Latest / Nonsense with cj little and Jeff Parker / HEADLINES: Olympic GPT, Border Scans, & The Ad-Free AI War

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HEADLINES: Olympic GPT, Border Scans, & The Ad-Free AI War · Nonsense with cj little and Jeff Parker

0:00
The challenge for Nathan's hot dog eating is you can't vomit.
0:02
Yeah, while you're still on camera.
0:04
Yeah, once you get behind where people can't see.
0:05
It they don't care. Sure, do whatever you want.
0:07
They know you're going to puke at that.
0:08
Point. Yeah, yeah, Chowder.
0:09
Everywhere. Absolutely.
0:09
If you puke on camera, you're disqualified.
0:11
There's a second set of cameras, the only fans feed is what picks
0:14
that up, and that's where they make all their margins quiet
0:17
please. The vomit Cam, The barf bucket
0:19
3. The Vomit Vessel 2.
0:31
The Apple Company presents a truly terrible podcast.
0:33
Welcome to Nonsense season 4, episode 10.
0:35
I'm Jeff Parker. I'm CJ Little.
0:37
This is our take on the week's business, tech and entertainment
0:39
headlines, this time inside the high tech revolution of Olympic
0:43
broadcasting. Forget.
0:44
AI in 2026, we finally get a curling camera, Jeff.
0:47
Canada, rejoice the rise of mobile fortify and the end of
0:50
anonymity. Wait, is that like the
0:51
competitor to mobile insurer? Mobile Fortify.
0:54
Yeah, it's like a protein shake the elderly can take while
0:56
while. Traveling, hopping mad.
0:58
Open AI blast Dishonest Super Bowl satire.
1:01
Altman said. Look, there's only room for one
1:03
dishonest AI company, and we were here first.
1:05
Also a big story later this week beyond lithium, the new battery
1:09
tech that just might kill range anxiety.
1:11
I mean, nothing's going to kill range anxiety.
1:12
Well, you got to put gas into the battery and then that would
1:15
kill range anxiety. How was your week going, Sir?
1:17
Oh. Man, my week is amazing.
1:19
I slept great on Sunday. I discovered something.
1:22
Yeah, better than a trifecta of like a cocktail of booze,
1:26
melatonin and Ambien. Something we always recommend.
1:29
Yes, super. Bowl 60.
1:31
I fought so hard to stay awake. That was a dull.
1:34
One, I mean, it wasn't like amazing defense.
1:37
It just doesn't make for a good game.
1:38
No, I was a bored to tears. In a game where the where a
1:42
kicker should be the MVP, that's a dull game in the third.
1:45
Quarter I was literally rooting for there to be like record set.
1:49
I was like, I just don't want to see any touchdown scored in this
1:51
game. Sure at all.
1:51
Like at this point I'm already in for a 2/3 of the game now.
1:55
Like, let's just make something that I can be like, Oh yeah, I
1:56
observed the boringest game ever where they only scored with.
1:59
Kickers or a shutout. You know, you wanted to see us
2:01
do the very first Super Bowl shutout Totally, but something.
2:03
Like that, I'm sure there was some some point shaving
2:07
something something going on there that is too smart for me.
2:10
But I, I, I found only really two things interesting.
2:12
One, yes, that the NFL somehow managed to cram this amazing
2:16
entire basically Bad Bunny concert into the halftime of the
2:19
Super Bowl. I don't even know how the
2:20
logistics. There's like a truck out there.
2:22
They had sugar cane at people inside Sugar Hurricane like a
2:25
bodega. It was just into Pedro Pascal,
2:27
just leisurely hanging out in the front of the bodega.
2:29
It's always amazing stuff. They can.
2:32
Say, do in that transition time this, they build like a city in
2:36
about four minutes. Yeah.
2:37
And. Someone doesn't affect the
2:38
field. I'm just like, how do you get
2:39
the truck out there without like, like putting in roots and
2:41
like the truck has no engine. They got to push it out here.
2:43
Is it light? Like what?
2:44
What did you do? Are the tires full of helium?
2:46
I had no idea. The other thing that oppressed
2:48
me was that I somehow was able to win 75% of the value of my
2:53
Super Bowl square pool. Did you do that?
2:55
So I forgot to click the link and buy the squares cause life.
2:59
And literally 10 minutes before kickoff, yeah, I wasn't going to
3:02
the party because I I was staying home with the kids to
3:04
like literally 10 minutes before kickoff.
3:06
I'm like, oh crap, I need to go buy squares.
3:08
And there were were were like 17 left and I'm like, I'm going to
3:11
just buy all the squares just so that it's full.
3:13
Sure, sure. Otherwise it's weird.
3:15
If it's not that, you know, square doesn't pay out or square
3:17
pays out sometimes finals buy them all.
3:19
I don't really care. Like I'm just supporting the
3:21
party. I then could not watch the game
3:23
live because I have children that decided they wanted to go
3:26
outside and and go bike riding and I'm not gonna tell them no.
3:29
So I watched the game. Late.
3:30
And then I I didn't check until the next morning to see who won.
3:33
So I had terrible numbers. I'm like, I'm not gonna win
3:35
anything. Sure.
3:36
And I won 1/2. Time and the the final score so
3:39
everyone's really very nice I. Was even.
3:40
There they were. Weird numbers anyway, they were.
3:42
Terrible numbers. I had terrible numbers to begin
3:44
with. I'm like, these are terrible,
3:45
terrible numbers. It was fun.
3:46
I, I mean, I enjoyed it. I guess I just thought the game
3:48
was, was super boring. You just slept through.
3:50
I couldn't imagine being there. Like, I't typically pretty bored
3:53
at Pro Football games anyway, but that one just looked like a
3:56
snoozer. I had no complaints.
3:57
It was a reasonably How about you?
3:58
How was? Yours I was fine.
3:59
I also like you. I watched the Super Bowl into a
4:01
Super Bowl party and had a fantastic time.
4:03
Even though the game was, as you say, super dull.
4:05
The halftime show was fun. The couple in the Bad Bunny
4:08
halftime show actually got married.
4:10
It was a real couple. Oh, it's amazing.
4:12
I was wondering story they had invited Bad Bunny to their
4:15
wedding and instead he said, I'm doing the Super Bowl.
4:17
Why don't we get you married during the Super Bowl?
4:19
And so they have this wedding that occurs during and it you
4:22
see it for a split second. He actually signed their
4:24
wedding, getting license as one of the witnesses after this.
4:27
Did he really? Oh, he is really cool.
4:28
Oh, it's amazing. Yeah.
4:29
Really sweet. It made history as the first
4:30
several halftime show performed almost entirely in Spanish.
4:33
I mean almost entirely is is almost as isn't doing a lot of
4:37
work there because it was pretty much all Spanish.
4:39
So I think 3 words. That was pretty cool.
4:42
I mean, I thought that was just, it was.
4:43
So the whole thing was just delightfully festive and fun and
4:47
joyous and all those things. Oh wait, hold on, I don't.
4:49
I'd say joyous. There were several times where
4:51
he was up way too high without being like clipped into a.
4:55
On the telephone pole, yes. Exactly, we all said right too.
4:57
We said he could fall. He is way.
4:59
Too high to not I am such. An old man, I was just like, oh,
5:02
he's good. I agree, don't do.
5:03
That I agree, it's crazy and, and, but there could have been
5:06
airbags down below. I have no idea how any of that
5:08
worked. Like the Olympic ski suits.
5:10
Yeah. You know, Lindsey Vonn, the ski
5:11
suit she airbag on is airbags. Incredible.
5:14
And somehow there's some little there's little sensors inside of
5:16
this thing and it knows when you're out of control.
5:18
Yeah, it inflates in milliseconds.
5:20
Literally can inflate before you even hit the ground.
5:22
I don't see you, you or I ever wearing one of those.
5:24
But they do make a version of that suit.
5:26
This is true for the elderly when they fall down.
5:28
Yeah. And it inflates to soften the,
5:30
the, the, the like the blow to the landing on the floor.
5:33
Yeah. And I feel like you and I should
5:34
be wearing those even, like, right now while we're recording
5:36
the show. I feel like we are squarely in
5:38
the window. So you got to ask yourself, why
5:39
did Bad Bunny even have those power poles?
5:42
Yeah, in the middle of the halftime show, and he was
5:44
protesting the Luma Energy, the blackout power outages in Puerto
5:48
Rico. Literally, like on Christmas
5:49
Day. Yeah, they had a blackout.
5:51
Yeah, that, that was my first thought when I saw it, 'cause
5:52
they had them like sparking and stuff too, and they had line
5:54
workers off. I mean, it was, it was really
5:56
neat. I was just nervous for the dude.
5:58
Yeah, being up that high. And then Bad Bunny proudly waves
6:01
the light blue version of the Puerto Rican flag, which was
6:03
great. That flag was effectively banned
6:05
out of the gag law, which made it illegal to display the flag
6:07
or sing patriotic independence tunes on the island.
6:09
But good for him, That was great.
6:11
First time a USC quarterback has started in the Super Bowl.
6:14
What the CSC winning a game on TV?
6:16
Yeah, sure. An adjacent win for USC.
6:19
Not a direct win, but an adjacent win.
6:21
I was more excited that it was darn old just because that that
6:25
dude I feel like everybody sort of gave up on.
6:26
Yeah. And I think it was cool to see
6:28
him up there and see him win a Super Bowl.
6:29
It was was obviously awesome. Although I did.
6:31
I don't know anything about these two teams, but they showed
6:33
a picture of the quarterback. The the Patriots quarterback.
6:36
Yeah. 10 years previous when he was at the Super Bowl with his
6:39
dad. Oh.
6:39
Yeah, that was great that. Was great and I was like, oh
6:41
man, this is like the how, how can you not like that is the
6:44
coolest thing ever. He didn't look all that much
6:46
older. So that was the first Trojan to
6:48
start as quarterback? Yeah.
6:50
In the Super Bowl, Yeah. How many, if any, do you think
6:53
UCLA has? I don't know.
6:54
The answer to that How many? So you want the answer to be
6:57
like -1 right? I mean, you want it to be
6:59
basically. Zero.
6:59
Obviously you're bringing it up. Yeah, yeah.
7:01
As it turns out, much disappointment.
7:03
The answer is 20. OK.
7:05
Troy Aikman and Bill Kilmer. Oh yeah, of course, of course.
7:07
But who has the most? This is This is the trivia
7:10
question. Who at what school is the most
7:11
starting quarterbacks in the Super Bowl?
7:14
Arguably right behind UCLA? Notre Dame.
7:15
Arguably right behind Notre Dame.
7:16
Notre Dame has three Joe Montana, Joe Heisman and Daryl
7:20
Lamonica. There is one school that has
7:22
more than that. Who?
7:22
Cal. Oh, was that right?
7:23
Yeah, Aaron Rodgers, Jared Goff, Craig Morton and Joe Cap, 4 from
7:27
Cal, which is pretty crazy. Yeah, only three schools have
7:30
started three, and only one school started four.
7:32
Thought that was pretty. Cool, and we have now started.
7:34
One, we have now started 1 so we were on the list.
7:37
We're on the board. We're finally on the.
7:38
Board. And that is because of Lincoln
7:41
Riley. How so?
7:42
Not in any way, shape or form. OK, that's what I thought.
7:44
I'm just trying to. Get.
7:44
I thought you had. Something there?
7:45
No, no, no. It happened before he was coach.
7:48
He called a guy who did it and who got us.
7:50
Yeah, I mean, at this point I'm I'm going to take up flag
7:53
football. Flag football's going to be in
7:54
the Olympics. I saw.
7:55
I'm kind of excited. About it, I'm really excited to
7:57
see how that comes down. I really think that's
7:58
interesting. That sounds like it's gonna be
8:00
really fun, yeah. There's some really fun Olympic
8:01
sports this winter and I'm really excited about summer in a
8:04
couple of years in our in our back. 28 Sure, sure, sure.
8:06
Yeah, as happens at every Super Bowl, this is not a a shocker.
8:09
I'm sure I ate yeah, I ate way too much.
8:11
It's. Not Thanksgiving.
8:12
What you eat too much? For me, the Super Bowl is like
8:14
Thanksgiving, only I eat more. Yeah, but the food was really
8:16
good and we had a. Good time in chicken wings.
8:18
Shall we get to our? Headlines.
8:19
I mean, I think so. How AI and drones are
8:22
reimagining the Winter Olympics You've been watching the Winter
8:25
Olympics, haven't you? Yeah, but like, they should just
8:27
ask AI to reimagine the Olympics.
8:29
Think about how cool that would be.
8:30
Like if you had an open claw for Olympics, Sure, there's just
8:33
like, OK, two guys on fire on skis, jump over the Grand
8:37
Canyon. You're like, wait.
8:38
What they actually change events?
8:40
You actually give the AIA chance to change your events.
8:42
Yes, and everybody has to compete against one AI in their
8:44
event like a like a Boston Dynamics autonomous robot robot
8:48
that. Never falls down and never
8:50
breaks legs, you know? Yeah, sure.
8:51
The 2026 Winter Olympics and Milano Cortino are redefining
8:54
this spectator experience through a high tech overhaul of
8:57
sports broadcasting. Artificial intelligence leads
8:59
the charge, powering real time 360° replays and automated
9:03
highlight generation to capture every crucial moment instantly.
9:06
For the first time, curling fans can track stones.
9:09
You made a joke about this earlier.
9:10
Yeah. With AI driven overlays while
9:12
first person viewed drones plunge viewers into the high
9:15
speed intensity of bobsleigh and luge, behind the scenes, the
9:17
shift to cloud based virtual broadcasting vans is slashing
9:20
power consumption by 50%, signaling A greener future for
9:24
mega events. From cinematic storytelling to
9:26
Olympic GPT providing instant stats, the 2026 Games aren't
9:29
just being watched, they're being experienced through an
9:32
immersive, data rich lens that brings fans closer to the ice
9:35
than ever before. Yeah, I mean nothing says oh man
9:38
that luge was amazing than a spreadsheet that pops up
9:40
afterwards. I love seeing the data.
9:43
Wow, but the drone stuff. As someone who flies drones, let
9:46
me tell you how cool those FPV drone shots are.
9:49
I hear the drones. Yeah, I, I.
9:51
Whipped my head around. I wasn't even watching it was it
9:53
was on TV behind me. I hear the drone.
9:54
I whip my head around it cuz I know I'm gonna see something
9:57
really cool. First of all, I think this is
9:58
super cool, and I am absolutely amazed at how much tech they
10:02
push into all sporting events, but especially the Olympics.
10:04
Yeah, I really don't even want to try to imagine the production
10:07
effort that goes into this thing because it just sounds like a
10:10
lot. And it's not like you're doing
10:11
it. Sure, week after week.
10:12
Like, you know, I feel like the NFL directors get into a rhythm
10:15
and the pressure gets into a rhythm.
10:16
And here you're just like, OK, this is all gonna happen in the
10:18
next two weeks. All brand new.
10:19
Yeah, which is crazy. They do it.
10:20
Four years to plan for it. It's not like it suddenly sneaks
10:23
up on. Yeah, but there's planning for
10:24
and then you get there and one of the guys is like, did you
10:26
order the Internet? And they're like, Nope.
10:29
Oh, oops. Like what?
10:31
You know, like it's hard to not do it.
10:33
They've proven out some of this tech I think at the Dakar Rally,
10:35
which is pretty cool. Yeah, a couple months ago or
10:37
last month, but but I want to .1 thing out that I have a.
10:40
Just a. Little bit of a problem with,
10:42
yeah. And I've read this now in a
10:43
couple articles, including this one that we're citing, which is
10:45
they're talking about these, you know, these virtual broadcast
10:47
vans slashing power consumption by 50%.
10:49
And I'm like sure, sure. OK, explain exactly what you're
10:52
talking. About I think what they're doing
10:53
is they're, they're, they're moving the actual production
10:56
process. So the editing the.
10:57
Switching van and the. Switching all of that gets
11:00
basically moved into the cloud, right?
11:01
So now you're just streaming content into the cloud and
11:04
they're editing on the cloud. Great, that's cool.
11:05
It may save power. I don't know if it's 50%, but it
11:08
might. Cool.
11:08
Glad you singled that out. Sure.
11:09
All the other crap you're doing is using 800% more power than
11:13
you have in previous years. You literally have Olympic GPT.
11:16
There are three towns in Norway that don't have lights for the.
11:19
Next day dark so you. Can power.
11:21
Olympic GPT, right? So I'm just like.
11:23
OK, you highlight the power and the van savings, but meanwhile
11:27
you're doing all this other stuff.
11:28
That's by the way, the vans probably weren't using that much
11:30
power. Exactly, exactly so it feels.
11:33
Like, OK, yeah, 50%. 'S a real number of a very small
11:35
number, yet you've made these whole new categories that are
11:38
much, much bigger. But it's very cool.
11:39
I'm very intrigued by this. The the thing that I find most
11:42
striking about really all these sporting events, but especially
11:44
the Olympics, they just keep raising the bar every two years
11:47
higher and higher, right, 'cause it wasn't exactly low when it
11:50
was in Paris, right? Not too long ago, right?
11:52
And you're like, whoa, like they just keep notching it up.
11:55
And I think that's impressive. Also don't hurt Snoop.
11:58
Like he's not a young spry man. What are you doing pushing him
12:02
down on like? A He was an athlete as a kid.
12:03
Yes, that was 70 years ago. No, don't.
12:06
That'll screw with Snoop. Like he just, I just, I love
12:09
that he's doing it by the way, and I love that.
12:10
This guy always so fun and he seems game for anything.
12:13
And every time the Olympics hits and he's and he's being the
12:16
Olympic, you know, sort of like NBC, like face of the Olympics
12:20
for them, There's always some set of tweets that appear where
12:22
someone's like, yeah, I had this long conversation with my mom
12:24
how much she loves watching Snoop in the Olympics.
12:27
And then I remind her that she grounded me for listening to his
12:30
albums 20 years ago, which I always find amusing, that
12:33
juxtaposition of the two. But it's very cool.
12:36
If you're not watching the Olympics at home, you should.
12:38
Even if you're not into the sports, just watching the the
12:40
camaraderie and the competition and the production is is pretty
12:43
cool. The tech changes so much.
12:45
When I was at USC, the Olympics for the 84 Olympics were coming.
12:48
Yeah. And they built the McDonald's
12:50
swim Stadium, which was as enormous swim pool complex with
12:54
diving and all the rest of it. They don't build that anymore.
12:56
Yeah. They don't do that anymore.
12:57
Yeah. What they do now is they erect
12:59
this enormous aquarium. Yeah.
13:01
So that you can see through it from every angle and have
13:03
cameras. It's absolutely.
13:05
Were you so cool? Now were.
13:06
You there for the 84 Olympics? Yeah.
13:07
Wow, that had to be an awesome experience.
13:10
It was pretty incredible, yeah. Was the village on campus?
13:13
Yes. Oh, as if I couldn't get any
13:15
more jealous of you. That had to be incredible.
13:17
Yeah. Meanwhile, I'm on 12 lists.
13:19
Try to get a ticket for a thing so I can maybe see somebody 300
13:22
yards away roll a bike down a hill 'cause it's all packed, no?
13:25
ISIS new face scanning app brings the border to the city US
13:28
immigration enforcement is entering A biometric checkpoint
13:30
era with Mobile Fortify, a powerful smartphone app
13:33
transforming how ICE and CBP operate.
13:36
Originally designated for border crossings, the tool is now being
13:39
deployed deep within the US interior, allowing agents to
13:41
identify individuals on the street simply by pointing a
13:44
phone at their faces. I mean, this is like literally
13:47
the Pokémon app gone awry. That's the problem.
13:50
We train these guys how to do this by playing Pokémon.
13:53
But now if you're like you captured a plus one, not what we
13:56
want. Are you taking a photo just for
13:58
your tourism sake or are you identifying people who are
14:01
standing here protesting? Yeah.
14:02
By instantly cross referencing scans against massive federal
14:05
databases and potentially commercial data, the app
14:07
provides what officials call definitive identification.
14:10
However, critics warn of a chilling expansion of
14:12
surveillance. Beyond privacy concerns, the
14:14
technology faces intense scrutiny over accuracy.
14:17
Reports of misidentification and racial bias suggests that a
14:20
single glitchy scan can now lead to the wrongful detention of
14:23
immigrants and U.S. citizens alike.
14:25
Well. Technically, it doesn't have to
14:26
be a glitchy scan. You can get what you think is a
14:28
good picture and still get LED down a pass.
14:30
Sure. And by the way, none of this is
14:32
a surprise. I've been using Face ID tech now
14:35
for over 10 years. I've spoken about it publicly at
14:38
large events. It's, it's really cool, but you
14:41
have to know it's, it's constraints, limitations, and it
14:43
seems like it's very hard to gather information about this
14:47
because there's not a lot of it. It's not very transparent.
14:49
So you're basically reading what some, some agencies have been
14:52
able to report on it. So you know, it's, it's bits and
14:55
starts that you can try to figure it out from, but it seems
14:57
like this app started or this program started with a
15:00
reasonable intent, which was we think this person might be one
15:05
of these people. When you are now trying to map
15:07
the entire public into that, you're going to have more false
15:10
identifications. That's the difference.
15:11
Of course, it's the difference between I have a person of
15:13
interest already because something else told me they're a
15:16
person of interest. Yes.
15:17
And now you want one additional piece of information.
15:19
Yes. And it serves some modicum of
15:21
purpose that way, right? But they're not using it that
15:22
they're using the inverse of. It the mass surveillance that
15:25
doesn't work a new thing? Because the problem is now you
15:28
can just map and like just about you could take a picture of a
15:30
potato and they'd be like, yes, we think this is Jeff Parker,
15:33
Sure. And you're like, but it was a
15:34
potato. But because you're matching it
15:35
to a universe, you're you're you're forcing it to match into
15:38
this universe. And my understanding of the app
15:39
is it provides you no confidence score, no certainty, right?
15:43
Like you're not getting specific scalar data right on what it is.
15:45
So that's just not great at all. What expectation?
15:48
Of privacy do you have as you I mean it just even drive around
15:52
Beverly Hills. Look at all the license plate
15:53
identifiers that sure are around not just Beverly Hills, but I
15:57
mean other cities. I was gonna say news to you.
15:58
We got no license plates all over the state, not just in
16:01
Beverly Hills, right? I know you never leave.
16:02
But so you know, whenever I go anywhere, you know exactly where
16:06
I'm going and there's actually cameras pointed down at me in
16:09
your junk all over the place. They can see me driving the car.
16:11
They know it's me. This.
16:12
Is part of the challenge. Now California has enacted some
16:15
legislation around this, specifically around the data
16:18
capture of license plates. It doesn't prevent it.
16:20
What it does is it puts some criteria around how you store it
16:24
to protect it and how long you can keep it, which is great.
16:26
It's something you can. Only keep it for 15 years.
16:28
That true? That's true on most of the
16:30
facial recognition stuff, as you keep it for 15 years unless you
16:33
have some reason to suspect the person is of interest.
16:35
At least there's some modicum over protecting the data, and I
16:38
think that was really to keep homegrown implementations that
16:41
just, you know, dump this crap to the web from existing.
16:44
So it's something. By the way, that's only true of.
16:47
The. Cities or the state governments
16:49
who enact those laws. For example San Francisco has
16:51
very strong anti facial recognition laws.
16:54
It only applies ties to city government.
16:56
If the federal government wants to come in and use facial
16:57
recognition, they can. Well, it doesn't change anything
17:00
for. Them yeah, I mean that's that's
17:01
part of the the challenge there right is when you start getting
17:03
into conflict between federal and state and state and local
17:06
law who who wins and that's that's a real federal yeah
17:08
exactly, it's all right you just.
17:10
Almost in every case exactly. So that that becomes certainly a
17:12
real challenge. Anytime you go to LAX, when you
17:13
approach a building, before you even get into a building at LAX,
17:16
they've already wrecked you. They know exactly who you are
17:19
before you even get into a. Building.
17:20
Well, yeah. So there is another program
17:22
that's in DHS specifically on the TS say, that is used in what
17:26
I would consider sort of the proper way, which is you have a
17:29
boarding pass, it has your name on it and you can match the face
17:33
that's registered to your name with the government right to
17:36
your face. That is a, in my opinion, a
17:38
reasonable example of facial recognition.
17:40
They still want me to have a little paper ticket and they
17:43
still want me to have some photo ID.
17:45
It's like, why do I need all this stuff?
17:47
You know exactly who I am. Kind of articulate the
17:49
difference here. The difference here is if you
17:50
took an app. No, I know that had.
17:52
Everybody who was flying tomorrow, I understand.
17:54
And you took a picture of some rando on the street and said,
17:56
who is this? Right?
17:58
It's going to map you to somebody in the app and be like,
17:59
oh, this is John Doe from Kansas.
18:02
He's flying from Kansas to South Carolina.
18:04
And you're like, but it's not John Doe.
18:05
Yeah, it's Jeff. Parker gets things wrong.
18:06
The point is you you're mapping into a population that isn't
18:09
necessarily the people that you're trying to find.
18:11
So that's that's part of the problem.
18:13
This is a limited time problem as well, because the rec
18:15
software is going to get better and better and better and
18:17
eventually it's not going to make mistakes and it's going to
18:20
know exactly. Who you.
18:20
I mean, it's gotten pretty darn good.
18:22
I think the the biggest problem is in the capture.
18:24
Yeah, and this is right now a real mess specifically for DHS
18:27
because you can't get a clean capture, meaning head on shot,
18:30
good lighting, Sure, because as someone moves around or if
18:34
they're looking down or if the lighting's terrible, which are
18:36
all things are going to happen out in the field.
18:38
Is anyone who's ever used the cell phone, take a picture knows
18:40
then you're just you're going to hurt the quality of the match.
18:43
What is I think most concerning about this is how we sort of got
18:46
here in recent time, which is that we had policies defined.
18:49
We actually had policies that were well defined over how to
18:52
use this tech and how DHS should use this tech and how they do.
18:55
Use it. And now we don't.
18:56
Yeah, those were totally erased. Like, it was erased like 3 weeks
18:59
after Trump's inauguration, right?
19:01
This is just like, Nope, we're pulling this all down.
19:03
We're not gonna follow it. And that's the part that I
19:05
really think you should be first and foremost concerned about is
19:07
there's no clarity in how it's being used. 0 oversight on it
19:10
too that sounds. Really bad.
19:11
To me it sounds a little authoritative A.
19:14
Little Orwellian and not what? We're supposed to want the tiny
19:17
the paquito. And for those two words in
19:18
Paquito, you're going to be arrested.
19:20
Oh, I'm already at the top of the list on there.
19:21
It's fine. Literally if you put glasses on
19:23
a potato it will come up as me. They already know.
19:24
There was a woman who was protesting and she was in her
19:28
car driving around Minnesota somewhere and that the ice guy
19:31
pulled her over and he identified her using this app
19:34
and magically her pre-check TSA went away like a week.
19:37
Later. Oh, weird.
19:38
Yeah. Shocking, surprisingly, how that
19:39
happens. Yeah.
19:40
Once you're accused of something, it all goes away.
19:42
They're all DHS programs, right? Yeah, makes sense.
19:45
This is a mess. I suspect this is going to get
19:47
worse before it gets better. Is it ever going to get better?
19:49
Well. At some point the sun has a heat
19:51
death and yeah, so. Something to look forward to
19:54
then. Counting down the.
19:57
Days had no idea you were this cheering.
19:59
Hey, what are you going to? Stop that fission, son.
20:01
Oh, soon. OK, just waiting.
20:04
The AI arms race hits TV During Super Bowl 60, Anthropic
20:08
launched a high stakes ad campaign mocking Open AI's
20:11
decision to introduce advertising into ChatGPT.
20:14
The commercials depict human like AI assistants shoehorning
20:16
cringe worthy product pitches like dating apps and height
20:19
boosting insoles into personal conversations.
20:22
Open AI My CEO Sam Altman didn't find the satirely, entirely
20:25
charming, blasting the ads as quote, clearly dishonest, UN
20:28
quote and deceptive. He argued that Open a eyes model
20:31
involves bringing free AI to billions, whereas Anthropics ad
20:34
free stance is a luxury for the rich.
20:36
Despite the friction Anthropics jab at dystopian ads resonated.
20:40
Data suggests their spots outperformed Open a Eyes in
20:43
viewer engagement, signaling a new public era of tech industry
20:46
mudslinging. Yeah.
20:48
It's a it's not muds, a little little bits of mud they're
20:51
slinging. It's not bad, yet you did leave
20:53
out the fact that that the the top of Altman's tweet did say he
20:56
found them funny, which which I can appreciate.
20:57
He at least said what I found them.
20:59
What else is he gonna say? I mean well.
21:00
That's the problem. That's.
21:01
The problem didn't even write. That, but that's the problem.
21:03
You shouldn't have said anything else.
21:04
You really should have just been like hilarious and that should
21:07
have been it full stop. And then some number of weeks
21:10
later you come out and be like, oh, hey, by the way, these are
21:12
the differences between the platforms like right, You can't
21:15
the ads, whether whether you are a open AI user or not, the ads
21:19
are still pretty damn funny. Like I think they did a really
21:22
good job of imitating what the current experience is like with
21:26
ChatGPT, the lag and then adding their take to it.
21:29
The lag was Brill. Oh, the lag is great.
21:31
The pause. You ask the question, and
21:33
there's this very long pause and then this generic cheery voice.
21:38
OK, here's how you get to know your mother better it.
21:40
Wasn't like, it wasn't like monotone.
21:42
It was generic perfect beige. You get this, like beige answer.
21:45
Yeah. And then the way that it
21:46
effortlessly sort of transitioned into an ad was what
21:49
I think a lot of people believe open AI could would do.
21:52
Sure, sure. Now, from my understanding, this
21:54
is not what open AI is looking to do.
21:56
They're they're doing something different.
21:57
But that's not the point. The point is this is a joke.
22:00
Like they are telling a thing that is a joke.
22:02
And I, an open AI think has really good facts or data and
22:05
and a belief in product that is not what was being represented
22:08
from Anthropic. Don't take the bait.
22:10
Sure, wait. Like just wait and come out with
22:12
that later then. And I was shocked to see this
22:15
'cause I knew the Anthropic ads were coming, right.
22:16
They released them. Yeah, sure.
22:17
Well before the Super. Bowl.
22:18
There were four of them, or six of them.
22:19
How many? Were there?
22:20
It was like 4, something like that.
22:21
Then I saw the opening AI spots during the Super Bowl and I was
22:24
like, oh, this is worse because the open AI spot was a very much
22:28
a like, hey, you can build stuff and this is this is kind of
22:30
cool, but but it didn't nearly like I felt like I was hanging
22:33
out at the nerd. Table.
22:34
That's so funny because I remember the anthropic ads and I
22:37
don't. Even remember the open.
22:38
Ones I don't even remember the open AI Yeah there.
22:40
It was it was primarily focused on codex and was talking about
22:43
kind of anybody can build something unmemorable, which was
22:45
really cool and I and I love that they were promoting that.
22:48
But man, relative to the Anthropic, like you missed
22:51
because the whole audio, the anthropic ads and understands.
22:53
I mean, if you don't use open AI, you can be like, Oh yeah, I
22:56
understand enough of what's happened in here.
22:57
Sure. The Codex 1 was like you're
22:59
trying to find the niche, like the three nerds that were
23:01
actually watching the Super Bowl was who that ad was for.
23:03
So like your acquisition cost was insane anyway, it was
23:07
interesting. I felt like the quality of ads
23:10
up front was better than recent years we've.
23:12
Blown off of this story? Haven't we've totally just gone
23:15
into Super Bowl ads? Oh yeah, I mean well as well.
23:17
Super Bowl ads were my war. Fun.
23:18
I was optimistic for the skiing, the Kurt Russell skiing
23:22
Budweiser commercial, Yeah. But it just, I've just felt like
23:24
it just no, it just didn't hit like it.
23:27
It, yeah. Didn't see it really.
23:29
How big was the charcuterie board you were at?
23:31
Was it like a room? Was it just like a charcuterie
23:33
room? It has, it's a room.
23:34
Sure, we only use it once a year, but damn, it's, it's worth
23:36
it. Well, I guess I didn't have
23:37
anybody over so I could pause it when I had to get up and get
23:39
stuff. But that's a lot of, that's a
23:40
lot of charcuterie. Now I'm hungry.
23:42
Thanks. OK, now with the headlines.
23:43
In fact, enough with the episode.
23:44
We have to get out of here. Special thanks to our floor
23:46
director, Scotty Bensick. Thanks, Scotty.
23:48
We'll be back later this week with our big story.
23:50
The end of the charging. Wait, new tech promises 0 to 80%
23:53
in minutes. Until then, thank you for
23:55
listening to all this nonsense. I'm Jeff Parker.
23:57
I'm CJ Little. Very nice.
23:59
Letters are hard, you say beautifully.
24:00
See you next time. Well, got some practice.
24:14
As you know, World War Two saw some dark and desperate hours
24:18
where the efforts of a single individual could mean the
24:20
difference between miraculous victory and crushing defeat.
24:23
Sure, courtesy of Muse Software, gamers can add their endeavors
24:27
to the glorious contributions of other wartime heroes with Castle
24:31
Wolfenstein. Oh, I love Castle Wolfenstein.
24:35
You would You must assume the role of a captured GI
24:38
incarcerated in the newly established Nazi headquarters at
24:41
Castle Wolfenstein The Furious. Minions will do anything to
24:44
learn your vital military secrets.
24:46
Yeah, a tortured cellmate gives you a fully loaded M98 pistol on
24:50
the knowledge of the Nazi war plans known as Operation
24:53
Reingold are somewhere in the ancient fortress.
24:56
As an army private, escaping with the plans is of paramount
24:59
importance to you. Turning them over to the Allied
25:01
High command will not only shorten the war and save lives,
25:04
but will also earn you a well deserved promotion.
25:06
Yeah, 'cause those two things are equivalent.
25:08
Find the Nazi war plans and make your escape from this ancient
25:11
fortress. Get Castlewolvenstein today 8995
25:14
at a retailer near you now I knew you were gonna like.
25:18
This this is so sweet 'cause I played this all.
25:21
The time it was very hard for me to not leak this to you.
25:24
Oh my gosh, I just loved this. Game.
25:27
I knew that would be the case. It really was Doom before doom.
25:29
So give me a year. Do you want to to know the first
25:32
iteration of Castle Wolfenstein when it first came out We.
25:35
Can go with the first. Yeah, we can go with the first.
25:36
OK, so in 19. 81 yes. Now what is it you were just
25:39
talking about? Cause what you were just talking
25:41
about was not 1981 because. Wolfenstein 3D was like 1992.
25:45
Yes, and that was the first real 3D version.
25:47
Yes, that is correct. You are accurate about this.
25:50
Now, this particular ad was from 1984, which was the Commer 64
25:54
version. I left that out to try to throw
25:55
you for a Oh yeah, yeah, they released the Atari before that
25:57
in 82. Commer 64 was 1983 ish and then
26:01
the MS-DOS platform later. But what's interesting and most
26:03
people don't know and I think you sort of sniffed out, is that
26:05
this was Muse Software. I left that hint for you on on
26:08
purpose because that was not the guys that bought the rights to
26:11
cast Wolfenstein for Wolfenstein 3D, which is what came out of I
26:14
D Software in the early 90s. Yes and yes.
26:16
It was the precursor to Doom which was an amazing game.
26:18
I remember running it, you know, on MS-DOS in TSR 640K984K mode.
26:24
Yeah, yeah, for sure. And there was nothing like it at
26:26
the time. I was so much.
26:27
Fun. I also love that Wolfenstein and
26:30
and even Doom, Doom, more so now, is like the thing that your
26:34
technologist makers will port onto every device.
26:37
Oh sure, like sure. I literally read an article last
26:40
week about a guy that ported Doom to run on a set of
26:43
earphones. Oh yeah, literally as a There's
26:46
so much more. Processing in it your.
26:47
Exactly. That's kind of the point.
26:48
A lot of fun, yes. Castle Wolfenstein.
26:50
Near and dear to My Heart 19. 84 but what is also worth pointing
26:53
out is that 8995 is today dollars.
26:57
It's actually like $93 in today dollars Yeah, it was 2995, a
27:00
time of release. And I put that in there because
27:02
I think it's somewhat important to notice that the cost of games
27:05
has actually gone down. Yeah, right.
27:06
Like we like to go Oh well, I had 60 bucks for a Switch game
27:09
that's a lot like, but actually it's down over the past 40
27:12
years. The last thing I want to leave
27:14
you, yes, and I apologize in advance for making you and all
27:17
of our listeners sad, is that Castle Wolfenstein, not
27:21
Wolfenstein 3D Castle Wolfenstein came out closer to
27:24
the end of World War 2 than to today.
27:26
Oh. That's true.
27:27
That's absolutely. True.
27:28
Good luck getting through the rest of your day.