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Garry Nolan (2025) - Unlocking Mysteries and Accelerating Discovery · The Joe Rogan Recap

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  Welcome to the Joe Rogan recap. Today, we're doing a deep dive
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  into the really compelling work of Doctor Gary Nolan.
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  He's a Stanford professor, and his research covers a lot,
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  everything from cancer immunology to AI and science and
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  even, you know, Uaps and strange materials.
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  Our goal here is to pull out the key insights, show how these
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  different areas are actually connected.
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  We'll talk about how cancer tricks our immune system, the
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  amazing potential of AI and some pretty wild findings about Uaps.
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  Gary, for some real aha moments. OK, so let's start with Doctor
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  Nolan's, you know, his main gig, Cancer Research and immunology.
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  He talks about cancer being like this intricate dance.
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  Right. A dance where the tumors don't
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  just hide, they actually trick the immune system.
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  Trick it into helping them grow even.
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  Yeah, it's the cleverness of it that's kind of mind blowing.
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  Doctor Nolan points out that every single day each of us
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  develop something like 5 cancer like objects. 5A day.
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  Yeah, roughly. But normally our immune system
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  just shuts them down, no problem.
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  The trouble starts when a tumor figures out how to turn off the
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  alarm bells. They manipulate these things
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  called MHC proteins, major histocompatibility complex
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  proteins. HC proteins and those are like
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  the ID cards for cells, right? Exactly.
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  They tell the immune system I'm healthy or I'm infected.
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  Cancer learns to fake its ID or just hide it all together.
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  Makes it invisible. OK, so if we understand that it
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  totally changes how we treat it. Absolutely.
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  Doctor Nolan brings up immunotherapy like the work Jim
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  Allison did. Won the Nobel Prize for it.
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  Right, finding ways to block those turn off signals cancer
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  uses. And the results were just wow,
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  Melanoma survival went from what, 5%?
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  To 50%. Yeah, a huge leap.
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  It showed we can actually harness the body's own defenses.
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  And Doctor Nolan's lab isn't just studying this, they're
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  building the tools, too. That's a key point.
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  They're developing instruments that generate way more data than
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  ever before, he mentioned. Going from looking at maybe 3
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  proteins at once to. 50 or 60 proteins.
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  Exactly 50 or 60. That sheer volume of information
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  let's them build these mathematical models.
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  Models to predict outcomes better, yeah.
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  And that pushes us towards really personalized medicine,
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  tailoring the treatment. And that personalization aspect
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  is super relevant for, you know, for you listening.
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  Doctor Nolan really hammers home this idea of biological
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  variability. Right, because even the same
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  type of cancer can act differently in different people.
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  So a drug that works wonders for one person might do nothing for
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  someone else. Precisely which means you need
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  medication tailored to the individual.
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  Which brings up that whole benefit to damage ratio thing he
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  mentioned. Yeah, that's crucial in
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  medicine. All drugs have side effects, of
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  course, and doctors often have to play the odds based on
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  statistics. Doctor Nolan argues we need
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  diagnostics that can perfectly marry a specific drug to a
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  specific subtype of the disease in that patient.
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  So instead of a drug working 60% of the time on average.
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  You could potentially get it to work 90% of the time for the
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  right patient. Much better outcomes, less harm
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  from side effects. He also gets personal talking
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  about his own genetic mutation. MIDF 318K.
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  Yeah, which gives him a higher risk for Melanoma and kidney
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  cancer. And that leads him to talk about
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  sunlight. You know how the advice has
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  changed. Right, it's not just sun bad.
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  No, it's the UV radiation specifically that's the danger
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  light itself gives us. Vitamin D helps regulate sleep
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  cycles and important stuff. And he looks ahead, suggesting
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  maybe one day a CRISPR ointment could fix mutations like his.
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  Yeah, imagine that, fixing a single point mutation so you can
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  enjoy the sun without that risk. Yeah, he also touched on RNA,
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  how it got a bad rap from vaccines.
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  But it's just a natural, vital part of our cells.
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  OK, sticking with health, What about early detection?
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  He's a big advocate, but with a major warning.
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  Yes, and this one surprises a lot of people.
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  He warns that routine CT scans, they're known to cause cancer.
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  Because of the radiation. Exactly.
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  He suggests MRI is often a safer bet if possible, and he really
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  stresses getting a baseline. Scan a baseline.
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  So you have a starting point. We all have these little weird
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  spots. He calls them phantom.
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  It's usually harmless, A baseline.
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  Let's doctor see if anything changes or grows over time.
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  That's how you catch real problems early.
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  And don't worry about the harmless stuff.
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  He also has this really interesting, almost
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  philosophical take on what cancer is.
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  Yeah, not just a disease, but like a devolution.
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  A breaking of contracts between cells, he said.
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  What does that actually mean? Well.
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  The implication is pretty deep if cancer isn't evolving forward
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  but regressing back to this primitive urge to just divide.
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  Then there's no single magic bullet.
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  Exactly means no one-size-fits-all drug will ever
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  work for all cancers. It just reinforces how unique
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  and complex each tumor is. And given his own health
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  situation, he shared a bit about his diet.
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  Right. He avoids too much meat,
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  especially charred meat, because of carcinogens.
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  Makes sense. And he limits sugar, calls it a
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  real problem with cancer. You can tell he just has this
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  immense respect, this awe for the complexity of the cell.
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  He calls it a universe. OK, let's shift gears.
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  The data deluge in science. So much information researchers
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  were drowning. Right, just overwhelmed.
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  And the solution, the Eureka moment, was AI, artificial
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  intelligence. Pretty much.
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  He explains how AI can now analyze literally millions of
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  published papers, 22 million papers, he said.
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  Like an immunologist scientist in a box.
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  Exactly, and in his lab they have this agentic AI.
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  You give it raw data, ask questions in plain English and.
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  It comes up with hypothesis suggests experiments, yeah.
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  And like 3 hours, a task that might take a grad student
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  months. Yeah, it's completely changing
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  the speed of research. He did admit, funny enough, that
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  the AI had a lot of hallucinations at first.
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  Yeah, but then he quipped. Some of my best students
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  hallucinate. Meaning the human is still
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  essential. Absolutely.
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  You need the human in the loop to guide it.
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  Check its work. So where are they applying this
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  AI specifically? One key area is understanding
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  the tumor immune interface, that battleground between the cancer
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  and the immune system and specifically these things called
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  tertiary lymphoid structures or TLS that can form inside tumors.
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  TLS. What do they do?
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  Well, mature TLS are linked to bitter outcomes from
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  chemotherapy. The AI helped them figure out
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  exactly which cell types are needed to build these mature
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  TLS. Which then leads to the
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  question. Right.
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  Can we actually make tumors form these helpful TLS structures
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  using therapy? That could be huge.
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  In the AI itself, he mentioned using Open AI but with a special
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  layer on top. Yeah, an agentic overlay
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  basically teaching the AI how scientists think, how they ask
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  questions, how they approach problems.
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  And he's open sourcing it, giving it away.
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  Putting it on GitHub for the whole scientific community,
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  which ties into his views on commercializing research from
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  universities. He ignored advice not to
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  commercialize. He did, and things he invented,
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  like a system called 293T for making retroviruses, have
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  generated significant money for Stanford through licensing.
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  But it also makes those tools widely available.
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  He sees it as giving back to the taxpayers who fund the initial
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  science. The impact of AI right now, he
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  says, is already creating dozens of potential new target
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  opportunities. Things that weren't even on the
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  radar a year ago. And looking further out.
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  He paints a picture of AI helping with things like those
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  CRISPR ointments we mentioned. Maybe Neuralink style brain
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  interfaces? Even a universal language
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  through brain chips leading to a hive mind.
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  Or a post scarcity environment. Yeah, it definitely makes you
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  wonder about humans. Merging with AI doesn't.
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  It but he's he's not just a tech optimist.
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  He sees the downsides, too. Oh, definitely.
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  He's really concerned about automation wiping out huge
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  numbers of jobs. A gigantic swath of the American
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  workforce, he said. Which?
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  Brings up things like universal basic income, Ubi.
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  But Ubi doesn't solve everything.
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  No, he points out. Work gives people identity, a
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  sense of worth. What happens if that disappears?
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  And he also flags the huge risks of AI in the military making
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  life or death decisions without, you know, human ethics or
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  morality. That's scary.
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  OK, now for the big shift. How does a top cancer researcher
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  end up studying Uaps? Right, it started, he said, with
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  the Otakama mummy. This tiny little skeleton
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  claimed to be an alien. Oh, I remember that.
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  He did. The DNA sequencing proved it was
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  human female Chilean ancestry specific genetic mutations.
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  Which probably didn't make him popular with the UFO crowd.
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  No, it angered a lot of them, but it got him noticed by a
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  scientific community that already existed that was quietly
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  working with the government on UAP analysis.
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  And that led to work with the CIA and an aerospace company
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  analyzing medical records. Yeah, records of people who
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  claimed they were harmed by strange phenomena.
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  And what was striking was that most of them were actually early
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  Havana Syndrome cases. Yeah, they showed clear damage
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  in the brain. It was concrete evidence that
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  something had happened that moved it beyond just stories,
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  you know, into measurable physical effects.
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  But there were others, about 10 people, who didn't fit Havana
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  Syndrome. Right.
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  These people claimed injury directly from UAP contact.
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  They had things like white matter disease in the brain or
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  actual physical welts like they've been zapped.
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  But these are one off events, hard to study scientifically.
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  Exactly. That's the challenge.
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  They're not reproducible in a lab, but the physical evidence
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  suggests something happened. He mentioned Jacques Valet being
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  a big help, a mentor, and how to approach this kind of tricky,
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  often stigmatized research. Nolan also talks about the
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  potential value commercial scientific if we could
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  understand UAP technology. Yeah, he compares it to the
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  impact silicon had on our world. Game changing potential.
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  And of course there's the whole debate about government secrecy,
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  alleged recovered craft. That's the whole can of worms.
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  Does he think understanding this tech could lead to that post
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  scarcity? It's a possibility he raises if
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  some intelligence, whoever they are, got beyond the problems we
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  face. Maybe there's a blueprint there.
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  It's partly why he helped start the Saul Foundation to create a
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  serious academic space to discuss Uaps without ridicule,
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  looking at ethics, religion, social impact.
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  And he's actually analyzed materials himself.
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  Anomalous materials, yeah. Like from Ubatuba, Brazil.
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  Yeah, back in the late 1950s, a fisherman saw a glowing object
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  explode. Found molten metal.
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  Afterwards Nolan analyzed a piece of silicone from it.
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  Found it was 99.999% pure silicone.
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  Which is hard to achieve. Very hard, especially then.
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  But the kicker was the magnesium isotopes.
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  The ratios of 24/25/26 were way off earth normal.
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  Off normal. How?
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  His calculation suggested it would require exposing normal
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  magnesium to a massive neutron source for like 900 years.
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  Something like an atomic bomb going off every few seconds.
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  Basically impossible in the 1950s.
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  Pretty much very hard, as he put it, points to something highly
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  unusual. Then there's the Council Bluffs
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  IA case from the 70s. Molten metal found after a UAP
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  sighting, right? Police found this pile of melted
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  stuff. His analysis showed it was a
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  weird slurry. Iron, titanium, Chromium, but
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  not uniformly mixed, like it hadn't been properly stirred
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  together. Not like a standard alloy.
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  No, and it wasn't thermite either, because there was no
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  aluminum oxide. But it clearly involved extreme
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  heat. And he notes, this isn't
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  isolated. There are reports worldwide of
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  molten metal dropped by these objects.
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  A pattern. So how do you definitively prove
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  these materials are not from around here he's building?
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  Something. Yeah, he's inventing a new kind
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  of instrument, an atomic imager. An atomic imager?
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  What will that do? It'll let him read its structure
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  directly, see exactly how the atoms are positioned, how
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  they're bonded. The idea is it might reveal
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  structures that humans simply couldn't create, at least not
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  with any technology we know of. And that tool would be useful
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  for regular material science too.
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  Oh. Absolutely huge value for
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  nanomaterials alloys regardless of the UAP angle.
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  He also touched on this Peruvian tridactyl mummies, the three
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  fingered ones. Yes, he mentioned MRI scans
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  showing what looks like real bone structure and fingerprints
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  that aren't human, and carbon dating puts them at 1700 years
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  old. Which makes the hoax explanation
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  pretty difficult for that era. Very difficult.
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  He stresses the need for careful, non sensational science
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  here, but the findings are intriguing.
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  Could they be some kind of offshoot hominid?
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  That's one idea he floats. Maybe a break off civilization
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  that evolved very differently. Think humans versus chimps.
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  Big difference from a common ancestor.
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  He speculates that a species relying heavily on technology
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  might become physically frail, petite with little muscle.
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  Kind of like the Gray alien archetype.
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  It does align with that common image, yeah.
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  Food for thought. And finally, the Nimitz
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  Incident, 2004 off San Diego, the Tic Tac.
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  The famous case Navy pilots saw this object doing impossible
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  maneuvers, he mentioned. Physicist Kevin Day calculated
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  the energy needed for its instantaneous acceleration and
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  deceleration. And the number was.
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  Basically, more than the nuclear output of the United States for
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  a year, just for those few moments of movement.
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  Which leads to the obvious massive question.
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  Exactly where are they getting the energy from?
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  Wow, OK, that was quite a journey through Doctor Nolan's
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  work. From cancer cells to AI building
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  hypotheses to potentially impossible materials and physics
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  defying objects. It really covers the map,
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  doesn't? It it really does the boundaries
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  of what we know seem to be constantly shifting.
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  And the thread connecting it all for Nolan seems to be rigorous
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  analysis, Whether it's cancer or AI or weird materials, he
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  emphasizes looking at the data, the evidence, relentlessly.
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  Even when it's strange or unpopular or off the curve.
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  Right. Keep that scientific integrity,
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  but stay open minded to where the evidence leads.
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  His work really embodies that, I think, curiosity combined with
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  rigor. So as we wrap up, what's the big
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  take away for you listening to all this?
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  Well, it makes you think, doesn't it?
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  If we really are getting close to understanding biology,
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  physics, maybe even consciousness in these
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  revolutionary new ways. If AI or maybe even other
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  intelligences could unlock truly immense power.
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  What kind of society do we need to be to handle that?
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  Exactly how do we manage that exponential increase in
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  technological evolution, as no one puts it?
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  How do we make sure it leads to, you know, human flourishing and
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  not, well, the alternatives, whether that's human misuse or
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  AI running wild? A lot to think about there.
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  Definitely something to keep mulling over.