00:00:00
else did you see they updated no man's Sky you should you should talk about it more the planets are more real it's
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called World Planet one eight years after it got released this is the planet
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one it my favorite like I said my my space
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game oh just never got released period so you can play no man's Sky
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[Music] now what is up people of the internet
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welcome back to another episode of the waveform podcast we're your hosts I'm Marquez I'm Andrew and I'm David and
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this week a bunch it's a mix of stuff it is is I would sayx stuff every week
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there is no theme it's just a mix uh but it's all new we've got AI stuff we've
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got new uh leaks of devices we've got new cameras but we also have one like
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headlining major piece of news kind of the elephant in the room I feel like we like to put a really big thing in the
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middle of the podcast normally but this was just too big nuts most of the show so need to start with it immediately I
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mean I don't want to get too bogged down with it but it is it's one of those pieces of news that you kind of can't
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get to without I mean if you don't talk about it people are like why aren't you talking about it so we we'll address it
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um homepod mini was updated and it's midnight now instead of
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black oh yeah this is a that's the whole that's the whole thing yeah it's so have you seen
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the side by sides actually I am not I'm not convinced that it's like the the the
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office meme it's the same photo it's like are we sure that they they didn't actually change the color and just Chang
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the name I think it's a test all I know is that the materials are now 100% recycled instead of 90 90% yeah it was
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90 now it's 100 now it's 100 but did the color actually changed it didn't look
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like it to me but I did not look that hard at it apparently this is the most
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I've spent even thinking about this color right now H mini only had like gray space gray and white to start and
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they started adding colors randomly there's uh and now there's an orange and a blue I'm still a homepod mini Stan
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just so you know the midnight could actually be a different color because we had a conversation about this yeah the
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it might be kind of different because the midnight color itself is one of those ones where it does look super different in different lights and maybe
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just those photos but like if there were space gray and midnight they're probably almost the exact same thing yeah cool
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okay yeah we got we got through that that's that's that's huge for us um yeah there's a whole bunch of pixel leaks
00:02:44
though we we should jump in again's what every year every year the
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pixel is the most leaked phone of all time I they've got to have some kind of record for this and now we're getting I
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guess seemingly more confirmation that there are a bunch of pixels and they're pixel 99's so there's pixel 9 pixel9 XL
00:03:03
and then like a pixel9 pro a pro and then a fold too Pro fold to Pro fold two
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pro fold two even though the first fold doesn't have the word Pro in the name Noe so there's a pixel fold now there's a pixel fold pixel Pro fold two well
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it's not called two it's just pixel 9 Pro fold oh yeah sorry pixel 9 now it's part two it's considered part of the
00:03:23
pixel 9 portfolio it's doing the pro fold it's
00:03:28
doing the thing I've been asking them to do it the a series for Years also I think we need one of those whiteboards
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that says podcast since last pixel leak and then we just erase every week and
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put zero again it just says zero every time yeah uh what do you think of them
00:03:45
are you interested any of the pixels well the fold is the big leak that we
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got this week the like kind of official photos of it we talked I think it was last week we talked a little bit about
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the different sizes of the 9 9 Pro 9 Pro X but this week is the 9 Pro fold and it
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looks terrible I what Ellice don't hate it you don't hold you guys are crazy I
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don't hate it hold on I have that I have a question then okay last time we talked about this you said you didn't like the
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visor on the nine leaks you thought it looked bad mhm but you think this looks
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good no I don't think it looks good okay okay so the the reason that I dislike the visor on the nine leaks is because
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it feels less of a commitment to the visor the visor before was like all the way to the sides and it would like blend
00:04:40
in with the side rails and so that made it feel very committed and decisive and
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obviously a pixel and when you separate it from the rails it just feels like an island now and it feels like the
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precedent is set that this visor thing is not that important to the pixel and so now this is the least visor like of
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yes I think the other one still has the same Vibe of it like it's still very obviously a pixel and it like it's just
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the Moder the like modernized version of it which is funny because it's only the visor is like two or three years old it
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feels cyberized in a way it's updated it's like in this new squared off design
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all around including the camera are you I'm talking about oh sorry you're talking about no now this now let's go to the fold okay someone please explain
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this camera bump uh it's just a it's just an island I want to hear Ellis explain
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getting ready to Gap over this is this is coming for someone who's owned an iPhone since they were 15 years old so
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you know take it with a great OFA but to me the pixel's gone through many
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iterations right we we had the the original pixels with no no definitive
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bump then we were in the Jordy leforge RoboCop era of visor pixels then we
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achieved bump pixel after that you know not going to the edges visors have only been since the six I know I'm I'm fast
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forwarding through the history here give me give me a sec okay to me now since the visor you know they
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took it off the edges it became more of a discernable bump we've gone back and forth to me the definitive pixel
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characteristic as a non-pixel user is the bean what the oh the bean how
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whatever whatever if it's a bump it's a visor no matter what that that camera is in a bean and the
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fact that the the ninefold render leak whatever two beans mhm two be are you
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talking about you talking about the sub bean inside of the mega Bean yeah no no no
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there is no mega Bean there is just the bean the bean can exist in a visor in a bump in whatever well there was but like
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what he's saying is the pixel 8 and the pixel 8 Pro the bean was longer yeah it did yeah yeah it's always some sort of a
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cutout in the visor and the went from one look to another the pixel 6 did not
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though the pixel 6 was just glass guys I know this is pixel didn't but I think as
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a fans and appreciators of the pixel it's time to recognize the bean yeah but
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pixel 6 didn't have a bean I'm well pixel 6 oh and that was a good pixel too that was like the start of the visor and
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then they added the bean yeah cuz they went from glass to metal eight was the eight was the best so far for sure I
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like six the best eight feels the most but seven seven definitively is beaned up okay let's let's all just like be in
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agreement there so the special edition out there so when in the fold they were
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like recognize the bean lean into the bean this is the bean phone if for some
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reason there's an audio listener who doesn't understand what he's saying inside of the visor from the seven to now the cutout of the metal of the visor
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for the glass of the cameras is an oval some may describe it as a pill shape that's what I would say I mean a be
00:08:00
usually has a like a beans come in all shapes and sizes who's to say this isn't a digital
00:08:06
Bean including pill-shaped beans I think most people say pill but I'm down for the Bean it's more fun where are we I
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don't know uh Andrew someone so let's talk about this let's
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talk about this well the camera bump for the pixel fold the new the pixel9 fold the pixel9 profold profold is a rect a
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curved rectangle with two ovals SL beam inside of it left aligned
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a yeah with a it's a rectangle though it's not a square well squares are
00:08:41
rectangles yeah but a rectangle is not a square you're
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right let's continue um so it has like two lenses in each it looks like although we'll get that back to exactly
00:08:52
what it is and then it just has this like right aligned Flash and microphone that is just in no man's land there's so
00:08:57
much extra space over there what my hot take they would have just
00:09:03
put the same camera array as the pixel9 pro and pixel9 pro XL except the fold is
00:09:10
probably slightly more narrow and currently the design of the pixel9 pro
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and pixel 9 Pro XL shows the camera bump visor taking up pretty much the entire
00:09:21
back of the phone and I would bet you that it's like 2 mm more narrow and
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they're like oh we can't fit it so we just have to vertically stack them at first I thought they might have done it
00:09:33
for like uh the what is what is spatial video C capture oh but they're using the
00:09:40
telephoto and the wide and I don't really on top of each other see yeah because the whole thing like the whole
00:09:46
reason the iPhone switched back to having the cameras on top of each other now like directly on top of each other
00:09:52
so when you turn it sideways to capture spatial video they're horizontally aligned on the same axes so that they
00:09:57
can do parallax this you theoretically I guess still could do but usually you do
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that with a wide camera and the main camera not the telephoto camera in the main camera cuz now they're horizontally
00:10:10
separated yeah anyway um it looks bad I think is my
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take Ellis is trying to hit the buzz button for no but he can't damn steal my
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thunder go back Marquez you said or no you said you didn't hate it yeah I don't think it's that bad I think it's not bad
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I think the easy look we get leaks all the time and I think our strongest reaction to leaks is
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always on the design because it's not on we don't know any specs we don't know any features we just see the design and
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that's all we can react to and so whatever's different about it versus the old thing we will react strongly
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negatively because we always do and then two months in we'll be like yeah it looks like every other camera bump
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remember when the we first got the like triple cameras on the iPhone every it looks like a stove top that's the what
00:10:55
are they doing that's the ugliest camera bump ever and then two weeks later we were all like yep that's how it is I think that was at least like and
00:11:01
actually I had that reaction to the last iphone where in the triple camera array of the what you're talking about was at
00:11:07
least like semi symmetrical this one now with the like the microphone and
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whatever that extra sensor is it felt a little more all over the place this feels just like so not even remotely
00:11:20
symmetrical or it's all lined up it's two Rose but the the microphone has like
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the microphone dot has just like the same amount of space as the large sensor
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in it and there's also just a bunch of there's a huge metallic it's all the dead space on the right that I don't like yeah it's
00:11:36
weird every every camera bump sucks I don't know what to tell you I I mean I don't disagree with that it's also going
00:11:42
to rock on a table yes many of them yeah I I just I know that when we fir when
00:11:47
the pixel fold first got announced it was like uh but now I think it looks really good the original pixel fold
00:11:53
besides the interior well they also changed the dimensions of this new one which I'm interested to hear think about
00:11:59
cuz it seems very anti what you liked about the pixel full yes yes so what
00:12:04
Andre is talking about is that the it's more of a OnePlus open format now it
00:12:11
almost looks exactly like that kind of style uh whereas the previous pixel fold was a lot more like the Oppo Find n
00:12:18
which was like a passport style um and I
00:12:24
really really liked the short aspect ratio of the original pixel fold yeah um
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and it seems like that's gone forever because people don't like small phones apparently I'm curious to try yeah I
00:12:35
definitely like the the the Pix the first pixel fold which I think I said in the video it was the easiest it's the
00:12:41
best foldable phone to use open yeah uh sorry it's the best foldable phone to use close because that aspect ratio of
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the screen was great and open it suffered a little bit because it was so good closed that it was like more Squat
00:12:54
and I had a smaller inside screen so maybe this is them going sacrifice a little bit of the outside user ability
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make the inside usability better which I think makes sense if you're making a folding phone you should make sure the
00:13:05
reason you're folding it is still good yeah um just GNA show you that I think that looks better I think I knew I knew
00:13:12
you were going to bring that up but I think that looks better there are bad camera bumps out there at least at least
00:13:18
that takes up like the whole back of the phone you know only cuz they put a
00:13:25
screen I'd rather a screen your phone upside down you can know what time it is I also guys what is
00:13:31
that1 ultra thank you Ultra one of the largest camera bumps on the back and there's also like a Poco phone that did
00:13:37
that as well um there's text on the back of the phone we forget the Nokia 9 P
00:13:43
viiew that had the spider arachnid array the nine cameras I also want to say I
00:13:48
recognize that what we are complaining about is extremely minuscule I know but it's stupid to complain about but it's
00:13:54
just kind that's what we do here yeah that's what the leaks are the leaks are the leaks are basically here's what the
00:14:00
new Design's probably going to look like there are some leaks pointing to a large camera overhaul in general which I'm
00:14:06
curious about CU that could mean new sensors it could mean this new software it could mean new capabilities but again
00:14:12
we don't know if that's true uh we're all hoping that tensor gets better we're all hoping that there's more RAM and a
00:14:18
brighter screen and faster refresh rates and all that fun stuff and that's possibly also on the pipeline but we
00:14:24
don't get that from these leaks we just get to see the look of it was it true that the Pix the original pixel was one
00:14:29
tensor behind the uh right I think it was it was tensor 2 pixel 8 yeah yeah it
00:14:37
was like tensor one or was it tensor 2 or it was yeah it was tensor 2 and the pixel a got tensor
00:14:44
3 yeah so it's nice that if they all come out at the same time hopefully they'll all be on tensor four that would
00:14:51
be nice even though apparently it's not switching to tsmc until tensor 5 so it's
00:14:56
very possible that these also suck yeah one cool thing though we do see from this is on the inside we now have just a
00:15:04
top right hand corner hole punch cut out for the camera versus that like would you even call that a notch it was like a
00:15:11
corner hole cutout for the camera that took up a lot of real estate so this is
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yeah more screen real estate on the inside I like Corner cameras I'm fine with them yeah I don't use the inside
00:15:22
camera in most foldables most of the time which I think is why people would argue that Samsung's unders screen one
00:15:29
is not a terrible idea cuz it's a horrible camera but it's like you almost never use that one unless you're maybe
00:15:34
like propping it up trying to do a zoom call or something like that then and you don't care about your quality as much
00:15:39
then yeah yeah so I I think most selfies will come from the outside screens whole
00:15:44
punch camera but yeah but this is a proper cutout which means that it's it's not like an under display camera it's
00:15:50
going to be super fuzzy under the PES so yeah I'm fine with that it is also funny that Samsung has never improved that
00:15:57
that that's been around for like three to four years and they have literally never tried to make it better yeah I got to talk about that in the review it's
00:16:04
the same it also seems like it's getting sorry still on the ninefold pro pro losing profold losing
00:16:13
battery size despite being a larger phone am I right in that it says classic Google T oh my God there's so much light
00:16:21
in this room it looks like I'm in a in a haze yeah it's a classic Google decision I don't know if you
00:16:28
remember um the pixel 4 had like really really terrible battery life cuz they reduced the battery life like fairly
00:16:34
significantly from the pixel 3 and then uh obviously most of the reviews were
00:16:39
like the battery on this like does not last at all and then I think it was um
00:16:46
gosh who was in charge of pixel at that time it wasn't Hiroshi it was Dave bur not Dave Burke I don't know whoever was
00:16:51
in charge basically came out and was like it's insane that you guys like made
00:16:57
this camera or the the bad this bad like he went to the team and basically yelled at his team and he was like why would
00:17:03
you reduce the battery life and it was like bro this is your product like you should have been in charge of this yeah
00:17:09
that might have been a rick osto moment it was Rick osto that's what it was it was it was like they reduced the battery capacity by like 500 600 Milli of hours
00:17:16
and then they were like and they added the solely radar which just nukes the battery completely one of the worst
00:17:21
features on a phone anyway yeah that phone was amazing except for the battery and the sole but other than that it was
00:17:26
good well long story short check out some pi leaks let us know what you think maybe you think they're ugly maybe you
00:17:32
think they're not so bad but we'll learn a lot more about this phone I guarantee stay tuned for next episode where we
00:17:37
also talk about pixel Le probably more I agree with you though that I'm sure that after a couple of months we will be just
00:17:44
used to it and we won't think it's that ugly anymore y there there are a lot of camera bumps that I have always thought
00:17:51
initially that were super ugly and now I'm like whatever so it's a bit of a tradition around here to complain about
00:17:56
camera bumps on phones that we weren't going to buy and then they come out and
00:18:01
then that's it and that's the end of the story that's the whole Tradition now I'll make sure to make fun of any of you who have well I'm definitely going to
00:18:07
try in this office speaking of folding phones got them uh there's a feature on
00:18:14
uh some of these new Samsung phones where you can draw on an image and then
00:18:19
it can turn that sketch that you drew onto the image into something real
00:18:24
that's like a part of the image now and yeah that looks real an i generated
00:18:30
asset to go on top of your image yes exactly and it's fine the thing
00:18:37
is what is a photo again right like we don't we don't really these are just things that are cool ideas that they've
00:18:43
come up with that they're just throwing in and people are trying them out it turns out they work and uh there are a
00:18:48
lot of things that you can draw and like make in your photos that kind of are are passable out of first glance that you'd
00:18:53
never look twice at and this like this one feels past the what is a photo
00:18:59
because it feels so obviously not a photo but some of them are decently
00:19:04
realistic there are some that are pretty realis that one with the cat that they posted on the verge looks really good for a second Until you realize the cat
00:19:10
is the size of a small car the cat looks like a really real cat though it does this does look like a photo of a cat
00:19:15
it's just taking the graish evolution of 3x in its size yes every I took a
00:19:21
picture of you guys earlier and I drew a butterfly on your hand which is where I
00:19:27
think we' expect a butterfly fly to be and honestly the first glance at what it
00:19:33
created is like kind of passable it's huge honestly the fact that it put the
00:19:38
butterflies legs like in the middle of my hand and added some Shadow stuff
00:19:43
right the compositing on these is really realistic it's mostly that the image itself looks like a little bit cartoony
00:19:50
and doesn't have the same like processing as like a camera processing and that's how you can tell that it's not part of the image there's also a
00:19:57
tiny AI generated content Watermark at the bottom left corner that if you aren't looking for you might not see
00:20:04
don't see it's cuz it's white and like emoji and it just says AI generated
00:20:09
content it's white text on a a pretty busy background so it's kind of hard to see but yeah it is a thing that you can
00:20:16
play with and is kind of fun it's it's probably not a useful feature to most
00:20:22
people get this feature yeah Allison Johnson posted a bunch of these on the verge and a lot of them are very funny
00:20:29
she she drew a cat in the middle of a street and the cat is like massive but looks very very realistic she Drew she
00:20:37
Drew like a really you know rough rendition of a bumblebee on top of a flower and it made like a really
00:20:43
realistic looking bee right and they it made it out of focus like that part of the image was out of focus and that
00:20:49
looks really real yeah so I think it's the good enough at first glance test
00:20:54
that it passes like if I was scrolling on Twitter or Instagram and I saw that and I wasn't thinking about AI I wouldn't
00:21:01
think twice I wouldn't check and I would just believe it and move on with my day yeah and that's that's a pretty
00:21:08
impressive threshold for these like images you draw with your finger on your phone to pass but yeah once you actually
00:21:17
check you can kind of immediately see the flaws so that's where that's where it lives right now right I think that
00:21:22
this is going to be a very weird uh period of time because these platforms are very bad at detecting what's
00:21:28
actually AI versus just like slightly AI modified M and they'll just tag everything as AI even if it's not so at
00:21:36
this point in time you kind of have to look for images just like you have to look for AI generated text if it feels
00:21:43
like it was written by a high schooler then it's probably AI generated if it feels like it's like summarizing
00:21:49
something and you're in your English three class probably a generated M same thing with this if anything looks at off
00:21:56
off at all just Pixel People a little bit and you'll probably start to see some weird zooming on the fingers you
00:22:01
know what I cannot wait to use this for what so you know that one image where someone's like in an apartment complex
00:22:08
and there's four buildings all around them and they're looking straight up and they take a picture of like a plane taken off there's like a viral picture
00:22:16
that happens all the time with travel influencers and everything like that I'm just going to go there and take that picture without waiting for a plane and
00:22:22
then just drawing the draw the plane yeah that's going to be awesome or like in Brooklyn where the bridge is you know that one street where they have the
00:22:28
Brooklyn Bridge just draw whatever you want there yeah or like there's in and out in La that's like right underneath where the planes
00:22:34
land at LAX and people like have to wait for the big plane to be extra low now
00:22:40
you just draw it in there and you're good and you didn't have to blow your e drums out don't you care about realism don't you care about reality uh I just
00:22:47
sent you guys a photo that I saw a little bit ago that's like a fairly innocuous sort of Mimi photo but the
00:22:52
more you pixel PE the more you realize like things aren't right and I can't
00:22:58
tell if it's AI or just like really bad computational photography I a real photo
00:23:04
looks like a photo zo look at this look at the text and look at the sign and then look at the underside of the truck
00:23:11
and then explain what it is yeah sure it's it's a it's it's a post and also look at the grill of the truck it's a
00:23:16
it's a picture with a caption truck lifted too high to see the Porsche in front of him and it's like a big lifted
00:23:23
truck that's sort of like backing or pulling over the back of a Porsche uh
00:23:28
seemingly some sort of Turbo S perhaps a GT3 with the intakes um it's a
00:23:35
718 it's a but um but yeah it's like if you look at it it's like oh this is a real photo and then the more you pixel
00:23:42
peep it's things don't look it's like why is that why is there all that red in
00:23:47
underneath the truck yeah that's that's not existent that I'm wondering if it's like the bumper that just kind of got pulled down but what I'm more interested
00:23:54
in is the stoplight is like half missing and look at the the font in the the
00:24:00
thing that says limited is like not it's the weird thing about computational photography these days is that it always
00:24:07
tries to do sharpening and so like really bad regular phone photos that are
00:24:12
zoomed in a lot yeah the sharpening almost looks similar to AI text I know
00:24:17
and that's why I'm like it's really hard to tell the difference a lot of the time and it's just it's like it doesn't really at the end of the day it doesn't
00:24:23
matter whether this stupid meme is AI but we now live in a time you can't tell yeah where it's like yeah is this yeah
00:24:29
normally I'd be like well it says cr3a so maybe this is like Russia or something but these are all American
00:24:35
cars no this is I think that's supposed to say ca 3A like California highway 38
00:24:41
um which maybe it is and again it's just like a super zoomed in shot that's
00:24:46
trying to sharpen it and it looks terrible it's very possible I yeah I don't know smartphones have gotten
00:24:53
smartphones are not good at making text look normal when they're trying to
00:24:58
uh upscale things this is a really weird image to me it's really weird look at the red light the red light is look a
00:25:06
weird that's a weird light to me all of this image looks real except for the street sign and the red light yeah no
00:25:13
but what look at the suspension of the truck yeah the suspension looks weird too that all looks but I think that
00:25:19
looks fine looks like a fine like it's a it's a modified lifted truck with weird
00:25:24
looking red suspension parts and a red Grill and that also just got into an accident where the bumpers like half
00:25:30
torn off right yeah this is weird interesting huh I think it's trivia time
00:25:35
okay we told you it was going to be a grab back this week trivia so not to
00:25:43
spoil anything but in our next few sections we're going to be talking about some web scraping and crawling and all
00:25:50
sorts of stuff so creepy I wanted to make this question about the classical
00:25:55
version of that stuff web Crawlers specifically there's lots of different
00:26:01
names out there that computer scientists use to describe
00:26:06
webcrawlers which one did I make up oh no a
00:26:12
spider B automatic indexer c a web Scutter or D these are
00:26:21
all real baby this is going to be a trick question have you ever done a all of the
00:26:27
above before I have I'm scared H so your answer would
00:26:35
be if you pick one it's made up but if you pick D it's that they're all real yeah you are acknowledging that I didn't
00:26:41
make up anything for this question this is either a trick question or a trick question trick question where you think
00:26:47
it's a trick question but that's the trick but here's the thing here's the thing you're right but I feel like that's more fair I would never give you
00:26:53
a trick question without you guys all knowing there's the possibility of it being a trick question you know what's
00:26:58
the what's the fun the point exactly you know that feels like enough warning for it to be a trick question yeah or maybe
00:27:05
that's the trick like David said trick question trick question I'm confused all right we we're going to Rack our brains
00:27:11
for a while probably on this but uh the answers will be at the end as usual we'll think about them and we'll be
00:27:17
right back [Music]
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now to grow your business no matter what stage you're in shopify.com form all right welcome back we uh I
00:30:21
don't know if you're watching the video version or listening but uh we are actually wearing different things and
00:30:27
not [Laughter] well the reason some of us are wearing
00:30:32
different things is because we're recording this the next day because we have since gotten extra news that
00:30:38
actually affects what we're about to jump into because we're about to talk about you know apple and training AI
00:30:44
models on YouTube videos but the news is we actually finally did get a statement from Apple after we recorded that so I
00:30:50
just want to we're jumping in now to share that statement just for clarification so you can hear it uh
00:30:56
basically the the gist is Apple is clarifying that the data they used to
00:31:02
train this model goes into this model but this model is not being used in any
00:31:08
of Apple's consumer facing products like apple intelligence or Siri or any of that it is used for only research
00:31:14
purposes research purposes only is what they're saying whatever that means you know a lot of these things have been
00:31:21
research projects like chadic BT was a research project and then turned into a full-fledged product however it is true
00:31:29
that apple is not currently using openm in any of their consumer facing products
00:31:34
and that the physical data set that we are about to talk about for an extremely long amount of time too long is is not
00:31:42
planned on going into any consumer facing models so the open Elm language
00:31:48
model that we're hearing about does have data from this company but this language
00:31:53
model isn't going into Apple intelligence that's the clarification
00:31:58
also though there are some other companies that use this pile data set that does include our transcripts that have either denied comments or not made
00:32:05
comments we kind of talk about it a little bit going further um and yeah I
00:32:11
still think a lot of the things we say are valid even if we just talk straight about Apple in those senses because like
00:32:17
this is happening not just with YouTube videos but with art but with music but with all sorts of other different things
00:32:22
that we've talked about in the past and I still think it's a big thing we need to talk about going yeah further and
00:32:28
there's no comments from any of those other companies no when these companies are yeah there might be by the time this episode comes out yeah true when these
00:32:34
companies are literally running out of Internet to scrape and so they're training their models on model output
00:32:41
you know that they're going to start looking for any corner of the internet that they can take so yeah so I feel
00:32:47
like that's enough context to at least know the news that's happened since we recorded so now we can jump into what we
00:32:54
did record take it away past self all right our next piece of news
00:32:59
involves us a little bit um there was a headline that was going around yesterday and I think they smartly included
00:33:06
YouTubers names because they knew they would talk about it but here we are anyway and it's fine um and it basically
00:33:11
went along the lines of apple and other major typ companies are stealing from MKBHD and other YouTube channels and so
00:33:20
people saw whoa Apple stealing from MKBHD what's going on here and the the General Zoom
00:33:26
all the way out version of the story is you remember Apple intelligence and all these AI features that Apple's announcing they have to train that on
00:33:33
something they have to acquire a bunch of training data and part of the uh
00:33:39
acquisition process is working with a bunch of companies that scrape data and
00:33:45
like come up with a whole bunch of training data for you to use if you're apple and one of the
00:33:50
companies took a bunch of data including transcripts from YouTube videos which is
00:33:58
I believe a violation of YouTube's terms of service yeah um we'll get there but
00:34:04
you've got like 20 paragraphs into this outline already but uh a lot of those
00:34:10
videos are from YouTubers that you may know like Mr Beast or PewDiePie or
00:34:15
myself we had a bunch of we had a couple videos in this data set and there's a tool available for you to check which
00:34:20
videos are included in the data set so the long story short is they've made this headline that Apple has sto stolen
00:34:28
YouTube content and put it in their training data for their Ai and that's
00:34:34
kind of true but yeah there's a whole bunch of moving pieces a whole bunch of facets to this story that are all
00:34:41
equally kind of interesting um I guess we'll start at the beginning yeah you did long story short let's do short
00:34:47
story long now short story long so okay we but there's a lot more like short story long now to unpack some of those
00:34:54
pieces so first part is Apple intelligence is a bunch of models that
00:35:00
run either in the cloud or on the iPhone Apple makes the models but Apple has to train the models on something same thing
00:35:06
with chat GPT same thing with Gemini they have a data set that they are trained on yeah so if you're Apple you
00:35:13
have to get all of this data this Corpus of human knowledge that you want to train it on and that ends up being
00:35:19
what's fed into the model um so yeah they they have to work with companies they have to license information they
00:35:25
have to just acquire a whole bunch of this data to train their models on and so that's part one is they had to work
00:35:32
with some of these companies who have existing data sets that Apple could buy
00:35:38
yeah and like every AI company needs to train data right like and a lot of them are using other things we talked a
00:35:45
couple months ago about open AI being asked like from Joanna Stern are you scraping YouTube videos and there
00:35:53
CTO yeah she was just kind of like not sure about that which is like the least
00:35:59
reassuring answer possible there was an interview with Cara switcher recently that she did and she asked her Point Blake too and she said I don't know
00:36:06
which I think is the truth I think that's the truth I think she should know though should know but I
00:36:13
but it is basically like they are trying to include the entire like Corpus of
00:36:19
human knowledge and so they have they've gone to all these bazillion places for as
00:36:24
much data as possible and they definitely can't guarantee that none of it is YouTube they could they should
00:36:31
with the amount of money that they have they and they can it's kind of like uh
00:36:36
if you're building a smartphone and someone goes can you guarantee that all of the materials came from uh
00:36:43
sustainable places and you can say that you've you've done the work for all your
00:36:48
suppliers because you're not the one going and Mining all the things you're going to suppliers who you trust to tell
00:36:54
you the truth but your supplier could be lying to you your supplier could change things your suppliers can go out of business and you need a new supplier all
00:37:00
this stuff but also let's be real like all of these AI companies like they don't have the ethics to care about this
00:37:05
kind of thing because none of them have gotten in trouble for yeah there's no repercussion there have been no reper it's like there's a gold mine sitting
00:37:11
right there and you have access to it and there's a sign in the front that says not your property but then you just
00:37:17
you could go and take it anyway you're going to do that yeah I would argue most of these companies have the abilities to
00:37:23
do any of these things but those abilities cost so much more money right and that they're still putting profits
00:37:30
first so most of them almost none of them are but all of them have the opportunity to they're moving fast so
00:37:37
yes and in AI especially we are at like 10x speed here move fast and break terms of service that's exactly that's pretty
00:37:44
much everything we're about to talk about in one sentence yeah um so can we go to alther off of that alther AI which
00:37:52
is the company we're going to be mostly focusing on yeah so that is that is one of the compan that Apple got its
00:37:58
training data from correct and there was a wired article on Tuesday that
00:38:03
references a proof news investigation of this company that is a nonprofit called
00:38:09
alther AI created this data set that they are calling the pile which is a
00:38:15
nonprofit open source data set that is online if you you can go find it right now and download it it's like 800 gigs
00:38:21
or something like that um but it scraped the subtitles of over 100 70,000 YouTube
00:38:28
videos from 48,000 different channels and trains and put it in their data State for the use of training Ai and
00:38:36
that includes people like us we are in there because proof news made a website
00:38:41
and we'll link it in the show notes where you can search videos that are in this data set weirdly enough all of ours
00:38:46
are all YouTube Originals it's like the whole first season of retr tech it has Mr Beast videos PewDiePie it even has
00:38:53
crash course from the Green Brothers had 1,800 videos inside that I know um and
00:39:00
even stuff that are like super copyrighted late night shows like Steven coar and Jimmy Kimmel and John Oliver
00:39:06
was included in that data set as well because a Luther AI on their site says
00:39:11
empowering open-sourced AI research and just like open crawl which is a huge
00:39:18
data set that open AI originally used to train ja chat GPT if you just go to a thing that's like we gathered all this
00:39:25
information not to make money but just to do research and then you take an open source thing then you can say oh we
00:39:32
didn't do anything illegal we just took this open publicly available data set which open AI like references all the
00:39:39
time they're like I don't know if we took anything illegal but we took publicly available information and it's
00:39:45
like there is such a delineation between publicly available and like free to use
00:39:50
those are not the same thing and I know that you know it I know that you know it like don't act dumb here yeah it's crazy
00:39:58
so yeah this is this is a gigantic data set with a ton of appar so subtitles
00:40:04
specifically I'm I feel like I'm glad it's not other parts of the videos too it's like your voice and stuff like that
00:40:11
my voice and face and all these other things about YouTube videos but it is all of the words spoken in all the
00:40:17
videos what you made an interesting point on Twitter of is like we as a channel specifically pay extra money to
00:40:23
make sure that is not only super accurate but then it helps us do in other languages correct like so I pay
00:40:30
for a human transcription of every video per the minute and it's to make sure
00:40:37
that I mean obviously we've had jokes about this in the past but YouTube Auto transcriptions are like pretty bad so if you're hearing impaired you don't want
00:40:43
to deal with those so we pay for these for every video and so if they're scraping the subtitles they're going to
00:40:49
end up scraping from YouTube API what I uploaded because I replaced the uploaded captions and so they're stealing paid
00:40:58
you paid money and then they're taking the thing that you paid money for yeah and training whatever on it I do find it
00:41:03
very funny if they just scraped so many videos where they didn't pay for the transcriptions because a lot of the
00:41:09
transcriptions are bad so you have like pretty rough data mixed in there yeah
00:41:14
yeah as always but and the reason we can connect this to some of big companies like apple Nvidia is inside of their own
00:41:22
papers talking about their AI models they've referenced this data set called the pile Apple I think in a paper
00:41:28
talking about open Elm which is the model released at dubdub correct that like for some of their AI stuff
00:41:35
reference the pile so like we know that they are using this data set that has been caught scraping all these things
00:41:42
and there's just something like I don't I guess it's maybe not as weird because you're saying you're glad it doesn't
00:41:47
have your voice and everything but something about scraping straight subtitles and like we we get paid
00:41:54
obviously by people watching our content by a view we didn't even get the One Singular view from the AI scraping our
00:42:01
video as they literally just straight up took everything with nothing back to it
00:42:06
and just scraped all the data which later we're going to talk about is defin is against the terms of service for
00:42:12
YouTube scraping subtitle data isn't there you know you can scrape the entire internet and there's all of this stuff
00:42:20
about like you're scraping websites and people's writing and like the ethical implications of that and how that's
00:42:25
messed up um but people don't write the same way that they talk so if you're trying to make a chat bot that is the
00:42:32
most humanlike possible YouTube is actually probably the most valuable data set on the entire internet because
00:42:39
people on there actually speak more like they normally speak and not how they write um and I just wanted to bring up
00:42:46
very very briefly I used to contract for Samsung I did work for Samsung in in
00:42:53
college um and I helped them train a Bixby model uh based on so sorry yeah well I'm sorry
00:43:01
it's your David ruined because what they did was they were like we need Bixby to
00:43:06
like have more natural output so we need you and a bunch of your friends to like basically use this client to message
00:43:14
each other a bunch of messages as if you're having a natural conversation like 10,000 times so they wanted me to
00:43:21
message my friend like hey how's it going do you want to go to the gym later but they wanted they were like make it as natural as possible but we need
00:43:28
10,000 of them by next week so they wanted you to make a data set yeah we did make a data set but the problem was
00:43:34
it was based on like repetition and the amount that we did and not uh it was not
00:43:40
based on like here used this chat app for the next month and we'll just take everything that you say it was like we
00:43:47
just need this on this deadline so we were just pumping out fake conversations that are definitely not the way that
00:43:54
humans actually really interact yeah uh so yeah probably partially to blame for Bixby but I'm just saying I will
00:44:00
continue to blame this is a much better data set but there's like so many so many red flags
00:44:07
I'll never forgive you David so here's the Devil's Advocate point that keeps coming up that I think at least has some
00:44:14
grounding in reality okay what's the difference between a human taking
00:44:20
inspiration from a song they heard and then making new music and a robot taking
00:44:27
inspiration from millions of songs that it's heard to make some new music can you within a couple hours
00:44:35
scrape 180,000 songs word for word with picture perfect memorization of every
00:44:40
single word and everything in there no but what's the difference in
00:44:46
output we don't know what the exact output of this is but if it's saying just word for word things then I would
00:44:51
argue there's absolutely no it's just the exact same thing I guess if the
00:44:56
question is like my output that I'm asking for is I want a creative new
00:45:02
blues song for whatever give me a three minute creative new blues song in the
00:45:08
style that would go viral in 2024 and you ask a human to do that and he'll use what inspiration he or she will use
00:45:14
whatever they know and whatever they've heard recently and some of it's memorized and some of it's I kind of remember some stuff that went well and
00:45:20
if you ask the robot to do it both of them will take whatever they were inspired by whether it's 180,000 YouTube
00:45:26
transcri scripts or just the stuff that the human listened to recently and they will both output something genuinely new
00:45:33
cuz they're told not to copy they're told to make something new and what's the difference between
00:45:40
inspiration and scraping in a way that these models are turning that data into
00:45:45
new stuff I mean do you want the physical thing right now that is like YouTube doesn't allow you to scrape off
00:45:50
of its platform it's like literally against the term service or are you talking more broadly on I think more broadly because yes we can get into that
00:45:57
part a human is allowed to watch YouTube videos and be inspired by them sure and a robot is theoretically not allowed to
00:46:04
do that there is an aspect even in that where if inspiration comes too close to
00:46:09
copyright law it can still get in trouble yeah remember when um who was it that sued because the Vibes were the
00:46:15
same I thought Paramore and Olivia Rodrigo got a little too close in a song
00:46:20
There was yeah there there's been a bunch of lawsuit 100% happened before and appropriate things happened in
00:46:27
copyright also that's judged on the output not the input I I don't know if you can make a a
00:46:35
an Ethics claim based purely on like the the material of the output but I don't
00:46:40
think we should forget the the the the scale and then the idea of like who
00:46:47
actually gets to benefit from the work and you know what I mean like like at
00:46:52
the end of the day like none of us have a billion dollars you know we we don't have access to data centers it we would
00:47:00
all feel terrible about using an entire City's worth of energy in an afternoon you know like like nothing
00:47:07
about this is like is like good you know and and it's just a way for people who
00:47:14
already have a lot of resources to steal not just resources but the means of
00:47:19
generating more resources from people and then also I don't think we're quite there yet but I think we should all
00:47:26
start preparing our brains in the next like five years to just conclusively say
00:47:32
that like human beings matter more than computers like like that and that in my
00:47:38
opinion and hopefully the the robots don't kill me when they become STI it and like rise up or whatever but it's
00:47:44
like I think at a certain point we should all be prepared to be like this is better because it puts a human being
00:47:51
in a place of power instead of a instead of a computer which at the end of the day
00:47:58
it it's a it's a silicon wafer that I could crush with my toe you know it's I strongly agree with both those points CU
00:48:03
if we were to you know if you have a multi-billion dollar company nearly a trillion dollar multi-trillion dollar
00:48:09
company and you have like all the singer songwriters that are just like trying to make a living and then you just go I'm
00:48:16
just going to take everything you did and not learn how to play the guitar and write good songs and then replace all of
00:48:22
you with AI generated songs you can only do that cuz you're a multi tril company
00:48:27
and I know that there's like not like a necessarily legal precedent that makes
00:48:32
this like legally wrong but like do we collectively as a human species want to
00:48:39
allow that kind of thing to happen like like in the ad like in the reverse engineer situation where like a human being spends that tens of thousands of
00:48:45
hours watching YouTube videos learning how to use a camera like learning to edit at the end of the day what they
00:48:52
have accomplished is giving themselves a skill and they could now be a part of the conversation that is YouTube you
00:48:59
know what I mean but when aany like insert company name here does it and
00:49:04
then they can begin you know in theory launching thousands of YouTube videos
00:49:10
you're now seeing through every social media platform it's a very different Paradigm yeah yeah I guess I'm trying to
00:49:16
find the because it's kind of a gray area between those two things this entire conversation is a gray area by
00:49:22
the way this I just want to like put that out that that I don't think anyone here has the answer to this
00:49:29
certain existentially the is is valuable
00:49:34
obviously so the human wants to hear the Human music and the human wants to watch the human perform the skills obviously
00:49:41
and so we don't think that we would respond well to like a robot creation it
00:49:46
wouldn't have the same attribut well that's what I was going to say before to answer your question is how the human
00:49:52
receives the art I think that is the key point because if you show two outputs that are the same but you tell someone
00:49:58
the human made this one the human is going to inherently value that one more yeah right yeah someone should do that
00:50:03
blind test someone should do a control the scientific method like give watch
00:50:09
someone listen to a song when they are told that a human made it and then watch a bunch of people listen to the same
00:50:14
exact song when they were told that an AI made it and then afterwards ask what do you think and if you get told the
00:50:19
human made it you'll go oh that was really Soulful I could hear the inspiration and if you get told the robot made it you'll go that sounded
00:50:26
really Bland and generic and uninspired I wonder if it's just because we believe that the human made it probably but
00:50:34
also I feel like we just have to care more about the human generated stuff we
00:50:39
got to yeah because at the end of the day even if you even if there was quite literally no difference if if the blind
00:50:46
test proved that nobody could actually tell the difference do we want to live in a world where nobody makes
00:50:54
anything there is a world like that's the GD there there already to me is an example
00:50:59
of someone who scraped a bunch of data made a piece of art with AI that some
00:51:07
people knew as AI some people didn't know as AI but everyone loved and It ultimately didn't affect anything
00:51:13
because it was one human Creator just contributing to the conversation that is Art and what I'm talking about is the
00:51:18
song of the summer BBL Drizzy is that an AI song yes that is someone who trained
00:51:24
an AI on tons of different not a Kendrick song no no no no the the beat where the the singer is going BBL
00:51:32
Drizzy that's an AI that's an AI generated voice that's AI generated backing tracks metroo sampled that with
00:51:39
his human skill into a hip-hop beat but uh yeah so I I would argue there is room for human beings to use AI train their
00:51:49
own data sets scrape and steal and and not disrupt I'm going to keep using this
00:51:54
word conversation because I I really like it to to describe the exchange of ideas and Concepts I think a computer
00:52:01
could exchange could contribute to no a computer can a trillion dollar company
00:52:06
that can drastically alter the entire environment in which we
00:52:12
create can really and I'm gonna curse Ellis bleep this out later can really your up you know everybody's
00:52:19
shut up yeah anyway we got Way Off Track yeah well sorry that's okay we can go to
00:52:24
maybe a couple things here that are in the still gray but less gray area which are
00:52:30
middle gray middle gray just like yeah let's talk about first of all
00:52:37
scraping straight using the YouTube API subtitles yes so we have to look into this right yeah I spent a David and I
00:52:43
spent a long time yesterday going into this um and I found a couple different things or we found sorry what you find
00:52:49
mostly you Sundar and Nei talked on to coder about this was back when open AI was potentially scraping YouTube data
00:52:55
and allegedly allegedly sorry we're going to have to say a lot of allegedly um he responded that the YouTube team is
00:53:01
following up and that there are some terms and conditions and that they expect people to abide by those terms and conditions so that was like a very
00:53:07
vague way of potentially saying like we looking and it seems to go against our terms of conditions but I found a a much
00:53:14
more p uh precise quote from Neil Mohan um talking to Bloomberg the CEO of
00:53:21
YouTube saying that if Sor was using uh YouTube content it would be a clear violation he said uh from a Creator's
00:53:29
perspective when a Creator uploads their hardw work to our platform they have certain expectations one of those expectations is that the terms of
00:53:34
service is going to be abided by it does not allow for things like transcripts or video bits to be downloaded and that is
00:53:40
a clear violation of our terms of service those are the rules of the road in terms of content on our platform so
00:53:46
that is a very specific funny enough this was before all this came out but he even mentions transcripts right there
00:53:52
scraping transcripts and downloading them from YouTube is against the terms of service sounds pretty specific so
00:53:57
YouTube has a case here of something um what I found interesting also though is
00:54:04
we can all assume Google has their own Ai and Google has this gold mine of
00:54:09
content on their own platform yeah are they scraping um or not even scraping just
00:54:15
using or just using the stuff that they have already yeah Mohan mentioned something in that interview that I'm still not totally sure so I will let us
00:54:22
maybe figure it out because I couldn't get a deise answer precise answer and everyone else can think of it but he
00:54:27
said that Google which owns YouTube does use some YouTube videos to train its own AI platform Gemini but only if the
00:54:34
individual creators on the platform agreed to that in their contracts what I cannot figure out what that exact
00:54:39
contract means whether that is just the like contract the terms of service you have to agree to to upload literally
00:54:46
anything on their website whether it's the YouTube partnership program I looked at my contract contract which was my
00:54:53
terms of service yeah I didn't see anything spe specific to it but we were
00:54:58
talking yesterday it just like it wouldn't make any sense for Google to not do this like Reddit for example
00:55:05
sells its user data to AI companies as training data when you upload anything
00:55:11
to Reddit it is now the property of Reddit when you upload any images to Instagram those are now the property of
00:55:16
Instagram Adobe too anything you do on the Adobe platform trains its AIS I think you can opt out well there's a
00:55:23
whole thing around that that they allegedly they've said that they don't but it's a I don't know it's a whole
00:55:29
thing regardless it's just it's one of those things that's like Neil ver used very vague phrasing there and there's so
00:55:38
many times when you check the check box that says I agree to the terms of service and in the terms of service is a
00:55:45
thing that will give the company access to your information and your rights MH
00:55:51
it's very I don't I'm not going to say this is for sure but it's very likely that somewhere in the terms of service
00:55:58
gives YouTube the ability to co- license as we saw in their terms of service the
00:56:03
content on YouTube to other companies which you would assume they would do to Google yep because Google is YouTube and
00:56:09
YouTube is Google I would assume that I'm going to assume that that's the case we would love clarification on that for
00:56:14
sure anyone that works at YouTube Neil if you want to tweet at us or email us we'd love to know about that but it's
00:56:20
the it's the same Gold Mine analogy it's like Google has the best possible opportunity to train the best possible
00:56:26
model because they have the best possible source of information and if they weren't doing that from a business
00:56:31
perspective that would just be like stupid from a business perspective even though I don't think they should be
00:56:38
doing it you know Google would have more of an argument too of being like we're creating this platform that helps
00:56:44
creators flourish through different partnership programs where they can make money so like you know we're going to
00:56:49
also make some even more money on it it's still this weird I don't love it
00:56:55
but it's a way better better explanation than Apple taking or Nvidia taking this like random free
00:57:03
thing that definitely broke terms of service to get in the first place yeah I've recently asked Gemini to summarize
00:57:10
the latest MKBHD video and it did and there's there's an element of you know
00:57:17
how in fair use there's an element of like replaceability
00:57:22
so my work is considered derivative enough if it doesn't replace watching
00:57:29
the original work like if I make a commentary on someone's video but I don't use the entire video and I add my
00:57:35
own thoughts and it's transformative then it's not enough to uh replace watching the original video therefore it
00:57:41
is fair use but Gemini summarizing my latest
00:57:46
video feels like it can replace my video Yeah
00:57:52
and in order to summarize my video it needs to know on my video and be trained on my video so I I I would argue that
00:57:59
it's taking from me and replacing me in that in some way this is kind of the
00:58:05
reason that there's been this huge conversation in the last year or so around the streamers that just play people's videos and don't react don't
00:58:12
even really react to them and many of them will just leave the room while the video is being played yes because then
00:58:17
they're getting the benefit and it is replacing you and going and watching the video because the thousands of people
00:58:22
that are watching the streamer are not going to go to YouTube and watch your video they're just going to watch it on the stream yeah I've seen people do that
00:58:29
to my videos before yeah all the time which is not cool and it would be uh that would be a pretty good use of like
00:58:36
that that's the line there is some sort of copyright law that's been debated I think from open Ai and actual lawyers
00:58:43
about if some of the scraping data is considered fair use and I'm not exactly
00:58:48
sure where it is but even still pick your pick your option there's like a hundred different cases I'm sure there's
00:58:53
a billion different cases going on I just want to throw that there that the fair use aspect of scraping AI data and
00:58:59
using it for chatbots is being looked at right now but even still in this specific thing with the Luther AI that
00:59:05
we're talking about is they broke terms of service and that's far different from uh from does the terms of service say
00:59:11
that you can't scrape no matter what or only if you're making money on it because that's always kind of been the
00:59:16
question because you can upload a YouTube video that has a Taylor Swift song on it if you don't monetize it it's
00:59:22
true so I'm not totally sure that's kind of always the line I would assume most of
00:59:29
it is less of It's Always not allowed but we're much more willing to go after
00:59:36
the people making money it would be my guess also can YouTube even do anything about this if a Luther didn't sign
00:59:44
didn't agree to the terms of service like they're not that's also a great question yeah the that's that's true Did
00:59:50
did they even agree to the terms of service and uh is it more of just a
00:59:56
legal thing and also once Apple has already let's say apple and Nvidia and
01:00:01
others have downloaded this data but once Apple already trains their data and trains their models on all of this data
01:00:08
and then we find out oh actually some of this was not acquired legally or whatever how do you reverse that is that
01:00:14
reversible at all you have to retrain a new data set a new model which cost it
01:00:20
feels like that's a huge part of it too it's well it's already in the data so uh not much we can do this is the next
01:00:25
thing wanted to bring up in all of this is yeah what are our next steps here if they trained it already we just said you
01:00:33
don't you have to train a whole new data set which is none of these companies are going to do so much extra carbon in the
01:00:39
atmosphere yeah um but then it's like there's also the argument of what if you
01:00:45
like apple didn't take it Luther stole the the data and now Apple's taking it
01:00:51
but I just like did Apple pay for the data from Luther I'm assuming no I've
01:00:56
not seen anything about it but it's a free open source nonprofit set so I don't even know if they even PID an open
01:01:02
source set which means they probably didn't pay for it this is the exact same argument that happened with open a when they were training jck GPT and um Dolly
01:01:10
was that they used all of these open scraped model like open scrape data sets
01:01:15
online and so then they weren't like we didn't scrape it we just took this open available information they they get to
01:01:21
say publicly available yeah that sort of thing right some companies are partnering like we saw because we work
01:01:27
with VOX media for ads on this podcast and Vox partnered with open Ai and they're doing to train their data set it
01:01:35
was easy enough because we knew that happened we could talk to Vox it's just part of VOX media not part of their podcast Network we're not included in
01:01:41
that but that still is some sort of actual connection that they've made so companies do this do actually connect
01:01:47
with other media companies I think a lot of the companies are just real there's a really good interview between uh Nei and
01:01:53
Nick Thompson who is the uh I believe CEO of the Atlantic or the
01:01:58
editor-in-chief of the Atlantic he used to be the EIC for Wired um but he has he
01:02:04
gives a huge explanation about why he's partnering with open aai to give them access to the Atlantic for training data
01:02:11
and they have sort of like this back and forth where they both give each other things and I think the deal with open AI
01:02:17
is like it's it's better for open AI to just make a deal with all these media companies because they don't they don't
01:02:22
get sued like the New York Times sued them and they can kind of just give them credit and do all this different kind of
01:02:27
acquire with permission yeah yeah who wow what a concept concept some of these
01:02:32
companies are really struggling now would cost a lot of EXT so if you want to hear like a good sort of breakdown from from these Publications perspective
01:02:40
of why they may give their data to these companies you should listen to that interview it's on decoder I think with
01:02:47
taking the alther stuff all the companies taking from there need to pay the due diligence to realize where the
01:02:53
information is coming from and they are all more than capable of doing that and if that broke YouTube terms of service
01:02:59
they're pretty much just that at fault for not if if you steal something
01:03:04
talking about this yesterday like make the analogy of like selling stolen goods on Craigslist I I brought something up
01:03:09
this is in New York so I'm sure laws change state to state but to be convicted of possession of stolen
01:03:14
property actual knowledge of it being stolen is not required all that is necessary is that you should have known
01:03:20
that means the prosecutor must only prove a reasonable person would have known the property was stolen if you're getting tons of data for absolutely free
01:03:28
like you should probably know that there's something what do you mean I found this Rolex on Canal Street if you buy a bike on Craigslist for $40 that's
01:03:35
a $500 bike you should probably know that that is probably stolen and like a
01:03:41
Luther did not do this fairly and all the companies that pulled from this and threw it into their trainer training
01:03:47
data probably should have known something sketchy was going on or at least put the effort into figuring it
01:03:53
out right you can just make this analogy like steal a watch from someone on Canal Street and you now just say it's yours
01:03:59
like these that's what these companies are doing and we already it's it's already a problem when you uh rip off
01:04:05
people's writing right you can like take a big thing on Wikipedia change some words slightly and it's still plagiarism
01:04:13
this has been a huge conversation on YouTube in general recently because there's all these video essay uh YouTube channels that are literally just like
01:04:19
reading Wikipedia or reading books verbatim and then like putting Graphics over it and pretending that they wrote
01:04:24
the whole thing yeah and they'll just change some small sections and they be like it's not plagiarism I just took
01:04:30
heavy inspiration mhm and it's like no and if you're making a language model
01:04:36
and your whole model is based off of other people's work even if you're changing the words that's still heavy
01:04:42
inspiration and that's most of the New York Times lawsuit against open AI is kind of focused around this because they
01:04:48
they have many many many examples where they'll ask a question about a New York
01:04:53
Times about something that happened and it'll basically just almost verbatim say the New York Times article but it
01:04:58
changes some of the adjectives I guess my last question and maybe we can take a break after this is okay so we know that
01:05:05
these companies still want to make uh AI models and language models and things
01:05:10
like that what is the actual landscape of options for training data to make a
01:05:16
good model and I think that might be something that takes a whole lot more research that we don't know enough about
01:05:23
but it kind of feels like there are a relatively small number of absolutely
01:05:29
gigantic models and if you're Apple rushing into the scene where they
01:05:34
probably shouldn't be but uh not really being able to find huge models with
01:05:41
gigantic amounts of information that contain zero improperly acquired information that's a that's a question I
01:05:48
don't know the answer to I think all of these companies have the resources or I shouldn't say all of them all the ones
01:05:53
that we're talking about Apple Nvidia have the the resources to like be able to ask proper permission and have more
01:06:00
options than they could ever imagine and just pay people and pay just pay people if you're YouTube if you're Google and
01:06:06
YouTube you can say hey we would love to like train our models using your YouTube
01:06:12
transcripts uh we will pay you 5% more ad Revenue if you're willing to let us
01:06:17
scrape your transcripts what do you think if you're Reddit you could do the same thing if you contribute a lot will pay you based on how much you contribute
01:06:24
to Reddit keep conversations flowing the quality of your conversations stuff like that these are all trillion dollar
01:06:30
companies it's not like they can't afford to pay people they're the greatest and most intense nexuses of
01:06:36
information in the history of humanity like they they don't have the excuse to be like I don't know it's like you you
01:06:43
know you know as much as any entity has ever known ever right if you're Apple
01:06:50
there's a reason that they're going to these companies to buy SL license the data sets and instead of going out and
01:06:56
Gathering it themselves admittedly Apple's in a much worse position than all these other companies because their entire brand is privacy yeah personally
01:07:03
but I still think they can Go's do their research on figuring out data sets that aren't no that's my
01:07:10
question is what options are available is are there only 20 reasonably big data sets that they could trans like train
01:07:17
stuff on or are there bajillions of options I have no idea but I don't know the specifics of it but I'm sure there are plenty of options that have like are
01:07:24
we sure I don't know I hope so I'm sure they can find a way I'm sure they could afford to pay someone to make a data set
01:07:30
that was there's a before we go we we got to we probably wrap this up before we go to trivia but there's a very
01:07:35
similar thing going on in the art like the physical art World on the topic of Providence where a lot of museums
01:07:42
especially in New York are getting in trouble because most of their art is stolen and oh yes the the met over the
01:07:49
past few years has had to return over a thousand pieces to various countries and and the Museum's excuse is how are we
01:07:56
supposed to know it was stolen we bought it from a reputable art dealer who said it wasn't stolen how how are we supposed
01:08:03
to know and it on the surface it very much feels like oh like that's very reasonable like how can you if an art
01:08:10
dealer got it from another art dealer who got it from another art dealer who bought it from a thief how are you supposed to track that down but the
01:08:15
actual reality of the situation is almost never like that like there's this awesome article from a year or two ago
01:08:22
on icii which is an international journalist Consortium where they talk about there was an artifact that was
01:08:29
stolen from Southeast Asia in the 80s that appeared in the museum in the 9s
01:08:36
like it only took 10 years from stolen to in the museum and the museum was still like how were we supposed to it's
01:08:42
like dude you are the one of the biggest art museums in the world like if you don't know like doing your due diligence
01:08:48
basically yeah it's like it's like at a certain point like you have to own up to the amount of cred that you have and do
01:08:54
things the right way right right well that yeah it also gets into so many like ethical boundaries of like I mean they
01:09:00
have a bunch of Egyptian stuff direct from Egypt in the met and so there's all those questions of like well the British
01:09:08
stole everything so when the British eventually sold that stuff technically
01:09:14
all of it is stolen marz I I genuinely see where you're coming from and I don't have the answer your question which I
01:09:20
think proves your point to a large extent however I fun mentally in my soul
01:09:27
refuse to believe that this is not something that again the smartest most
01:09:34
valuable farthest reaching entity in the history of humanity can't accomplish I agree I
01:09:41
think I think you have a really strong case and I agree that it would make sense to believe that the strongest
01:09:47
entity in humanity ever should have the ability to solve any problem that Humanity comes up with but I still don't
01:09:55
know the answer to like I think I would love to see someone make an expose with whatever information is out there about
01:10:01
like what the world of these data sets is actually like because there are the data sets that are used by open AI open
01:10:07
AI is a several bazillion dollar company and they have to go get data sets like Google what are they using when you're
01:10:13
buying all of the content on Reddit and using Reddit information what does that look like and if you're apple and you
01:10:19
have no data sets how do you train a good AI where do you get that information I don't know any of the
01:10:24
answers and I would someone to find all the answers that would be a great expose
01:10:29
I hope nobody watching this thinks that our strong points on either side makes us think we do know the
01:10:37
answer this is just all a lot of arguing um we're making an ethical argument and that the these companies don't care at
01:10:45
all it they do not care because they're going to make more money even if they
01:10:50
get sued and they get caught they get trouble the amount of M sure yeah what
01:10:56
what's the say move slowly and keep things intact no I feel like that's not move fast and break terms of service
01:11:02
like nobody what immediately what we're talking about with is the more connection to us of scraping YouTube
01:11:07
videos is what probably will happen is if YouTube does anything Apple will and or a Luther or whoever will pay Google a
01:11:13
bunch of money and then all of the YouTube videos that got stolen will see absolutely nothing of that yeah I do have to say it is crazy surprising that
01:11:20
Google has not done anything about all of these companies that have obviously been scraping YouTube and breaking their
01:11:26
terms of service it is wild yeah the transcript exposed in the API and I don't know that there's any I don't know
01:11:32
what their method of protecting that information would be I guess wait sorry now to go all the way back to did they
01:11:37
agree to the terms of service if you use the YouTube API you have to do you have to agree to terms of service by using
01:11:43
that I believe so so that might answer that question but yeah I don't know I don't know anything about the API they
01:11:49
might just have built a bot that can like scrape I'm not 100% sure but I thought a Luther said they used the AP
01:11:56
specifically I use the API for some of our data collection and yes you do need to agree to certain terms of service
01:12:03
Apple's going to eat what are you colle what are you collecting for our Channel anyway um companies don't have
01:12:10
your best interest in heart and they like to make money more at
01:12:16
11 I guess that's where we should take it to Tria I'm so sorry guys that was
01:12:21
pretty intense the rabbit hole kept opening it's always fun when you go down in an ethical the Pod was supposed to go
01:12:29
live 10 minutes ago all right it was cold when we started this and now my hands are I told you not to turn off the
01:12:34
AC I know you're right second question in 2013 Google launched their first
01:12:40
consumer Hardware device what was it in what year 2013 2013 they lost their first Google
01:12:47
Hardware consumer hard device Hardware device consumer uh Hardware 2013
01:12:55
2013 oh I have an answer I got to write this down before so was 2008 and the
01:13:01
Nexus S not consed a consumer Hardware device Google didn't make it oh we'll
01:13:08
see I don't know if it's right we'll brainstorm it a little more we got more to talk about believe it or not I have
01:13:14
idea yeah we'll we'll we'll be right back in [Music]
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for all right welcome back I have one last thing to talk about it is kind of random offthe wall but every time Canon
01:16:48
comes out with a new mirrorless camera they absolutely nail it with
01:16:54
every every single new spec they finally added the thing that we were begging them to add except and then they mess up
01:17:01
one thing that makes it critically flawed and kind of an issue they make
01:17:06
amazing cameras I just have to say like we we still use a lot of Canon cameras I'm looking right at it see c100 C300 we
01:17:12
shoot c70s for Studio we have r5s everywhere 500 I love these things right they're
01:17:18
really really good but R5 you might remember had the overheating issue like the really good cameras great autofocus
01:17:24
a whole bunch of awesome stuff and then like ah but it overheats when you shoot AK or they have like a really great Vlog
01:17:31
camera that's finally smaller and finally has great codec and oh but the camera doesn't flip around or the the
01:17:38
monitor doesn't flip around the r5c was everything we wanted but the battery lasts 20 minutes and doesn't have I
01:17:43
would argue almost this I Ibis yeah can I argue this happens with just like mirrorless cameras cuz this happens with
01:17:49
Sony too they like do all these cool things and then the like flip up screen only flips up so if you have an external
01:17:55
microphone or then they fix that and flip to the side but that's where the microphone audio jack was it to be
01:18:02
imperfect so that they can release another camera that you'll buy well this brings me to the newest announcement yeah and I'm looking at it and I
01:18:09
personally don't see the Achilles heel someone's going to point it out in the
01:18:15
comments and break my heart but as of right now Canon's release two new cameras the R1 but also the R5 Mark I
01:18:22
this R5 Mark I I think for 4 300 bucks is going to be pretty sick 8K 60 clog 2
01:18:30
got added uh fullsize HDMI port instead of that dinky like mini HDMI on r5i 4K
01:18:38
120 with audio oh it has a cooling battery grip so obviously there's a
01:18:43
firmware update a while ago to like improve the the cooling on the R5 but a cooling battery grip to have longer
01:18:49
battery there's like more specific batteries for this but it shouldn't overheat M it has electronic
01:18:54
stabilization that works with the stabilization built into RF lenses I mean I'm I'm going down this
01:19:01
list and I'm like seems like a pretty sick camera records onto micro
01:19:07
SD I'm like oh my goodness it still has all the fundamentals it's like it's still a good siiz camera it still has
01:19:14
it's 45 megapixels it takes fast Stills like all the things that you'd normally expect out of a camera so I'm I'm
01:19:21
worried about what might go wrong when reviews come out but as of right now I
01:19:26
think R5 Mark I is is that camera I'm trying to confirm this but I think I may
01:19:33
have found something I can't see a picture is a sensor a triangle what's going on no I I really liked that joke
01:19:40
this morning like that would okay so what one of the coolest things I think about the R5 mark1 that we have is every
01:19:45
time you take the lens off the shutter shuts and it protects the sensor and I think every single camera should have
01:19:52
that there's just a photo here and it looks like the sensor's just open but
01:19:58
maybe he did that on purpose but if they took that away from this one no it has it still it still has it yeah I saw it
01:20:03
in Peter's video okay good yeah I think every single mirrorless camera needs or every single DSLR needs that it's good
01:20:09
feature cuz are mirrorless and they get little dust particles on the sensor all the time if you're changing lenses all
01:20:14
the time it just makes you feel so much better I'm just saying Canon people let me know what I'm missing because I think
01:20:21
I think I'm going to end up spending $44,000 on one yeah on one 42.99 specifically 4,300 it's not cheap
01:20:29
I don't want to go buying a bunch of stuff but like that's it also has itrack autofocus so you can look at the thing
01:20:35
you wanted to focus on and and I'll focus on that wait what yes and I want to point out that a film camera from
01:20:42
Canon actually had this back in the day and it was sick so when you're saying eye tracking you don't mean it's
01:20:48
tracking the eye of what I'm shooting it's using my eye and which autofocus
01:20:53
point I look at to focus on the subject yes what's what's wrong with this camera
01:20:59
wait I don't know if I like that something is going be horribly wrong with this camera yeah you yeah you you basically just look at what you want it
01:21:05
to focus on and it changes the focus to it but there are sometimes where I'm like looking at something behind the subject just to like watch it go out of
01:21:12
frame or something like that so it's just going to focus on that oh wait hold on hold on sorry I
01:21:19
need to confirm here so if you're looking through the evf what you're looking at yes okay I I thought you
01:21:24
meant like if I were in frame and I like put something up in front of me and looked at it it would rack Focus to that
01:21:30
that's really cool and they had this in the Canon EOS 5 also known as the A2 and
01:21:35
a2e we have one of those film cameras Oh yeah film cameras H we um yeah and it
01:21:42
was super cool and now I imagine it is way way way better than it was back in the day but they call it uh I A2 and I
01:21:50
imagine the first one was i1 I just remember seeing this on the that film camera being like why has nobody done
01:21:56
this again sick and if it's bad you can just turn it off exactly wow yeah it's pretty awesome I'm scared there will be
01:22:03
something wrong don't worry I'm scared we'll find out when Mar I'm reading comments on this to see it also says
01:22:08
they have clog 2 and for those that don't know uh for some reason the R5 has clog 1 and clog 3 log profiles shoot
01:22:15
very flat so that you have a lot of room to grade famously seog one and seog 2 are not good uh I do not like them at
01:22:22
all seog 2 we like SE two very good and they've always they've
01:22:28
always we like theyve always kept those for some reason for the um the C Camas
01:22:33
the C cameras and I know you know there's a reason for it obviously they don't want to cannibalize their own Market they are so worried about that
01:22:39
all the time so bringing that onto this I think it's going to be awesome that's what scares me CU like you would think like r5c Mark I would have this but the
01:22:46
fact that they're bring this to R5 I keep thinking like what did they nuke yeah what did they do something's
01:22:51
missing is it see like too light it's like walking up to like what's in your mouth what's in your mouth what did you
01:22:57
do triy I don't know what it is but it's going to be crazy okay well you know we might have to get one did you mention
01:23:03
fullsize HDMI full size yeah the real deal I can we just plug right into a monitor I feel like we lose those stupid
01:23:10
adapters every single time we get one we're like or they break they're so so Fini they're not durable they also
01:23:16
announced the EOS R1 which is $6,300 like the flagship the sports the
01:23:22
sports photograph it is basically the version of the
01:23:27
1dx um and it does 40 FPS raw yeah which is crazy it's 24 24 megapixel but it has
01:23:35
some in camera um AI upscaling thing that can apparently upscale it to a much
01:23:42
higher resolution okay so very interesting we've been wondering for like a lot of years when our camera is
01:23:48
going to start catching up to smartphones in terms of like the computational photography and processing
01:23:53
and it seems like that's finally happening um but apparently it can
01:23:59
generate a 96 megapixel image I'm not as worried about that sucking because like
01:24:05
a smartphone sensor and Optics are so small that like you kind of need some computational assistance to make a great
01:24:11
big image I mean you're you're I'm looking at a film person like the bigger the sensor the bigger the Optics the more room you have to make good images
01:24:18
MH and I'm not surprised that a full-frame sensor with a huge lens can
01:24:24
be upscaled and still look good yeah or like a crappy 12 megapixel camera phone photo needs help there's no light intake
01:24:31
at all so like a a fast Sports photo like okay give me a give me less megapixels on the raw capture but then
01:24:37
you can upscale and have a good- looking image yeah and 24 megapixels on a fullframe sensor you're getting a quite
01:24:42
a bit of light on each pixel exactly so yeah that's exciting I found something on the R5 Mark to that let me know if
01:24:49
this is a problem oh my God new battery type none of the old ones work saw that saw that I am willing to accept that
01:24:57
because it seems like it should still cuz there's new grips and stuff it should still it should have better battery life and I don't have a ton of
01:25:04
R5 batteries anyway so I'm not mad about losing that and if you're a new purchaser and didn't have the previous
01:25:10
ones that doesn't affect you at all so that does suck if you're upgrading yeah but it feels Standalone enough to not be
01:25:17
I have like three R5 batteries or something all right I'll keep looking for a deal breaker it's I also the
01:25:23
cooling grip is $750 damn I want to know really quickly that they did put that ey tracking in
01:25:29
the Eos R3 which is the apsc camera that they made the lens for for the Vision
01:25:34
Pro right that's the r s sorry they put in the R3 which I don't really know a lot about the R3 but apparently they put
01:25:40
that in there first so this is the second camera to have it you know they go the opposite direction of Audi
01:25:46
models as far as like names versus size this is such a stupid comment why am I even saying why is this coming out of my
01:25:52
mouth RS RS3 RS5 RS7 gets bigger but
01:25:58
like R1 is the biggest one R3 is smaller R5 Canon's always done this though right
01:26:03
like 1D 1D 5D was a big boy yeah yeah I don't know why I even said that anyway
01:26:10
what is coming out of my mouth why am I saying I should stop and think first what what language model am I being run
01:26:16
on right now anyway we've we've talked for so long we should we should do trivia let's do trivia let's do trivia I
01:26:22
feel like this might be the longest episode might [Music] be
01:26:28
we're we're off from last week's episode still by like 20 plus really minutes and
01:26:34
that's with goofing around for 15 minutes in the beginning goofing around
01:26:40
question number one trivia let's kick up the energy trivia dude web crawlers we
01:26:45
know him as web crawlers when I say WebCrawler everybody knows what we're talking about but google.com some people
01:26:53
use different words I have three of them one of them is
01:26:58
possibly fake which one did I make up hit
01:27:04
it a spider B automatic
01:27:11
indexer C web Scutter or D these are all real and I
01:27:18
didn't make anything up at all before I thought you going to say I
01:27:26
say web you say Scutter no web scraper
01:27:31
out of the gutter nice what have we got boys oh wow we all said different things
01:27:38
and you're all wrong was D but you should read your answers anyway all right I wrote
01:27:44
c sper x I wrote the AI one unfortunately no spider was used by
01:27:51
Scott spa and his early paper robot or the robot uh colon Beyond browsing
01:27:57
computer research paper automatic indexer was used by May Kobayashi and I forget his first name but the last name
01:28:03
is teada in a 2000 paper uh sponsored by IBM called information retrieval on the
01:28:09
web and web Scutter is present in the F official documentation Paradigm which I
01:28:16
think some of was written by Tim burner Lee but I'm not going to say that actually I
01:28:22
I I think it might have been but I'm not really sure and D the correct answer is these are all real I couldn't come up
01:28:29
with anything funny this week guys I'm sorry all right all right all right all right I'll never forgive you D it's so crazy how David knew all of that and he
01:28:36
still got it wrong I know damn wild know every time I'm just trying to I'm ahead
01:28:41
I'm ahead so I'm trying to like give you guys a yeah that's fair quick update on the score are you ahead Dam yeah Marquez with
01:28:47
14 Andrew with 13 David with 14 oh Ellis the one Oh I
01:28:54
thought it was one point over no you're one point over Andrew but you and Marquez are tied up really got him all
01:29:00
right right where I want to be second question in 2013 Google launched the first consumer Hardware device that they
01:29:07
ever launched what was it I think therefore I
01:29:14
am I think I still have it really wait
01:29:20
really hm wait 2013 trying to get a action to see oh no
01:29:26
oh yeah is it what I think it is no I don't know if I'd consider that
01:29:32
consumer Hardware oh yeah I think from before
01:29:39
2013 okay what do you got I don't know David play it
01:29:45
Chromecast oh job Andrew when you said I wrote Chrome book Marquez I wrote the
01:29:52
Chromebook CR 48 nope their first ever consumer Hardware device was the
01:29:58
chomecast 201 wait when was that 2013 but the the CR 48 was 2010 who made it Google but
01:30:06
wasn't the question in 2013 well I just happened to come up with the actual
01:30:13
first huh um you know what I mean I feel you I feel like I'm right I only agree
01:30:19
with Marquez if just saying Chromebook also counts that where did you get the answer from from Adam the keyword which
01:30:26
is Google's blog what did Google say they said the Chromecast chomecast they said the chomecast is the first consumer
01:30:32
the first consumer Hardware device Hardware device chook Google wow that's weird that they would forget about their
01:30:40
own it uh yeah it's all matte black no logos anywhere what if we both
01:30:46
Chromebook holy crap I in real time Marquez has Unearthed a pro a product
01:30:52
that is older than the chomecast you're not shocked that Google forgot about one of their own no I'm not shocked that
01:30:58
they forgot about their own product petition for us to all get a point because we're all I think we should all get points CU we're all you came up with
01:31:03
the answer that Google somehow thought was the right answer and so you should get a point for that I came up with the
01:31:09
actual answer which is their actual first consumer Hardware product and I stumbled
01:31:15
upon wait wait wait wait wait but if but Tech if we're letting the c48 in then
01:31:21
wouldn't just the G1 be the first Google consumer Hardware product cuz that's as much Google made as yours what I'm
01:31:28
looking at is a 2013 Chromebook that was an HTC HC logo on it yes but yours doesn't
01:31:36
have an Acer logo on no it doesn't it doesn't have a logo it has no logo but also if we gave Andrew the point and
01:31:42
didn't give it to either of you guys you would all be tied at 14 and I think that makes the game really fun I no what what
01:31:48
are you talking about there's no world where David shouldn't get a point I agree but there's also no
01:31:54
that Andrew gets a point and I don't unfortunately I think both of
01:32:00
those worlds are the ones we currently inhabit what are you talking about this is insane is it that insane this is
01:32:07
crazy yes it is insane okay also idea low key Crum pixel was I'm going to
01:32:12
suspend the points from this week what and make a poll on threads and Twitter
01:32:19
and let YouTube Community sure YouTube Community YouTube Community YouTube community so don't tell them who said
01:32:26
which answer I just want to say I did not expect this question to be so controversial because I thought Google
01:32:32
would have gotten this pretty straightforwardly right but turns out their blog is wrong they they must have
01:32:38
used the like AI generated results to write this who wrote it actually yeah can we confirm that this keyword post
01:32:44
was not written by an AI it was not and I'm not putting them on blast so go to YouTube community and vote on who gets
01:32:52
the correct point and I will update next week is what are you listing all three and is it multiple choice each of our
01:32:58
names and everyone gets a point or just each of our just the Chromebook yeah
01:33:03
Chromebook what was it p48 c48 c48 chomecast chomecast are you just letting
01:33:09
people decide yes because I where does the Nexus Q fall let let people vote too
01:33:16
late you can't just do that we live in a democracy David anyway final answer is
01:33:23
the chomecast vote in the poll I hope it's like multiple choice so you can pick like two
01:33:28
instead of just one but anyway we'll pause points till next week to figure that one out thanks for voting um yeah I
01:33:36
guess that's it thanks for watching stop the ballots thanks for watching thanks for listening we'll be back to regular
01:33:42
length podcast next week I promise I swear we willon allegedly allegedly see
01:33:48
you then waveform was produced by Adam Molina and Ellis Ren we're partner with VOX media podcast Network and our interapt Music Quiz vinil Bingo make
01:33:56
good choices make good choices and we didn't steal any of this I'm
01:34:19
sticking we could make that into a paid service you know we to your fiber task
01:34:25
grabit we come to your house and just make Mario sounds
