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All right, everybody. Welcome back to
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your favorite podcast, the AllIn
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podcast. Today we have a conspiracy
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corner episode for you. We're going to
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go over the 9/11 inside job. We're going
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over flat earth, JFK assassination. It's
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going to be all conspiracy all the time
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after our amazing blockbuster episode
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during Ski Week. We're going all
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conspiracy here. Our guest today, Alex
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Jones.
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>> How many views did it get? Nine views. I
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mean, it's tough when you have one out
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of four besties. It doesn't Michael
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Tracy is on standby.
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>> Not true. I can carry an episode for at
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least 400,000 views.
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>> I mean, you might. You might. I like
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your Hey, for people who don't know,
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Jimoth has his own YouTube channel. He's
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got his escape hatch for when this train
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wreck burns to the ground. He started
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his own YouTube channel. He's hedging
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his bets. Freyberg's working on his solo
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project. Everybody's doing solo project.
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The band's got a lot of solo projects.
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>> The Beatles are experimenting. The
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Beatles.
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>> They're experimenting. We had a little
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Yokoono situation going on here. You
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know what the number one topic for this
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show was by the all-in AI bot sacks.
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>> What's up?
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>> The number one was Daario versus Hegs,
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the uh Department of War versus
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anthropic was the number one topic
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selected by our AI bot as a programming
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note for folks. That decision will be
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made end of the day Friday when this
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podcast comes out. So, we will talk
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about it next week. But, let's get to
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work. We've got a full docket. The
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clawed kill list has expanded and an AI
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fanfiction substack tanked your 401k on
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Monday. Let's get into it. Anthropics
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generational run continues. They're now
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three for three in tanking different
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market sectors in February.
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Congratulations. This is like they they
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took the the mantle from Brad Gersonner
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uh tanking the market.
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>> The Enthropic list.
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>> It is February 3rd. Anthropic announces,
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hey, we got a legal plugin for Claude
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Co-work, Thompson Reuters, Lexus, Nexus,
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Legal Zoom, all down at least 10% since
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February 3rd. Then on February 20th,
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Claude Code Security is announced in a
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limited research preview. Stocks tank
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again. Crowd Strike, Cloud for Octa, all
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down. Then February 23rd, Anthropic
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announces Claude can modernize Cobalt
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databases. If you don't know Cobalt,
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that's the like oldest coding language
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in the world. That's where Sachs learned
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code when he was in college in the 70s.
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It's used for banking, payroll,
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government,
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>> healthare.
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>> Healthcare runs 95% of ATMs in the US
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and it powers social security payments.
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85% of all coal code runs on IBM
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machines. So IBM decided they would tank
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13% on Monday, their worst day since
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2000. 31 billion in market cap losses.
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So let's stop here before I get into the
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fanfiction piece.
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What's your take here of what's
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happening in the market, Shmath? Is this
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simply people are looking for an excuse
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to trim their positions because things
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have been top ticking all-time highs and
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people are just looking for an excuse or
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is this reality? Is this the go forward
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reality that AI is going to compress
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these kind of stocks because it solves a
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lot of problems?
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>> I'm going to give you two explanations.
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I don't know what percentage I would
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allocate
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across the two, but I think one is
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tactical and one is much more strategic,
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but I think both are happening. The
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tactical one is that we are at a moment
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in time where a lot of the smart money
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hedge funds are starting to massively
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degross. And what that means is they're
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trimming a lot of positions and they're
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just taking on a lot less risk. Why? I
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don't exactly know. It could be
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motivated by the second thing that I'm
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going to talk about. But the point is in
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a deg
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risk and making your position sizes much
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smaller. So the longs become less long,
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the shorts become less short and you
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just shrink. And so there's just general
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downward pressure. That is a clear
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behavior right now. But I think the
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structural change is the more important
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one. And this is sort of what I talked
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about this morning. In a normal
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functioning market,
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what we are always debating is when a
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set of cash flows go from becoming
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highly confident to less highly
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confident. It's a when conversation. So
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when will Coca-Cola's cash flows be
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impacted? When will Eli Lily's cash
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flows be impacted? When will Meta's cash
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flows be impacted? And the answer to the
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when
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gets translated by the public markets
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into three things. Your price to
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earnings multiple where if you invert
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that number what that is equivalent to
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is the yield on the money that you get.
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Okay. So if you you know 20 times PE
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that's a 5% yield.
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The second is a revenue multiple. And
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the third is what's called your weighted
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average cost of capital. Which is to
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say, if you look at the next 20 to 30
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years of earnings and you want to figure
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out what that is worth today,
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you have to discount all of these back
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and you have to assume
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a percentage of interest effectively
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that it takes to get there. And the
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basic math of this is that when you have
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a high whack, it's called, you're
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massively discounting these cash flows.
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When you have a low whack, you're
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assuming that these things are very
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durable. Okay. So, what is happening?
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We used to debate when this is no longer
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a when moment. The market is very much
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in an if mode.
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Are these cash flows durable at all?
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>> Could they fall off a cliff in year
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three? Is there some AI model that's
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going to come around the corner and
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obliterate this business without me
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knowing it? And because they've shifted
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into this if mindset,
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your risk becomes totally different. You
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have this event risk that you don't know
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how to price. And whenever the market
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shifts into that mode, what you see are
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that the holders of those equities want
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a massive margin of safety. What does
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that mean? They have to take pees way
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down. If you used to trade at 40, you
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should trade at 20. If you used to trade
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at 20, you should trade at 10.
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They take revenue multiples down. You
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used to trade at 10 times revenue. Now
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you're going to trade it three times.
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You take the whack way up. Used to be a
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6% discounted weighted average cost of
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capital. You know what? I'm taking you
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to 12 or 13. That's the market's way of
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saying, I'm now debating
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if these things will even exist and so I
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need to give myself a huge buffer to own
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this stuff.
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>> That's what's happening right now. It
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has a lot of ripple effects that we can
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talk about. Freeberg and I have talked
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about this a lot. The most obvious
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impact is how these tech companies
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recruit and retain talent because the
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biggest thing that it starts to eat into
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are the cash flows of a business which
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really directly tied to stockbased comp
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and all this other stuff. But let me
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just stop there. So we are we have moved
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away from a when
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>> to now an if and I think that that is a
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very smart question to be asking. The
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answer may be from any of these
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companies that they will survive, but we
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don't know how long. And until that
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becomes clearer, you have to give
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yourself room to be wrong.
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>> You said when, then if. Did you mean if?
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>> No, no, no.
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>> To when?
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>> We we've always debated when. When will
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these cash flows disappear? Now it's
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like
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>> will they even exist?
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>> Got it. Okay. So the second part of the
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story Friedberg and Sachs is that a
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Substack post fanfiction
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uh taking place in the fictional 2028 uh
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global intelligence crisis went mega
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viral. 28 million views on X. It was
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posted Sunday night. It made the market
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tank on Monday. In this fictional
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Substack post, the author said there's
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going to be essentially a death spiral
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that happens because of AI. How does
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that work? Well, first, companies
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embrace AI. Everything goes right.
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They're able to cut staff. Their margins
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go up, similar to how Amazon has, you
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know, trimmed their white collar staff.
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Then they're so successful at this that
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they lose their customer base because
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consumers don't have discretionary
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funding to spend. Then it creates a
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death spiral where the companies keep
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deploying AI to try to hit the margins,
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cutting staff, and the entire economy
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collapses. Dr. Doom level stuff.
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Unemployment's at 10%, S&P goes down
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from 38% highs. After this piece came
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out which speculated that agents would
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get rid of all the 3% interchange fees
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and move everybody to settle
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transactions on stable coins. All the
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financial stocks got hit on Monday. Amex
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down 8%, Capital 1 down 8%, Mastercard
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6%, Visa 4%, yada yada. Finally, this
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piece got a lot of push back. There was
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a silly piece in it or a section in it
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where they said AI agents would vibe
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code their way to displacing Door Dash.
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And uh that's kind of silly if anybody's
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run a networkbased business knows. Sax,
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I assume you read this piece or at least
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saw the fallout from it. What's your
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take? And then we'll go to you Freeberg.
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>> Yeah. Well, I I know that this uh
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Catrini article got passed around like a
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join at a Grateful Dead concert, but I'm
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starting to question how legitimately
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viral it really was. There's some
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information that just came out that the
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attribution of the article has been
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amended, meaning the co-authors have
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been amended to include a short fund
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that was shorting some of the names
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mentioned in the article. This is
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according to another post that just came
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out. According to this post, the
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authorship attribution attributed to
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market moving was changed after
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publication of the co-author is the
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managing partner of a $262 million SEC
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registered hedge fund who confirmed
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short positions in the companies the
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report named. So I think that's point
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number one is I just wonder did this
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article truly go viral or did the
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authors do anything to kind of amplify
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it and we just don't know the answer to
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that question. But regardless of that,
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let's just take the arguments on their
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face. I think one of the best responses
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to it was by another writer named Derek
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Thompson who wrote a article called
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Nobody Knows Anything, which I think is
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a reference to a famous take by
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legendary Hollywood writer William
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Goldman.
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>> Yeah.
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>> In any event, what the article says is
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no one really knows what's going to
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happen with AI in two years, never mind
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20 years. And so they resort to science
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fiction writing masquerading as
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analysis. And the author here, Derek
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Thompson, says that the conversation
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about AI is really just a marketplace of
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competing science fiction narratives.
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And he says, "That's not to say I think
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the technology is a parlor trick, but
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rather that the level of uncertainty is
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so high and the quality and supply of
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real world real-time information about
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AI's macroeconomic effects so poultry
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that very serious conversations about AI
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are often more literary than genuinely
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analytical." So in other words, what
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he's saying is, look, this guy is
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writing very compelling science fiction,
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but there's no real analytics behind it
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to defend it. And yes, this could
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happen. Here's a prediction market on
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whether people believe the Catrini
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report's going to come true. Something
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like 12% believe the Catrini scenario is
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going to happen. But the truth is, no
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one really knows. I mean, there's other
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dueling science fiction narratives where
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AI is going to create such a world of
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abundance that we're not going to need
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for anything. And just by the way, Derek
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Thompson is one of the abundance guys
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with Ezra Klein.
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>> This is why the market's getting
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whacked. I think that you're right,
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Saxs, nobody knows. So, if you can get
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5% for owning government bonds, why are
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we taking excessive risk here?
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>> Yeah. Let me just build on your point
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about SAS. So the reason why there's so
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much uncertainty around SAS is that SAS
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used to be such a easily modeled and
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predictable category and you know I saw
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as a VC we saw the same story play out
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across many many different categories of
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software. You'd have this initial period
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where there'd be this experimentation
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phase you have a bunch of different
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products that come to market. There'd be
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a battle and then the market would
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eventually settle and they'd be a
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category leader and they would capture
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most of the market share and the vast
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majority of the market capitalization
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and they would have very very
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predictable metrics. It was very easy to
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grade a SAS business. You look at ARR,
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you say annually recurring revenue. You
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look at the net dollar retention you
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want to see depending on the phase
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>> RPO RPO revenue under performance.
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>> And so you know these things began to be
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seen as like a annuity with growth right
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because
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>> they were rock solid. Yeah.
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>> Yeah. Because a good net dollar
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retention would be something like 120%.
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Which means that your sort of cohort of
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existing customers on balance would all
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renew the next year and actually they
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would renew at 120% of the previous
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year's contract values. And the reason
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you got that extra 20% is they would buy
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more seats or there'd be additional
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products or features they would upsell.
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It got to be very very predictable. And
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so when people were buying software
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companies at I don't know 13 times ARR,
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they thought they were buying a growth
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annuity. And now all of a sudden you got
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to factor into that. Well, wait a
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second. What if AI disrupts the whole
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market? What if it doesn't eliminate? I
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don't think AI is going to get rid of
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Salesforce, but it could eat into their
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growth opportunity. We just don't know
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what if it changes the pricing model. I
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mean, it just creates a whole lot of
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unknowns. And I I actually don't believe
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in the Catrini or or the doomer take on
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this, but I can see why the market would
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feel this level of uncertainty
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>> 100%.
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>> Given how predictable a category SAS
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used to be just say a year ago.
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>> Yeah. Well, chaos is a ladder, Freeberg,
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and this means opportunity. So, if we
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look at this and SAS has headwinds, then
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is there a winner? Is open source the
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winner? Or is this all deflationary in
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your mind, Freeberg? And we just make
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less money and the earnings of these
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companies get compressed, the size of
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them gets compressed. How do you think
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about it? I think fundamentally if
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you're driving productivity with AI,
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you're driving leverage on human time
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and leverage on capital.
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The question is how quickly can you
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drive that up? And that's a function of
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how much consumption there is, how much
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capacity there is for consumption. So on
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the one hand, I'll just speak broadly. I
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think like humans have this desire to
00:14:48
improve their livelihoods by roughly 10%
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every year. Meaning like your income and
00:14:53
your ability to purchase stuff that's
00:14:54
new relative to where you were last year
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has to go up by 10% for you to be happy.
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If it's less than 10%, you're probably
00:14:59
unhappy.
00:15:00
>> Is that that's your anecdote or that's
00:15:01
like
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>> that's just like an anecdote. Like I
00:15:03
think I think that's sort of like my
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rubric for thinking about like why are
00:15:07
people unhappy? You're happy. So if your
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earnings are the same but things are
00:15:09
getting more expensive, you're not
00:15:11
happy. If your earnings go up by 10% and
00:15:13
things stay the same price, you got 10%
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more than you had last year. You're
00:15:17
you're going to be happy. I just think
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like all humans are driven by this need
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to consume more each year than they did
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last year. So I think for me that's like
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the lower limit on consumptive capacity
00:15:28
in the world.
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The question that we're now facing which
00:15:33
we've never faced in human history
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before is there a upper limit
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>> on consumptive capacity because AI
00:15:41
creates such a profound shift in
00:15:44
productivity and in leverage that
00:15:47
normally you would say hey when we get a
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new tool or we get new leverage in a
00:15:50
system we build a new technology we can
00:15:52
make more with less. Therefore, everyone
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gets access to more things for the same
00:15:57
price or the cost of things that they
00:15:59
consume come down by a certain price.
00:16:01
But there may be a situation now where
00:16:04
the ability to make stuff exceeds the
00:16:08
capacity to consume stuff. And that is
00:16:11
something that I don't think we've faced
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before. And I think that's sort of where
00:16:14
a lot of the models start to break. Just
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general economic models, just general
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productivity models, and general social
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models. And this goes to the point about
00:16:23
like what is everyone going to do? In
00:16:25
the same way that I think we've argued
00:16:26
that maybe SAS was a transitory business
00:16:29
phenomenon that existed between the
00:16:32
foundation of the internet and the era
00:16:35
of AI. It may be the case that knowledge
00:16:38
work in general is also a transitory
00:16:41
phenomenon that only existed between the
00:16:43
foundation of the computer or computing
00:16:46
tools and the existence of AI generally
00:16:48
speaking. And if all of that goes away
00:16:50
very quickly and all of those people can
00:16:53
be redistributed and recast into doing
00:16:55
other higher level, more creative
00:16:57
things, their productivity goes up by
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100x.
00:17:00
Is there really a consumer on the other
00:17:02
end of all of that productivity? Is
00:17:04
there really enough consumptive
00:17:06
capacity? And I think that's the
00:17:08
profound question that we all face. I
00:17:09
don't think that there's any limit.
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>> Is that your way of saying that SAS goes
00:17:13
to zero or that's your way of saying
00:17:16
these companies go to zero? I'm just
00:17:18
saying knowledge work in general like
00:17:20
the the like what is the implication
00:17:22
>> is this just another dueling science
00:17:24
fiction take I mean or what's your
00:17:26
evidence for this
00:17:28
>> I think it's fine to have a sci-fi take
00:17:30
intuition I think is data because I can
00:17:33
show you some data that I think
00:17:35
contradicts what you're saying
00:17:36
>> and I have some firstirhand sort of
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>> in the sense that there's more leverage
00:17:40
stacks that people are able to actually
00:17:42
>> well Jake I want to hear what you have
00:17:43
to say because I know you're
00:17:44
experimenting with this but let me just
00:17:45
show you a few data points real quick um
00:17:47
because I think this is relevant. So
00:17:49
we're really talking about the
00:17:50
disruption caused by coding assistance,
00:17:53
right? This is like the first big killer
00:17:55
app of AI. I mean I guess after writing
00:17:57
and research for chat bots and we'll
00:18:00
have agents later, but really it's all
00:18:02
about coding assistance, right? And the
00:18:04
ability to more easily create code.
00:18:05
That's what's creating the disruption to
00:18:07
the SAS category. Well, so let's just
00:18:09
focus on the data we see right now
00:18:11
around that. And there are a lot of
00:18:14
people who are pointing this out that
00:18:17
Enthropic right now has a job listing
00:18:20
for a software engineer on their website
00:18:23
right now for $570,000.
00:18:27
And a lot of people are kind of pointing
00:18:28
out, okay, so wait, so what Anthropic is
00:18:30
saying is they're still trying to hire
00:18:32
software engineers at a very high wage,
00:18:34
but somehow they think these jobs are
00:18:36
going to be eliminated.
00:18:38
>> Timoth might apply for that job. is.
00:18:40
>> Yeah. Austerity measures sounds pretty
00:18:42
good to me.
00:18:43
>> That's a lot of money.
00:18:44
>> Jim might take that job and then just
00:18:46
have AI do it for him.
00:18:47
>> No, I'm I'm I'm worried like I hope my
00:18:48
8090 team doesn't see that offer. That's
00:18:50
a
00:18:51
>> that's a big number.
00:18:53
>> Our equity is way higher, but our
00:18:54
salaries are not that high. I mean, you
00:18:57
look you put these things together, it's
00:18:58
like that equity is money good. The
00:19:00
reality is like those guys are doing 5
00:19:02
to6 billion structured secondaries every
00:19:05
year now or they're starting which means
00:19:06
that they will. That's like cash
00:19:08
compensation. So for for me to match
00:19:11
that, I need to be 3x higher than that.
00:19:13
>> Right? And I think a lot of people are
00:19:14
kind of pointing out, well, this is a
00:19:15
contradiction. Anthropic doesn't really
00:19:17
seem to be practicing what they're
00:19:18
preaching if they're paying enormous
00:19:20
amounts still for software engineers
00:19:22
even as they claim they're obsoleting
00:19:23
the entire category. Something doesn't
00:19:25
quite add up. Citadel Securities did a
00:19:28
new report that rebutts that Catrini
00:19:32
report and they show a couple of stats
00:19:34
here which I think are really
00:19:35
interesting. So, job postings for
00:19:37
software engineers are rapidly rising.
00:19:40
They're showing, I think it was roughly
00:19:42
a 10% year-over-year increase in the
00:19:45
demand for software engineers. On a
00:19:47
related note, they also show that
00:19:51
company formation is also rapidly
00:19:54
expanding and that may have something to
00:19:56
do with AI making it easier to start a
00:19:58
business or to get leverage to your
00:20:00
point, Freeberg. So look, there's a
00:20:02
couple of competing effects going on
00:20:04
here. And I think Aaron Levy had a
00:20:06
really good explanation of why you might
00:20:10
see something very counterintuitive
00:20:11
happening. And again, it all goes back
00:20:13
to Jeban's paradox. But what Aaron says
00:20:16
is that when you lower the cost of
00:20:18
something that was previously supply
00:20:20
constrained, demand for that thing goes
00:20:22
up. Software engineering is just one of
00:20:24
the easiest examples to contemplate, but
00:20:26
there are going to be many other jobs
00:20:27
like that. But think about software
00:20:29
engineering. Even among startups in
00:20:31
Silicon Valley, which I think are
00:20:33
probably some of the most attractive
00:20:34
places for software engineers to work,
00:20:37
there's always been a chronic shortage
00:20:39
of them. Then you've got the Fortune 500
00:20:41
companies, non- tech companies, which
00:20:43
have always had an even harder time
00:20:45
hiring technical talent. So, you have
00:20:47
this massive unfilled need for software
00:20:51
engineers across the entire economy.
00:20:53
Now, you're going to be able to get a
00:20:55
lot more leverage out of software
00:20:56
engineers. It doesn't mean they're going
00:20:58
to get fired. It just means that now
00:21:00
maybe you can have a lot more 10x
00:21:03
software engineers and they're getting
00:21:05
those jobs are now being spread
00:21:07
throughout the whole economy. You know,
00:21:09
I also think just to put some numbers on
00:21:11
this, I think the cost structure of the
00:21:12
average Fortune 500 business is
00:21:15
something like 5% it includes all of
00:21:18
their IT, not just their software. You
00:21:21
know, what should it be? What should the
00:21:23
percentage of software be in an
00:21:26
enterprise cost structure? Elon
00:21:28
describes companies as cybernetic
00:21:30
organisms that are part software, part
00:21:32
human.
00:21:34
>> If you think about the current Fortune
00:21:35
500 company being one or two percent
00:21:37
software, maybe they should be 50%
00:21:39
software. I think what Aaron is saying
00:21:41
here is the market for software and
00:21:44
software engineers was so constrained by
00:21:46
the lack of availability
00:21:48
that even if we 10x or 100x the
00:21:51
productivity of software engineers, the
00:21:52
demand will be there to absorb this new
00:21:55
supply. And so it could lead to this
00:21:57
explosion in productivity without the
00:21:59
massive job loss.
00:22:00
>> I think you're right. I think the the
00:22:02
thing that I would look at is I would
00:22:05
expect OPEX as a percentage of revenue
00:22:07
to fall off of a cliff but within that
00:22:10
opex the percentage of it that you
00:22:13
allocate to technology and technology
00:22:15
related things probably goes way way up
00:22:17
than what it is today. Okay, Jason, the
00:22:19
batch of people that are applying for
00:22:21
launch,
00:22:23
has SAS stopped? Has software stopped?
00:22:25
>> It's AI first companies obviously and
00:22:28
people
00:22:29
>> are they rebuilding traditional SAS
00:22:31
tools just cheaper?
00:22:32
>> Basically, everybody's building the
00:22:35
great, you know, as we talked about at
00:22:36
the all-in summit like some of these
00:22:38
companies are trying to build the best
00:22:40
pilot in the world or Whimo's trying to
00:22:42
build the best driver in the world.
00:22:43
People are now trying to build the best
00:22:45
SDR in the world, the best salesperson,
00:22:47
the best executive coach. And so we have
00:22:50
been like obsessed with claude co-work,
00:22:53
but mainly OpenClaw. And so what we did
00:22:56
was and and I think it's not developers
00:22:59
that are going to do all this work, it's
00:23:01
knowledge workers. So we had we have 20
00:23:04
people in our firm. We had 15 of them
00:23:05
come in this weekend and they all got
00:23:08
trained over like six or seven hours had
00:23:10
to have their own openclaw agent and we
00:23:12
started building it. Every piece of
00:23:14
software that we wanted to buy or build
00:23:16
over the last 10 years that we never got
00:23:19
to my people are building in the last 30
00:23:22
days. As an example, you know, when
00:23:24
you're selling ads for a podcast, you
00:23:27
want to check all the other podcasts and
00:23:28
what advertisers they have. We trained
00:23:30
an agent to go take the top 100
00:23:33
podcasts, look through the transcripts,
00:23:35
figure out who the advertisers are,
00:23:36
check those advertisers in pipe drive,
00:23:38
tell us when the last time we contacted
00:23:40
them and put it into the sales room.
00:23:41
That was an SDR job that we wanted to
00:23:43
fill and software we wanted to build.
00:23:45
Then we wanted people to have
00:23:47
>> hold on that was a that was a human that
00:23:49
you were paying money and now you've
00:23:50
replaced with software or that human
00:23:52
still exists but now they just do it in
00:23:54
a better way.
00:23:54
>> Redeploying that human. We had a human
00:23:56
doing it. we're going to redeploy them
00:23:58
to do other things and the consistency
00:24:00
of this chimoth and the accuracy and
00:24:02
then it's doing it all night long. So we
00:24:05
have like seven of these agents in these
00:24:07
kind of roles. The next piece we did was
00:24:09
we gave my agent which is like the
00:24:10
ultron root access to Gmail, calendar,
00:24:14
zoom, notion, slack. And what it's doing
00:24:18
is it's giving each person here's what
00:24:20
you got done this week with their
00:24:21
manager. Here's the emails you sent.
00:24:23
Here's the meetings you took. Here's the
00:24:24
contacts. here the threads you were
00:24:26
involved in and then it's helping manage
00:24:28
those people and so we are
00:24:31
>> okay but all that all that to me says
00:24:33
you Jason despite all your dumerism
00:24:36
seems like you're growing and you're
00:24:38
going to be hiring more people and
00:24:39
you're more productive am I getting this
00:24:41
wrong
00:24:41
>> I'm not dumerous what I think's going to
00:24:43
happen in this position is
00:24:44
>> but you're growing and you're going to
00:24:45
be hiring more people
00:24:46
>> no no we're not going to add more people
00:24:48
definitely not adding people we have are
00:24:51
becoming 10 or 20% more efficient every
00:24:54
week Because the software we would have
00:24:55
paid for or built from another vendor if
00:24:57
we had the time or we wanted to build
00:25:00
custom software we had 10 engineers it's
00:25:02
being built by our openclaw agents. As
00:25:05
an example when we make clips for this
00:25:07
podcast other podcasts we have it go and
00:25:10
look at like uh this weekend startups
00:25:12
episode from 10 years tell us the three
00:25:14
best moments and it makes the clip it
00:25:16
puts the subtitles on it and then it
00:25:17
puts the clip into the Slack room. That
00:25:19
was something that was going to be a
00:25:21
full-time job. So, we're getting 10 20%
00:25:24
more efficient. Then I started doing it
00:25:26
at home. So, I had to take our
00:25:28
Instacart, pull out the last 10 orders
00:25:30
we did, and then tell us what we order
00:25:32
most of time. And then it's going to
00:25:34
automatically build a car for us. Every
00:25:36
single knowledge work job is being
00:25:38
automated right now. And you can take it
00:25:41
and if you're a business process head,
00:25:43
where you know how to like do a business
00:25:45
process and you can structure it and
00:25:47
write it with an agent, it'll just run
00:25:49
it every day, every week. We did another
00:25:51
agent, how do you make better
00:25:53
thumbnails? And we said, every Saturday
00:25:57
in your skills, so when you build an
00:25:59
open claw, it has like a soul file and
00:26:01
it has a skills file. In the skills
00:26:03
file, we told it sax every week go out
00:26:05
and look for people discussing how to
00:26:08
make better thumbnails on YouTube, how
00:26:10
to make better titles. It found this
00:26:12
week, Chimath, somebody at Mr. Beast
00:26:15
company talk about how they're using
00:26:18
heat maps. It was an article I would
00:26:20
have never known. It added it to its
00:26:22
skill and now whenever we post a
00:26:24
thumbnail, it tell tells us based on its
00:26:26
skill that it refineses every week how
00:26:28
to make that thumbnail better. And it's
00:26:30
starting to make the thumbnails. This is
00:26:32
becoming recursive. So you keep the same
00:26:34
number of people, but they get 10 or 20%
00:26:36
more efficient. I don't know what this
00:26:38
means for the larger economy. All I know
00:26:39
is it's the most exciting time I've had
00:26:42
online since the web came out, since the
00:26:44
internet came out. It is so much fun to
00:26:47
automate all this stuff. The big
00:26:48
question that I am thinking about that I
00:26:52
haven't gotten a good answer about so I
00:26:54
don't I don't know what you guys think
00:26:55
is
00:26:56
all these businesses are going to need
00:26:58
to batten down the hatches and give
00:27:00
themselves room to figure this all out
00:27:02
right like if you take Sax's point like
00:27:04
if you take your point Jal which is the
00:27:07
young nimble companies like yours are
00:27:09
going to be rapidly experimenting the
00:27:12
bigger larger companies are going to
00:27:14
slowly onboard themselves to start
00:27:16
experimenting All of that means we're
00:27:18
going to get much clearer answers to all
00:27:20
of this. But what it also means is that
00:27:22
you're going to have to have time so
00:27:25
that you can figure this all out.
00:27:27
>> And
00:27:28
if you want to buy yourself time, you're
00:27:31
going to need a ton of cash. And if
00:27:33
you're going to think about saving cash,
00:27:35
the one place tech companies literally
00:27:38
incinerate cash is how they do
00:27:41
compensation.
00:27:43
And so I kind of think like at some
00:27:45
point the next shoe will drop and all of
00:27:47
these tech companies have to really look
00:27:48
at stockbased comp because they
00:27:51
literally incinerate most if not all of
00:27:53
their free cash flow fighting the
00:27:55
delilution from stockbased compensation.
00:27:57
So if you want five or six years to just
00:27:58
be in the arena on the field figuring
00:28:00
this out, you're going to want to kind
00:28:03
of be very cash flow generative and
00:28:05
really conservative in how you spend
00:28:07
your money. Yeah, Saxs, the people who
00:28:09
embrace this, I think, become five or
00:28:11
ten times more valuable than the people
00:28:13
who are not. That's where I think the
00:28:14
opportunity in the economy is. So,
00:28:16
unless you think humanity is going to
00:28:18
run out of problems to solve, I think
00:28:20
it's going to be boom. It's going to be
00:28:21
boom town. And I think people are going
00:28:23
to start more companies because the the
00:28:26
barrier to start a company is no longer
00:28:27
three or four million dollars. You can
00:28:29
just have two or three people and you
00:28:31
start setting up these agents and man
00:28:32
you can
00:28:34
>> make software, you can do sales, you can
00:28:36
do PR, everything is getting faster and
00:28:38
faster and faster. So the time between
00:28:41
like conceiving of a product and
00:28:43
publishing it and finding a developer,
00:28:45
you don't even need a developer, you can
00:28:46
just publish software, the the wakeup
00:28:49
moment for me was we were talking to our
00:28:51
agent about, hey, we want to get this
00:28:55
functionality out of Slack. And it's
00:28:56
like, "Yeah, Slack doesn't have that,
00:28:58
but have you considered Matterpost?" I'm
00:29:00
like, "What's Matter Post?" Like, "Oh,
00:29:01
it's an open source project. I can spin
00:29:02
it up this weekend. Export your Slack
00:29:04
instance and put it there." And I was
00:29:05
like, "Oh, don't do that. We're only
00:29:07
spending 6K a year on Slack or 10K a
00:29:10
year." But the software is building CRM
00:29:13
systems for us. It's building agents for
00:29:15
us, and it wants to just build all the
00:29:18
software stack. So you could when you
00:29:20
renegotiate with Slack or HubSpot or
00:29:24
whatever company you're working with,
00:29:27
you're going to be able to say to them,
00:29:28
hey, we could roll our own and uh when
00:29:30
you want to upsell us on this latest
00:29:32
thing like you talked about SAS,
00:29:33
upselling is such a big part of SAS.
00:29:35
You're like, I can actually build that
00:29:37
software myself internally. I don't need
00:29:38
you to do it.
00:29:39
>> Ryan Peterson just posts on XC Claude
00:29:42
for legal seems to work just as well as
00:29:45
Harvey by the way. Now it's the SAS
00:29:48
apocalypse is going after private
00:29:50
companies now too.
00:29:51
>> Well, I think for a while now there has
00:29:53
been a question of which layer of the
00:29:54
stack is going to capture all the value.
00:29:57
>> So is it going to be the model companies
00:30:00
or could it be the applications that are
00:30:01
built on top of the models or you know
00:30:04
if there's a lot of competition at both
00:30:05
those layers of the stack did the chip
00:30:06
companies get it all? I think it's a
00:30:09
unclear question but
00:30:10
>> totally
00:30:11
>> yeah I think you know for any given
00:30:12
vertical application you do have to
00:30:16
defend why you think your value prop
00:30:19
will be sustainable as the underlying
00:30:22
foundation models get better themselves
00:30:25
>> and it's open source like this week we
00:30:27
put up Kimmy 2.5 it can do about 80 85%
00:30:31
of the jobs so we lowered our token
00:30:33
bills massively when we stood that up
00:30:35
all right listen this is TBD We got a
00:30:38
lot more to think about on this topic.
00:30:40
>> Just on this point of a lot of these
00:30:42
debates about AI are dueling science
00:30:46
fiction narratives. I just think that
00:30:48
the doomer narratives are inherently
00:30:50
more appealing to people. I mean, I
00:30:52
think it's partly just you look at most
00:30:54
sci-fi movies are dystopian, not
00:30:56
utopian. In addition to that, I think we
00:30:59
have a bunch of heristic biases in favor
00:31:01
of the dumer narrative. So, one of them
00:31:03
is the scene versus the unseen. It's a
00:31:05
lot easier to see the jobs that already
00:31:08
exist that could be obsoleted than it is
00:31:11
to imagine the new jobs and the new
00:31:13
business models that haven't been
00:31:15
created yet. And that will likely take
00:31:17
some great innovator or a genius to
00:31:19
think of in order to create. So we have
00:31:22
that huge heristic bias of not being
00:31:24
able to see the creation that's coming.
00:31:26
It takes way less creativity to think
00:31:28
about the potential destruction. And
00:31:30
then finally I think you know the other
00:31:31
heristic is just the whole fixed pie
00:31:34
fallacy. Most people do tend to think of
00:31:37
the economy as a fixed pie. This is why
00:31:39
you see so much anger against you know
00:31:41
millionaires and billionaires is because
00:31:44
of this idea that if someone's getting
00:31:45
rich it must be at the expense of
00:31:46
someone else. That's not actually the
00:31:48
case. The economy itself could be
00:31:50
growing larger as a result of someone
00:31:52
inventing something new that increases
00:31:54
production. A really good line from
00:31:56
another article that was written just a
00:31:57
couple weeks ago was the economy is not
00:32:00
a a pie, it's a garden and technology is
00:32:03
rain. So again, you know, all of this
00:32:05
technological innovation is going to
00:32:08
increase the growth rate of the garden.
00:32:10
It's not a fixed pie. And just because
00:32:13
you see an expansion and productivity in
00:32:17
one part of the economy does not mean
00:32:18
that you're going to see job loss in
00:32:20
another part of the economy.
00:32:21
>> Yeah. I think the job people are not
00:32:23
seeing but I'm seeing right now is the
00:32:25
person who creates agents, manages them
00:32:28
and is the maestro of the agents. The
00:32:31
person who can take the business
00:32:34
process, explain it and train the agent
00:32:36
to do it. And there are certain people
00:32:37
in business who are just really good at
00:32:39
operations. You were one of them Sachs
00:32:41
running companies and like that person
00:32:43
who can fire up an agent, train the
00:32:45
agent and figure out how to manage them
00:32:47
and figure out how to increase
00:32:49
>> with any new technology. Great job. and
00:32:51
it's not a developer.
00:32:52
>> Look, with any new technology, there's
00:32:54
always a huge change management aspect
00:32:56
with enterprises because it's hard for
00:32:59
them to adapt and change. And the people
00:33:01
in the organization who can lead that
00:33:04
change management are the ones who are
00:33:06
going to create an amazing career
00:33:07
opportunity for themselves. But it's
00:33:09
hard to do and that's going to slow down
00:33:10
the rate of change just the amount of
00:33:12
inertia in the economy. And also one
00:33:14
other constraint is going to be that at
00:33:16
some point here we may be token
00:33:18
constrained, right? I mean, we may not
00:33:19
have enough energy like we've talked
00:33:21
about, even though the chips are getting
00:33:23
so much better, that tokens per second,
00:33:26
tokens per watt, and tokens per dollar
00:33:29
are all increasing very fast, but we're
00:33:31
still going to probably be constrained
00:33:33
in the next couple of years on some
00:33:35
dimension, whether it's land, power,
00:33:36
shell, or just energy production or
00:33:38
maybe chip production. There are real
00:33:40
world constraints on just how fast we
00:33:43
can scale the infrastructure and that
00:33:45
will mean that these like hyper utopian
00:33:48
or hyperdystopian narratives will be
00:33:50
wrong. I don't think there's time in the
00:33:52
next few years for the whole economy to
00:33:54
change in the way that the extremes
00:33:56
would present.
00:33:57
>> I think you're right. I think you're
00:33:59
going to see a 10xing in
00:34:03
the demand for tokens, but I also think
00:34:05
you're going to see a 90% price
00:34:08
reduction in the cost of an output token
00:34:10
probably by the end of this year. So, I
00:34:12
think that to your point, like it's it's
00:34:15
going to just create an enormous upswell
00:34:17
of demand because we're going to be able
00:34:19
to cut the prices of an output token so
00:34:21
dramatically. And I think by the way
00:34:23
>> that discussion we had Shamath last week
00:34:25
when we talked about co the tokens
00:34:26
outpacing the employee salary and just
00:34:29
where are these tokens all going to come
00:34:30
from that was our most viewed clip or
00:34:33
one of the most viewed clips in the
00:34:34
history of this podcast. So people are
00:34:36
actually really focused on this.
00:34:38
>> I had my team at 89 we we redid our cost
00:34:40
model and now we have that as a line
00:34:43
item. When we think about fully burdened
00:34:46
cost of employees, we now factor that in
00:34:49
because we're we're at a place where
00:34:51
some of our engineers are just racking
00:34:53
up ginormous bills and then separately
00:34:55
just general runs that we do for general
00:34:59
purpose stuff that we need to just run
00:35:00
our product is it's so expensive. So I
00:35:03
am waiting with baited breath for what
00:35:05
Zach said which is like we need an
00:35:06
explosion in the capacity that's
00:35:10
available because I do think that the
00:35:12
the silicon solutions are coming that
00:35:14
will cut the cost but we need a large
00:35:17
block of land power shell ready to then
00:35:20
turn all of this stuff on so that we can
00:35:21
actually take advantage of it.
00:35:23
>> Rumors the new Mac Studio is coming will
00:35:26
have an M5 chip in it and will be
00:35:28
language model ready. So that's the
00:35:30
rumor is that they're building it for
00:35:32
models. So that could be an incredible
00:35:34
turn of events. Everybody's desktop
00:35:36
running the local model. Sax, you want
00:35:38
to have the final word here? Uh Free or
00:35:39
Freeberg before we
00:35:40
>> just to go back to what Jamath was
00:35:42
saying there. I mean, you've got
00:35:44
political forces that want to stop the
00:35:46
construction of all data centers in the
00:35:47
United States. So
00:35:49
>> if that gains steam, then that's going
00:35:50
to be a huge constraint on any change
00:35:52
whatsoever.
00:35:53
>> Can I tee this up for you, Jal? So I I
00:35:55
went back this weekend
00:35:57
and I looked at the number of data
00:36:00
centers that have faced local opposition
00:36:03
and whether there were patterns. And I I
00:36:05
posted it on X. So Nick, maybe you can
00:36:07
put this up, but
00:36:09
it was really a a very small
00:36:14
behavior which was pushing back on data
00:36:16
centers and getting them cancelled. We
00:36:18
had about 25 projects total of which
00:36:22
20 were just in Q2 alone. There are 100
00:36:25
data center projects right now that are
00:36:27
facing some form of local opposition.
00:36:29
>> So interesting.
00:36:30
>> If you take that 40% number and you
00:36:34
apply this and then you multiply by the
00:36:37
number of megawatts that they have
00:36:38
announced. Last year we lost almost 5
00:36:42
gawatt
00:36:44
in terms of cancel projects.
00:36:46
This year coming in 26 we have about
00:36:49
seven that could be cancelled if you use
00:36:51
this math. If then you flow that through
00:36:55
open AI Sarah Frier said this that every
00:36:58
gigawatt for her for open AAI is about
00:37:00
10 billion of revenue. So if you if you
00:37:03
assume that that's roughly accurate plus
00:37:04
or minus a billion here or there. What
00:37:07
that means is that 2025 the industry as
00:37:11
a whole lost
00:37:13
50 billion of revenue
00:37:15
and this year if 7 gawatt gets canceled
00:37:18
it's about 70 billion. Now you're
00:37:20
talking about 130 billion of lost
00:37:21
revenue over these two years that'll go
00:37:23
forward in time that we miss out on. I
00:37:27
think that that's really bad. We need to
00:37:28
figure out a way to nip this in the bud.
00:37:30
>> So confounding because we were sitting
00:37:33
here 5 years ago, 10 years ago, local
00:37:36
municipalities were fighting and giving
00:37:38
discounts to try to get these data
00:37:39
centers open to get the jobs and get the
00:37:41
revenue. And now we've got people trying
00:37:43
to stop them. This is a perfect
00:37:45
transition for the State of the Union.
00:37:46
Before we get there, two important
00:37:49
programming notes. All-In is going to
00:37:51
host two events in 2026. One of them,
00:37:53
liquidity, May 31st to June 3rd, uh, in
00:37:56
Yonville, uh, up in Wine Country.
00:37:58
Chimath has taken control of the event
00:38:01
and he has set a standard for who gets
00:38:03
on stage.
00:38:04
>> None of you mids can control the
00:38:05
programming. I just
00:38:06
>> That's it. Chimath came in and he
00:38:09
dropped the hammer. Who do you got so
00:38:10
far? You want to tease a couple of
00:38:12
people who you invited to come speak?
00:38:14
>> I'll tease two. The first is an
00:38:17
incredibly dear friend of mine,
00:38:19
>> the axe of axes,
00:38:22
Dan Loe, who founded Third Point, who is
00:38:26
an unbelievable investor in literally
00:38:30
every domain, private credit,
00:38:33
public equities, private tech.
00:38:36
He's he's just a he's
00:38:39
>> a beast. So, he'll be doing a really
00:38:41
important keynote. He has not done one
00:38:43
of these public speaking slots in a very
00:38:45
long time. And then the second is the
00:38:47
CFO of OpenAI, Sarah Frier.
00:38:50
>> Oh wow.
00:38:50
>> Unbelievable start. And we're going to
00:38:54
double click into the entire business
00:38:55
model of OpenAI on stage in front of
00:38:57
everybody.
00:38:57
>> So uh go to allin.com and then for those
00:39:00
of you who plan ahead for travel,
00:39:01
>> more coming more coming every week.
00:39:04
>> If you are an All-In Summit fan, I can't
00:39:07
believe it. Freedber, we're going to be
00:39:08
in our fifth year September 13th to
00:39:10
15th. only gets better. Gets better
00:39:13
every year. I could have some good
00:39:14
parties, too. I mean, that Back to the
00:39:16
Future and the Bladeunner parties, those
00:39:17
were epic.
00:39:18
>> allin.com/events. Hey, can I give a plug
00:39:21
to friend of the pod,
00:39:23
>> Bill Gurly? He's got an amazing new
00:39:24
book, Running Down a Dream. Please,
00:39:26
>> wait, wait, wait, wait. Before we start,
00:39:28
>> before I start,
00:39:29
>> there it is. Running down a Dream, I
00:39:30
just want everybody to just stop the
00:39:32
pause the podcast. I want you to buy
00:39:33
three copies, give it to two young
00:39:35
people and a parent. You know,
00:39:36
>> this book is incredible.
00:39:37
>> It's a great book. It's a great book. It
00:39:40
It really is. inspiring for kids and uh
00:39:42
Bill Gurly, friend of the pot. He always
00:39:44
shows up for us.
00:39:44
>> Jal, do an impression for us of what it
00:39:46
would be like if you and Bill Gurley
00:39:48
started a podcast together.
00:39:49
>> All right, everybody. Welcome to the
00:39:50
JCBG podcast. I'm your host, Jason
00:39:53
Calakanis. and I'm Bill Gurly and we're
00:39:56
here in Texas at Terry Blacks where
00:39:58
we're getting some beef ribs and we're
00:40:00
going to discuss investing in
00:40:03
marketplaces
00:40:04
as well as my new book running down a
00:40:08
dream which will teach your kids how to
00:40:10
not be fuckups and if your kids are ups
00:40:14
you can hit them in the back of the head
00:40:16
with the book
00:40:18
Texas style.
00:40:20
One of the big topics uh and I think
00:40:22
something you're working on with
00:40:24
President Trump's acts is uh this energy
00:40:28
pledge. I've been seeing uh rumblings
00:40:30
about this. Explain what's going on in
00:40:31
terms of getting the country in sync
00:40:34
around these data centers and energy.
00:40:37
Well, the president announced in the
00:40:38
State of the Union last night that he
00:40:40
supports a rateayer protection pledge
00:40:44
which requires uh the major tech
00:40:47
companies to provide for their own power
00:40:49
needs for AI data centers so that
00:40:52
residential consumers do not see their
00:40:53
rates going up. I think this makes total
00:40:55
sense. I think Chamas, to your point,
00:40:58
this is the reason behind a lot of the
00:41:00
opposition to new data centers is that
00:41:02
the local residents fear that their
00:41:03
electricity prices are going to go up
00:41:05
and that shouldn't be the case. And so
00:41:07
the president has said that he's
00:41:09
committed to not allowing residential
00:41:11
rates to go up as a result of data
00:41:13
centers. It's pretty straightforward.
00:41:15
You get the big tech companies, the
00:41:16
hyperscalers to pay for the increase in
00:41:18
the electricity cost or you let them set
00:41:22
up their own power behind the meter. The
00:41:23
president's been talking about this for
00:41:25
over a year that our biggest AI
00:41:27
companies would also become big power
00:41:29
companies because we would let them uh
00:41:31
stand up their own power generation
00:41:32
behind the meter. So these data centers
00:41:36
don't even have to connect to the grid.
00:41:38
They could just do collocation
00:41:40
themselves. But also, I think that with
00:41:42
this rateayer protection pledge, what
00:41:45
you're going to see is that it could
00:41:46
actually bring down consumer prices
00:41:49
because what happens is that when these
00:41:51
data centers then set up their own power
00:41:53
and connect to the grid, they can give
00:41:55
back the excess to the grid. Also, they
00:41:58
will make investments in scaling the
00:42:00
infrastructure. So, although electricity
00:42:03
is priced at a metered rate, the costs
00:42:05
to generate it are not all variable.
00:42:07
There's a lot of huge fixed costs in
00:42:09
there. So when you increase scale then
00:42:12
you can actually reduce the the metered
00:42:14
rate. So again you know this is really I
00:42:17
think the rebuttal to Bernie Sanders who
00:42:19
just wants to stop all progress
00:42:21
whatsoever.
00:42:22
I saw a funny post calling it bananas
00:42:25
which is build absolutely nothing
00:42:26
anywhere near anyone. So this is the
00:42:30
>> bananas is replacing the new nimi. So
00:42:32
you just can build absolutely nothing. I
00:42:34
think the president's approach finds a
00:42:36
very good balance here, which is look,
00:42:38
>> we can have progress. Just don't make
00:42:40
residential consumers pay for it. Let
00:42:41
the big tech companies pay for it
00:42:43
themselves. And I think you'll see more
00:42:44
coming out about this from the White
00:42:46
House next week.
00:42:47
>> Quite a deaf move. Freeberg, how should
00:42:50
America be thinking about this great
00:42:53
data center buildout, energy usage, you
00:42:56
know, if you expand it out over the
00:42:58
coming decade? And how do you sell that
00:43:01
to the backdrop that you talk about the
00:43:03
socialist movement? You got a great
00:43:04
interview coming out with Ray Dalio and
00:43:06
the all-in interview program next week.
00:43:09
How do you think about those competing
00:43:11
forces? You've got the socialists saying
00:43:13
bananas, nimi, slow down, del, and then
00:43:18
you've got this incredible race we're in
00:43:20
for efficiency and this opportunity and
00:43:22
abundance. How would you sell it to kind
00:43:25
of bring these two sides together? Or is
00:43:27
it just
00:43:30
impossible. The data coming in and out
00:43:32
of data centers moves at roughly the
00:43:34
speed of light. So you could put them
00:43:37
anywhere. And I think that our policy
00:43:40
makers need to be very cognizant of that
00:43:43
fact. You have and we do connect the
00:43:47
internet using high-speed cable,
00:43:50
high-speed
00:43:52
fiber optic throughout the world. And so
00:43:54
theoretically if we don't embrace and
00:43:58
allow the economic development of the
00:44:01
data center industry and it will
00:44:02
fundamentally be an industry because it
00:44:04
is almost like the new sort of oil.
00:44:07
Where are the oil rigs going to go?
00:44:09
Where are the railroads going to go?
00:44:11
Where are the telegraph lines going to
00:44:12
go? Where are the factories going to go?
00:44:14
If we don't put them here, someone else
00:44:16
will put them on their shores. Someone
00:44:18
else will put them in their country.
00:44:19
Someone else will put them in their
00:44:20
jurisdiction. And a lot of the economic
00:44:22
value that arises from the people that
00:44:25
will build those facilities, the energy
00:44:28
that will be installed to produce power
00:44:30
for those facilities, and then all of
00:44:33
the second and third order industries
00:44:35
that emerge as a result of those
00:44:36
installations, that value will acrue
00:44:39
elsewhere.
00:44:40
>> Such a good point.
00:44:40
>> So,
00:44:41
>> yeah,
00:44:42
>> it's not going to like just go away. The
00:44:44
the demand is there. The economy is
00:44:45
moving forward. AI is moving forward. We
00:44:49
live in a world with 196 countries and
00:44:52
data centers do not take up a lot of
00:44:54
space. They're very small relative to
00:44:56
the economic value that they produce. If
00:44:58
you zoom out on the map of the world,
00:45:00
all the data centers in the world fit
00:45:02
under the tip of a pin. And so this is a
00:45:06
very small footprint and if we're going
00:45:08
to give up hundreds of thousands of jobs
00:45:11
and many billions of dollars of economic
00:45:14
value creation, we're being pretty silly
00:45:15
and pretty obtuse in our view of the
00:45:17
world. I would just like encourage the
00:45:19
system that I think is the right system
00:45:21
and we talked about this last time where
00:45:23
provided data centers are producing
00:45:25
their own electricity. That means that
00:45:27
you're taking electricity consumption
00:45:29
off the grid because they otherwise are
00:45:32
not being used on the grid and that will
00:45:34
reduce the cost of electricity for other
00:45:36
residential and industrial users. So,
00:45:39
it's silly to think that we need to put
00:45:40
a moratorium on data centers. As soon as
00:45:42
you do that, the companies that use data
00:45:44
centers are not going to slow down.
00:45:45
they're going to go put them somewhere
00:45:46
else and we're going to miss out.
00:45:47
>> And it's such a good point, Chimamoth,
00:45:49
because you were recently in the Middle
00:45:50
East and I've been there a bunch in
00:45:53
Saudi, UAE. These are the folks who
00:45:56
built a large portion of those oil
00:45:58
refineries. And they are savvy to this.
00:46:01
And what are they doing in Saudi, UAE,
00:46:04
Qatar, all of these regions? They're
00:46:06
doubling down. They're 10xing their data
00:46:08
center builds. So to your point,
00:46:11
Freedberg, either we build them or
00:46:13
they're going to go somewhere else. And
00:46:14
there are people who are willing to
00:46:16
underwrite these and they're willing to
00:46:18
take out the red tape
00:46:21
from the process here and move quicker
00:46:23
than us. So we I think this is a pretty
00:46:24
deaf move by President Trump to say,
00:46:27
"Hey, you guys should all just guarantee
00:46:29
that consumers don't get impacted." The
00:46:31
water thing is a total hoax. Like the
00:46:33
water is recirculated. That's a hoax. I
00:46:35
think this is really smart. I think that
00:46:37
what the president's doing and what Sax
00:46:39
is doing is really smart. The thing to
00:46:41
keep in mind is that there's still a
00:46:44
risk that prices go up and it has
00:46:45
nothing to do with these data centers
00:46:47
and it has everything to do with the
00:46:48
business model of being a utility
00:46:51
because what happens is in order to get
00:46:54
a license a monopoly license in an area
00:46:58
to provide energy to generate energy for
00:47:01
a community.
00:47:03
The exchange works in the following way.
00:47:05
You go and you present a capex plan to
00:47:08
the public utilities commission. That's
00:47:10
effectively your budget that says here
00:47:12
are the lines I'm going to upgrade. Here
00:47:14
are the generators I'm going to upgrade.
00:47:16
Independent of data centers. The reality
00:47:18
is the draw the electricity consumption
00:47:21
of individual Americans is going up
00:47:23
because we have more devices, we have
00:47:25
cars, we have all of these other things.
00:47:27
So what we also have to do is we have to
00:47:29
look at how utilities's business model
00:47:31
actually incentivizes them to increase
00:47:34
prices by making all kinds of
00:47:37
investments. So we have to do a good job
00:47:39
of making sure we hold everybody
00:47:40
accountable because otherwise what you
00:47:42
could see is that the data centers
00:47:45
taking on the burden for themselves but
00:47:47
price is still continuing to escalate
00:47:49
because a utility says I need to spend a
00:47:51
billion dollars this year to upgrade my
00:47:53
infrastructure. And what that allows
00:47:55
them to do is take that billion dollars
00:47:56
and essentially invest it for a return.
00:47:58
That's the business model of utility.
00:48:00
And this is really happening in blue
00:48:03
states. Micron has a hundred billion
00:48:06
dollar mega fab in New York. And there's
00:48:08
a lawsuit by six 1 2 3 4 5 citizens.
00:48:13
>> That's shameful.
00:48:13
>> And the project has taken 12
00:48:17
>> 1200 days. 1,200 days
00:48:20
>> between their announcement and the
00:48:21
groundbreaking. And they spent 612 days
00:48:24
on the environmental impact study.
00:48:27
People wake up. Just go to Texas. Elon
00:48:30
built his factory here, the Gigafactory,
00:48:33
in under like 18 months. This is the
00:48:36
great state of Texas. Come here. We'll
00:48:38
build it for you and you'll be done.
00:48:40
>> Yeah. I don't know why anyone bothers
00:48:41
with the blue states anymore. They make
00:48:43
it too hard to build.
00:48:44
>> It's [ __ ] It's so dumb. It's such a
00:48:46
self-owned, too. Like, what? Don't you
00:48:48
want to be part of the future? You're
00:48:49
literally ankling the entire country to
00:48:53
scratch the odd.
00:48:54
>> By the way, there are a lot of people in
00:48:55
New York who want to work. This is not a
00:48:56
case actually of this new fab being
00:49:00
unpopular.
00:49:02
The majority of people in the area
00:49:04
actually want this plant being built.
00:49:06
They want the jobs that are going to
00:49:07
come there. A lot of people say data
00:49:09
centers don't create a lot of jobs. This
00:49:10
is actually a chip fab. So, it will
00:49:12
create a lot of jobs. A lot of good high
00:49:14
paying jobs. People want it. But six
00:49:16
people can stop it with a lawsuit after
00:49:18
it's already been through a two-year
00:49:20
environmental review.
00:49:21
>> It's not blue and red states. These are
00:49:23
nonprofits that get organized to create
00:49:24
this kind of chaos. I remember looking
00:49:26
at a massive lithium investment in
00:49:31
Nevada. And the whole point was to
00:49:34
domesticate
00:49:35
lithium production. And what was
00:49:37
interesting is this enormous deposit
00:49:40
that's just sitting there ripe for
00:49:41
development right before they were about
00:49:43
to get environmental approvals or right
00:49:45
after there was a lawsuit by people who
00:49:48
wanted to protect the upper land grass.
00:49:50
It's seared in my mind that the upper
00:49:52
land grass of Nevada is the reason why
00:49:54
we do not have domestic national
00:49:56
security around lithium.
00:49:59
And you have to ask yourself why is this
00:50:01
possible? And it's possible because you
00:50:03
have these environmental nonprofits that
00:50:06
can go and create this chaos with
00:50:08
absolutely no risk to them. Zero. They
00:50:11
can fund raise around it and they can
00:50:12
create this chaos. I mean, Nick, to this
00:50:14
point, this is an example of Greenpeace.
00:50:17
And specifically here, they were pushing
00:50:20
back on an oil pipeline to such a degree
00:50:22
and they created so much chaos that they
00:50:24
were sued. And a North Dakota judge just
00:50:27
said that he's going to order Greenpeace
00:50:28
to pay damages. That should total almost
00:50:30
$350 million in connection to those
00:50:33
protests.
00:50:34
>> And it should not be the case that six
00:50:36
people can slow down a hundred billion
00:50:38
investment package. That's not right.
00:50:40
Well, I think there's and I just want to
00:50:42
highlight this important point. There's
00:50:44
not a lot of logic and reason.
00:50:47
You guys are right. But I do think
00:50:49
there's a lot of emotion and there's a
00:50:52
huge aversion to big tech, a huge
00:50:54
aversion to wealth creation by select
00:50:56
individuals, select companies, a huge
00:50:59
aversion to economic growth that doesn't
00:51:01
benefit everyone. There's a fundamental
00:51:03
kind of underlying left behind emotion
00:51:06
that drives a lot of this. And I've said
00:51:08
it before, but I think unless there's
00:51:10
systems or mechanisms that get folks to
00:51:12
come along with the value creation ahead
00:51:14
and and help them connect their own
00:51:17
lives to the value creation that's being
00:51:18
realized, they're not going to be
00:51:20
supportive because there is this kind of
00:51:22
diametric opposition towards big tech,
00:51:25
towards the wealth gap, towards value
00:51:27
acrruel to a select few companies or
00:51:29
select few individuals and this fuels
00:51:31
and feeds that. So I think fundamentally
00:51:33
maybe it's not just about giving the
00:51:35
data centers their own power capacity
00:51:38
but there's got to be mechanisms and
00:51:40
tools that helps the broader population
00:51:42
understand or recognize or get some
00:51:44
benefit from it as well where they're an
00:51:46
owner in it or participant in it because
00:51:49
they have the power as we're seeing they
00:51:50
have the power to stop it. Therefore
00:51:52
they want to have some benefit for
00:51:54
providing authority to do it. And these
00:51:56
six people are concerned about housing
00:51:59
costs, worker exposure to toxic
00:52:02
chemicals, pollution in air and water,
00:52:04
greenhouse gas emissions, energy
00:52:06
consumption, flooding of the wetlands,
00:52:08
all these things that obviously could be
00:52:10
mitigated. All right, let's keep moving
00:52:12
here. We got a lot more docket to get
00:52:13
through. State of the Union came in at
00:52:16
108 minutes
00:52:19
and it's the longest in 60 years.
00:52:20
actually the longest since they started
00:52:22
tracking this. The theme of President
00:52:24
Trump's State of the Union this year,
00:52:26
America at 250, strong, prosperous, and
00:52:30
respected. Trump took a bunch of victory
00:52:32
laps, inflation, jobs, closing the
00:52:34
border, all those have gone really well.
00:52:36
But this comes to the backdrop of
00:52:38
Trump's approval rating being super
00:52:40
challenged. He started his first year at
00:52:44
plus 11.7%. Now he's negative 14 14.3%
00:52:49
26 point swing. Economy started plus 3.4
00:52:52
down to 18.2 and trade started at 5.9%
00:52:56
and we'll talk about the tariff stuff
00:52:57
later and went down to 22.7.
00:53:01
So let's call balls and strikes here,
00:53:03
gentlemen. Favorite moments. What were
00:53:05
your favorite moments from the State of
00:53:07
the Union and just general impressions
00:53:09
of 1 hour and 45 minutes of Trump going
00:53:14
to town?
00:53:16
I thought it was great.
00:53:18
>> Favorite moment? Favorite moment or two?
00:53:21
Well, I had a couple.
00:53:24
One was the
00:53:26
Elon Omar Rashida Tlay death stare and
00:53:31
them just like losing their minds and
00:53:34
and screaming. I just thought it was so
00:53:38
unamerican. The second was when he was
00:53:40
calling for law and order where and
00:53:43
focusing and prioritizing on American
00:53:45
citizens and
00:53:47
>> illegal uh aliens
00:53:49
>> and none of the Democrats stood up. I
00:53:52
thought that was kind of foolish. It was
00:53:54
like obvious things and the Democrats
00:53:55
wouldn't applaud but this time they did
00:53:57
like they did for the hockey team which
00:53:58
I thought was like the right thing to
00:53:59
do. And then the fourth thing is just a
00:54:01
a shout out to our friend Brad Gersonner
00:54:03
who got a big shout out from the
00:54:04
president. I don't know Sax if you
00:54:05
engineered that or not but that was
00:54:07
>> that was fantastic.
00:54:09
He got like a double shout out. It was
00:54:10
like a double tap.
00:54:12
>> Yeah, that was really cool.
00:54:13
>> That was surreal.
00:54:14
>> Our group chat group chat went crazy. It
00:54:16
was really That was really cool.
00:54:18
>> Those are my four highlights.
00:54:20
>> Great. Here's your uh here's your clip
00:54:22
of uh yeah, Democrats not standing for
00:54:26
Americans uh over illegal aliens. 20
00:54:30
seconds.
00:54:31
>> If you agree with this statement, then
00:54:33
stand up and show your support. The
00:54:36
first duty of the American government is
00:54:39
to protect American citizens, not
00:54:42
illegal aliens.
00:54:52
>> Why wouldn't you stand for that? That's
00:54:53
an easy one to stand for. Doesn't make
00:54:56
any sense.
00:54:57
>> Would you stand for it, Chico?
00:55:00
>> Yeah. I mean, I I'm I'm pro I can be
00:55:02
anti-ICE, but I'm pro-American and I'm
00:55:05
pro reasonable immigration like 90% of
00:55:08
the country is. So, it just doesn't make
00:55:10
any sense. Uh, do you have any
00:55:12
highlight?
00:55:12
>> Do you think American citizens should be
00:55:14
prioritized over illegals?
00:55:15
>> Well, of course, of course. Yes. Of
00:55:18
course. Yes. And then I I also think
00:55:20
there should be a path to citizenship
00:55:22
for people who have been here for a
00:55:23
while. And I think that's what the
00:55:24
majority of the country thinks as well.
00:55:25
>> Your point is I can hold two thoughts in
00:55:27
my head. I would have stood if he asked
00:55:29
me.
00:55:30
>> Yes, obviously we should take care of
00:55:32
American citizens first. Yes. And we
00:55:34
should deport violent criminals. We've
00:55:36
been over this like a million times
00:55:37
here. This is like consensus.
00:55:39
>> But what do you what do you think is
00:55:40
going on in everybody else's head when
00:55:42
they're like we got to we cannot stand
00:55:43
for this?
00:55:44
>> These two sides I mean I think it's like
00:55:46
the tariff thing. It's like the ice
00:55:48
thing. These two sides cannot work
00:55:49
together. It's just the most polarized
00:55:52
it's ever been. Trump is not like the
00:55:54
kind of guy to reach across the aisle.
00:55:56
the Democrats are now digging in. So, we
00:55:58
just have a dysfunctional government
00:56:00
where, you know, in a more functional
00:56:02
time period, like under Clinton, let's
00:56:05
say, or Bush, people would have gotten
00:56:07
together, and I'm I'm jumping ahead to
00:56:09
the tariff discussion. And they would
00:56:10
have said, "Yeah, of course, tariffs are
00:56:11
done in Congress. That's the law.
00:56:13
Whatever. What are your thoughts, Mr.
00:56:15
President? How can we support your
00:56:16
tariff program?" But now it's like, "Oh,
00:56:18
well, we don't work together. We don't
00:56:20
actually have discussions anymore.
00:56:22
There's no bipartisan,
00:56:24
you know, collaboration. All these
00:56:26
politicians are disgraceful descriat
00:56:28
across the board. They should be working
00:56:30
together for the American people. If the
00:56:31
president wants to do tariffs,
00:56:33
>> they should be reasonable about it and
00:56:35
give him the power to do reasonable
00:56:37
tariffs and he should be reasonable and
00:56:38
say, "Hey, I understand that's your
00:56:39
power. Let's get together and we'll
00:56:41
we'll chop it up and let's have dinner
00:56:42
together." But they're just too
00:56:43
polarized. It's just disgraceful where
00:56:45
this country has gotten to. I blame both
00:56:46
parties.
00:56:49
Whenever the Democrats get smoked out as
00:56:52
being radicals and extremists, you
00:56:54
always want to basically say a pox on
00:56:56
both your houses and blame the
00:56:57
Republicans and Democrats equally. The
00:56:59
fact of the matter is the president said
00:57:02
to the audience, to the members of
00:57:04
Congress, hey, if you agree with the
00:57:06
statement, stand up. And of course,
00:57:08
every single Democrat sat there
00:57:10
stonefaced and refused to applaud or
00:57:14
acknowledge what he was saying. This was
00:57:17
a very easy test for the Democrats to
00:57:19
pass.
00:57:20
>> What I just said,
00:57:21
>> in fact, it was what I said.
00:57:22
>> In fact, it was a political risk for the
00:57:24
president because it was so easy for the
00:57:27
Democrats to demonstrate that they're
00:57:29
operating in good faith and that they're
00:57:30
willing to be bipartisan and they're not
00:57:32
extremists and they're actually common
00:57:34
sensical and logical and they completely
00:57:37
failed the test. And by the way, it
00:57:39
wasn't just on that one. I mean, let me
00:57:40
just tell you some of the other ones
00:57:42
where they refused to applaud. So they
00:57:45
refused to applaud the grieving families
00:57:48
of innocent American women and children
00:57:50
murdered by criminal illegal aliens,
00:57:52
including the mother of Ireina
00:57:55
Zeritzkaya.
00:57:56
>> That was very sad. That was sad.
00:57:58
>> That was unbelievable. They refused to
00:58:00
applaud for securing our homeland and uh
00:58:03
ending the invasion of criminal illegal
00:58:06
aliens, killers, rapists, gang members,
00:58:08
and traffickers. They refused to applaud
00:58:10
for unifying against political violence.
00:58:13
So, the president mentioned the
00:58:14
assassination of Charlie Kirk. They
00:58:16
would not even do a polite clap for
00:58:19
Erica Kirk and unifying against
00:58:20
political violence. They refused to
00:58:23
applaud for keeping violent criminals
00:58:25
locked up. They even refused to applaud
00:58:28
for lower prescription drug prices for
00:58:30
millions of Americans because it was
00:58:31
President Trump who orchestrated that
00:58:33
policy. And there were so many other
00:58:35
examples like that. And you know, I
00:58:37
think the reason why this speech was so
00:58:39
effective, and by the way, it's not just
00:58:41
me saying it. something like twothirds
00:58:43
of the people that CNN pled, so
00:58:45
twothirds of CNN watchers said it was
00:58:48
highly effective and something like
00:58:49
threearters of CBS news viewers said it
00:58:52
was highly effective is because the
00:58:54
president laid out 8020 issue one after
00:58:57
another, right? Or even 9010 issues or
00:59:00
955 issues. I mean, these were all
00:59:03
issues where the overwhelming number of
00:59:05
Americans, I think, agree with the
00:59:07
policy the president laid out. And in
00:59:09
every single case, the Democrats
00:59:11
supposed to wouldn't even give it
00:59:12
applied applause. And that is different
00:59:14
than than in the past. And you can say
00:59:16
that's because of hyperartisanship and
00:59:18
polarization, but it's also because of
00:59:20
another thing. It's because the
00:59:21
Democrats have become a party of
00:59:24
radicalism and extremism. And the
00:59:27
viewpoints that they expressed through
00:59:30
their aesthetics the other night, they
00:59:33
do express those things in policy and in
00:59:35
speeches all the time. So it's not just
00:59:38
like a oneoff or you know somehow like
00:59:41
we have a misconception of who these
00:59:43
guys are. I think you know the big line
00:59:45
of the night was when Trump just sort of
00:59:47
said these people are crazy. I mean he
00:59:49
said it in like almost mournful and
00:59:51
regretful way. He doesn't want them to
00:59:52
be crazy. He wants them to be rational
00:59:54
so he can work with them. I mean,
00:59:56
>> but I think that point re I'll I'll
00:59:57
still point the other side, which is
00:59:59
this has been going on for a couple of,
01:00:01
>> you know, state of the unions here
01:00:03
across this. The Republicans didn't
01:00:04
stand for the Democrats often and uh
01:00:07
it's a bit of showmanship. But the truth
01:00:09
is Trump is the divider and chief chief.
01:00:11
He always is attacking people. He's
01:00:13
always mocking people. So, they don't
01:00:15
want to play ball with him. So, I do
01:00:17
think you can both choice in politics.
01:00:19
You got to counter punch.
01:00:20
>> Uh no, I don't think so. That's actually
01:00:22
the that's actually the problem with the
01:00:25
that philosophy, Trump's philosophy of
01:00:27
we have to counter punch, we have to
01:00:28
attack, we never have to apologize, we
01:00:30
never have to be reasonable. That's part
01:00:32
of what's broken down in our politics
01:00:33
and these two sides should work
01:00:35
together. We should go back to a
01:00:36
bipartisan.
01:00:37
>> Are you going to work with Helen Omar
01:00:39
when he is when the president going to
01:00:40
be easy, but she is the mirror. Hold on,
01:00:42
I'll finish my statement. You asked a
01:00:44
question. I think Trump is the mirror of
01:00:47
that. He has been hostile towards these
01:00:49
Democrat. He doesn't give them an inch.
01:00:50
they should be more collaborative. That
01:00:52
that's what the balance of power between
01:00:55
the executive branch, you know, and and
01:00:58
these uh you know, congressmen and and
01:01:00
the Congress and the Senate. Like this
01:01:02
is how it's supposed to work. And these
01:01:04
two sides need to learn how to get back
01:01:06
to listening to each other,
01:01:08
understanding each other's positions,
01:01:09
and then finding a middle ground. And
01:01:11
that's why the Democrats lost last time
01:01:13
because they didn't have the common
01:01:14
sense to say, "Hey, everybody wants the
01:01:16
border closed." To your point, it's a
01:01:18
90% issue. and Kla Harris was too dumb
01:01:21
to just say, "Yeah, we should have
01:01:22
closed the border. It's closed now." And
01:01:24
uh we've got it. Anyway, the whole thing
01:01:26
is a mess. I understand you got to fight
01:01:28
for your team. I don't like the
01:01:29
>> count. You just actually made the key
01:01:31
point. You made the key point which is
01:01:33
underlying the optics and the
01:01:34
polarization. You have issues and on
01:01:37
those issues, President Trump is on the
01:01:40
side of the American people. the issues
01:01:42
where 80% of the American people agree.
01:01:44
Some huge percentage, I don't know
01:01:45
exactly what it is, thinks that the
01:01:47
Somali daycare fraud in Minnesota was an
01:01:51
outrage. And the president is right to
01:01:54
point that out. And what's the
01:01:55
Democrat's reaction? You've got Ilan
01:01:57
Omar screaming from the audience at him.
01:02:00
>> Yeah, she's alone. I mean, at the end of
01:02:02
the Democrats are not that different.
01:02:03
You did have you did have Elizabeth
01:02:06
Warren stand for uh stopping Nancy
01:02:10
Pelosi from trading stocks and that gave
01:02:11
Trump his best oneliner of the night.
01:02:13
That was his best oneliner clearly and
01:02:15
they stood for Iran too and stopping
01:02:18
Iran from being a nuclear.
01:02:19
>> I give Elizabeth Warren credit for that.
01:02:21
>> There you go. You don't have to punch
01:02:22
her back.
01:02:23
>> Stop insider trading act without delay.
01:02:27
>> Yeah. See, that's something bipartisan.
01:02:29
Look at that, Zach. That's what you need
01:02:31
to get the country back to. But that
01:02:33
hold on. But this this disproves the
01:02:35
point you were making before. You said
01:02:37
that it was polarization.
01:02:38
>> You stood up for that. I can't believe
01:02:41
>> can't believe Nancy Pelosi stand up if
01:02:44
she sing pal. Good job.
01:02:47
>> That's why he's so good is he's in the
01:02:49
moment and he's reacting to what's
01:02:50
happening in the chamber. He's not good.
01:02:52
He's not just reading from a
01:02:53
teleprompter. And he nailed it. But
01:02:55
look, that moment disproves what you
01:02:57
were saying, Jal, because this is not
01:02:58
just about polarization. On that issue,
01:03:01
Elizabeth Warren was willing to stand
01:03:02
because she actually, to her credit,
01:03:04
wants to ban insider trading by members
01:03:06
of Congress. Yes. But on the rest of
01:03:08
those issues, like securing the border,
01:03:09
she did not stand. Why? Because she does
01:03:11
not agree with the president on that
01:03:13
issue.
01:03:14
>> We just have to get back to these sides
01:03:16
working together. That's my personal
01:03:18
feeling.
01:03:19
uh Freeberg, any thoughts on the uh
01:03:21
theatrics and uh Trump's first year at
01:03:24
large and you know the sort of back and
01:03:26
forth and is there any hope that these
01:03:29
two teams could collaborate at some
01:03:32
point on something like say the
01:03:34
ballooning deficit which Trump has not
01:03:36
gotten under control in his first year
01:03:38
and it's going to be $2.5 trillion
01:03:40
dollars added. What are your thoughts
01:03:42
here on them collaborating on anything
01:03:44
important? Friedberg, that's probably
01:03:45
one thing they can agree on is just keep
01:03:47
the money flowing. Got it. They'll both
01:03:49
give a They'll both give a a standing
01:03:51
ovation for burn more capital and put us
01:03:53
more in debt. Well said my guy David
01:03:57
Friedberg, sultpan of science, it is
01:04:00
your time to shine. The world's greatest
01:04:03
moderator has decided we're going
01:04:05
directly to science corner. This is your
01:04:07
time to shine.
01:04:09
>> Sax's time to drop a deuce.
01:04:10
>> Sax went immediately off camera.
01:04:12
>> Yeah, he has to drop a deuce.
01:04:13
>> What's up?
01:04:16
>> But what do you need me for? This is
01:04:17
very important for you.
01:04:19
>> Freeberg's going to talk.
01:04:20
>> Lightning round for science corner. Go
01:04:21
Freeberg.
01:04:22
>> Wait, wait, wait. Are we doing any more
01:04:23
topics after this or can I just leave?
01:04:24
>> Yes, tariffs.
01:04:25
>> Yes, we're doing tariffs.
01:04:26
>> Wait, why would we do that?
01:04:27
>> Because I want to get the audience to
01:04:30
sleep. I'm not saying Science Corner
01:04:32
doesn't have its audience.
01:04:33
>> Listen, you can go.
01:04:34
>> Why wouldn't we do Yeah, exactly. You're
01:04:37
screaming.
01:04:37
>> Let him do his work.
01:04:38
>> Let him let him cook. Let him cook.
01:04:40
>> Freeberg, tell us about this Harvard
01:04:41
scene.
01:04:42
>> Speaking of science, I think that
01:04:43
there's a very important moment
01:04:44
happening right now. We've talked a
01:04:46
number of times on the show about
01:04:47
Yamanaka factors. These are these four
01:04:50
proteins that were discovered by Shina
01:04:53
Yamanaka that we found later that when
01:04:56
applied to cells, mamalian cells can
01:04:59
actually reverse the age of those cells,
01:05:01
reset the epigenetic clock, reset the
01:05:04
epiggenome, which is the little markers
01:05:05
on top of the DNA that turn genes on and
01:05:07
off back to a youthful state.
01:05:10
extraordinary groundbreaking work that
01:05:12
was done that won the Nobel Prize led to
01:05:14
the foundation of several companies.
01:05:16
There's a Harvard uh scientist named
01:05:18
David Sinclair. He's a bit of a
01:05:20
controversial character. Do you guys
01:05:21
know him? I think you guys one one or
01:05:23
two of you may have met him. Chim, you
01:05:24
ever met him?
01:05:25
>> I I I followed him. I've seen his stuff.
01:05:28
So Sinclair is kind of bemoaned a little
01:05:31
bit by the scientific and academic
01:05:33
community for being a little too
01:05:34
overhypy snake oil salesman as some of
01:05:38
folks have claimed because years ago he
01:05:40
sold a company to GSK saying resveratrol
01:05:43
would reverse aging and you know he made
01:05:45
$720 million on that and it didn't end
01:05:47
up working and he's promoted certain
01:05:49
supplement companies and so on. So, I
01:05:51
want to preface with that before I kind
01:05:52
of underwrite what he's saying with this
01:05:54
next thing, but he's a co-founder of a
01:05:56
company called Life Biosciences, and
01:05:59
they've reached a major agreement with
01:06:00
the FDA to be the first company to treat
01:06:03
humans with Yamanaka factors.
01:06:06
Specifically, what they're doing is
01:06:07
they're going to be delivering these
01:06:09
Yamanaka factors, these are these
01:06:11
proteins
01:06:13
that rejuvenate cells and make them
01:06:15
youthful again into the eye. And so
01:06:18
their their first indication is to
01:06:20
actually inject them into the vitrial
01:06:22
fluid in the eyeball and they'll affect
01:06:24
the retina in the eye to address people
01:06:28
that have gotten blind from glaucoma or
01:06:31
one of these kind of stroke like
01:06:33
diseases that happen in the eye. And the
01:06:35
expectation with this phase one clinical
01:06:37
trial is that the delivery of these
01:06:39
Yamanaka factors into the eye will
01:06:41
rejuvenate the retina, make it youthful
01:06:44
again, and restore vision. If it works,
01:06:47
which it's expected to because we see
01:06:48
this result happen in animal models, it
01:06:51
could be an extraordinary breakthrough,
01:06:53
not just in terms of blindness, but in
01:06:55
terms of the first human application of
01:06:58
Yamanaka factors to reverse aging. The
01:07:01
way they're doing it is they're actually
01:07:03
packaging up DNA that will make these
01:07:06
proteins into viruses, AAV virus that is
01:07:12
delivered into the eye. The virus will
01:07:14
then go into the retinal cells and then
01:07:17
will deliver this payload for this DNA
01:07:19
to make these proteins in the eye uh
01:07:21
cells and it can be turned on and off.
01:07:24
Amazingly they've created a switch
01:07:26
mechanism in it where the protein
01:07:28
production the production of these
01:07:29
Yamanaka factors can be turned on and
01:07:31
off by taking an antibiotic called
01:07:34
doxycyc. So the person that gets the
01:07:36
delivery of this drug takes the
01:07:38
antibiotic turns on the production of
01:07:40
these Yamanaka factors and then
01:07:41
theoretically their eye cells will deage
01:07:44
will get youthful and their vision will
01:07:46
be restored. So phase one clinical
01:07:48
trials underway. First time in human
01:07:50
history we're seeing Yamanaka factors
01:07:52
being delivered into humans. Literally
01:07:54
the tip of the iceberg. There are now
01:07:56
over a dozen startups that are trying to
01:07:59
deliver Yamanaka factors which are these
01:08:01
proteins or some other sort of protein
01:08:03
that can actually reverse aging by
01:08:05
restoring the epiggenome and cells and
01:08:07
make them young again. So this is the
01:08:09
beginning of a wave of what I think will
01:08:11
be the most extraordinary revolution in
01:08:14
human therapeutics and ultimately could
01:08:16
lead to
01:08:18
you know some people would argue the
01:08:20
fountain of youth. Is this just a talk
01:08:22
study? So is it mechanism?
01:08:25
>> They're not. Yeah, they're they're well
01:08:26
they'll see results. They'll see
01:08:27
results, but they're going to they're
01:08:28
going to keep dosing low. But you will
01:08:30
see results.
01:08:31
>> God, that's going to be incredible.
01:08:32
>> It's going to be incredible. By the way,
01:08:34
the number of other folks that are
01:08:36
gearing up for phase one using if not
01:08:39
the Yamanaka factors, other factors that
01:08:41
they've identified or designed as an
01:08:44
alternative to Yamanaka factors again to
01:08:46
rejuvenate the cells. And just to remind
01:08:47
folks, the way this works is it was
01:08:49
discovered that these proteins when they
01:08:51
go into a cell, they take all of those
01:08:53
little markers that sit on top of your
01:08:55
DNA that turn genes on and off and they
01:08:58
create a system that causes them all to
01:09:00
move to the right place. So, it resets
01:09:02
the markers so that those cells will
01:09:04
start to operate like they're supposed
01:09:05
to when they were young again.
01:09:07
>> That's going to be
01:09:08
>> it's going to be incredible. Yeah. Do
01:09:10
you think like No, in all seriousness,
01:09:11
people's knees or joints or what where
01:09:14
do you think it could flow to next in
01:09:16
arthritis?
01:09:17
>> Yep. Um and and by the way, when applied
01:09:19
and if it's distributed in the skin,
01:09:21
they've seen some results in monkeys
01:09:22
where like wrinkles go away.
01:09:24
>> It like literally makes these cells all
01:09:26
work youthful again. And so a lot of the
01:09:28
damage that happens over time is not
01:09:31
damage to DNA. It's damage to the
01:09:33
epiggenome. It's the parts that sit on
01:09:36
top of the DNA that turn genes on and
01:09:38
off. And they get moved to the wrong
01:09:39
place as you get older. And by resetting
01:09:41
them and getting them back to the right
01:09:42
place, boom, the cell is young again,
01:09:44
the organ is young again, and suddenly
01:09:46
you look and act and feel young again.
01:09:48
It's an incredible technology. We're
01:09:50
just at the early stages, the early
01:09:52
innings of turning it into therapeutics.
01:09:54
Again, the discovery goes back to 2006
01:09:57
and now we're starting to see it get
01:09:58
into clinic.
01:09:59
>> All right, let's rejuvenate. Let's
01:10:00
rejuvenate some hairlines on this
01:10:02
podcast. Uh, that would be next up.
01:10:04
>> Speak for yourself.
01:10:05
>> I don't know. You got You got a little
01:10:07
uh You got a little peaks going there,
01:10:08
my brother. A little peak.
01:10:09
>> What are you talking about, bro? My
01:10:10
hairline's incredible. I'm 50.
01:10:12
>> I mean, it's not bad for 50. I give you
01:10:14
credit. You're You're holding your own.
01:10:15
All right, let's talk about our final
01:10:16
topic. Scotas struck down Trump's
01:10:19
emergency powers tariffs. Last Friday,
01:10:22
Scotas voted 63 against President
01:10:25
Trump's tariffs. Six judges voted
01:10:28
against. three conservatives, Roberts,
01:10:30
Barrett, Gorsuch, uh, and three liberals
01:10:33
via Bloomberg. This is the biggest
01:10:35
rebuke of existing executive policy in
01:10:39
91 years since Scottish struck down
01:10:41
FDR's first new deal in 1935.
01:10:45
UPUP Wharton Analysis says the tariffs
01:10:48
collected about 175 billion to date, 50%
01:10:51
of all tariff duties, um, might wind up
01:10:54
being refunded. This is going to take
01:10:57
some time to sort out in the courts.
01:10:59
2,000 importers have already filed for
01:11:01
refunds. We we talked about it here. I
01:11:04
think the majority of people felt like
01:11:05
this is the way the decision would go.
01:11:08
And we talked about here that there were
01:11:10
other options for President Trump to
01:11:12
pursue. He immediately said he was not
01:11:16
deterred and invoked a 15% global tariff
01:11:18
across the board via section 122 of the
01:11:21
1974
01:11:23
trade act. Here's your poly market. Will
01:11:26
the court force Trump to refund tariffs?
01:11:29
18% chance but spike to 40% after the
01:11:32
SCOTA's decision. How will Congress
01:11:34
react? Poly market says 3% chance.
01:11:37
Congress passes any tariffs by March
01:11:40
31st. So again, as I referenced earlier,
01:11:44
these two sides just can't seem to work
01:11:46
together. And that would have resolved
01:11:48
the whole thing. Saxs, you want to um
01:11:51
give us your take here?
01:11:52
>> First of all, I don't think that the
01:11:53
tariffs are going away. What the court
01:11:56
basically indicated especially the
01:11:58
70page Kavanaaugh descent is that
01:12:00
there's multiple alternative bases in
01:12:02
law for the tariffs in existing law. So
01:12:06
for example section 122 of the trade act
01:12:10
of 1974
01:12:12
enables temporary 150day tariffs of up
01:12:16
to 15% to address balance of payments
01:12:19
issues and the president has already
01:12:21
invoked this. So we are now operating
01:12:23
under that. What the 150 days is going
01:12:25
to do is buy the administration time to
01:12:28
substantiate via studies and agency
01:12:32
reviews. What it needs to prove in order
01:12:34
to invoke more sweeping tariff authority
01:12:38
under section 301 of the trade act and
01:12:40
under section 338 of the tariff act.
01:12:45
Section 301 authorizes tariffs
01:12:46
responding to unfair foreign trade
01:12:49
practices. Section 338 of the tariff act
01:12:52
allows tariffs against countries
01:12:55
discriminating against US commerce. The
01:12:57
Kavanaaugh descent actually provided a
01:12:59
roadmap for the administration to put in
01:13:03
place tariffs using one of these
01:13:05
alternate uh bases. So, I think that one
01:13:08
way or another, the tariff policies of
01:13:09
this administration and the favorable
01:13:12
trade deals that they allow us to strike
01:13:13
with many nations, they will continue.
01:13:15
And I think the court seems to know that
01:13:18
because the majority's opinion as
01:13:20
concurrences collectively said nothing
01:13:23
about how the administration should go
01:13:24
about refunding the tariff revenue
01:13:27
already collected. I think that if they
01:13:29
expected this decision to end the tariff
01:13:31
policies altogether, they probably would
01:13:33
have said something about that. And I
01:13:36
think that brings up a really important
01:13:37
point just on the merits here, which is
01:13:40
why would we want to give back hundreds
01:13:42
of billions of dollars to a bunch of
01:13:44
importers when we're trillions of
01:13:46
dollars in debt? And I'll just say that
01:13:48
the people who originally predicted that
01:13:50
somehow these tariffs would be
01:13:51
catastrophic for the economy. Those
01:13:53
predictions all prove not to be true. So
01:13:56
I think that this is ultimately, I
01:13:58
think, going to be a popular policy. The
01:14:00
administration will figure out a
01:14:01
different way to do it. And I predict
01:14:02
that future administrations, whether
01:14:04
they're Republican or Democrat, will
01:14:07
keep some version of the tariffs in
01:14:08
place, but I think that they will be
01:14:10
ultimately popular on a long-standing
01:14:12
basis. Chamathy, your thoughts?
01:14:15
>> I think we've proven the experiment has
01:14:17
been successful.
01:14:20
>> What was the experiment?
01:14:22
We needed to smoke out what the right
01:14:25
balance of trade should be between the
01:14:27
United States and all of its partner
01:14:29
countries. I think that what we
01:14:31
uncovered is that for the most part they
01:14:33
were structural imbalances that were
01:14:36
made not because they made economic
01:14:37
sense for America, but it was just part
01:14:40
of a hodgepodge of globalist dril that
01:14:44
people just bought into. And if you
01:14:45
strip all that stuff away, we had a
01:14:48
hollowedout manufacturing class and we
01:14:50
have a hollowedout middle class and the
01:14:52
tariffs will create more equality for
01:14:55
the American worker in the end. So now I
01:14:57
think the debate should be about how to
01:14:59
implement these in a structural and
01:15:01
permanent way.
01:15:03
I think we talked about this before
01:15:04
Jason that this was sort of expected and
01:15:08
>> there are many other mechanisms. I think
01:15:10
the president activated one of them
01:15:12
immediately.
01:15:13
>> I don't think this is going away and I
01:15:15
don't think it should go away. So I
01:15:17
think now the point is
01:15:19
Congress really should ratify these
01:15:21
things because it is clear that it was
01:15:23
the right thing to do
01:15:25
and if they don't then you know the
01:15:28
president still has a lot of room to get
01:15:29
these done but these make smart economic
01:15:31
sense in my opinion.
01:15:32
>> Freeberg any thoughts on the ruling?
01:15:34
Does it give you
01:15:37
some I don't know um respect for the
01:15:40
courts that they made a judgment not
01:15:42
along party lines for once? Uh does it
01:15:45
Yeah. Okay. Exactly.
01:15:46
>> Yeah. And I think I think that all I
01:15:48
think all Americans
01:15:50
should feel assured and comforted in the
01:15:53
fact that I think a lot of people view
01:15:55
the Supreme Court as having a high
01:15:56
degree of partisanship.
01:15:59
The fact that the president despite
01:16:01
having a majority of what others would
01:16:03
think were kind of politically aligned
01:16:05
appointees on the court had a ruling
01:16:07
that he did not want.
01:16:10
I think should give everyone good faith
01:16:11
that the system that the founders set up
01:16:14
is working that there is a judicial
01:16:15
branch that adjudicates the law against
01:16:18
the executive branch when they think
01:16:19
that um it doesn't map and I think that
01:16:22
that was very important to see. So, you
01:16:25
know, I clearly you the the debate about
01:16:27
tariffs, the economic effect of tariffs,
01:16:29
the security structural trade
01:16:31
relationship effect of tariffs and the
01:16:33
importance of that is a separate
01:16:34
conversation, but I do think that the
01:16:35
read of the law being what I would say
01:16:37
is nonpartisan with respect to the
01:16:39
court's action is important and probably
01:16:42
very valuable. I'll reiterate that this
01:16:44
is a great moment, I think, for uh the
01:16:47
Supreme Court to make a thoughtful
01:16:49
decision. And I think we need to think
01:16:51
about executive power a whole bunch.
01:16:53
Whether it's Biden with student loans or
01:16:55
Trump with tariffs, we have this
01:16:58
beautiful system set up by the founding
01:16:59
fathers. I know it's frustrating.
01:17:01
Gridlock's frustrating. Having to work
01:17:03
together is frustrating. Trust me, we we
01:17:05
all come to this podcast every Thursday.
01:17:08
We have to work together. It's hard to
01:17:09
work together. You got to learn to work
01:17:11
together. And we don't want an executive
01:17:13
branch that can unilaterally just roll
01:17:15
over the other branches. And uh that's
01:17:18
going to end. I think Trump's going to
01:17:19
lose the midterms and we're going to get
01:17:21
to more chaos again and it we might as
01:17:24
well start this reconciliation process
01:17:26
of these two sides stopping their law
01:17:29
for against each other and working
01:17:31
together for the American people on the
01:17:33
important issues. The tariffs there are
01:17:36
some fundamentally important things that
01:17:38
Trump was doing there and they were
01:17:40
working. They could have been chaotic.
01:17:43
uh that's a reasonable um you know
01:17:46
criticism of them because business
01:17:47
owners didn't know what to do. So Trump
01:17:49
did it in a chaotic way. That's just a
01:17:50
fact. He should have done it in a more
01:17:52
thoughtful way and the Congress should
01:17:54
have been alongside him saying, "Hey,
01:17:56
what tools do you need? How can we help
01:17:58
support this? We know that there's trade
01:18:00
imbalances. We know that people are
01:18:03
being unfair. Let's work together as one
01:18:05
America to negotiate these things." So
01:18:07
both sides start having dinner together,
01:18:10
start playing cards together, and do
01:18:11
what we do here on this podcast, which
01:18:13
is you fight it out. You argue, but then
01:18:15
you come together and try to find some
01:18:16
resolutions for this stuff. So they
01:18:18
should go and tell Trump, "Hey, we'll
01:18:21
approve all the tariffs you did. We will
01:18:23
not force you to get refunds." The
01:18:25
Congress should come out and just say
01:18:26
that. And then they should say, "Hey,
01:18:28
and when you want to do them in 2026,
01:18:30
just run them by us or ask us for some
01:18:32
parameters that you want and let's just
01:18:34
be thoughtful about it. These are our
01:18:35
concerns. That's it. Thank you for
01:18:37
coming to my TEA talk. Can
01:18:38
>> I just do one?
01:18:39
>> Absolutely. I'm sure you have some
01:18:40
debate club points that you want to
01:18:42
point that out.
01:18:42
>> Well, I just want to make one. I mean,
01:18:43
do you think Susan Rice is going to
01:18:46
respect your call for comedy and
01:18:50
basically working together Kumbaya?
01:18:53
>> I want the Aspree to corpse. No, I
01:18:54
don't. I think both sides. She just had
01:18:57
a diet tribe where she basically said
01:18:58
that Republicans and actually not just
01:19:02
like partisan Republicans, but even tech
01:19:04
companies that merely were working with
01:19:06
the administration should expect to get
01:19:08
prosecuted. I mean, she was basically
01:19:10
outright saying she's she and the
01:19:12
Democrats are going to pursue lawfare as
01:19:14
soon as they get back in charge.
01:19:16
>> They're they're absolutely going to do
01:19:17
that. Just like when Trump got in, he
01:19:19
went after Comey, he went after Jerome
01:19:21
Pal. The lawfare is happening on both
01:19:22
sides. Both sides need to drop the
01:19:24
lawfare. We need to get rid of these
01:19:25
pardons. They're ridiculous. And these
01:19:27
team this, we have to be a team. So,
01:19:30
let's just get some aspa of corpse and
01:19:31
teamwork going in Washington DC. And
01:19:34
that's what we should vote for in the
01:19:35
midterms. We should vote for moderates
01:19:37
who want to work together. And in 2028,
01:19:40
we should have some kind of moderates
01:19:43
and tickets that want to work together.
01:19:46
That would be better for all Americans.
01:19:48
This kind of chaos is not good, folks.
01:19:50
All right. Listen, this has been another
01:19:51
amazing episode of the All-In podcast,
01:19:53
your favorite podcast. Uh, like,
01:19:55
subscribe, whatever the hell you want to
01:19:57
do on your own time for David Sachs,
01:20:00
David Freeberg, Chamal Pia. Love you,
01:20:03
boys. I am the world's greatest Monterey
01:20:05
J. See you next time. Byebye. Byebye.
01:20:09
>> We'll let your winners ride.
01:20:16
And it said, "We open sourced it to the
01:20:18
fans and they've just gone crazy with
01:20:20
it."
01:20:21
>> Queen of
01:20:29
>> besties are
01:20:32
my dog taking notice your driveways.
01:20:37
>> Oh man, my habitasher will meet up.
01:20:40
>> We should all just get a room and just
01:20:41
have one big huge orgy cuz they're all
01:20:43
just useless. It's like this like sexual
01:20:45
tension that we just need to release
01:20:46
somehow.
01:20:51
>> Your feet.
01:20:53
We need to get merch.
01:20:55
>> I'm going all in.
01:21:03
I'm going all in.
