Latest / Combat Veteran News / Livestream: 3AC Unveils MASSIVE Liberation in Vivaldi

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Livestream: 3AC Unveils MASSIVE Liberation in Vivaldi · Combat Veteran News

• 0:00
  All right, let me finagle finagle all of
• 0:03
  the all of our all of our topics, all
• 0:06
  everything we got to chat about today
• 0:07
  because it's it's a [ __ ] crazy day.
• 0:11
  It's a [ __ ] crazy day.
• 0:14
  Okay,
• 0:18
  literally things are already
• 0:22
  going sideways
• 0:25
  from where we were
• 0:28
  like a like a few days ago.
• 0:36
  So, you know
• 0:41
  what else is new? What are we going to
• 0:44
  talk about? We're going to talk about
• 0:45
  Elon Musk throttling Starlink for no
• 0:49
  reason. Then allegedly unthrottling it.
• 0:55
  And then we're going to talk about
• 0:59
  the
• 1:00
  huge retaking liberation of
• 1:05
  occupied Ukraine announced today,
• 1:09
  but also a whole bunch of other stuff
• 1:13
  like
• 1:15
  Open AI getting spied on
• 1:18
  by the Saudis or somebody. We'll talk
• 1:21
  about it in a sec.
• 1:28
  But we'll let people filter in here.
• 1:30
  We'll chat about it.
• 1:34
  By the way, guys, I if you haven't one,
• 1:36
  I I think we are at our we are so close
• 1:40
  to our
• 1:42
  our fundraising goal.
• 1:44
  You can see we are 97%
• 1:47
  of the way there. I know there's some
• 1:50
  bank transfers they got to add in.
• 1:54
  Shout out to James. Just a bill. Okay.
• 1:57
  $100 is not just a bill. That's a lot of
• 1:59
  money.
• 2:00
  Jose Quuerto. Nice. Nice. $350 euro. I
• 2:03
  love it. Right. Don Taylor. Shout out to
• 2:05
  all you guys that are stepping up in a
• 2:07
  big way for these these guys. You
• 2:09
  contributed. Pat yourselves on the back.
• 2:12
  You guys helped with that for sure.
• 2:19
  Poor
• 2:26
  bots. Yeah, you know, look at them,
• 2:28
  right? I heard a cyber bank data center
• 2:30
  just got hit. Nobody can access their
• 2:32
  bank accounts.
• 2:35
  Yeah, AI definitely get getting spied on
• 2:38
  by themselves, right?
• 2:49
  Yeah. Yeah. That's another good point,
• 2:52
  right?
• 3:00
  Yeah. That [ __ ] that [ __ ] really like
• 3:02
  hurts my soul that people are just human
• 3:06
  lives are just so trivial to this
• 3:08
  administration. I understand like like
• 3:10
  if you want to lead a country every
• 3:12
  decision is going to involve cost in
• 3:14
  human lives, right? Healthcare policy,
• 3:15
  some people are going to die, some
• 3:17
  people are going to live longer lives,
• 3:18
  right?
• 3:20
  Um,
• 3:24
  so
• 3:27
  but like the the level of like
• 3:29
  cavaleress, it costs barely anything, a
• 3:32
  trivial amount of money. And it's not
• 3:34
  like the Russians were stopping when
• 3:36
  there weren't early warnings. It's like
• 3:37
  we're just going to kill some people
• 3:39
  because you hit an oil refinery. Like a
• 3:41
  [ __ ] oil refinery, dude.
• 3:49
  And also like if you care about peace,
• 3:52
  it just like the Ukrainians have
• 3:54
  repeatedly
• 3:55
  shown up, made real peace offers, made
• 3:58
  real ceasefire offers. The Russians have
• 4:00
  done no such thing. They've never abided
• 4:02
  by a single declared ceasefire. Not a
• 4:05
  one.
• 4:13
  Yeah, let's talk about it. I see people
• 4:15
  filtering in. Should we talk about
• 4:17
  Starlink first? Here, we we'll do a
• 4:19
  little poll. We'll do a little poll.
• 4:22
  What should the first story be?
• 4:59
  Okay. Whoa. Pulls up. Hey, Clearon.
• 5:03
  Thanks for the two for the peace. Yeah,
• 5:05
  we we the the reduction in Russian bots
• 5:08
  alone is a source of of of genuine
• 5:11
  genuine peace, man. It is it has really
• 5:14
  made uh certainly the chat just a much
• 5:17
  more pleasant place to be. Uh no no
• 5:20
  doubt about it. No doubt about it.
• 5:25
  What were the options again? Uh
• 5:30
  oh, it's a 5050 split. Damn. I hope you
• 5:32
  This is why I crowdsource things so I
• 5:34
  don't have to make decisions, but you
• 5:35
  guys can't make the decision either.
• 5:43
  It's not letting me vote in your poll.
• 5:44
  Did you vote once already? I don't know.
• 5:46
  The the poll is new to me, too. So, if
• 5:48
  you're like, "This poll sucks." Um
• 5:54
  might be
• 6:03
  you know Starling can be hacked and it
• 6:04
  services used for free. I would not hack
• 6:07
  a Starlink. Okay.
• 6:21
  Yeah, Raymond. Yeah, at this point you
• 6:22
  got to I mean there's not really an
• 6:24
  alternative.
• 6:26
  Keep saying your vote didn't go through.
• 6:28
  Try again. Are you a bot, Clearon?
• 6:32
  Check carefully. Pinch yourself.
• 6:35
  Do you Do you have Do you have arms and
• 6:37
  legs? And you're probably not an AI. You
• 6:40
  could be. Elon could have neurolinked an
• 6:42
  AI right into your brain.
• 6:46
  The stories of the bots's demise is
• 6:47
  probably premature. Like, don't
• 6:49
  discount. I'm sure the Russians are
• 6:51
  working day and night to get Yandex bots
• 6:53
  back up online, but you know, it was fun
• 6:56
  while it lasted.
• 7:01
  Clamarian. Yeah, it could be a bot.
• 7:03
  Okay. Okay. Uh, let's let's let's bot
• 7:06
  test Clarian.
• 7:09
  Okay. Quick, solve. Give me an answer to
• 7:12
  an unsolved physics problem. Ready? Go.
• 7:20
  Oh, David Vermont. I know. You know, the
• 7:23
  one thing that's nice about the bots is
• 7:25
  that like Twitch view bots, it makes me
• 7:26
  look more popular than I am, right?
• 7:30
  Like, it makes me look like I'm like one
• 7:32
  of those um shitty kick streamers. Like,
• 7:35
  let's just let's just on a goof here.
• 7:38
  We'll get into the stories in a sec, but
• 7:40
  if I were to look like like okay um
• 7:45
  you know if I I don't know I'm averaging
• 7:48
  let's say uh uh
• 7:52
  let's say with the bots a thousand
• 7:54
  concurrent viewers. Okay. And so if I
• 7:58
  wanted to get a you know how big what
• 8:00
  kind of
• 8:02
  English English English India okay so to
• 8:05
  get a thousand viewers on kick
• 8:09
  uh that would make me
• 8:13
  I'd have to be
• 8:16
  oh for a second I thought this was
• 8:17
  Candace Owens. I was like, "Oh my god,
• 8:21
  I have to be as big as
• 8:24
  a PUBG streamer.
• 8:28
  Big Loaf. Damn.
• 8:31
  I'd have to be like Classy Beef and do a
• 8:33
  be be a gambling streamer. Look at this.
• 8:36
  This guy's not even moving."
• 8:39
  Oh, no. There he goes. He's moving. He's
• 8:41
  moving again.
• 8:43
  Yeah. Look at this. I, you know, I could
• 8:46
  be a gaming streamer
• 8:48
  or a kicked out of the house streamer.
• 8:52
  Damn, I really missed my calling. You
• 8:55
  know, I could have been whatever that
• 8:57
  guy does. Whatever these guys do.
• 8:59
  Literally, you could be in GTA
• 9:02
  on kick. You could be a Okay, I can't
• 9:05
  even show a pool or hot tub streamer.
• 9:07
  Let's see what's Yeah, the point is is
• 9:11
  that if I had more viewbots, I could be
• 9:13
  I could be one of these guys. This could
• 9:15
  be me. Where's categories?
• 9:19
  My god. I could be I'm 1/8 of an asmin
• 9:22
  gold, guys. I mean, think about it.
• 9:26
  Damn. Actually, kick is as big as
• 9:29
  [ __ ] Damn. Kick's as big as uh
• 9:34
  as big as Twitch. What the [ __ ]
• 9:37
  Damn, that's got to be some serious view
• 9:39
  botting.
• 9:40
  Look at me. Look at me. We don't even
• 9:42
  know how many people clvicular have. I I
• 9:44
  don't know. There's not even a real
• 9:45
  clvicular. Probably 10,000.
• 9:48
  Damn. But look, but look how fat the
• 9:50
  falloff is.
• 9:54
  Jim Jim Bose. But this is just critical.
• 9:56
  But it's not real. It's not the real
• 9:57
  critical. Someone rereaming somebody
• 10:00
  void elf. I could be as big as Foy elf.
• 10:02
  Guys, I just need the view bots. I need
• 10:05
  those bots to come back. Dixie, thanks
• 10:06
  for the five, man. You're not a bot.
• 10:10
  Yeah, man. When I when those Russian
• 10:12
  bots were in here, yeah, they were kind
• 10:13
  of annoying, but I was as big as Clue
• 10:18
  or Feed My Fish. I could have been as
• 10:20
  big as Feed My Fish. I could have been a
• 10:22
  fish streamer.
• 10:26
  Could have been a fish streamer.
• 10:29
  Look at me.
• 10:31
  Do Viewbots donate money? I don't think
• 10:33
  so.
• 10:36
  But again, advertisers pay more to run
• 10:38
  ad to show ads even to bots. And don't
• 10:41
  kid yourself. I think the bots are just
• 10:42
  getting smarter. Okay, the bots probably
• 10:44
  have more humanlike behavior. All right,
• 10:48
  that's just me. All right, let's talk
• 10:50
  about Operation Vivaldi. Let's let's
• 10:51
  let's crack into it here. I'm going to
• 10:53
  turn off my AC so the audio isn't dog
• 10:55
  [ __ ] I just want to kiss my fist. Isn't
• 10:58
  there a disease? Isn't there Isn't that
• 10:59
  like a major disease vector? Like, you
• 11:01
  should not do that. All right.
• 11:08
  In an absolutely wild announcement, a
• 11:10
  third assault has officially declared
• 11:13
  the end of Operation Vivaldi with a
• 11:15
  shocking 110 km square of Ukrainian
• 11:19
  territory has been rolled back from the
• 11:22
  Russians. This is crazy for a variety of
• 11:25
  reasons, but most of all, it shows just
• 11:29
  how poorly the Russian army is currently
• 11:33
  operating in Ukraine. And no amount of
• 11:38
  favors or handouts from the White House
• 11:41
  seems to be changing Russia's
• 11:42
  battlefield reality. Take a look. So
• 11:48
  operation vivaldi this is the third
• 11:50
  assault cor's uh systematic recapture
• 11:53
  liberation of Ukrainian territory has
• 11:56
  announced the liberation of DNA leov and
• 11:59
  ko diazi. Now this is a three major
• 12:03
  settlements in the Lyman sector and this
• 12:06
  reflects a uh this reflects the
• 12:09
  culmination of operation Vivaldi.
• 12:12
  Ukrainian forces retaking 16 settlements
• 12:14
  and a total of nearly 300 km of
• 12:16
  territory. Russian forces reportedly in
• 12:18
  the operation alone suffered 8,000
• 12:20
  personnel losses. And uh third assault
• 12:23
  has said that of course its operations
• 12:26
  continue and that uh during operation
• 12:28
  revaldi its unmanned systems units
• 12:30
  launched 36,000
• 12:33
  strike missions targeting Russian supply
• 12:35
  lines and logistics infra infrastructure
• 12:37
  and some of those missions you guys
• 12:39
  should congratulate yourselves on
• 12:41
  because our fundraiser fundraisers
• 12:43
  plural contributed massively to that.
• 12:46
  Right? I'm still going to put the link
• 12:47
  in the description. We are so close to
• 12:48
  hitting our $100,000 goal. Right. Turtle
• 12:51
  assault obviously still very much in the
• 12:53
  fight and we're getting them the ground
• 12:54
  drones, components for some of their
• 12:55
  heavy strike drones, thermal and night
• 12:57
  optics, Starling terminals when they
• 12:58
  work, batteries, chargers, and more.
• 13:01
  Shout out to all the guys who donate,
• 13:02
  right? James dropping $100 and being
• 13:05
  like, it's not much, but trust me, it's
• 13:08
  a lot. Uh, Jose Quuerto, badass name,
• 13:12
  uh, badass donation, €324.
• 13:15
  uh USD. Uh even guys like Colin Love
• 13:19
  dropping five bucks in. Uh and that's
• 13:23
  pretty sick, right? I always appreciate
• 13:25
  the guys that show up dropping in just
• 13:27
  fives and tens. That's somebody who sat
• 13:28
  there and said, "Hey, listen. I could go
• 13:30
  to Starbucks or I could just make coffee
• 13:32
  at home, right, in honor of all the
• 13:33
  non-S Starbucks drinkers, right? They're
• 13:35
  like $7 and their coffee tastes like
• 13:36
  [ __ ] I'm sorry. I'm sorry. You can just
• 13:38
  buy nicer coffee from anywhere else. So
• 13:42
  do that and you could go help the
• 13:44
  Ukrainians,
• 13:46
  you know, send the Russians back to
• 13:47
  Moscow.
• 13:50
  Cheers. So
• 13:54
  the other point I want to make before we
• 13:56
  go into not just the detail, but what
• 13:58
  this means for the strategic
• 13:59
  environment, the change that it makes to
• 14:00
  the whole strategic environment is also
• 14:04
  that we have a sale going on on
• 14:06
  strike.com. So get your caffeine. Don't
• 14:10
  you don't have to drink coffee at all.
• 14:11
  You can just stop buying energy drinks
• 14:13
  entirely and depend on strike gum with
• 14:15
  90 milligrams. I literally would be
• 14:17
  drink would be chewing my strike gum
• 14:18
  right now. Um but I literally ran out
• 14:21
  yesterday. I ran out of my own gum. We
• 14:23
  need to sell less of it. I need to sell
• 14:24
  less gum. In fact, um use promo code uh
• 14:27
  holiday 25 to get 25% off. I think I
• 14:30
  think it's going on for one more day.
• 14:31
  Yeah. Here we go. Here we go. Look at
• 14:32
  this. Look at this. No AI [ __ ] slop
• 14:34
  here. This is pure human slop. Okay.
• 14:37
  Yeah. 25% off holiday 25. Why do we do
• 14:41
  holiday? Because nobody in in the United
• 14:43
  States can read consensus on what this
• 14:45
  holiday is. Is it indigenous people's
• 14:46
  day? Is it Columbus Day? Listen, we can
• 14:48
  celebrate all of them, right? I promise
• 14:51
  you as as as someone who has some
• 14:55
  Italian uh heritage,
• 14:58
  uh I can tell you we're not a people
• 15:01
  that are particular about the exact
• 15:04
  cause for a holiday. If we can have some
• 15:06
  wine and some pasta, I don't really give
• 15:09
  a [ __ ] about the pretext. So, they can
• 15:12
  all have it. Go to strikegum.com,
• 15:14
  promo code holiday25. So, let me take a
• 15:17
  look at the the the total territory.
• 15:19
  One, I I want to point out that on some
• 15:22
  maps, the Russians were never reported
• 15:24
  to have advanced to Stavki, but in some
• 15:28
  they actually were. And and when you
• 15:30
  look about the remember this is a
• 15:32
  four-monthlong operation but you can see
• 15:34
  that in July this was a very different
• 15:36
  environment. This salient was almost
• 15:38
  entirely Russian controlled and again
• 15:41
  this was a huge cancer that Russia was
• 15:44
  trying to use to actually encircle Lyman
• 15:46
  it seemed and it would have been pretty
• 15:48
  bad. It would have put a lot of pressure
• 15:50
  on Slovian. And so flipping this uh
• 15:53
  rolling back some of the Russian gains
• 15:55
  here and fully liberating some of this
• 15:57
  territory is a is a tactical win for
• 16:02
  Ukraine and a tactical disaster for the
• 16:04
  Russians because again their efforts to
• 16:07
  retake to take Lyman uh to pressure
• 16:11
  uh the northern part of the fortress
• 16:13
  belt here in Slovian u is is is done.
• 16:17
  Right. This took them I mean this was a
• 16:20
  a multi-yearlong effort for the Russians
• 16:23
  right we can go back to January of this
• 16:25
  year and you could see I mean again the
• 16:27
  Russians had this but they had been
• 16:28
  trying to create this bottom pinser I
• 16:30
  mean you see it here pushing trying to
• 16:33
  create this encirclement and you could
• 16:35
  see that again the Ukrainians said
• 16:37
  listen you can do the the the
• 16:39
  encirclement on the bottom as much as
• 16:40
  you want but we're just going to roll
• 16:42
  you back on the top and that
• 16:46
  has the Only times Russians have been
• 16:48
  able to capture territory uh
• 16:53
  at any kind of reduced cost, human lives
• 16:56
  and resources has been in an
• 16:58
  encirclement. When you create
• 17:00
  encirclement in envelopments, uh cutting
• 17:03
  or risking cutting off Ukrainians, the
• 17:05
  Ukrainians are always forced to withdraw
• 17:07
  to preserve their manpower. Again,
• 17:09
  sometimes I'm actually have been very
• 17:10
  critical of how late the Ukrainians will
• 17:12
  remain in a cauldron in an envelopment.
• 17:15
  But again, it's easy for me to backseat
• 17:17
  drive. Um, but there is this is this is
• 17:21
  truly the best solution to an
• 17:22
  envelopment is to simply tear a new hole
• 17:26
  in the cauldron, right? Uh, you can't
• 17:28
  envelop somebody if you you know, it's
• 17:31
  like trying to get swallowed by a whale.
• 17:33
  If the whale doesn't have a jaw, it
• 17:35
  can't swallow you. And I think what is
• 17:38
  more significant though is that this is
• 17:42
  also a reflection. And remember this
• 17:43
  strategy also has or this tactical win
• 17:46
  also has an operational component. The
• 17:49
  operational component is that it has
• 17:50
  killed a lot of Russians. As they have
• 17:52
  said, it inflicted 8,000 Russian
• 17:53
  casualties and that is in a sector where
• 17:56
  the Russians were not conducting a major
• 17:58
  offensive. So this was not defensive
• 18:01
  Russian casualties. This was a fight
• 18:02
  that the Russians did not want to have.
• 18:06
  They were not planning on fighting in
• 18:07
  linemen. Certainly not to the scale of
• 18:10
  8,000 casualties. And so they have had
• 18:12
  to now divert what would have been
• 18:15
  thousands of troops that would have gone
• 18:17
  into offensive units, units pushing in
• 18:21
  uh Costantine or Gulopou and instead had
• 18:25
  to divert them to Lyman or had to
• 18:27
  backfill units that were destroyed in
• 18:29
  Lyman. This is contributed to again this
• 18:32
  this is a month old this is from the end
• 18:33
  of August but it it remains actually
• 18:36
  more true that Russia is losing more
• 18:38
  than it has a net loss each month of
• 18:41
  reportedly up to 6,000 troops or 20% of
• 18:44
  its monthly recruitment total. It's
• 18:47
  falling short and it's not because
• 18:49
  Russian recruitment is slowing down.
• 18:51
  Right? Russian recruitment by all
• 18:53
  accounts has been steadily steady at
• 18:55
  30,000 troops a month. Now, the
• 18:57
  coercion, the motivation of these troops
• 19:00
  is somehow even lower given that in most
• 19:03
  cases, it's believed that this is sort
• 19:04
  of a backdoor draft. Individuals are
• 19:06
  being voluntarily mobilized, but they're
• 19:08
  picked up by police, have drugs planted
• 19:10
  on them, and then get told in no
• 19:12
  uncertain terms that congratulations on
• 19:14
  signing up for the army. Um, because the
• 19:17
  alternative is of course facing drug
• 19:19
  trafficking charges. And even in the
• 19:23
  face of these coercive uh practices, the
• 19:26
  Russians are still not able to offset
• 19:28
  their losses. And 6,000 troops being
• 19:31
  lost every month is a huge problem. That
• 19:34
  equates to about 1,200 Russian
• 19:37
  casualties a day to 1,000 recruits. So a
• 19:40
  200 daily net loss. But as we have
• 19:43
  talked about, these are the kind of
• 19:45
  stories we would expect to see if the
• 19:47
  Russian army is losing troops on a
• 19:49
  steady basis because they are becoming
• 19:50
  more brittle. And what that what I mean
• 19:54
  by that is that the average Russian
• 19:56
  fighter has inferior supplies, inferior
• 20:00
  motivation, inferior weaponry, inferior
• 20:03
  uh food, water, weapons, radio
• 20:06
  batteries, potentially even training,
• 20:08
  certainly motivation because there are
• 20:11
  troops that are either being
• 20:14
  uh the frontline troop. he is not
• 20:16
  getting the supplies he needs both
• 20:17
  because of Ukrainian middle strike drone
• 20:19
  capabilities but also because there are
• 20:22
  not enough truck drivers because the
• 20:24
  Russian army like there's 6,000 vacant
• 20:27
  positions every month and
• 20:30
  the Russian army has made clear that
• 20:32
  they are going to be filling infantry
• 20:34
  positions first and that means that the
• 20:37
  remaining troops in the rear again
• 20:40
  mobile strike team mobile air defense
• 20:42
  team something we've seen that the
• 20:44
  Russians basically didn't have to field
• 20:47
  uh uh 6 months ago are now a decisive
• 20:52
  battlefield problem. And they have to
• 20:53
  the Russians have to pull troops off the
• 20:55
  front lines, staff these mobile fire
• 20:56
  teams, include truck drivers, right?
• 20:59
  Include all these logistics troops,
• 21:02
  include the troops pushing the logistics
• 21:04
  to the front lines. And
• 21:07
  this is
• 21:09
  that's where those gaps are occurring.
• 21:11
  That's where these losses are starting
• 21:13
  to compound. But when you have fewer
• 21:15
  logistics troops, when you have more
• 21:17
  troops on mobile fire duty, what you end
• 21:20
  up with is a a thinner front line with
• 21:23
  less troop density, the troops that do
• 21:26
  fight run out of food, water, or
• 21:28
  ammunition way faster. And we're seeing
• 21:31
  this. We're seeing more stories about
• 21:32
  Russian PS who just sort of give up. We
• 21:35
  see a lot even in the videos that are
• 21:37
  being released about Operation Vivaldi.
• 21:39
  You see more and more of these Russians
• 21:41
  who put up sometimes very small amounts
• 21:44
  of resistance. Sometimes you'll have one
• 21:46
  or two Russians that that that actually
• 21:48
  have some fight in them and the rest
• 21:50
  don't even put on their body armor. It
• 21:51
  appears don't even appear to pick up a
• 21:53
  weapon. And that's probably because they
• 21:56
  have been defeated by their own poor
• 21:58
  logistic system, by their own degraded
• 22:00
  logistics system, and by their own
• 22:02
  inability to be supplied. Again, there
• 22:04
  will be a there is a point just in human
• 22:06
  biology where you will be so thirsty or
• 22:09
  so hungry that you the prospect of
• 22:12
  getting into a gunfight is just not
• 22:13
  going to happen for you. You're just not
• 22:15
  going to do that. And that is going to
• 22:17
  compound and you're going to see that
• 22:19
  the ability of Russian troops to dig in
• 22:21
  and fight for every meter of territory.
• 22:23
  You're going to see less of it. And
• 22:25
  that's what we've seen already. Again,
• 22:27
  this is not because like the the
• 22:29
  Ukrainians have gotten better. They have
• 22:31
  improved their abil their drones
• 22:33
  immensely. They've improved their
• 22:35
  ability to conduct coordination among
• 22:37
  drone units to coordinate drones uh
• 22:41
  artillery um uh infantry, right? They
• 22:44
  have a protocol and a process for
• 22:46
  retaking to conducting offensive
• 22:48
  operations, but
• 22:51
  they but that is that is necessary but
• 22:54
  not sufficient to conduct these kinds of
• 22:56
  significant scale um offensive
• 22:59
  operations. And that require that
• 23:01
  requires
• 23:03
  a Russian army that is just been
• 23:06
  degraded that's been attrded down over
• 23:08
  weeks and months. And you see now this
• 23:10
  is the this is the chart of ca Russian
• 23:12
  casualties
• 23:14
  uh from the last 90 days or so. And you
• 23:17
  can see or excuse me from the last 6
• 23:18
  months or so goes back to goes back to
• 23:21
  June June 15th. So yeah
• 23:24
  90 days or so. But you can see that this
• 23:27
  1,00 mark, this is the very bottom here.
• 23:30
  And you can see on the biggest days, the
• 23:33
  Russians are losing twice the troops
• 23:36
  that they are recruiting. And you're
• 23:40
  seeing even now a typical day, right?
• 23:42
  You may say, "Oh, yesterday that doesn't
• 23:44
  look like that exceptional a day." It
• 23:46
  was 1,600 Russian losses, guys. The
• 23:48
  Russians lost an entire
• 23:51
  battalion of troops that there is no
• 23:54
  replacement for and there is almost no
• 23:57
  day literally even the worst the lowest
• 24:00
  casualty day for the Ukrainians still
• 24:03
  had a net gain of 100 or a net loss for
• 24:06
  Russia of 130 troops. So, I think you're
• 24:10
  going to see if these stats are are are
• 24:13
  in the even ballpark of correct, you're
• 24:16
  going to see more and more Russians
• 24:20
  Russians sort of have these collapses in
• 24:22
  their front line, right? Where the
• 24:24
  Ukrainians are going to choose a place
• 24:25
  and they're going to push on the
• 24:27
  Russians and they're going to fall over
• 24:29
  faster. They're going to there's going
• 24:31
  to be more instances where Russians
• 24:33
  don't really want to have these
• 24:35
  aggressive fights where these fights
• 24:36
  just don't happen. And so, um, you know,
• 24:39
  we're going to see, but probably if I
• 24:42
  were a betting man, I would bet that
• 24:43
  even now there are operations that are
• 24:46
  driving Russian forces back in key
• 24:48
  locations. Uh, anyway guys, please
• 24:51
  subscribe if you haven't. YouTube has
• 24:52
  been unsubscribing people from the
• 24:53
  channel. Thanks to Colin, Dan, Deborah,
• 24:55
  John, Douglas, Gabriel, GMAT, James, and
• 24:57
  all the Lieutenant people. Um, and
• 25:00
  again, check to make sure you're still
• 25:01
  subscribed,
• 25:03
  okay?
• 25:08
  So, we'll end the poll. Sorry. See that?
• 25:12
  Uh, there we go. Yeah, the poll seems a
• 25:14
  little weird.
• 25:30
  All right, I see some of you guys uh
• 25:32
  gave me some super chats. Thanks to
• 25:34
  Dixie, thanks to Mr. badges have decided
• 25:35
  to refer to Trump's sanctions really for
• 25:37
  Putin as a reachound. Oh man, it's um
• 25:42
  Yeah. Yeah, that's a pretty good that's
• 25:44
  a pretty accurate description because it
• 25:46
  doesn't like the benefits to Trump don't
• 25:49
  aren't really I can't really tell what
• 25:52
  they are. And I I'll tell you one thing
• 25:55
  that sort of keeps me awake at night is
• 25:56
  you know the Russian oligarch that paid
• 25:58
  for Don Jr.'s wedding.
• 26:01
  Anybody else think that was kind of
• 26:02
  weird? Right now, as we talked about, if
• 26:04
  the amount is too small to be to be the
• 26:08
  actual business deal, but it is likely a
• 26:11
  wedding gift to someone who has enriched
• 26:13
  him considerably.
• 26:18
  Like the fact that that that
• 26:21
  Don Jr. got his wedding paid for by a
• 26:23
  Russian oligarch
• 26:24
  and then
• 26:26
  Trump turns around and gives Russia
• 26:28
  massive sanctions relief
• 26:31
  and [ __ ] Ukraine like kills some
• 26:33
  Ukrainians is is like ghoulish dude. It
• 26:36
  is super [ __ ] up. And again, it's not
• 26:38
  the wedding. The wedding gift is
• 26:40
  definitely a gift for a larger deal, a
• 26:45
  larger transfer of money or money-making
• 26:47
  scheme to the Russians. I personally
• 26:50
  speculate that it's Don Jr. getting um
• 26:53
  his uh crypto scam company, World
• 26:55
  Liberty Financial, um getting it
• 26:57
  chartered as a US bank that will enable
• 27:00
  Russian cryptocurrency uh sanctions
• 27:02
  evasion uh to take place by transferring
• 27:05
  crypto to that bank and then exchanging
• 27:08
  it for Howard Lutnik's um uh USD Tether
• 27:13
  Tether stable coin. So, effectively
• 27:15
  allowing the Russians to launder um uh
• 27:19
  uh funds through um through Don Jr.'s
• 27:23
  company,
• 27:24
  but that's my speculation.
• 27:28
  And that as a thank you to saying,
• 27:29
  listen, you you saved our economy. you
• 27:32
  saved our ability to conduct these
• 27:34
  payments to beat US sanctions um using
• 27:36
  cryptocurrency which again to to date 20
• 27:39
  years after Bitcoin was invented um is
• 27:42
  only only utility is criminal
• 27:44
  enterprises. Um I'm just pointing that
• 27:48
  out there.
• 28:03
  Yeah, I'm gonna talk about it next.
• 28:08
  Ryan, you're steal my thunder. Every
• 28:10
  military worth it all is going to avoid
• 28:11
  being relying on the capriccious drug
• 28:12
  add billionaire for their internet in
• 28:13
  the field.
• 28:16
  This guy gets it.
• 28:23
  The thing is it was we're not even on
• 28:25
  Russia's side. Russia isn't on our side.
• 28:27
  They killed American soldiers.
• 28:30
  Like Trump is just stupid. Like he's
• 28:33
  just stupid.
• 28:59
  The world's most unpopular ketamine
• 29:02
  addicted billionaire has decided to take
• 29:04
  it upon himself to help President Trump
• 29:07
  and screw Ukraine as Ukrainian sources
• 29:11
  across the front lines are reporting
• 29:13
  that Starlink has mysteriously become
• 29:16
  restricted, imposing a bizarre speed
• 29:19
  limit, essentially killing any terminal
• 29:22
  that exceeds 160 km an hour, effectively
• 29:25
  killing all Ukrainian airborne drone
• 29:27
  operations. Now, this is crazy because
• 29:32
  uh well, for for a variety of reasons,
• 29:34
  but the overall story is that there are
• 29:36
  restrictions that have begun affecting
• 29:37
  Starlink units in Ukraine for
• 29:40
  whitelisted Ukrainian users of the
• 29:42
  military Star Shield package. Now, this
• 29:45
  was first detected last night, uh,
• 29:47
  making logistics and drone operations
• 29:49
  extremely difficult, bordering on
• 29:50
  impossible, and these restrictions
• 29:52
  affected speeds over 100 m an hour.
• 29:56
  Again, this is something that middle
• 29:57
  strike drones and even a lot of FPV
• 30:00
  drones comfortably exceed. Now, uh,
• 30:04
  units reported connections dropping at
• 30:06
  different speeds, ranging from as little
• 30:08
  as 72 to as high as 161 km an hour. And
• 30:11
  it report this is it seems to be
• 30:14
  confirmed SpaceX unilaterally i.e. Elon
• 30:18
  personally has decided to impose these
• 30:20
  speed restrictions on Starshield
• 30:21
  terminals used by Ukraine's defense
• 30:23
  forces on October 14th without any
• 30:25
  advanced warning. Uh the restrictions
• 30:27
  hampering drone missions but notably
• 30:29
  including interceptor and medium-range
• 30:30
  strike operations. Uh it's worth noting
• 30:32
  that in order to intercept the most
• 30:35
  advanced Russian Garand drones, these
• 30:37
  are uh Garands that instead of a
• 30:39
  propeller uh system have actually a jet
• 30:42
  propulsion engine, something like
• 30:44
  doubling their speed and making them uh
• 30:46
  almost impossible to intercept by
• 30:48
  standard FPV frame FPV drone based
• 30:52
  interceptors. It requires faster moving
• 30:55
  interceptors which again are uh now have
• 30:59
  now been throttled.
• 31:01
  I think a typical uh uh Garan is Jearan
• 31:05
  exceeds 200 mph. So to intercept it of
• 31:08
  course you have to at least reach that
• 31:09
  speed or close enough to it. And so the
• 31:12
  the this restriction is a huge problem
• 31:15
  for the Ukrainians to conduct simple
• 31:17
  defensive operations. And this is
• 31:19
  something that again if Elon hadn't
• 31:22
  fried his brain with ketamine, uh not
• 31:24
  allegedly, by the way, he's gone on
• 31:26
  interviews and and said, this is a
• 31:27
  direct quote, he was prescribed ketamine
• 31:30
  by an actual real doctor, which is of
• 31:32
  course how I describe my doctor to
• 31:33
  everyone. And they don't find it weird
• 31:35
  at all. My actual real doctor, the
• 31:37
  actual real one that I actually really
• 31:39
  use. Um
• 31:42
  now obviously
• 31:46
  uh the Ukrainians called the US, SpaceX
• 31:49
  and NATO trying to figure out what's
• 31:51
  going on and the the it is generally
• 31:57
  believed to be to have been to have
• 31:59
  occurred inside of SpaceX because
• 32:01
  civilian Starlink terminals inside
• 32:03
  Ukraine um are not affected by this only
• 32:07
  the militaryra star shield system.
• 32:11
  And there is of course fairly obviously
• 32:13
  a suggestion that this is a um action
• 32:17
  taken by Elon Musk in support of
• 32:19
  President Trump who has um inexplicably
• 32:22
  decided that uh nearly a year after the
• 32:26
  Ukrainian campaign against Russian
• 32:28
  refineries has began. That
• 32:31
  now the Ukrainians have inexplicably
• 32:33
  gone too far. Right? the first 400
• 32:36
  strikes were not a problem, but this one
• 32:38
  is. Now, obviously, this is because
• 32:40
  President Trump um delusionally believes
• 32:44
  that the price of diesel, he doesn't
• 32:45
  delusionally believe it, I think he
• 32:46
  knows, the price of diesel has risen
• 32:48
  precipitously um in perfect lock step
• 32:51
  with his war in Iran, right? The price
• 32:53
  of diesel plummeted when he signed a
• 32:55
  ceasefire. And when the ceasefire fell
• 32:57
  apart, it spiked up again. The day the
• 33:00
  Iranians closed the straight is when oil
• 33:03
  prices diesel prices began to climb. Um,
• 33:05
  and of course the first 3 to four months
• 33:07
  of the Ukrainian campaign against
• 33:09
  Russian uh refineries had no impact on
• 33:13
  diesel prices. And that's basically a
• 33:15
  function of the fact that the sanctions
• 33:17
  already prevented the United States from
• 33:19
  purchasing Russian diesel. Russian, you
• 33:21
  know, Russian diesel wasn't really
• 33:23
  making its way to the market in the
• 33:24
  first place. And when it was, it was
• 33:26
  subject to price caps. And those price
• 33:28
  caps actually kept diesel cheap. Uh
• 33:31
  that's what happens when you have real
• 33:33
  economists designing a sanctions regime.
• 33:35
  You make it so that it actually makes uh
• 33:37
  fuel cheaper for the sanctioning entity
• 33:40
  and much much much less profitable for
• 33:42
  the unsanctioning for the uh sanctioned
• 33:45
  entity.
• 33:46
  Now
• 33:48
  the Ukrainian foreign minister has said
• 33:50
  recently that Ukraine and the United
• 33:52
  States are continuing some intelligence
• 33:53
  sharing. But there is uh there is also
• 33:56
  some pretty suspicious stories here that
• 33:58
  the uh Russian strikes uh last night.
• 34:03
  Typically the United States provides
• 34:05
  some level of advanced warning to Keev
• 34:07
  that the Russians have launched uh
• 34:09
  missiles. This is again likely a
• 34:11
  satellite reconnaissance and that uh
• 34:13
  mysteriously the Ukrainians never
• 34:16
  received any kind of advanced warning.
• 34:18
  Right. Ukraine quote received no
• 34:19
  advanced warning from our partners when
• 34:21
  Russia launched ballistic missiles at
• 34:22
  Kev. Um, and this, uh, again, one source
• 34:27
  said, "American officials told the
• 34:28
  Ukrainian counterparts, the system used
• 34:29
  to detect Russian missile launches
• 34:31
  failed due to bad weather." But this is
• 34:32
  obviously a lie because the weather is
• 34:36
  is not exceptionally bad in Kev right
• 34:38
  now. I I have a friend who's who's there
• 34:41
  right now and said that the weather is
• 34:43
  actually beautiful. He sent me a bunch
• 34:44
  of pictures. It's gorgeous there. Um, so
• 34:46
  except for the bombing part, but the
• 34:51
  uh the Ukrainians said, "We don't
• 34:54
  believe their excuse and the US is
• 34:55
  playing around with the system." Right?
• 34:57
  And they said on Wednesday that the US
• 34:59
  early warning system appeared to be
• 35:01
  working again. Now, uh the
• 35:06
  the fact that yes, the US is playing
• 35:08
  stupid games and uh killed some people,
• 35:13
  you know, is is kind of twisted a
• 35:15
  baseline. And I understand that when you
• 35:16
  run a country, you have to make some
• 35:18
  tough decisions, but um like randomly
• 35:22
  pulling your support uh is kind of
• 35:25
  [ __ ] up, but actually
• 35:28
  the crazy part is that this is stupid.
• 35:32
  If you're Elon, this is like
• 35:34
  unbelievably stupid. And not like
• 35:37
  because we support Ukraine because
• 35:39
  they're a democracy, because Russia is
• 35:40
  an autocracy, because Russia gave Iran
• 35:43
  the intelligence used to um kill a dozen
• 35:48
  American soldiers. Uh not because the
• 35:50
  Russians are enabling Iran. uh not
• 35:53
  because of all of those things, but but
• 35:55
  even if you are just a shareholder in
• 35:56
  SpaceX, you should be tearing your hair
• 35:59
  out proverbally because I don't own
• 36:01
  SpaceX and I never will. Now, before we
• 36:04
  talk about that, I want to mention guys
• 36:05
  that if you are being driven to the edge
• 36:08
  of madness, uh I can't help you. You you
• 36:11
  need you need you need an actual real
• 36:13
  doctor to deal with that. But if you're
• 36:15
  just sort of tired of BS or just tired,
• 36:17
  don't buy energy drinks. They're like
• 36:19
  six bucks. Uh, this one's made in in
• 36:24
  bottled. It doesn't even say where it's
• 36:26
  bottled, right? And
• 36:29
  you know, it's probably made in the
• 36:31
  straight of Hormuz or in China or
• 36:33
  something. But you know what? Leave it
• 36:35
  behind. You want to pick up some Strike
• 36:37
  Gum because Strike Gum, literally, this
• 36:40
  is an empty package uh because I I
• 36:44
  chewed it all on stream. Uh, but it's
• 36:46
  got 90 milligrams of caffeine, 100
• 36:47
  milligrams alpha GPC, zero sugar. Go to
• 36:50
  strikegum.com. Use promo code holiday25
• 36:55
  to to to to get 25% off. What holiday is
• 36:59
  it? Don't start. It's a culture war
• 37:01
  thing in the United States. Don't even
• 37:02
  worry about it. What you got to worry
• 37:04
  about is locking in, getting your
• 37:05
  caffeine. Strike.com or on Amazon, promo
• 37:08
  code holiday25.
• 37:10
  So,
• 37:12
  here's here's where things are stupid.
• 37:15
  Okay. One,
• 37:18
  the polls. Elon Musk does not provide
• 37:20
  Starshield, the government and military
• 37:22
  component of Starlink. It doesn't
• 37:24
  provide that for free. It is a service
• 37:26
  purchased by the EU. Polish foreign
• 37:28
  minister said, "Listen, we pay for those
• 37:30
  Starlinks." Right?
• 37:34
  And again, the presidential advisor to
• 37:37
  Poland said that these limits affecting
• 37:39
  terminals moving at high speed were
• 37:41
  introduced without warning and disrupted
• 37:42
  several military missions. And
• 37:46
  you know, the Polish foreign minister
• 37:49
  said that European customers were
• 37:50
  watching his actions after reports that
• 37:53
  unexpected stalling restrictions
• 37:54
  disrupted Ukrainian military operations.
• 37:56
  The exact tweet was, "Hey Elon Musk, big
• 37:59
  man, are you playing politics with your
• 38:00
  products again? As European consumers,
• 38:02
  we are watching you." And what is what
• 38:05
  is the idea here? Well, this
• 38:09
  this is pretty simple. If you are Elon
• 38:11
  Musk, SpaceX, so SpaceX guys is a
• 38:14
  company. I don't know if you I don't
• 38:15
  know if you heard SpaceX is a company,
• 38:17
  not just a company, a publicly traded
• 38:19
  company on listed on international stock
• 38:21
  markets. So, one of the reasons that
• 38:24
  SpaceX introduced its white list is
• 38:26
  because it was incidentally the Russians
• 38:29
  were purchasing using straw men in third
• 38:31
  countries, purchasing Starling
• 38:32
  terminals, activating them in Russia,
• 38:34
  and then using those to coordinate their
• 38:36
  military operations in Ukraine, and even
• 38:38
  sometimes strapping them to shaheds to
• 38:40
  guide them onto Russian targets.
• 38:42
  knowingly providing material support to
• 38:44
  Russia would would subject SpaceX to
• 38:48
  sanctions in the European Union, cutting
• 38:50
  off something like 40% of SpaceX's
• 38:54
  potential investors and customers.
• 38:57
  That's why Elon stepped in and said,
• 38:59
  "Okay, okay, okay. I'm not I'm going to
• 39:01
  stop pretending like I'm not supporting
• 39:03
  Russia. I'm going to step in and stop
• 39:05
  Russia from being able to use our
• 39:06
  systems."
• 39:08
  Which is good. But here's the problem
• 39:10
  within SpaceX. You may think SpaceX,
• 39:12
  they make a lot of money. They do not.
• 39:14
  SpaceX's AI company loses an insane
• 39:17
  amount of money. SpaceX's uh let's see,
• 39:21
  uh let's I'll actually have it pull it
• 39:23
  up. Right.
• 39:27
  So, SpaceX's business units. This is my
• 39:31
  favorite. By profitability, income,
• 39:33
  profit or loss, simple connectivity.
• 39:36
  This is their Starlink. The Starlink
• 39:38
  branch of SpaceX is in the positive. It
• 39:41
  made nearly $1.6 billion dollars. It is
• 39:44
  profitable with a massive 39% operating
• 39:46
  margin. If you developed this system on
• 39:49
  your own, you would be a tremendously
• 39:51
  successful businessman. There's a
• 39:53
  problem.
• 39:55
  The space launching business, the thing
• 39:56
  that launches the Starlinks into orbit,
• 39:59
  that loses money. It's unprofitable,
• 40:02
  right? And obviously they have a bunch
• 40:04
  of R&D, but some of that money, some of
• 40:07
  those profits are supposed to come from
• 40:10
  the Starship system that they can't seem
• 40:11
  to get to work at scale, right? It seems
• 40:14
  actually inevitable that not only are
• 40:16
  they unprofitable, but they're not going
• 40:18
  to be able to deliver the contractually
• 40:20
  required um uh logistics capability to
• 40:24
  fulfill their their leg of the Artemis
• 40:26
  mission. And then you have XAI, which is
• 40:29
  Gro, their their AI company. It is
• 40:32
  losing [ __ ] crazy money. $1.2 billion
• 40:37
  dollar a year. And I want you to
• 40:41
  understand that 60% of the revenue, even
• 40:43
  if somehow all of these companies had no
• 40:45
  costs at all, 60% of SpaceX is Starlink.
• 40:52
  And within Starlink, guys, the reason
• 40:55
  why government contractors are so
• 40:57
  profitable is because of what's called
• 40:58
  lock in, which look at it like this.
• 41:03
  Look at the Ukrainian military at this
• 41:05
  point. They have contracts that build
• 41:10
  systems with the expectation that
• 41:11
  Starlink terminals are going to be
• 41:12
  dropped into them. They have entire
• 41:14
  systems dedicated that assume that
• 41:17
  Starlink is going to be operational for
• 41:19
  these Ukrainian units. There are Again,
• 41:22
  there's a reason why when we fund raise,
• 41:24
  we are always buying Starlink terminals
• 41:26
  because not only the UK the Ukrainian
• 41:29
  military runs on Starlink
• 41:32
  and that is true or could be true that's
• 41:36
  true of every contractor system.
• 41:40
  Look at
• 41:42
  uh like think of it like aircraft
• 41:44
  carriers. you score a contract to to
• 41:48
  build and maintain aircraft carriers,
• 41:50
  you are going to have as a company a
• 41:52
  guaranteed 50-year lifespan. You're
• 41:54
  going to be making money for decades to
• 41:56
  come because those carriers are going to
• 41:58
  launch planes. Those carriers, remember,
• 42:00
  the plane builders are going to build
• 42:02
  their planes to be launched from your
• 42:04
  carrier, right? If you manufacture the
• 42:07
  F-22 or the F-35, well, every single
• 42:10
  other arms manufacturer, everyone that
• 42:12
  makes the radios and the bombs and the
• 42:14
  bullets and whatever else, they're going
• 42:16
  to build them, assuming the F-35 is
• 42:19
  going to be flying them. And so when you
• 42:22
  build the when you own the system, you
• 42:25
  guarantee yourself not three quarters of
• 42:28
  income, you guarantee yourself three
• 42:30
  decades of business. It is the scoring a
• 42:35
  a infrastructure government contract a a
• 42:39
  system provider government contract is
• 42:42
  the holy grail of business contracts.
• 42:45
  Okay.
• 42:47
  And Starshield
• 42:50
  is stands to make a fuckload of money. I
• 42:54
  cannot emphasize this enough. The
• 42:57
  government contract system
• 43:00
  is of unbelievable value because imagine
• 43:05
  again we've shown it is combat proven.
• 43:08
  It's proven that the Russians throwing
• 43:11
  everything they have to shut this system
• 43:13
  down cannot touch it and the Russians
• 43:16
  can't even build their own. They keep
• 43:18
  falling out of the sky. They'll ne at
• 43:20
  this rate they will literally never
• 43:22
  build their own. They cannot keep the
• 43:23
  satellites in orbit.
• 43:25
  So you have demonstrated that you have
• 43:27
  an extremely desirable product and that
• 43:30
  European and and
• 43:34
  Pacific and North American militaries
• 43:37
  are dying to put your product in their
• 43:40
  militaries and build their military
• 43:42
  strike capabilities around your product.
• 43:45
  There is just one problem and you have
• 43:49
  shot yourself in the [ __ ] foot. The
• 43:53
  reason he shot himself in the foot is
• 43:55
  because he sent a message to every other
• 43:58
  country, France, Germany, Poland,
• 44:02
  America, Canada. Think about it. Would
• 44:05
  the Japan,
• 44:07
  South Korea, all of those countries
• 44:11
  know that if they have a a a war in
• 44:14
  which they have to use Starlink, in
• 44:16
  which their troops depend on Starlink
• 44:19
  and the adversary or they do something
• 44:21
  controversial or they make a tough
• 44:23
  decision that Elon doesn't like
• 44:27
  that he's going to turn off their
• 44:28
  Starlink, he's going to [ __ ] them.
• 44:32
  And when you know that about a system,
• 44:35
  you're just not going to buy it.
• 44:36
  Imagine, would you ever buy a gun
• 44:39
  that says, "Listen, if the gun senses
• 44:42
  that the person is is also a Glock
• 44:45
  customer, we we just won't let you shoot
• 44:47
  the guy." You go, "What? What do you
• 44:49
  mean? It's my firearm."
• 44:53
  Like imagine if you built a plane that
• 44:58
  simply turned off mid-flight when it was
• 45:01
  on a fire mission. If not just another
• 45:04
  country, but a random guy who made the
• 45:07
  plane decided he didn't really like what
• 45:09
  you were doing with it.
• 45:12
  Now, don't get me wrong, the US plays
• 45:13
  this game. that provides some of these
• 45:15
  operating systems, these capacities, and
• 45:18
  if you start committing war crimes with
• 45:19
  it, and you're not Israel, it'll turn
• 45:23
  off the it'll turn off the pipes. It'll
• 45:24
  turn them off. But there's a huge
• 45:26
  difference between saying, "Listen, the
• 45:28
  United States of America, who decides if
• 45:32
  you commit war crimes with this, we're
• 45:33
  going to turn off your help." sometimes
• 45:37
  and Elon Musk getting baked out of his
• 45:41
  gourd on ketamine and then calling up
• 45:43
  his engineers and being like turn it off
• 45:45
  and then turn it on again.
• 45:47
  That kind of risk is something that
• 45:49
  militaries can't assume.
• 45:51
  And that's why when you look at SpaceX
• 45:54
  the day after this was announced
• 45:57
  today, the stock price is down 3%. For
• 46:00
  those of you keep me score at home, Elon
• 46:02
  Musk has lost $60 billion today from his
• 46:06
  SpaceX stock because he took its only
• 46:09
  profitable business and lit that thing
• 46:12
  on fire and told every other customer
• 46:15
  that if you put your military depend on
• 46:18
  this system, bought and paid for, sign
• 46:20
  the contract, we are going to [ __ ] you
• 46:23
  whenever we want for any reason. And you
• 46:27
  won't even find out about it. You'll
• 46:28
  find out about it when your soldiers
• 46:30
  come home in body bags.
• 46:32
  So yeah, the market says, "Yo, SpaceX is
• 46:36
  not going to be the turbo government
• 46:38
  contractor you thought." And again, I
• 46:40
  laugh at Elon Musk losing $40 billion
• 46:42
  because he's too stupid to realize that
• 46:44
  he signed a contract guaranteeing a
• 46:46
  service and that providing an excellent,
• 46:49
  unbeatable, unjammable military
• 46:52
  connectivity system
• 46:55
  is
• 46:57
  is so valuable. It's like
• 47:01
  watching him like grab the golden ring
• 47:04
  and then like like chuck it into a river
• 47:07
  is like wild to me. It's like a wild
• 47:10
  level of stupidity. And again, losing 40
• 47:13
  billion, I laugh. I think that's funny.
• 47:15
  I laugh at Elon's misfortune. But
• 47:20
  I don't laugh because again, Ukrainian
• 47:22
  soldiers like some somebody's dad got
• 47:24
  killed yesterday because they were
• 47:26
  depending on this thing working cuz an
• 47:28
  FPV drone needed to hit a Russian who
• 47:30
  was take going after a Ukrainian
• 47:33
  position and couldn't, right? A a
• 47:36
  Russian truck carrying ordinance or
• 47:38
  launching a a drone didn't get it blown
• 47:42
  up because of Elon's decision.
• 47:46
  And that's what sort of bothers me about
• 47:47
  this is just how cavalier and the
• 47:51
  inability to actually hold a belief, the
• 47:54
  inability to have a policy
• 47:56
  uh from Elon Shore, but also from
• 47:59
  President Trump. Now, it's worth noting
• 48:00
  again, Elon has also spent $250 million
• 48:04
  that we know about trying to influence
• 48:06
  midterm elections here in the United
• 48:08
  States, but that seems to be going uh
• 48:11
  disastrously for Elon. He's one of the
• 48:13
  most unpopular human beings on planet
• 48:15
  Earth, actually. So,
• 48:18
  you know, couldn't have happened to a
• 48:20
  nicer guy. Uh anyway, be sure to vote if
• 48:24
  you're in the US. Check your early vote
• 48:26
  v voting dates. Check to make sure in a
• 48:28
  lot of Republican districts, um they're
• 48:30
  closing polling places. Uh so, just
• 48:32
  thanks to Alfred Allen, Andreas,
• 48:34
  Bastion, Brent, Brendan, Charles,
• 48:35
  Christine, and all lieutenant folks. Um
• 48:38
  early voting starting soon. Put it on
• 48:40
  your calendars, guys.
• 48:47
  All right, I see I see all y'all's
• 48:51
  uh super chats.
• 49:04
  All right, let's see. Ace Cam, thanks
• 49:05
  for the five. If I was an investor in
• 49:06
  SpaceX, I demand that Elon be replaced.
• 49:08
  I don't care how much hype man he is
• 49:09
  with Tesla. He's a loose cannon. Uh
• 49:11
  yeah. Well, here's the problem is that
• 49:12
  Elon's pay packages um are structured in
• 49:16
  a way that he can never be removed. And
• 49:18
  so, but you're not an investor in it,
• 49:19
  right? Because you know it's a shitty
• 49:22
  business.
• 49:25
  Happy Badgers. Thank you, Nikob. Thanks
• 49:27
  for the five Canadian. That's like
• 49:28
  that's like a million American hot dogs.
• 49:32
  How can you keep morale? I'm depressed a
• 49:34
  with world news. I'm not even American,
• 49:35
  but keep bringing the news. Um I worry I
• 49:39
  worry a lot about AI. Um
• 49:43
  uh I shouldn't I worry a lot about our
• 49:46
  inability to regulate it basically like
• 49:50
  uh I've actually read a story that a lot
• 49:53
  of uh engineers at AI have have taken up
• 49:56
  smoking expressly as a statement of
• 50:00
  basically they say listen either AI is
• 50:02
  going to kill all human beings long
• 50:04
  before I develop lung cancer or AI is
• 50:08
  going to cure all cancers.
• 50:10
  and I won't have to worry like like me
• 50:14
  getting lung cancer is going to be
• 50:16
  meaningless. Now smoking is stupid
• 50:18
  because it's expensive. Yes, it will
• 50:20
  give you lung cancer and yes, even if it
• 50:21
  cures cancer, you'll still get emphyma
• 50:23
  or heart disease which are harder nuts
• 50:24
  to crack. Uh but also um also if AI
• 50:28
  creates an apocalypse, you probably you
• 50:30
  probably want to have pretty good cardio
• 50:32
  like like cardiovascular fitness is
• 50:35
  pretty helpful in in an apocalypse. Just
• 50:38
  a thought.
• 50:41
  GG. Thanks for the five. Ever since
• 50:42
  2022,
• 50:44
  we were never once bored. There was
• 50:45
  always something happening. Yeah, man.
• 50:48
  The nothing ever happens uh crew is in
• 50:50
  [ __ ] shambles, dude. Before co
• 50:53
  nothing ever happens was a meme that
• 50:55
  like there was a bunch of bad stuff that
• 50:56
  people thought could happen and then it
• 50:58
  didn't. The problem is now nothing ever
• 51:00
  happens. It it things are happening too
• 51:04
  much. Right now it's now it's the
• 51:06
  [ __ ] meme, dude. It's the [ __ ]
• 51:09
  It's the things are going to get way
• 51:11
  worse meme,
• 51:15
  which I I [ __ ] love,
• 51:18
  right?
• 51:20
  Yeah, this is this is my favorite. This
• 51:22
  is this is this is my meme, dude. This
• 51:23
  is my heart.
• 51:26
  This should be like my phone background.
• 51:30
  The dude in a gas mask driving through
• 51:32
  just annihilated Chetchna. Now it's just
• 51:34
  like, listen, dude, everywhere is
• 51:35
  Chetchna. Like the whole world is just
• 51:38
  [ __ ] Groznney.
• 51:40
  Now obviously that's not that's that's
• 51:42
  partially untrue.
• 51:45
  I mean literally Kremursque is Groznney.
• 51:48
  And as I always tell my friends it's
• 51:50
  like listen I I have some friends who
• 51:52
  are like neurotic preers and I'm like
• 51:54
  listen dude one you're a [ __ ]
• 51:56
  suburban like guy living in a an
• 51:59
  apartment in a in a middle market urban
• 52:02
  area.
• 52:03
  I'm like if you want to talk about
• 52:05
  surviving a world that is collapsing um
• 52:12
  like
• 52:14
  the like I've been to Cremator I've been
• 52:16
  to Hark okay and guess what even in
• 52:19
  those places on the edge of
• 52:21
  survivability is Zoom
• 52:24
  like
• 52:26
  don't underestimate the power of of
• 52:28
  capitalism all right uh
• 52:32
  Because you can you in hark in
• 52:35
  crerematorsque two years ago admittedly
• 52:37
  current is in way worse shape but two
• 52:40
  years ago man you could have a hot
• 52:41
  shower you had power you had electricity
• 52:43
  you could you you could you I could I
• 52:45
  could have streamed [ __ ] video games
• 52:47
  I could have streamed Fortnite from
• 52:49
  crerematorsque okay and maybe next visit
• 52:52
  I will because yolo I guess or whatever
• 52:55
  I think that'd be funny um
• 52:58
  but uh I just want to point. Like I want
• 53:02
  to make that point because like
• 53:05
  like the preers of the world are
• 53:07
  neurotic and stupid and and fail to app
• 53:10
  uh to um to apprise risk properly. But
• 53:16
  uh
• 53:20
  the
• 53:23
  like yeah the AI thing worries me a lot,
• 53:26
  right? like the best case scenario and
• 53:29
  listen I'll grow up in if you tell me AI
• 53:31
  is going to cure all cancers and um but
• 53:34
  in exchange 50% of jobs will go away
• 53:36
  I'll actually take that trade like I
• 53:39
  think human lives are more important
• 53:40
  than economic value and
• 53:44
  like like
• 53:47
  jobs have already been vanishing right
• 53:49
  like uh here uh
• 53:52
  US for participation rate Uh yeah, here
• 53:57
  we go. BLS's civilian labor force
• 53:59
  participation rate. Okay. Uh over the
• 54:02
  last 20 years, you can see that civilian
• 54:03
  labor force participation is
• 54:06
  unbelievably low. In fact, uh in July,
• 54:09
  it was lower uh than it's been since CO
• 54:14
  like
• 54:17
  and people are like that's bad. And I'm
• 54:20
  like, it's kind of bad. But like
• 54:25
  the deeper story is that people are
• 54:27
  like, it's going to destroy all jobs.
• 54:29
  It's like, listen, tech is already
• 54:30
  destroying jobs. Okay? And and I I don't
• 54:35
  want to be like that's okay. I mean, you
• 54:37
  can see here, this is an even more
• 54:38
  interesting chart. In the 1950s, labor
• 54:41
  force participation rate, which is which
• 54:43
  is men and women in the labor force, was
• 54:45
  basically like 60%.
• 54:47
  And then women enter the workforce
• 54:49
  doubling it. And that's not like a
• 54:51
  there's not a value judgment. Don't be
• 54:52
  like oh Paul's mad that that happened.
• 54:55
  Uh I'm not. It increased sorry it
• 54:57
  increased from 58% to 67%. In 98 and
• 55:02
  then has been like on the steady decline
• 55:04
  as technology has made it so that like
• 55:08
  the country can grow economically
• 55:11
  but without a rise in labor force
• 55:12
  participation. Some of this is good.
• 55:14
  Some of this means that people retired.
• 55:16
  People saved enough money to retire
• 55:18
  comfortably. Some of this is good
• 55:20
  because it means more people are
• 55:21
  spending more years in education, right?
• 55:24
  So like it used to be in 1950 you turned
• 55:27
  18, you went to work at the factory and
• 55:28
  you worked there until you were 65 and
• 55:30
  then you died at 67.
• 55:33
  And now you say, "Hey, man." You spend,
• 55:38
  you know, you go to college for four
• 55:39
  years, maybe you get an additional
• 55:41
  training, you do an apprenticeship, and
• 55:43
  you're in the workforce four years
• 55:45
  later, four to six years later.
• 55:48
  And the
• 55:51
  and then you but your time in that
• 55:53
  workforce is more productive, right?
• 55:55
  Because of technology. So, if you told
• 55:57
  me, "Listen, dudes, uh, AI is going to
• 56:00
  be so productive that it's going to
• 56:02
  bring us back down to 65 and 10% more
• 56:04
  people are going to either be able to
• 56:06
  retire early, are going to spend more a
• 56:08
  few more years in education. Um, you
• 56:11
  know, maybe there will just be like a
• 56:13
  more productive society could say, "Hey,
• 56:15
  listen. If you have a kid, listen, the
• 56:17
  government, we tax AI, we tax by the
• 56:19
  token or whatever, and we put that money
• 56:22
  and we just pay you both parents. You
• 56:24
  get to stay home with your kid. You have
• 56:26
  a kid. Mom and dad instantly get
• 56:28
  Medicare. We put you on Medicare. You
• 56:30
  get three extra years on Medicare. And
• 56:32
  you hang out. You hang with your kid.
• 56:35
  You you you know, you sing dumb songs to
• 56:38
  them. And you walk around the park. Like
• 56:40
  that would make a a pretty do that'd be
• 56:42
  pretty dope. That'd be a pretty dope
• 56:44
  thing for a society that made um you
• 56:47
  know the ultimate productivity machine
• 56:49
  to do to be like yeah but a machine
• 56:53
  can't love your kids so like we'll pay
• 56:55
  you to do that you know
• 57:06
  Olaf Hans that's a great point right and
• 57:08
  and trust me I spent enough time
• 57:12
  I spent enough time in the government
• 57:13
  where I was like I was drawing a
• 57:14
  paycheck but I was like waiting for
• 57:17
  legal to review a report and I couldn't
• 57:19
  do anything until legal got back to me
• 57:20
  and and legal took like 3 days. So, you
• 57:24
  know, at least at least 5% of my working
• 57:27
  days in the government, my job was wait
• 57:29
  for [ __ ] legal to do something or or
• 57:33
  [ __ ] Yeah, it was always it was
• 57:35
  always OC. It was always Office of
• 57:37
  Council. But my point is is that when
• 57:39
  people are like the AI is going to
• 57:40
  [ __ ] destroy all jobs, I'm like, you
• 57:43
  know, the country wasn't exactly a
• 57:45
  bastion of instability in like 50 55 or
• 57:47
  65. 65 wasn't great, but but you know,
• 57:50
  you know what I mean. We could stand the
• 57:53
  country would would would survive, but
• 57:56
  you have to have policies that make
• 57:57
  sense. Um, but again, I worry about the
• 58:00
  the bad scenario, you know, the one the
• 58:03
  one where like AI helps like like
• 58:07
  basically we're like imagine if a school
• 58:10
  shooter got access to a nuclear weapon.
• 58:12
  That's what scares me. Like you wake up,
• 58:14
  you're like, "Okay, I'm going to be a
• 58:16
  school shooter today." But instead of
• 58:17
  shooting up a school and and killing
• 58:18
  like 10 kids, um you go, I'm going to
• 58:21
  make a virus that just kills kids. And
• 58:23
  like it does it. It's like, sure, here's
• 58:25
  a recipe for your grandma's virus that
• 58:27
  kills only children. You know, that's
• 58:29
  what worries me.
• 58:37
  Yeah. Ace camps. Listen, the only two
• 58:39
  options I see it, we either make Star
• 58:42
  Trek Universe, right? We make We make
• 58:44
  And again, I'm not like Star Trek
• 58:45
  Universe. I'm a believer in the free
• 58:47
  market, but you know, just like today,
• 58:50
  like if you can't afford food, guess
• 58:52
  what? We just give you a [ __ ] card
• 58:53
  and you swipe it and the government pays
• 58:56
  for some food for you and it doesn't
• 58:58
  bankrupt us. We don't worry about it.
• 59:00
  So, we say, "Okay, at the very bottom of
• 59:02
  the of the of the of the band, we say,
• 59:05
  "Listen, we won't let you we won't let
• 59:06
  you not have food. We'll get you some
• 59:08
  food one way or another." And maybe we
• 59:11
  can sit there, you know, sometimes we we
• 59:13
  do it also for kids with health
• 59:14
  insurance. Like kids have no other
• 59:16
  health insurance in most states. You go,
• 59:18
  listen, you're under 18, you don't have
• 59:20
  health insurance. Listen, we'll put you
• 59:21
  on a state program. You're going to get
• 59:23
  to see a pediatrician. All right? We're
• 59:25
  just we just say, listen, there's a
• 59:26
  there's a floor of stuff that we just
• 59:28
  say, listen, we're not going to let this
• 59:29
  happen. We got enough we got enough
• 59:32
  money floating around this country. We
• 59:33
  can cough up a little bit to make sure
• 59:35
  nothing terrible happens to people,
• 59:37
  right? And my hope is that in in an era
• 59:41
  of AI abundance, we can build that floor
• 59:44
  up a little bit. Be like, "Listen,
• 59:46
  listen. If you're in school or whatever,
• 59:48
  don't worry about your beard parents
• 59:50
  insurance. We'll put you on a Medicare.
• 59:54
  You'll see a PA who consults with an AI
• 59:57
  doctor. They'll refer you out to a
• 59:59
  specialist if you have to, but it's
• 1:00:01
  fine. We got enough abundance. We can
• 1:00:04
  give we can hook you up." We say,
• 1:00:06
  "Listen, yeah, you're broke, but listen,
• 1:00:10
  the government makes all this money from
• 1:00:11
  AI. If you can't afford a place to live,
• 1:00:14
  we'll give you a voucher. We'll put you
• 1:00:15
  up in in a basic apartment and and
• 1:00:17
  you'll survive, you know.
• 1:00:29
  Oh no. Is it true? Am I really am I uh
• 1:00:33
  uh did I desync? Did my audio desync?
• 1:00:38
  Yeah, but I still think like yeah, you
• 1:00:39
  could have this baseline, but you should
• 1:00:41
  still have like a capitalist economy,
• 1:00:42
  right? And like you go, oh, maybe maybe
• 1:00:46
  the the you know, we'll have more humans
• 1:00:50
  doing human [ __ ] right? Where you go,
• 1:00:52
  oh man, maybe it'll be more dope
• 1:00:54
  restaurants. Like more people will be
• 1:00:56
  like, "Hey, I want to cook something
• 1:00:57
  that like doesn't exist anywhere else."
• 1:01:00
  Or you'll have more [ __ ] Twitch
• 1:01:03
  streamers. You'll have more
• 1:01:04
  entertainers, more maybe more athletes,
• 1:01:06
  maybe more sports leagues. Like human
• 1:01:09
  beings will always be willing to spend a
• 1:01:12
  little extra money to purchase some
• 1:01:14
  convenience and purchase goods or
• 1:01:16
  services. Like that is something that
• 1:01:17
  has been consistent through all of human
• 1:01:19
  history. Like as long as as soon as
• 1:01:22
  humans beings were able to organize into
• 1:01:24
  governments, they were willing to pay
• 1:01:25
  for certain things. They were willing to
• 1:01:26
  say, "Listen, I will consolidate my
• 1:01:28
  labor into some kind of currency and
• 1:01:31
  then I will give you that currency in
• 1:01:34
  exchange for something that you have
• 1:01:36
  that I want that I can't do myself."
• 1:01:39
  Again, I mean, that's always going to
• 1:01:41
  happen, right?
• 1:01:47
  So,
• 1:01:50
  again, I think that's still going to
• 1:01:51
  happen in the United States and other
• 1:01:52
  countries. I think it I think it might
• 1:01:54
  actually become more competitive because
• 1:01:56
  like for a lot of people they say listen
• 1:01:59
  I can't I can't open my own restaurant
• 1:02:01
  because if I do how am I going to afford
• 1:02:04
  my kids healthcare? How am I going to
• 1:02:06
  afford what's going to happen if I have
• 1:02:08
  a heart attack? And imagine living in a
• 1:02:10
  world where we go hey man you have a
• 1:02:12
  heart attack don't worry about it. Your
• 1:02:13
  restaurant's not off the ground yet. No
• 1:02:15
  problem.
• 1:02:16
  You don't have to worry. just pay your
• 1:02:19
  taxes, you know, and and and and you'll
• 1:02:21
  get it.
• 1:02:29
  Yeah, it's a social safety net, but it
• 1:02:30
  also like but but from a frame again,
• 1:02:35
  you can sit there and go, hey man, this
• 1:02:37
  is also something that is an enabler of
• 1:02:39
  economic growth, right? Like you look at
• 1:02:42
  for example
• 1:02:44
  again uh
• 1:02:47
  you look at the countries with the
• 1:02:48
  fastest
• 1:02:50
  GDP growth in the last 10 years right
• 1:02:54
  countries with the fastest GDP growth
• 1:02:56
  again co's going to goof everything up
• 1:03:00
  but you look at China is a great example
• 1:03:03
  China has a state healthcare system
• 1:03:05
  over the last 10 years China's economy
• 1:03:08
  has gone [ __ ] gang busters gone
• 1:03:10
  bananas and somehow they did it with a
• 1:03:14
  state-run healthare system. I think it's
• 1:03:17
  a I think it's a hybrid. Most of these
• 1:03:19
  are hybrids. Hybrid seems to be the
• 1:03:20
  consensus best,
• 1:03:24
  you know, like you look at Guyana,
• 1:03:26
  right? Let's see. Let's see. Uh
• 1:03:30
  or Ethiopia, right? Let's use Ethiopia
• 1:03:33
  averaging 10% over a decade, right?
• 1:03:46
  So again,
• 1:03:49
  uh
• 1:03:57
  so they have a
• 1:04:00
  private health insurance doesn't exist.
• 1:04:03
  uh they have a community based health
• 1:04:05
  insurance
• 1:04:06
  which covers large portions of the
• 1:04:08
  population. 80% of citizens are covered
• 1:04:10
  by community based health insurance
• 1:04:12
  which is funded through a mix of
• 1:04:13
  government allocations and out-of-
• 1:04:15
  pocket payments. So it seems like even
• 1:04:17
  Ethiopia,
• 1:04:19
  even a developing country still has
• 1:04:22
  again primary care, community level
• 1:04:23
  health posts,
• 1:04:26
  uh zone zone hospitals and tertiary
• 1:04:28
  specialized care.
• 1:04:31
  And these efforts combined to a rapid
• 1:04:33
  decline in mortality under five uh and
• 1:04:36
  major improvements. Right? So Ethiopia
• 1:04:40
  hasn't had to choose between socialized
• 1:04:42
  healthare
• 1:04:44
  uh hasn't had to choose between
• 1:04:46
  socialized healthcare and rapid growth.
• 1:04:48
  It's actually gotten rapid growth uh in
• 1:04:50
  part because of its decision to
• 1:04:52
  socialize healthcare. You can see that
• 1:04:53
  in the last 10 years 10 years ago let's
• 1:04:55
  see Ethiopia had a life expectancy of 65
• 1:04:59
  today 68 which is crazy. That means
• 1:05:03
  Ethiopians and by the way in 2000 an
• 1:05:06
  Ethiopian would have expected to live
• 1:05:09
  about 51 years. Now they live 68.
• 1:05:14
  I mean you could see basically I mean
• 1:05:15
  there was the famine in the 80s but you
• 1:05:17
  could see that
• 1:05:19
  even in the last 10 years like yeah they
• 1:05:20
  made a bunch of gains but even in the
• 1:05:23
  last 10 years you could see that they
• 1:05:25
  have really continued to push their life
• 1:05:27
  expectancy. Um,
• 1:05:31
  I mean that's 60 68 is crazy. Like let's
• 1:05:34
  see if we can find
• 1:05:38
  a list of countries by life expectancy
• 1:05:41
  again. And this is Ethiopia, guys. It's
• 1:05:43
  kind of embarrassing. So, okay, here's a
• 1:05:46
  list of countries by life expectancy
• 1:05:50
  overall. Again, they say at 15 and 65
• 1:05:53
  80. We're just going to do at birth. At
• 1:05:55
  birth is apples to apples. So you can
• 1:05:57
  see basically all these countries in the
• 1:06:00
  60s all subsaharan Africa but again
• 1:06:03
  Ethiopia
• 1:06:05
  just not having this problem
• 1:06:08
  right Angola Equatorial Guinea Bundi
• 1:06:10
  Kenya Madagascar notably these don't
• 1:06:12
  have these have these these have
• 1:06:14
  extremely weak governments Afghanistan
• 1:06:17
  actually somehow living longer
• 1:06:19
  right in a state of civil literal civil
• 1:06:22
  war okay Sudan South Africa that's
• 1:06:25
  actually pretty sad head. Um, that's
• 1:06:28
  depressing,
• 1:06:29
  right? Malawi, Timor, Pakistan,
• 1:06:33
  again, Sagal, like you notice these
• 1:06:35
  countries are just [ __ ] broke.
• 1:06:39
  Here's Guyana, 70, another one of the
• 1:06:42
  fastest growing countries on Earth with
• 1:06:44
  also a very long life expectancy.
• 1:06:48
  What's also wild to me is again like
• 1:06:51
  Turk menistan 70, Greenland. Greenland
• 1:06:55
  has a life expectancy of 70. Whoa, dude.
• 1:06:59
  That's wild, guys. Yemen 69, Libya 69.
• 1:07:05
  Uh, still can't find Ethiopia. Maybe
• 1:07:08
  Ethiopia is even higher now.
• 1:07:11
  Maybe. India 72, Venezuela 72, Russia
• 1:07:16
  73. I wonder where the US is. There's
• 1:07:18
  the world average. Ukrainians. Literally
• 1:07:21
  a country in a state of total war. Still
• 1:07:23
  living longer than average.
• 1:07:26
  But like, let's see if we can find
• 1:07:28
  America.
• 1:07:31
  Beautiful America. Uh, let's see. Oh,
• 1:07:34
  here we go. Change in life expectancy.
• 1:07:36
  Uh,
• 1:07:38
  sex gap. All here we go. So, the largest
• 1:07:44
  change
• 1:07:47
  Uh let's see if we can find this chart.
• 1:07:49
  2023 this is okay co recovery stuff. All
• 1:07:52
  right so the countries with the biggest
• 1:07:56
  o 2022 to 2023 Palestine a loss of 11
• 1:08:00
  years of life expectancy. That just
• 1:08:02
  makes me sad. But here you go. Central
• 1:08:04
  African Republic gaining 38 years of
• 1:08:05
  life expectancy probably due to an end
• 1:08:07
  of a war. Somalia and Namibia UAE right
• 1:08:11
  Brunai. Puerto Rico. Oman reunion
• 1:08:14
  island. Greece gaining life expectancy.
• 1:08:16
  And see all these have something in
• 1:08:18
  common which is strong socialized
• 1:08:20
  healthcare.
• 1:08:27
  Purple dinosaur. Two bucks for the
• 1:08:29
  strike life extension. Hell yeah. The
• 1:08:30
  biosticle. Thanks for the five.
• 1:08:34
  Amen to that, dude. You'll live forever.
• 1:08:38
  Who knows, man? Maybe we all live
• 1:08:40
  forever in the AI. You know, who the
• 1:08:41
  [ __ ] knows? Dude, listen. I want you to
• 1:08:43
  understand how insane it is that in a
• 1:08:45
  couple of hours AI solved mathematics
• 1:08:48
  and recently I read a report that they
• 1:08:51
  are doing the same thing towards like
• 1:08:52
  highle theoretical physics problems
• 1:09:01
  like I want you to understand how
• 1:09:03
  [ __ ] crazy it is. So yeah, the
• 1:09:04
  mathematicians are like seething and and
• 1:09:06
  I get it. You didn't get to solve your
• 1:09:08
  puzzles anymore, but
• 1:09:11
  like
• 1:09:13
  the solving the puzzles
• 1:09:16
  like we we
• 1:09:19
  like
• 1:09:22
  we we got to time warp,
• 1:09:25
  you know, like if you're a 60-year-old
• 1:09:26
  mathematician, you are going to see 20
• 1:09:28
  years of human breakthroughs. That's
• 1:09:30
  what you were going to that's what you
• 1:09:31
  were allowed to see in your lifetime.
• 1:09:32
  and you just had to have faith that that
• 1:09:35
  long after you're dead,
• 1:09:37
  maybe some other problems would be
• 1:09:39
  solved by some future versions of
• 1:09:41
  humans. But instead, you got to peek
• 1:09:44
  open the curtain and look a century,
• 1:09:47
  maybe 200 years ahead of what would be
• 1:09:49
  human progress. And an AI is like, "Hey,
• 1:09:51
  here you can read them all. You can read
• 1:09:53
  the solutions of math problems from 200
• 1:09:56
  years in the future."
• 1:09:58
  Like imagine doing that with physics
• 1:09:59
  being like, "Yo, you want to see what
• 1:10:01
  what human beings would have gotten to
• 1:10:02
  in in 250 years on fusion?"
• 1:10:06
  Like some [ __ ] opus is like, "Here it
• 1:10:07
  is." Now, obviously math is pure logic.
• 1:10:10
  Like math can be solved internal to an
• 1:10:13
  AI whereas like medicine has to be field
• 1:10:16
  tested, you know, like you have to put
• 1:10:19
  it in human bodies and and see if it
• 1:10:21
  actually does what it says it does.
• 1:10:24
  But
• 1:10:26
  it's still just so [ __ ] wild, dude.
• 1:10:30
  Like, it's a crazy time to be alive. I
• 1:10:32
  don't know what else to tell you.
• 1:10:36
  Ace cams. Wait, so we may have AI
• 1:10:38
  discover faster than light travel. Yeah.
• 1:10:41
  Yeah. What I mean, or reach a conclusion
• 1:10:44
  about the state of of FTL, like
• 1:10:54
  Uh, let's see.
• 1:10:59
  Yeah, AI came from math. Now it's
• 1:11:00
  chasing the rest of science. I mean, you
• 1:11:02
  got to understand like there's there are
• 1:11:05
  all these interviews with mathematicians
• 1:11:06
  where they're they're sobbing, dudes.
• 1:11:08
  They're sobbing. Their field has been
• 1:11:10
  eliminated
• 1:11:12
  because it's been entirely solved. They
• 1:11:14
  don't even know what the next round of
• 1:11:16
  the they don't they can't even theorize
• 1:11:20
  like they have to understand all the
• 1:11:22
  mathematical everything like they have
• 1:11:24
  to understand the solutions that have
• 1:11:26
  been presented and now they have to
• 1:11:27
  formulate new ones.
• 1:11:37
  It's crazy.
• 1:11:52
  Yeah.
• 1:11:57
  So like Yeah.
• 1:12:01
  I mean again these guys were solving
• 1:12:03
  some problems in December but just now
• 1:12:09
  again it was funny in 2026
• 1:12:11
  like
• 1:12:13
  people or in February they were like
• 1:12:16
  maybe can is it really solving the math
• 1:12:18
  problems or not now it's like uh it just
• 1:12:21
  did [ __ ]
• 1:12:25
  solving problem can it best the world's
• 1:12:26
  top mathematicians now the
• 1:12:28
  mathematicians are just sobbing
• 1:12:30
  Right.
• 1:12:34
  It's It's [ __ ] crazy, dude. It's
• 1:12:37
  [ __ ] crazy.
• 1:12:41
  Like, I'm just like choosing to have
• 1:12:42
  faith a little bit that we're going to
• 1:12:45
  make we're this technology will be used
• 1:12:46
  for good, you know?
• 1:12:53
  Yeah, it totally has to get checked. You
• 1:12:54
  still need very capable human
• 1:12:56
  mathematicians. like I can't understand
• 1:12:58
  the solutions. So like there has to be
• 1:13:00
  human mathematicians and like it kind of
• 1:13:02
  sucks that like the AI is doing like the
• 1:13:04
  hard work and that your job is to kind
• 1:13:05
  of like supervise and guide the AI
• 1:13:07
  towards finding solutions but um and and
• 1:13:10
  and like confirming whether it connects
• 1:13:13
  to base reality but
• 1:13:16
  like
• 1:13:18
  like you know
• 1:13:20
  it's like when they when they developed
• 1:13:22
  like combines and threshers and
• 1:13:24
  harvesters like what did you think as a
• 1:13:26
  farmer? Were you like, "Oh [ __ ] we're
• 1:13:27
  all going to get put out of work." And
• 1:13:29
  like that was 99% true. But the
• 1:13:31
  abundance it introduced for human beings
• 1:13:35
  means that like farmers kids got to do a
• 1:13:37
  bunch of other [ __ ] They became lawyers
• 1:13:39
  and doctors and engineers and and all
• 1:13:41
  this stuff, right? Like you drafter used
• 1:13:43
  to be a profession and now a computer
• 1:13:46
  program does all drafting and engineers
• 1:13:49
  do more engineery stuff, right? like
• 1:13:50
  like the world it has been good for the
• 1:13:52
  world and like it's really rapid and we
• 1:13:55
  need to have an understanding that like
• 1:13:58
  it won't be the farmer's kids like at
• 1:13:59
  some point maybe in the next two years
• 1:14:02
  like as a YouTube creator I I'm going to
• 1:14:05
  get I won't be like I'm going to get
• 1:14:07
  lost in a sea of AI like there'll be a
• 1:14:10
  thousand of me doing AI stuff like
• 1:14:12
  reading the news distilling it into a
• 1:14:15
  chat a talk talking to chat like an AI
• 1:14:18
  will be able to do it you you know,
• 1:14:21
  and like I understand that I say I tried
• 1:14:24
  really hard to save a lot of money. Um,
• 1:14:30
  uh, but
• 1:14:34
  you just I I don't know what to tell
• 1:14:36
  you. Like that's okay. Like I'm I'm I'm
• 1:14:40
  like I understand that you get to do
• 1:14:43
  things for a certain period of time and
• 1:14:45
  then you then you can't, right?
• 1:15:06
  Yeah. What policy?
• 1:15:10
  Shouldn't have put your skill points and
• 1:15:11
  intelligence. Exactly. That's a fact,
• 1:15:12
  dude. I should have just done either
• 1:15:14
  luck or uh I should have done luck or
• 1:15:19
  [ __ ] I don't know um charisma. Maybe
• 1:15:23
  charisma would have been a good one.
• 1:15:42
  Yeah, my fear is not that like AI will
• 1:15:44
  be better than a human streamer. My fear
• 1:15:49
  is that AI will just be able to do more
• 1:15:51
  volume. Like if it's half as good as me,
• 1:15:53
  let's say, but remember, I do this for
• 1:15:56
  90 minutes a day. AI could be on stream
• 1:15:59
  for 8 to 12 hours a day,
• 1:16:03
  24 hours a day, right? It doesn't need
• 1:16:04
  to sleep or eat or drink coffee. It
• 1:16:07
  never makes an annoying slurp sound. It
• 1:16:09
  doesn't ask questions about sponsors. It
• 1:16:12
  always brings the energy. It never gets
• 1:16:13
  sick. It never gets tired. And my fear
• 1:16:16
  is that 99% of audience watch hours are
• 1:16:21
  going to be for AI creators and that the
• 1:16:24
  human creators are going to get less
• 1:16:26
  than 1%.
• 1:16:28
  That's my fear.
• 1:16:33
  And
• 1:16:36
  like
• 1:16:38
  yeah, I don't know what that future
• 1:16:39
  looks like, but I but I have faith that
• 1:16:42
  like again I will accept that future if
• 1:16:44
  it also means that that someone says
• 1:16:48
  listen man the odds of your children
• 1:16:50
  dying of cancer have dropped to zero.
• 1:16:52
  Like they will live full healthy hap
• 1:16:54
  they will live full healthy lives. as a
• 1:16:57
  as a dad, you go, I'll [ __ ] resign
• 1:17:00
  today if that's the trade, you know? Um
• 1:17:06
  Yeah. Yeah. If you're like, "Listen,
• 1:17:10
  your kid will never have to be a grunt
• 1:17:11
  infantryman, like like the the the the
• 1:17:14
  blowy up part of war might be done by a
• 1:17:17
  robot." I'll go, "Okay, okay, I'll lose
• 1:17:20
  my job."
• 1:17:26
  Yeah, AI may not make take AI will
• 1:17:28
  probably take a lot of the entertainment
• 1:17:29
  space.
• 1:17:37
  AI may have an audience of AI. It's
• 1:17:38
  true.
• 1:17:47
  But that's also a problem, right?
• 1:17:48
  Because then I mean, how do you make
• 1:17:50
  money doing that?
• 1:17:56
  AI Paul clone can't be bargained with,
• 1:17:58
  can't be reasoned with. I don't feel he
• 1:17:59
  won't feel pity, remorse, or fear. Yeah,
• 1:18:06
  Paul, explain the difference between an
• 1:18:07
  AI and an LLM. My understanding is that
• 1:18:10
  a large language model
• 1:18:13
  like
• 1:18:15
  Okay, AI is whatever you mean it. AI is
• 1:18:18
  whatever you want it to mean. and LLM. I
• 1:18:20
  mean, LLM is a large language model. Uh,
• 1:18:23
  I'm not sure that I'm not sure there's a
• 1:18:27
  difference. I think AI is just a general
• 1:18:30
  term for like any sort of machine
• 1:18:32
  learning and an LLM is like a subtype.
• 1:18:44
  But let's see. You know what? Let's find
• 1:18:46
  out together.
• 1:18:53
  But I'm going to say that an AI is
• 1:18:55
  probably just
• 1:18:57
  it's probably just one of those generic
• 1:18:59
  terms like
• 1:19:01
  Yeah,
• 1:19:03
  there you go. Oh man, I nailed it. AI is
• 1:19:05
  a broad field and LLM is a specific tool
• 1:19:07
  inside the field. AI is vehicles. LLM is
• 1:19:09
  a sports car. Every car is a vehicle,
• 1:19:11
  but not every vehicle is a sports car.
• 1:19:12
  Nailed it. [ __ ] yes.
• 1:19:16
  And then it has a little graph.
• 1:19:18
  Artificial intelligence, machine
• 1:19:20
  learning. Oh, uh, interesting. Machine
• 1:19:21
  learning is a subt type of artificial
• 1:19:23
  intelligence. Oh, I didn't know that.
• 1:19:24
  Neural networks and large language
• 1:19:26
  models.
• 1:19:31
  Artificial intelligence include
• 1:19:32
  rule-based systems, chess engines. Okay.
• 1:19:35
  Yeah, that's I guess that makes sense.
• 1:19:36
  predictive or classification models like
• 1:19:38
  credit card fraud detection,
• 1:19:39
  recommendation engines, computer vision,
• 1:19:42
  medical scan analysis, self-driving car,
• 1:19:44
  robotics, LLMs, contextual
• 1:19:46
  comprehension, writing, summarizing,
• 1:19:48
  translating, conversational reasoning,
• 1:19:49
  generating code, structure, text
• 1:19:51
  reasoning.
• 1:19:53
  I guess that's fair. I guess that's
• 1:19:55
  fair. But LLMs, okay, interesting. LLM,
• 1:19:58
  GPT, Claude, Gemini, and Llama. Hm.
• 1:20:04
  When your bank flag, suspicious swipe,
• 1:20:06
  or car inside a highway lane. That is
• 1:20:07
  traditional AI. Huh? Traditional AI.
• 1:20:10
  Never thought I'd live in that world,
• 1:20:11
  huh?
• 1:20:35
  Yeah, I saw the same a uh AI uh talk by
• 1:20:39
  Ben Affleck and I was like, damn, this
• 1:20:40
  guy's [ __ ] smart. You understand why?
• 1:20:42
  One, raging alcoholic, but still why
• 1:20:45
  like um who's his wife? Jennifer Garner.
• 1:20:49
  Jennifer Garner is just like clearly in
• 1:20:51
  love with the guy. Uh Paul, okay, thanks
• 1:20:54
  other Paul for the 20. People need to
• 1:20:56
  know that LM are not intelligent. they
• 1:20:57
  just spit out characters based on
• 1:20:58
  statistics with zero regard for factual
• 1:21:00
  research. So that is that is just not
• 1:21:02
  true.
• 1:21:04
  Like
• 1:21:06
  I think that's an outofdate concept. Um,
• 1:21:12
  the LLM's the the current the current
• 1:21:16
  permutations seem to be deeply committed
• 1:21:19
  to factual research
• 1:21:22
  like it it
• 1:21:26
  and like they clearly are able to do
• 1:21:28
  original thoughts, original thinking,
• 1:21:30
  right? And they have been for a while
• 1:21:32
  because like you can ask it to come up
• 1:21:33
  with things that don't exist
• 1:21:36
  and it can do so pretty well.
• 1:21:40
  like uh let's let's let's see let me let
• 1:21:43
  me show you guys an example here. Let me
• 1:21:45
  let me uh let me see I can pull up my
• 1:21:47
  chat GPT. We'll we'll we'll waste we'll
• 1:21:49
  waste some money with the highest
• 1:21:52
  possible
• 1:21:53
  uh stat. Okay. Um
• 1:21:58
  Okay. I wanted to just chat. I want to
• 1:21:59
  just chat with it. Uh All right. I'm
• 1:22:02
  gonna ask it to do some actual creative
• 1:22:04
  work. Um,
• 1:22:06
  can you come up with some
• 1:22:10
  totally
• 1:22:12
  original games to play with my
• 1:22:16
  threeyear-old?
• 1:22:20
  So, like this is a pretty simple
• 1:22:22
  creative task. Three-year-olds love
• 1:22:24
  games, right? Um, can I come up with
• 1:22:28
  totally original things we can do with a
• 1:22:30
  three-year-old?
• 1:22:31
  Okay, it says the invisible animal
• 1:22:34
  hospital. Premise. Invisible animals
• 1:22:35
  keep showing up to your house with
• 1:22:36
  ridiculous problems. You hold an
• 1:22:37
  imaginary animal and announce, "Oh no,
• 1:22:39
  the giraffe's neck has turned into
• 1:22:40
  spaghetti. Your child is a veterinarian
• 1:22:41
  who has to figure out how to fix each
• 1:22:43
  animal. The elephant's forgotten how to
• 1:22:44
  trump it or the penguin can't stop
• 1:22:45
  hopping. Child fixes the animal. They
• 1:22:47
  have to teach you how to take care of
• 1:22:48
  it. You must get everything hilariously
• 1:22:49
  wrong." That's a perfect game. She would
• 1:22:52
  delight in that. The floor is getting
• 1:22:53
  sleepy. You have to move around the room
• 1:22:54
  without waking it up. Okay. The floor's
• 1:22:57
  dream about dinosaurs. You have to walk
• 1:22:58
  like tiny dinosaurs. or the floor is
• 1:23:00
  snoring. Freeze. Do you notice how these
• 1:23:02
  are creative and original, but they hang
• 1:23:04
  together?
• 1:23:06
  Like, this isn't statistics. This isn't
• 1:23:09
  statistical nonsense. You know what I
• 1:23:11
  mean? This isn't just a compilation of
• 1:23:14
  gobbledegook words that sound like a
• 1:23:16
  children's game. These are actual
• 1:23:17
  children's games.
• 1:23:20
  Okay, this is so cute. You're a robot
• 1:23:23
  that has that answers every question
• 1:23:24
  incorrectly. Your child has to repair
• 1:23:26
  you by teaching you basic facts. What
• 1:23:27
  does a cow say? Pizza. Oh my god, these
• 1:23:29
  are so fun. Actually, I love this.
• 1:23:33
  You say it cannot come up with original
• 1:23:35
  thoughts. Full stop. But like I
• 1:23:38
  understand, but that's like saying a
• 1:23:40
  human being can't come up with an
• 1:23:41
  original thought. Like by that by by the
• 1:23:43
  standard of original thought you're
• 1:23:45
  applying like Van Go didn't have never
• 1:23:47
  made an original painting because all of
• 1:23:48
  his paintings were influenced by poalism
• 1:23:50
  and other impressionists and and d like
• 1:23:53
  a whole bunch of traditions. So you're
• 1:23:55
  like Van Go didn't make original
• 1:23:57
  paintings. I know I'm not somebody who's
• 1:23:58
  like AI's like an AI doesn't feel an AI
• 1:24:03
  like an AI doesn't understand the
• 1:24:05
  goofiness. But I want to point out that
• 1:24:07
  what it's describing in this is are are
• 1:24:11
  original ideas. They are novel ideas and
• 1:24:15
  they are they have real idea
• 1:24:17
  characteristics. They are not
• 1:24:19
  compilations of statistical language.
• 1:24:22
  Right?
• 1:24:35
  Now, this is a ton. Okay, the AI almost
• 1:24:38
  like, for lack of a better term, enjoyed
• 1:24:39
  this.
• 1:24:43
  Like, it it gave me a way larger answer
• 1:24:45
  than I would expect.
• 1:25:00
  like okay so AI is a program it's nor
• 1:25:03
  intelligence it's just a program to
• 1:25:04
  generate an output
• 1:25:07
  the artificials are done because all
• 1:25:09
  executable programs are artificial yeah
• 1:25:10
  it's artificial
• 1:25:13
  and it generates an output but like
• 1:25:17
  it performs
• 1:25:19
  something it performs a type of thinking
• 1:25:22
  and it perform it performs a type of
• 1:25:24
  thinking not like a human thinks clearly
• 1:25:27
  but like it's not sentient but it
• 1:25:30
  thinks.
• 1:25:33
  Does that make sense? Like it's not it's
• 1:25:35
  not sentient. It's not self-aware,
• 1:25:38
  but it can perform original thinking
• 1:25:49
  de I that isn't the point I'm making.
• 1:25:52
  Are you sure they're original? They are
• 1:25:55
  compilations of statistical language.
• 1:25:58
  But the Okay, the question is, is there
• 1:26:00
  an underlying idea expressed by the
• 1:26:02
  language? And I argue yes like like
• 1:26:06
  there is an idea of invisible animal
• 1:26:09
  hospital, right? There is an idea of
• 1:26:12
  invisible animal Oh my god. Sorry. Hold
• 1:26:14
  on. Wait. Sorry. I clicked away and
• 1:26:17
  everything went haywire.
• 1:26:21
  Like there is there is some kind of
• 1:26:23
  underlying theoretical concept that is
• 1:26:25
  the game of invisible animal hospital
• 1:26:28
  and it uses words to express but it it
• 1:26:33
  is a cohesive idea.
• 1:26:40
  Do you see what I mean? So like
• 1:26:45
  for in for reasons and in ways that like
• 1:26:49
  using a mechanism that we don't fully
• 1:26:50
  understand
• 1:26:52
  it it can it can ach it can
• 1:26:54
  conceptualize for lack of a better word
• 1:26:57
  again I'm using a human word to describe
• 1:26:58
  machine process but it can it can
• 1:27:01
  clearly traffic in a a theoretical
• 1:27:04
  concept and again you have this weird
• 1:27:06
  stuff about our own thinking like am I
• 1:27:11
  like what does it mean when I picture
• 1:27:13
  playing Invisible Animal Hospital with
• 1:27:15
  my daughter, right? Like what is that?
• 1:27:17
  What what am I trafficking in there?
• 1:27:28
  But like, okay, at what point does auto
• 1:27:30
  does AI as autocomplete at what point is
• 1:27:33
  it is it thinking
• 1:27:36
  like is it self-aware? I don't know. I
• 1:27:38
  don't think so.
• 1:27:41
  This is sort of the trip, right? This is
• 1:27:42
  what sort of blows my mind. It's like it
• 1:27:44
  thinks as well, maybe even better than a
• 1:27:46
  human, but doesn't
• 1:27:49
  have human beings desires. Like it
• 1:27:53
  doesn't have consciousness.
• 1:27:54
  You know,
• 1:28:03
  John Ber right there is no idea. just
• 1:28:05
  creating something that resembles an
• 1:28:06
  idea
• 1:28:09
  requiring a huge amount of brute force
• 1:28:10
  computing.
• 1:28:13
  But like here's the thing. So you're
• 1:28:15
  like, okay, it's a bunch of monkeys.
• 1:28:18
  It's the computer version of a bunch of
• 1:28:19
  monkeys on typewriters and one of them
• 1:28:21
  statistically will land on Shakespeare
• 1:28:23
  to think there's they're again I don't
• 1:28:25
  know enough about the science but I
• 1:28:27
  would believe that except for the fact
• 1:28:29
  if you told me though like the monkeys
• 1:28:32
  knew when they when they landed on
• 1:28:34
  Shakespeare, right? Like like you said,
• 1:28:37
  hey, I'm going to put a billion monkeys
• 1:28:38
  in a room. They're all going to type on
• 1:28:39
  typewriters and statistically one of
• 1:28:41
  them will produce Hamlet. That I believe
• 1:28:44
  could totally happen. but that one of
• 1:28:47
  the monkeys would know that they
• 1:28:49
  produced Hamlet and would hand it to
• 1:28:51
  you. So like it knew that it needed to
• 1:28:54
  have the games hang together and make
• 1:28:56
  sense.
• 1:28:59
  Do you see what I mean?
• 1:29:07
  Yeah. And and that's rep Cisco. We have
• 1:29:09
  to define how we think. That's the
• 1:29:11
  problem. We don't like when I play um
• 1:29:15
  when I play like
• 1:29:18
  um
• 1:29:20
  you know when I play silly restaurant
• 1:29:22
  with my daughter
• 1:29:25
  where where did I come up with that?
• 1:29:27
  Like where'd you come up with silly
• 1:29:28
  restaurant or with my son? We we we have
• 1:29:32
  a game I guess it's called boopity doop.
• 1:29:33
  It doesn't make any sense. We just say
• 1:29:35
  the thing and then we then then I sort
• 1:29:37
  of hold him by his legs and swing him.
• 1:29:40
  Uh,
• 1:29:41
  but like where did I come up with
• 1:29:43
  boop-doop? I don't know. And like I'm
• 1:29:46
  not sure even a a like neurologist or
• 1:29:51
  like a like a cognition researcher could
• 1:29:53
  really tell me like how'd you land on
• 1:29:55
  Boop Buddy Doop? Like I
• 1:29:59
  But if we can't say if but we So like
• 1:30:02
  that's why I'm kind of like suspicious
• 1:30:03
  when people are like well if a LLM does
• 1:30:06
  it it's not thinking but when we do it
• 1:30:08
  it's thinking. I'm like, I don't know.
• 1:30:11
  Like, I can tell you this doesn't feel
• 1:30:14
  like I feel excitement. Maybe we'll try
• 1:30:16
  to play Animal Hospital. And it excites
• 1:30:18
  me to be like, "Oh, she's going to love
• 1:30:20
  it." But like, the AI cannot feel
• 1:30:23
  excitement, anticipation. Like, it it
• 1:30:26
  can't capture that. It's unable to
• 1:30:29
  because it's a machine. It doesn't have
• 1:30:31
  feelings.
• 1:30:36
  Like, I I wonder if I can just ask it.
• 1:30:38
  Okay. It can be like, "Do you want me to
• 1:30:39
  invent 10 more games?" So this one I
• 1:30:41
  love to know. What kind of play does
• 1:30:42
  your three-year-old enjoy most? Being
• 1:30:44
  silly, laughing, making adults do funny
• 1:30:45
  things, running, jumping, chasing,
• 1:30:47
  pretend play, storytelling, imaginary
• 1:30:48
  worlds, solving mysteries, finding
• 1:30:50
  things, little challenges, quiet games,
• 1:30:52
  cuddling, bedtime activities. That's so
• 1:30:53
  funny.
• 1:31:17
  right? Like the AI can make a can act
• 1:31:21
  like a dog, but it can't love you like a
• 1:31:23
  dog.
• 1:31:38
  Yeah. I mean, listen, I I again, I was
• 1:31:41
  somebody who was like an AI hater and an
• 1:31:43
  AI skeptic and like I was somebody who
• 1:31:46
  was also like, "Yeah, it's a stoastic
• 1:31:48
  parrot. They're just statistical
• 1:31:49
  machines." But like every time I would
• 1:31:51
  so often I ask it questions like this
• 1:31:54
  that require
• 1:31:56
  that require original thinking creating
• 1:31:58
  something that an idea that doesn't
• 1:32:00
  exist.
• 1:32:02
  And it doesn't and it doesn't and it
• 1:32:04
  does it like this, right? Like it it it
• 1:32:08
  has to have what I some it has to have
• 1:32:11
  some type of understanding
• 1:32:15
  of
• 1:32:16
  of games, right?
• 1:32:27
  I definitely want to try Invisible
• 1:32:28
  Animal Hospital. That sounds like a lot
• 1:32:30
  of fun.
• 1:32:42
  I'm drinking coffee and then I'm also
• 1:32:43
  drinking just ice water. Okay. All
• 1:32:45
  right. We got one more story. Oh, ask
• 1:32:48
  the AI if it understands anything it
• 1:32:50
  gave you or if we're just giving you the
• 1:32:51
  words it thought were the correct
• 1:32:53
  response.
• 1:32:55
  Yeah, that sounds kind of fun. Yeah,
• 1:32:57
  let's see.
• 1:33:28
  Okay, I asked it. What is your
• 1:33:29
  understanding of what the games entail?
• 1:33:31
  Or are you just giving me the words you
• 1:33:33
  think are the correct response?
• 1:33:37
  What you
• 1:33:39
  understand the games to be?
• 1:33:46
  Okay. And I want it to think a little
• 1:33:48
  bit.
• 1:33:49
  Actually, think really hard. I wanted to
• 1:33:51
  think really hard because now we're now
• 1:33:53
  we're talking about philosophy.
• 1:34:02
  Uh
• 1:34:05
  so it says game is an interactive
• 1:34:07
  experience which participants act in
• 1:34:08
  some sort of shared set of rules and
• 1:34:10
  actions.
• 1:34:11
  rules don't need to be written down.
• 1:34:12
  There doesn't have to be a winner.
• 1:34:14
  Right?
• 1:34:16
  Again, it thought about what a
• 1:34:17
  three-year-old was. Uh let me explain
• 1:34:22
  the wrong answer machine. The mechanic.
• 1:34:23
  It explains the mechanic,
• 1:34:26
  right? Uh that deliberately violates
• 1:34:28
  something child already knows. Create
• 1:34:29
  opportunity for the child to recognize
• 1:34:30
  the error and correct it,
• 1:34:35
  right?
• 1:34:36
  Talks about
• 1:34:39
  the button factory, right? It talks
• 1:34:40
  about so it's it's discussing and then
• 1:34:43
  it says why my response
• 1:34:46
  fell short.
• 1:34:50
  Uh okay as to why I'm simply I generate
• 1:34:54
  appropriate responses by processing
• 1:34:55
  learned patterns but that doesn't mean
• 1:34:56
  I'm restricted to reproducing plausible
• 1:34:58
  sounding descriptions. I can reason
• 1:35:00
  about the rules simulate how a sequence
• 1:35:01
  of interactions. Uh I have firsthand
• 1:35:04
  experience playing with three-year-old.
• 1:35:05
  I cannot personally know whether a
• 1:35:06
  particular child find the pros game
• 1:35:07
  delightful confusing or boring. The
• 1:35:09
  distinction I think matters whether an
• 1:35:10
  idea actually works when you attempt to
• 1:35:11
  play it. Can you explain it in seconds
• 1:35:13
  so the child understands? This is a high
• 1:35:15
  bar and I apply consistently.
• 1:35:18
  Are you challenging whether I understand
• 1:35:20
  the experience of playing a game or
• 1:35:21
  whether the activities I suggested
• 1:35:23
  qualify as games? Those are two
• 1:35:24
  different questions. Um I am trying to
• 1:35:29
  understand
• 1:35:30
  your thinking.
• 1:35:33
  You
• 1:35:35
  completed the task
• 1:35:38
  of generating games
• 1:35:43
  exceptionally well.
• 1:35:47
  Your thinking and what it is like to
• 1:35:51
  think as an AI.
• 1:35:55
  I'm just so curious. I'm I'm I know this
• 1:35:57
  is like not I should be making a video
• 1:36:00
  where we should be like covering stuff.
• 1:36:05
  Yeah, Sebastian. Yeah, it's almost like
• 1:36:07
  talking to Claude. You're going to end
• 1:36:08
  up
• 1:36:11
  like you're going to or open AI you're
• 1:36:12
  going to end up with these weird
• 1:36:14
  conversations
• 1:36:18
  and I know I can Yeah.
• 1:36:25
  Uh,
• 1:36:28
  what does it mean for AI to understand
• 1:36:29
  something rather than produce language
• 1:36:30
  that resembles understanding
• 1:36:33
  event games? I wasn't simply searching
• 1:36:35
  through a mental catalog of children's
• 1:36:36
  games or replacing details. Combining
• 1:36:38
  concepts, reason about how they
• 1:36:39
  interact, develop new scenarios. Yeah,
• 1:36:40
  there's definitely some reason, right?
• 1:36:42
  He says, "The invisible button factory.
• 1:36:43
  To construct the game, several ideas
• 1:36:44
  have to fit together. A threeo can
• 1:36:46
  understand that pressing buttons causes
• 1:36:47
  things to happen. Children enjoy
• 1:36:48
  controlling adults silly behavior.
• 1:36:50
  Imaginary buttons don't require
• 1:36:51
  equipment. Give the child the power to
• 1:36:52
  invent buttons and create possibilities.
• 1:36:54
  I don't specify in advance. Once a few
• 1:36:55
  buttons exist, the interactions create
• 1:36:57
  opportunities for surprising outcomes.
• 1:36:58
  These relationships matter. If you
• 1:36:59
  remove one, the game changes. That's a
• 1:37:02
  form of reasoning about an experience
• 1:37:03
  I've never personally had. I can model
• 1:37:06
  an experience without experiencing it.
• 1:37:08
  Uh, I can I suppose you ask about what
• 1:37:12
  happens when pressing a magic button and
• 1:37:13
  her father's nose and their father's
• 1:37:14
  nose starts quacking like a duck.
• 1:37:17
  I can reason about the likely
• 1:37:18
  consequences. I can anticipate that the
• 1:37:20
  second press might be funnier than the
• 1:37:22
  first.
• 1:37:24
  I have no sensory access to the room. A
• 1:37:26
  child's laughter, the emotional
• 1:37:27
  relationship between parent child. My
• 1:37:28
  account of the situation comes from
• 1:37:29
  learned representations and reasoning.
• 1:37:32
  Whether an AI could have any kind of
• 1:37:33
  subjective experience is an unresolved
• 1:37:35
  question. I wouldn't claim to have
• 1:37:36
  settled it.
• 1:37:39
  Linguistic understanding, structural
• 1:37:40
  understanding, experiential
• 1:37:41
  understanding.
• 1:37:44
  Uh I can represent the relationships in
• 1:37:46
  that imagined scenario and reason about
• 1:37:48
  what would happen if something changed.
• 1:37:49
  But that I shouldn't assume that the
• 1:37:51
  representations involved resemble your
• 1:37:53
  mental pictures, that there's a
• 1:37:54
  subjective experience accompanying them.
• 1:37:57
  We may be able to arrive at similar
• 1:37:58
  conclusions through different processes.
• 1:38:02
  That is really interesting.
• 1:38:07
  Yeah.
• 1:38:12
  Yeah. It's it's definitely more than a
• 1:38:14
  next token predictor. I really believe
• 1:38:15
  that. And not believe it. I I it it it
• 1:38:18
  evidently is because it can reason.
• 1:38:27
  Yeah. All right. Well, this is a [ __ ]
• 1:38:30
  Well, this is a [ __ ] acid trip. So,
• 1:38:32
  let's let's talk about let's actually
• 1:38:34
  let's actually pivot.
• 1:38:39
  All right. Let's This is crazy.
• 1:38:43
  It's not exactly a secret that AI has
• 1:38:45
  been blowing up in the news, but a
• 1:38:49
  shocking tale of espionage seems to have
• 1:38:52
  erupted inside of Open AI. And we're
• 1:38:54
  going to talk about who well stands to
• 1:38:56
  gain the most from getting inside of
• 1:38:59
  Open AI and what's so crazy about it.
• 1:39:02
  Let's take a look. So, this is a wild
• 1:39:05
  story, guys, because a Saudi national
• 1:39:07
  was charged with planting a spying
• 1:39:09
  device in an OpenAI executive conference
• 1:39:12
  room. A Saudi national working as an
• 1:39:14
  engineer for OpenAI was charged on
• 1:39:15
  Tuesday with secretly bugging an
• 1:39:17
  executive conference room at one of the
• 1:39:19
  OpenAI's buildings in San Francisco.
• 1:39:22
  Federal prosecutors alleged that Abdul
• 1:39:24
  Raman Alonsen, 35, inserted a
• 1:39:27
  surreptitious audio recording device
• 1:39:28
  into a USB port in the back of a
• 1:39:30
  television in the room. He appeared in
• 1:39:31
  federal court Tuesday is charged with
• 1:39:32
  using or attempting to use a device to
• 1:39:34
  intercept oral communications carries a
• 1:39:36
  maximum sentence of 5 years and a
• 1:39:37
  $250,000 fine. Prosecutors said the
• 1:39:40
  conference room host meetings discussing
• 1:39:42
  sensitive proprietary research products
• 1:39:43
  and business plans as well as government
• 1:39:44
  engagements and commercial
• 1:39:45
  relationships. According to the criminal
• 1:39:47
  complaint, OpenAI staff found the device
• 1:39:49
  on September 30th, just two weeks ago,
• 1:39:51
  around 2 days after it had been
• 1:39:52
  installed. The recordings on the device
• 1:39:53
  were encrypted and the device itself was
• 1:39:55
  wrapped in toilet paper. There's
• 1:39:56
  literally a picture of the device
• 1:39:58
  inserted into a USB uh sticking out the
• 1:40:00
  back of the TV. Nothing sus about that.
• 1:40:02
  And there's the device itself. Very
• 1:40:04
  small, right? Alphons joined last year
• 1:40:07
  in July. According to prosecutors,
• 1:40:09
  security footage showed him near the
• 1:40:10
  room several times before the device was
• 1:40:11
  discovered. He was not authorized to
• 1:40:12
  enter the room or attend meetings being
• 1:40:14
  held there. Alphonsen used an internal
• 1:40:16
  productivity tool to search for building
• 1:40:18
  addresses, meeting room calendars, and
• 1:40:20
  locations of leadership and exec
• 1:40:21
  meetings before the device was
• 1:40:22
  installed. A chatbot associated with
• 1:40:24
  Alfons's wife's account
• 1:40:26
  was found to have submitted prompts
• 1:40:28
  specifically related to the building
• 1:40:29
  installing a remote accessing the
• 1:40:30
  recording device. Security footage
• 1:40:32
  captured a week after the device was
• 1:40:33
  discovered show Alons entering the
• 1:40:34
  conference room and apparently checking
• 1:40:36
  behind the TV. That day, Open Security
• 1:40:37
  found a bag he left unattended
• 1:40:39
  containing his wallet ID and a second
• 1:40:40
  similar recording device. Now, this is
• 1:40:44
  crazy for a bunch of reasons. Uh first
• 1:40:48
  off, it's a
• 1:40:52
  uh one, well, before we talk about what
• 1:40:55
  exactly he searched his wife's uh
• 1:40:57
  chatbot for, um but also who I think is
• 1:41:00
  behind it, I want to mention guys that
• 1:41:02
  competing in the AJI can already feel
• 1:41:04
  kind of overwhelming and as a human
• 1:41:06
  being, you know, we may not be able to
• 1:41:07
  solve physics problems, but we can we
• 1:41:09
  can work hard in the real world. And if
• 1:41:11
  you want to push it to your limits,
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  Strike's got you covered. Don't waste
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  your money on these. Five bucks a pop at
• 1:41:16
  a gas station, you can get the same
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  caffeine, zero sugar in one piece, a
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  single piece of five gum or five gum,
• 1:41:23
  excuse me. Oh my god. Strikegum. Use
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  promo code holiday25
• 1:41:30
  to get 25% off your order.
• 1:41:33
  Go to strikegum.com.
• 1:41:35
  Don't be dumb. Just pick some up. Now,
• 1:41:38
  here's a kind of a trip. This is from
• 1:41:39
  Twitter, so take it with a grain of
• 1:41:40
  salt. But a chatbot tied to Alon's
• 1:41:42
  spouse, which shared identifiers with
• 1:41:44
  his own account, submitted prompts
• 1:41:45
  between September 24th and September
• 1:41:47
  30th about building, installing,
• 1:41:48
  obscuring, and remotely accessing a
• 1:41:50
  recording device. Queries included,
• 1:41:52
  build a continuous audio recorder,
• 1:41:54
  encrypt the SD card. Right. And the
• 1:41:57
  account asked about a specific device
• 1:41:58
  that was later found, including its
• 1:41:59
  unique MAC address.
• 1:42:02
  Open engineer reportedly, according to
• 1:42:04
  this random tweet with an anime uh
• 1:42:06
  profile picture, that he was making a
• 1:42:08
  million dollars a year. used wife's
• 1:42:09
  chatb account to ask how to bug open
• 1:42:11
  AAI. So the question then you're left
• 1:42:14
  with is why? So
• 1:42:17
  I have a couple of theories. The first
• 1:42:19
  is that this was a foreign actor
• 1:42:22
  conducting oper conducting espionage on
• 1:42:25
  behalf of someone else. And they may
• 1:42:28
  have been offered an incredibly large
• 1:42:29
  sum of money to obtain proprietary data
• 1:42:33
  about the activities going on inside of
• 1:42:36
  OpenAI.
• 1:42:38
  And my first thought is China.
• 1:42:40
  Reportedly, China is working at a
• 1:42:42
  breakneck pace to try to keep up with
• 1:42:45
  American labs. uh and reportedly Chinese
• 1:42:48
  labs now trail the US frontier models by
• 1:42:50
  just seven months and uh by 39 different
• 1:42:54
  benchmarks. Um the frontier math and
• 1:42:56
  software engineering uh models the
• 1:42:59
  frontier models from deepseek are
• 1:43:02
  uh just seven months behind American
• 1:43:05
  frontier models. That is crazy. uh
• 1:43:10
  and again the
• 1:43:15
  uh you know Chinese models again trailed
• 1:43:18
  by the US frontier by an average of 7
• 1:43:19
  months since 2023. The gap ranging from
• 1:43:22
  as little as four months to as much as
• 1:43:23
  14 depending on the model and the
• 1:43:25
  metric. First Chinese model to beat GBT4
• 1:43:27
  did it in May of 2024, 14 months after
• 1:43:29
  GPT4 shipped. No Chinese model has yet
• 1:43:32
  matched OpenAI's 03 model released in
• 1:43:34
  April of 2025. But the crazy part is
• 1:43:38
  again that the Chinese do not want to be
• 1:43:40
  at a disadvantage. Again to them it is
• 1:43:43
  like an arms race uh like the nuclear
• 1:43:45
  race. When the US had the bomb and was
• 1:43:48
  the only country with a nuclear bomb um
• 1:43:50
  it was a all hands-on deck situation for
• 1:43:53
  the Soviets because as long as the US
• 1:43:54
  had the bomb and the Soviets didn't, the
• 1:43:56
  US could make a could could threaten
• 1:43:59
  Soviet interests in ways they could not
• 1:44:01
  match. The Chinese never want to be in
• 1:44:02
  that situation. They see obviously the
• 1:44:04
  AI the military applications of a
• 1:44:06
  frontier model um not just the econom
• 1:44:09
  but the economic ones as well and they
• 1:44:11
  absolutely want to sit on the frontier
• 1:44:13
  with American companies. Um now
• 1:44:17
  the the
• 1:44:21
  so on one hand it's possible this guy
• 1:44:24
  Saudi national could have been
• 1:44:25
  approached by an intelligence service
• 1:44:27
  like the Chinese or maybe even the Saudi
• 1:44:29
  intelligence services and said listen
• 1:44:31
  the Chinese would be really interested
• 1:44:34
  in helping us and we could really
• 1:44:36
  extract a lot of concessions from China
• 1:44:38
  if you could give us insider information
• 1:44:40
  about America's frontier model companies
• 1:44:43
  like OpenAI
• 1:44:45
  And
• 1:44:47
  I think that is uh that is very
• 1:44:50
  possible, right? But what I want to
• 1:44:53
  point out is that some of this stuff is
• 1:44:54
  kind of amateur and we're talking about
• 1:44:57
  commercially available listening
• 1:44:58
  devices. We're talking about disguising
• 1:45:00
  them in toilet paper. We're talking
• 1:45:01
  about chatting with an LLM about it,
• 1:45:05
  which is which is dumb in its own right.
• 1:45:08
  And that is not something that a
• 1:45:10
  professional intelligence service would
• 1:45:12
  do. But that doesn't matter because
• 1:45:13
  professional intelligence services are
• 1:45:15
  almost never the people doing the
• 1:45:17
  collection themselves. Professional
• 1:45:19
  intelligence services are almost always
• 1:45:21
  recruiting proxies that are connected
• 1:45:24
  that it's not suspicious for them to be
• 1:45:26
  in there. And the truth is that a real
• 1:45:29
  intelligence service would almost
• 1:45:30
  certainly have a much more undetectable
• 1:45:33
  listening device that they would ask
• 1:45:36
  they would pass along to the engineer
• 1:45:38
  and say, "Listen, we want you to put
• 1:45:39
  this sticker onto behind a TV." Like a
• 1:45:46
  commercially available continuous
• 1:45:47
  listening device, one is not necessary.
• 1:45:49
  It could be activated uh when when a
• 1:45:51
  meeting is taking place. That would be
• 1:45:53
  that would be right there. But also like
• 1:45:56
  a very small listening device um would
• 1:45:59
  be much more common. Uh again
• 1:46:08
  like
• 1:46:12
  I mean some of these micro listening
• 1:46:14
  devices are [ __ ] this is commercially
• 1:46:17
  let let me give you an idea. This is
• 1:46:18
  commercially available on Amazon and
• 1:46:20
  it's like the size of a thumbnail. Okay.
• 1:46:23
  So if that's what you can buy on Amazon,
• 1:46:26
  imagine what you can buy what the CIA
• 1:46:28
  and Chinese MSS have access to, it's
• 1:46:31
  probably next level. So that makes me
• 1:46:33
  think this guy was an actual amateur,
• 1:46:35
  which makes me think either one, he was
• 1:46:37
  trying to spy on OpenAI in order to
• 1:46:39
  defect with the information to another
• 1:46:41
  company or uh he was and this this I
• 1:46:46
  think is actually the most likely theory
• 1:46:47
  because it was so [ __ ] stupid. Um, I
• 1:46:50
  think he was trying to beat Poly Market.
• 1:46:53
  I think he wanted to know about OpenAI
• 1:46:55
  um activities
• 1:46:57
  uh before they went down, before they
• 1:46:59
  happened. And he wanted he probably
• 1:47:02
  wanted to place bets on Poly Market in
• 1:47:04
  order to make a make even more money,
• 1:47:07
  which is stupid. You make a million
• 1:47:09
  dollars a year, dog. How much more money
• 1:47:11
  you need? But and you're Saudi. You're
• 1:47:15
  you're you're Saudi, dude. You get Saudi
• 1:47:17
  money. work at OpenAI a couple years and
• 1:47:19
  then go work for Riad. I'm sure they'll
• 1:47:23
  throw all the money you want at at them.
• 1:47:24
  Like it's very shortsighted, but I never
• 1:47:27
  underestimate um
• 1:47:30
  I never underestimate engineers ability
• 1:47:32
  to be stupid. Like really smart
• 1:47:34
  engineers that are also like
• 1:47:35
  unbelievably dumb. If you've ever
• 1:47:37
  interacted with tech guys, you
• 1:47:38
  understand that intuitively. But I think
• 1:47:41
  the larger theme here is that you have
• 1:47:43
  to understand that this is national
• 1:47:45
  security research. This is like the
• 1:47:47
  Manhattan project but not a secret. Um,
• 1:47:50
  again, like the Manhattan project,
• 1:47:52
  before you built a bomb, you solved a
• 1:47:54
  bunch of complex math problems, which is
• 1:47:58
  what
• 1:47:59
  OpenAI recently did. And now they
• 1:48:03
  reportedly, some reporting indicates
• 1:48:05
  they're turning their attention to
• 1:48:06
  unsolved highle theoretical physics
• 1:48:08
  problems, which are just
• 1:48:11
  just slightly
• 1:48:13
  slightly more applied mathematics.
• 1:48:17
  And you would have to be crazy if you
• 1:48:20
  think the Chinese MSS is not doing every
• 1:48:23
  single [ __ ] thing in their power to
• 1:48:26
  get all the information, technical data
• 1:48:28
  about OpenAI anthropic and other
• 1:48:30
  American frontier labs. Um, I could
• 1:48:34
  basically guarantee it. That's how sure
• 1:48:36
  I am. And if you think the Russians
• 1:48:39
  aren't doing the same thing, they would
• 1:48:41
  love to get their hands on something
• 1:48:43
  this powerful. It is It is too powerful.
• 1:48:45
  Um, and
• 1:48:49
  like so I suspect that this is not going
• 1:48:52
  to be the first time. And if it's a real
• 1:48:54
  government hack and leak oper or a real
• 1:48:57
  government operation, it's probably way
• 1:49:00
  more complex. Like honestly, the Chinese
• 1:49:02
  would probably just hack into the TV.
• 1:49:05
  Um, anyway guys, that's all I had. Hit
• 1:49:08
  subscribe. Thanks to John, Kevin,
• 1:49:10
  Michael, Rob, Thomas, William, Al, and
• 1:49:12
  all the tentor folks. We really
• 1:49:13
  appreciate you guys. And uh we're going
• 1:49:15
  to catch you uh in the next one.
• 1:49:18
  Subscribe.
• 1:49:19
  All right. Dewey, thanks to Five
• 1:49:20
  Canadian for movies like Enemy State.
• 1:49:22
  How far and powerful did intelligence
• 1:49:23
  communities have gotten? What are their
• 1:49:24
  capabilities that we're not aware of? Uh
• 1:49:27
  big dog. Unfortunately, I am also
• 1:49:29
  unaware. Uh I never got read into
• 1:49:31
  surveillance programs. So, I don't know.
• 1:49:34
  Um
• 1:49:36
  I don't know. I know it's not a really
• 1:49:39
  satisfying answer.
• 1:49:41
  Um, sometimes, honestly, I have been
• 1:49:43
  more shocked by how stupid government is
• 1:49:46
  in terms of its ability to track people
• 1:49:48
  and and things. Um, they're way more
• 1:49:50
  stupider than they are uh sophisticated.
• 1:50:02
  Yeah. Greed never ends. Yeah.
• 1:50:11
  All right, guys. I'm going to get out of
• 1:50:13
  here. It's almost 4, so I I got a bunch
• 1:50:15
  of work to do still. Jesus, how is it
• 1:50:17
  almost 4 here? All right.
• 1:50:20
  Um,
• 1:50:22
  but thank you guys. I'll see you
• 1:50:23
  tomorrow. Peace out. Cheers.