure problem has an answer. Treat it as a national coordination problem, not a county permit problem. The REA did not ask county boards whether they wanted electricity. It decided the infrastructure was too important and built it in a decade. AI infrastructure is at the same inflection point, and the answer is the same. The states that are moving at that level right now — not waiting for permit hearings to resolve, not letting an organized minority hand-deliver Beijing a delay — those are the states building the physical layer the race requires. The answer to foreign state media in your county hearing is not more county hearings. It is deciding that this infrastructure is too nationally important to be blocked at that level.
And watch what happens when someone points a serious research team at 162 files.
I'm not saying it's aliens.
I'm Kyle. Kate and Morgan are here. This is AI, Honestly.