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Date: Fri, 11 Jul 2025 18:07:39 +0100
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I hope you enjoyed free access to Wednesday’s issue of The Hidden Layer, Ian 
Krietzberg’s new private email on the artificial intelligence industry. 
Given how many readers enjoyed his first dispatch, we decided to also unlock 
his second official email—featuring a must-read interview with Runway 
co-founder Anastasis Germanidis, plus additional exclusive intel—to give you 
another taste of his remarkable reporting on the complex world of A.I.









Hi again,



I hope you enjoyed free access to Wednesday’s issue of The Hidden Layer, Ian 
Krietzberg’s new private email on the artificial intelligence industry. 
Given how many readers enjoyed his first dispatch, we decided to also unlock 
his second official email—featuring a must-read interview with Runway 
co-founder Anastasis Germanidis, plus additional exclusive intel—to give you 
another taste of his remarkable reporting on the complex world of A.I.



If you like what you read, make sure to take advantage of our limited-time 
offer of 25% off an annual subscription to Puck with code THEHIDDENLAYER at 
checkout, which also unlocks access to all our industry-defining 
newsletters.



Enjoy!









Born to Runway



A candid conversation with Anastasis Germanidis, the C.T.O. and co-founder 
of Runway, the major A.I. image- and video-generation company, about the 
trouble with building “world models,” the next steps in advancing the 
technology, the highly contentious issue of automated media, and much more.




 	Ian Krietzberg




A classic concept in cognitive science is what researchers call mental 
models—or how our internal representation of the external world informs how 
we navigate reality. An illustrative example: Michael Jordan was able to 
close his eyes and still make a free throw because his “mental model” 
included the exact size, height, distance, etcetera of the basket, and that 
doesn’t go away just because you close your eyes. A neural network–based 
system, lacking a reliable model of the physical world, would likely not be 
able to make that free throw. This shortcoming has increasingly become a 
point of focus for A.I. companies, who are attempting to build their own 
“world models” (another term whose definition changes depending on whom you 
talk to) in order to provide machines with a stable, physically accurate 
internal representation of certain parts of the external world. For the 
self-driving car company Waymo, that could mean a world model designed to 
simulate traffic patterns. For chess-playing machines, it could be what 
author and cognitive scientist Gary Marcus recently referred to as “board” 
models, which offer rule-based, constantly updating representations of a 
given game board.

So far, there’s no evidence that large language models possess world models, 
even though some researchers and engineers believe they might naturally 
emerge over time. And it is this absence of grounded, rules-based modeling, 
Marcus recently argued, that explains why L.L.M.s often “hallucinate” in 
strange and unexpected ways: “What L.L.M.s do is to extract correlations 
between bits of language (and in some cases images) but they do this without 
the laborious and difficult work (once known as knowledge engineering) of 
creating explicit models of who did what to whom when and so forth,” he 
wrote.

It’s a problem that Runway, the pioneering A.I. image- and video-generation 
company, is hoping to solve. The company, founded in 2018, has raised $536 
million from investors such as Nvidia and Softbank, according to Crunchbase 
data, and has secured a partnership with Lionsgate Studios. (Runway’s models 
were notably leveraged by visual effects artist Evan Halleck when he was 
working on Everything Everywhere All at Once in 2022.) But taking the 
software to the next level requires eliminating those often-viral 
hallucinations that might show, for example, seven fingers on a man’s hand, 
or a bunch of dogs merging out of one dog, or a cat sprouting random 
additional limbs. These generations are the result of massive statistical 
analyses—not an actual understanding of physics, or human hands, or cats.

To learn how Runway is tackling this problem, I caught up with Anastasis 
Germanidis, the company’s C.T.O. and co-founder. This conversation has been 
lightly edited and condensed for clarity.



World Simulators



Ian Krietzberg: Runway is an image- and video-generation company. How do you 
go from that to building world models?

Anastasis Germanidis: We did a lot of the foundational research in image and 
video generation, and what we saw as we were building better and better 
video generation models is that, in order to solve video generation—to 
generate videos that are physically realistic, high quality, and high 
fidelity—those models essentially need to learn how to simulate the world. 
They need to understand physics, and understand how humans interact in 
space, and to understand different aspects about the world, and the dynamics 
of the world. This created our initial interest in building world 
simulators, as we call them.

Can you say a little more about the application of “world simulators”?

There are, I would say, two broad areas of world simulators that are 
interesting from a use-case perspective. One involves creating new forms of 
entertainment—and this is something we’re increasingly going to be doing on 
top of those models. Imagine gaming experiences where a game is generated as 
you’re playing it. We imagine most video generation will become real-time 
and personalized, and it will be generated on the fly as you’re experiencing 
it.

The other aspect where world simulation is very relevant, I think, is that 
simulation will essentially power most model training in the coming years. 
Because if you want to build models and systems that can operate in the real 
world—like robots that can help you with household tasks—it’s much more 
effective to train them in simulated environments versus deploy them in the 
world. And that same [thing] applies in robotics and in building 
self-driving cars.

Models today are limited in their capacity to consistently and reliably 
produce physical representations of the real world. Are you exploring other 
architectures? Do you think the neural networks of today will become more 
capable?

There are always algorithmic advancements being made, and we’re working on 
new types of architectures. So traditionally, on image and video generation, 
diffusion models were the architecture of choice, while in language models, 
it’s autoregressive models. What we’re increasingly seeing is a convergence 
between the two—the best of both of those worlds—and we’re working on some 
new architectures along that direction.

But I would say, more than the architectures themselves, the way you’re 
training those models will be the thing that changes the most. So 
effectively, training models to perform tasks in simulated environments over 
long time horizons will become the way to further improve performance, more 
than any specific algorithmic improvements.

You’ve said that one of the biggest bottlenecks involves ensuring that these 
model simulations are physically realistic. How do you overcome that 
bottleneck?

You overcome the bottleneck by essentially scaling those simulators with 
enough data and compute: finding a sufficient amount of data that captures 
the environment that you want to simulate, and then increasing the model and 
compute scale.



The Bitter Lesson



You mentioned self-driving cars as an example of how world models can be 
applied. But the problem with self-driving cars is that it’s a physical 
impossibility to capture sufficient data for all possible edge cases. And 
that gets us to the root question around genuine machine understanding and 
generalizability: We’re trying to brute-force our way to simulating 
generalizability, but it’s not really generalizability, because it’s built 
on such a massive scale rather than on systems that can reliably generalize 
based on a small dataset. Are you at all exploring methods of world modeling 
that don’t rely on massive scale?

Are you familiar with “The Bitter Lesson”? The thing that has repeatedly 
worked in this field has been finding the methods that can leverage more 
compute and more resources, and increasing the scale that you apply them at. 
There are going to be improvements in data efficiency—learning from less 
data—but I don’t expect that to be the biggest driver of progress. We still 
haven’t trained on a sufficient amount of observations from the world. I 
think we’re still very early in leveraging all the data and all the 
observations that are available. So I don’t think we’re anywhere close to 
actually saturating  that available data.

What does this all mean for Runway as a business? Are you eyeing a push 
beyond simple image and video generation?

Yeah, I think the potential of those models goes beyond content creation. I 
would say gaming is the most proximate area that we’re exploring. We have a 
new platform that we call Game World, where essentially anyone can generate 
a new world from a premise, and by kind of describing the game mechanics, 
they can then create a game they can share with others. But beyond gaming, 
there are applications that we’re exploring in robotics and in self-driving 
and a few other areas. We do think those models are very general, and so we’re 
going to be announcing some different collaborations and partnerships on 
many different fronts.

That opens up the highly contentious issue of automated media, which has 
already been resulting in job loss within these industries. Do you see this 
as something that will be associated with a reduction in the necessary 
workforce?

I think that there’s definitely going to be a change in the roles and the 
kind of jobs that someone working in gaming, for example, would perform. 
Traditionally, with new technologies, they end up expanding what jobs are 
possible. We saw that with different generations of creative software as 
well—there was the narrative that Photoshop would destroy all visual art or 
visual design. I think the same will happen with gaming.

There’s still going to be a big importance on taste and vision and coming up 
with the best ideas and designs for game experiences—but the creation of 
those games will not look the same as it looks today. You might not need to 
create every single asset and every single object in the game world. It’s 
more about designing the overall rules of the system. Maybe the absolute 
number of games will increase, and the kinds of things that you can do as a 
game designer will change, but I don’t necessarily see it as a reduction in 
the amount of jobs that are available in this field. It’s more going to be a 
change.

Artificial general intelligence is practically meaningless as a term, but is 
Runway interested in becoming an A.G.I. lab?

To me, simulation goes beyond A.G.I., and I also think the goal of getting 
parity on tasks with humans seems like it’s not the right goal to strive 
for. I think we should use A.I. techniques to go far beyond and augment 
human ability. So I wouldn’t call ourselves an A.G.I. lab., and I think even 
A.G.I. labs will move beyond this goal, because really what you want is to 
expand what humans can do to accelerate scientific progress, to solve all 
those different challenges. And that doesn’t necessarily mean that you need 
to get as good as humans in those challenges. You need to build systems that 
go beyond what humans can do.





Hope you enjoy this rainy weekend. I’ll see you next week.

Ian




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MjUlMjlcdTAwMjZ1dG1fY29udGVudD1UaGUrSGlkZGVuK0xheWVyK0FjY2VzcytOb24tVEhMK=
y0rQWxsK0xFQURTKyUyODclMkYxMSUyRjI1JTI5XHUwMDI2dXRtX21lZGl1bT1lbWFpbF9hY3=
Rpb25cdTAwMjZ1dG1fc291cmNlPWN1c3RvbWVyLmlvXHUwMDI2dXRtX3Rlcm09ZjZjNjA2MTV=
lM2QzMDFkNDhkMjgiLCJpbnRlcm5hbCI6ImY2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwibGlua19p=
ZCI6MjI2NjM3MX0/d462ed08c1a04cebe8a0985a0fc228e97bedccfd8119421ae7d2a2526=
5c2666f" =
style=3D"text-decoration:underline;color:#d40000;">checkout</a>, which =
also unlocks access to all our industry-defining =
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style=3D"margin:0;">Enjoy!</p></div>
</td></tr></tbody></table>
<table class=3D"divider_block block-2" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"pad" style=3D"padding-bottom:32px;"><div class=3D"alignment" =
align=3D"center">
<table border=3D"0" cellpadding=3D"0" cellspacing=3D"0" =
role=3D"presentation" width=3D"30%" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"divider_inner" =
style=3D"font-size:1px;line-height:1px;border-top:2px solid =
#d40000;"><span style=3D"word-break:break-word;">=E2=80=8A</span>
</td></tr></tbody></table></div>
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</td></tr></tbody></table>
<table class=3D"row row-3" align=3D"center" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td>
<table class=3D"row-content stack" align=3D"center" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;background-color:#ffff=
ff;border-radius:0;color:#000000;width:600px;margin:0 auto;" =
width=3D"600"><tbody><tr><td class=3D"column column-1" width=3D"100%" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;font-weight:400;text-a=
lign:left;padding-bottom:12px;vertical-align:top;border-radius:0px;">
<table class=3D"image_block block-1" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"pad" style=3D"width:100%;"><div class=3D"alignment" =
align=3D"center"><div style=3D"max-width:600px;"><a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9wdWNrLm5ld3MvaG=
93LXJ1bndheS1pcy10cnlpbmctdG8tc29sdmUtYWktaGFsbHVjaW5hdGlvbnMvP3V0bV9jYW1=
wYWlnbj1UaGUrSGlkZGVuK0xheWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTKyUyODcl=
MkYxMSUyRjI1JTI5XHUwMDI2dXRtX2NvbnRlbnQ9VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrT=
m9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9tZWRpdW09ZW=
1haWxfYWN0aW9uXHUwMDI2dXRtX3NvdXJjZT1jdXN0b21lci5pb1x1MDAyNnV0bV90ZXJtPWY=
2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwiaW50ZXJuYWwiOiJmNmM2MDYxNWUzZDMwMWQ0OGQyOCIs=
ImxpbmtfaWQiOjIyNjcyMjR9/e56ea98abf2911e48818108885ec6db3daa5f08f8c76d714=
1a2637483ca9b1db" target=3D"_blank"><img =
src=3D"https://userimg-assets.customeriomail.com/images/client-env-107382=
/1752181276044_THL_01JZV28ZEQGCNGVRC8JTFWE1PP.jpg" =
style=3D"display:block;height:auto;border:0;width:100%;" width=3D"600" =
alt=3D"Born to Runway" title=3D"Born to Runway" =
height=3D"auto"/></a></div></div>
</td></tr></tbody></table>
<table class=3D"heading_block block-2" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"pad" =
style=3D"padding-bottom:16px;padding-left:24px;padding-right:24px;padding=
-top:16px;text-align:center;width:100%;"><h1 =
style=3D"margin:0;color:#000000;direction:ltr;font-family:&#39;PuckSerifD=
isplay&#39;,&#39;Georgia&#39;;font-size:48px;font-weight:400;letter-spaci=
ng:normal;line-height:1.2;text-align:left;margin-top:0;margin-bottom:0;
mso-line-height-alt:58px;"><a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9wdWNrLm5ld3MvaG=
93LXJ1bndheS1pcy10cnlpbmctdG8tc29sdmUtYWktaGFsbHVjaW5hdGlvbnMvP3V0bV9jYW1=
wYWlnbj1UaGUrSGlkZGVuK0xheWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTKyUyODcl=
MkYxMSUyRjI1JTI5XHUwMDI2dXRtX2NvbnRlbnQ9VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrT=
m9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9tZWRpdW09ZW=
1haWxfYWN0aW9uXHUwMDI2dXRtX3NvdXJjZT1jdXN0b21lci5pb1x1MDAyNnV0bV90ZXJtPWY=
2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwiaW50ZXJuYWwiOiJmNmM2MDYxNWUzZDMwMWQ0OGQyOCIs=
ImxpbmtfaWQiOjIyNjcyMjR9/e56ea98abf2911e48818108885ec6db3daa5f08f8c76d714=
1a2637483ca9b1db" target=3D"_blank" =
style=3D"text-decoration:none;color:#d40000;" =
data-mce-attribute-name-1=3D"" data-mce-attribute-value-1=3D"" =
data-mce-attributes-count=3D"1" rel=3D"noopener"><span =
class=3D"mce-content-body mce-edit-focus" =
style=3D"word-break:break-word;position:relative;" =
id=3D"754a41d7-a645-4b0f-8c0a-69511ffb9576" data-position=3D"40-0-1" =
data-qa=3D"tinyeditor-root-element">Born to Runway</span></a></h1>
</td></tr></tbody></table>
<table class=3D"paragraph_block block-3" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;word-break:break-word;=
"><tbody><tr><td class=3D"pad" =
style=3D"padding-left:24px;padding-right:24px;"><div =
style=3D"color:#000000;direction:ltr;font-family:&#39;Inter&#39;,&#39;Ari=
al&#39;;font-size:19px;font-weight:400;letter-spacing:0px;line-height:1.5=
;text-align:left;mso-line-height-alt:29px;"><p style=3D"margin:0;">A =
candid conversation with Anastasis Germanidis,
the C.T.O. and co-founder of Runway, the major A.I. image- and =
video-generation company, about the trouble with building =E2=80=9Cworld =
models,=E2=80=9D the next steps in advancing the technology, the highly =
contentious issue of automated media, and much more.</p></div>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table class=3D"row row-4" align=3D"center" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td>
<table class=3D"row-content stack" align=3D"center" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;background-color:#ffff=
ff;border-bottom:8px solid transparent;border-left:24px solid =
transparent;border-radius:0;border-right:24px solid =
transparent;border-top:8px solid =
transparent;color:#000000;width:600px;margin:0 auto;" =
width=3D"600"><tbody><tr><td class=3D"column column-1" width=3D"100%" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;
font-weight:400;text-align:left;border-bottom:1px solid =
#d40000;border-top:1px solid =
#d40000;vertical-align:top;border-radius:0px;">
<table class=3D"icons_block block-1" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;text-align:left;line-h=
eight:0;"><tbody><tr><td class=3D"pad" =
style=3D"vertical-align:middle;color:#d40000;font-family:&#39;PuckSerifDi=
splay&#39;,&#39;Georgia&#39;;font-size:20px;font-weight:400;padding-botto=
m:8px;padding-right:8px;padding-top:8px;text-align:left;">
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adding-left:0px;padding-right:0px;" cellpadding=3D"0" cellspacing=3D"0" =
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<!--<![endif]--><tbody><tr><td =
style=3D"vertical-align:middle;text-align:center;padding-top:0px;padding-=
bottom:0px;padding-left:0px;padding-right:0px;"><a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9wdWNrLm5ld3MvYX=
V0aG9yL0lhbi1LcmlldHpiZXJnLz91dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXllcitBY2N=
lc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9jb250=
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jExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2=
U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIsImludGV=
ybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX2lkIjoyMjU4MDMwfQ/f5d84b0d0=
82d8c25c6c25689d415755e5941b652f6219a8be670a477bf46fa1d" =
target=3D"_self" style=3D"text-decoration:none;"><img class=3D"icon" =
alt=3D"Ian Krietzberg" =
src=3D"https://userimg-assets.customeriomail.com/images/client-env-107382=
/1748887621842_avatar-ian_01JWRX6M8H1QYPP3CAF3J03PYH.png" =
height=3D"auto" width=3D"48" align=3D"center" =
style=3D"display:block;height:auto;margin:0 auto;
border:0;"/></a>
</td><td =
style=3D"font-family:&#39;PuckSerifDisplay&#39;,&#39;Georgia&#39;;font-si=
ze:20px;font-weight:400;color:#d40000;vertical-align:middle;letter-spacin=
g:undefined;text-align:left;line-height:normal;"><a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9wdWNrLm5ld3MvYX=
V0aG9yL0lhbi1LcmlldHpiZXJnLz91dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXllcitBY2N=
lc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9jb250=
ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4NyUyR=
jExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2=
U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIsImludGV=
ybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX2lkIjoyMjU4MDMwfQ/f5d84b0d0=
82d8c25c6c25689d415755e5941b652f6219a8be670a477bf46fa1d" =
target=3D"_self" style=3D"color:#d40000;text-decoration:none;">Ian =
Krietzberg</a>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table class=3D"row row-5" align=3D"center" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td>
<table class=3D"row-content stack" align=3D"center" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;background-color:#ffff=
ff;border-radius:0;color:#000000;width:600px;margin:0 auto;" =
width=3D"600"><tbody><tr><td class=3D"column column-1" width=3D"100%" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;font-weight:400;text-a=
lign:left;padding-left:24px;padding-right:24px;padding-top:12px;vertical-=
align:top;">
<table class=3D"paragraph_block block-1" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;word-break:break-word;=
"><tbody><tr><td class=3D"pad" style=3D"padding-bottom:32px;"><div =
style=3D"color:#000000;direction:ltr;font-family:&#39;Inter&#39;,&#39;Ari=
al&#39;;font-size:17px;font-weight:400;letter-spacing:0px;line-height:1.5=
;text-align:left;mso-line-height-alt:26px;"><p style=3D"margin:0;">A =
classic concept in cognitive science is what researchers call
<a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9vZWNzLm1pdC5lZH=
UvcHViL2VlN3k0b3BnL3JlbGVhc2UvMT91dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXllcit=
BY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9j=
b250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4N=
yUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9zb3=
VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIsIml=
udGVybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX2lkIjoyMjY3MjI1fQ/63263=
9ef3598d559042e946af371cb689b9facac6ef7f11fc2751a2545001c71" =
style=3D"text-decoration:underline;color:#d40000;"><em>mental =
models</em></a>=E2=80=94or how our <em>internal</em> representation of =
the external world informs how we navigate reality. An illustrative =
example: <strong>Michael Jordan</strong> was able to close his eyes and =
still <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly93d3cueW91dHViZS=
5jb20vd2F0Y2g_dj16dWdLNVRmNHZKOFx1MDAyNnV0bV9jYW1wYWlnbj1UaGUrSGlkZGVuK0x=
heWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTKyUyODclMkYxMSUyRjI1JTI5XHUwMDI2=
dXRtX2NvbnRlbnQ9VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEU=
yslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9tZWRpdW09ZW1haWxfYWN0aW9uXHUwMDI2dX=
RtX3NvdXJjZT1jdXN0b21lci5pb1x1MDAyNnV0bV90ZXJtPWY2YzYwNjE1ZTNkMzAxZDQ4ZDI=
4IiwiaW50ZXJuYWwiOiJmNmM2MDYxNWUzZDMwMWQ0OGQyOCIsImxpbmtfaWQiOjIyNjcyMjZ9=
/401ba0e278183a915b8085765822db7edf7ceb17517d6755b4ff81bf91a0d8a6" =
style=3D"text-decoration:underline;color:#d40000;">make a free throw</a> =
because his =E2=80=9Cmental model=E2=80=9D included the exact size,
height, distance, etcetera of the basket, and that doesn=E2=80=99t go =
away just because you close your eyes. A neural network=E2=80=93based =
system, lacking a reliable model of the physical world, would likely not =
be able to make that free throw. This shortcoming has increasingly =
become a point of focus for A.I. companies, who are attempting to build =
their own =E2=80=9Cworld models=E2=80=9D (another term whose definition =
changes depending on whom you talk to) in order to provide machines with =
a stable, physically accurate
internal representation of certain parts of the external world. For the =
self-driving car company Waymo, that could mean a world model designed =
to <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly93YXltby5jb20vcm=
VzZWFyY2gvc2NlbmVkaWZmdXNlci1jaXR5LXNjYWxlLXRyYWZmaWMtc2ltdWxhdGlvbi12aWE=
tYS1nZW5lcmF0aXZlLXdvcmxkLW1vZGVsLz91dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXll=
citBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0b=
V9jb250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJT=
I4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9=
zb3VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIs=
ImludGVybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX2lkIjoyMjY3MjI3fQ/45=
f46beb29a324dcfb42cb5479cebe848af3164effff5b552d423adeedabb6a9" =
style=3D"text-decoration:underline;color:#d40000;">simulate traffic =
patterns</a>. For chess-playing machines, it could be what author and =
cognitive scientist <strong>Gary Marcus</strong> recently
<a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9nYXJ5bWFyY3VzLn=
N1YnN0YWNrLmNvbS9wL2dlbmVyYXRpdmUtYWlzLWNyaXBwbGluZy1hbmQtd2lkZXNwcmVhZD9=
1dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFE=
UyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9jb250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQ=
WNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbW=
VkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1=
fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIsImludGVybmFsIjoiZjZjNjA2MTVlM2QzMDFk=
NDhkMjgiLCJsaW5rX2lkIjoyMjY3MjI4fQ/0b7c207c81387ee85249f0c34246ea86756553=
278e37b16142b0dc91c34d2c67" =
style=3D"text-decoration:underline;color:#d40000;">referred</a> to as <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly9jb2RlY2F0YWxvZy=
5vcmcvYXJ0aWNsZXMvc3RvY2tmaXNoLWJvYXJkLXJlcHJlc2VudGF0aW9uLz91dG1fY2FtcGF=
pZ249VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJG=
MTElMkYyNSUyOVx1MDAyNnV0bV9jb250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vb=
i1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYW=
lsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM=
2MDYxNWUzZDMwMWQ0OGQyOCIsImludGVybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJs=
aW5rX2lkIjoyMjY3MjI5fQ/1059b29aa4ee7b07b8a2016c820f0f0cfdfd1917f68f39d3ea=
d234cbcb446c19" =
style=3D"text-decoration:underline;color:#d40000;">=E2=80=9Cboard=E2=80=9D=
 models</a>, which offer rule-based, constantly updating representations =
of a given game board.<br/><br/>So far, there=E2=80=99s <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly94LmNvbS9rZXlvbl=
Yvc3RhdHVzLzE4MDM4Mzg1OTEzNzE1NTUyNTI_dXRtX2NhbXBhaWduPVRoZStIaWRkZW4rTGF=
5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1=
dG1fY29udGVudD1UaGUrSGlkZGVuK0xheWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTK=
yUyODclMkYxMSUyRjI1JTI5XHUwMDI2dXRtX21lZGl1bT1lbWFpbF9hY3Rpb25cdTAwMjZ1dG=
1fc291cmNlPWN1c3RvbWVyLmlvXHUwMDI2dXRtX3Rlcm09ZjZjNjA2MTVlM2QzMDFkNDhkMjg=
iLCJpbnRlcm5hbCI6ImY2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwibGlua19pZCI6MjI2NzIzMH0/=
9777e1c09fc91d00513846238c5599edf03fb1b8e994a187f30da5f2c44d7565" =
style=3D"text-decoration:underline;color:
#d40000;">no evidence</a> that large language models possess world =
models, even though some researchers and engineers believe they might =
naturally emerge over time. And it is this absence of grounded, =
rules-based modeling, Marcus recently argued, that explains why L.L.M.s =
often =E2=80=9Challucinate=E2=80=9D in strange and unexpected ways: =
=E2=80=9CWhat L.L.M.s do is to extract correlations between bits of =
language (and in some cases images) but they do this without the =
laborious and difficult work (once known as
knowledge engineering) of creating explicit models of who did what to =
whom when and so forth,=E2=80=9D he wrote.<br/><br/>It=E2=80=99s a =
problem that Runway, the pioneering A.I. image- and video-generation =
company, is hoping to solve. The company, founded in 2018, has raised =
$536 million from investors such as Nvidia and Softbank, according to <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly93d3cuY3J1bmNoYm=
FzZS5jb20vb3JnYW5pemF0aW9uL3J1bndheW1sP3V0bV9jYW1wYWlnbj1UaGUrSGlkZGVuK0x=
heWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTKyUyODclMkYxMSUyRjI1JTI5XHUwMDI2=
dXRtX2NvbnRlbnQ9VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEU=
yslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9tZWRpdW09ZW1haWxfYWN0aW9uXHUwMDI2dX=
RtX3NvdXJjZT1jdXN0b21lci5pb1x1MDAyNnV0bV90ZXJtPWY2YzYwNjE1ZTNkMzAxZDQ4ZDI=
4I2ZpbmFuY2lhbHMiLCJpbnRlcm5hbCI6ImY2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwibGlua19p=
ZCI6MjI2NzIzMX0/75dcecca3ac231b4b2ba7665b7fd2ee2120f5dd8411f144af73e46ce5=
d44e6b7" =
style=3D"text-decoration:underline;color:#d40000;">Crunchbase</a> data, =
and has secured a partnership
with Lionsgate Studios. (Runway=E2=80=99s models were notably <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly92YXJpZXR5LmNvbS=
8yMDIzL2FydGlzYW5zL25ld3MvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtcnVud2F5LWV2ZXJ=
5dGhpbmctZXZlcnl3aGVyZS1hbGwtYXQtb25jZS0xMjM1NTMyMzIyLz91dG1fY2FtcGFpZ249=
VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJGMTElM=
kYyNSUyOVx1MDAyNnV0bV9jb250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vbi1USE=
wrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYWlsX2F=
jdGlvblx1MDAyNnV0bV9zb3VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM2MDYx=
NWUzZDMwMWQ0OGQyOCIsImludGVybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX=
2lkIjoyMjY3MjMyfQ/6faad3e2af8eb6c5dbc39d68dc96a4cbc232243438b825398a87730=
4c01d747c" =
style=3D"text-decoration:underline;color:#d40000;">leveraged</a> by =
visual effects artist <strong>Evan</strong> <strong>Halleck</strong> =
when he was working on <em>Everything Everywhere All at Once</em> in =
2022.) But taking the software to the next level requires eliminating =
those often-viral hallucinations that might
show, for example, seven fingers on a man=E2=80=99s hand, or a bunch of =
dogs <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly94LmNvbS9jYXlkZW=
5naW5lZXIvc3RhdHVzLzE3NTgyMzMxNDk2NTIyODMzOTU_dXRtX2NhbXBhaWduPVRoZStIaWR=
kZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlc=
dTAwMjZ1dG1fY29udGVudD1UaGUrSGlkZGVuK0xheWVyK0FjY2VzcytOb24tVEhMKy0rQWxsK=
0xFQURTKyUyODclMkYxMSUyRjI1JTI5XHUwMDI2dXRtX21lZGl1bT1lbWFpbF9hY3Rpb25cdT=
AwMjZ1dG1fc291cmNlPWN1c3RvbWVyLmlvXHUwMDI2dXRtX3Rlcm09ZjZjNjA2MTVlM2QzMDF=
kNDhkMjgiLCJpbnRlcm5hbCI6ImY2YzYwNjE1ZTNkMzAxZDQ4ZDI4IiwibGlua19pZCI6MjI2=
NzIzM30/187c19a400bfcef62bfadf4d0239dd4db65c65f3814fa5b4bacefb0bddddfaee"=
 style=3D"text-decoration:underline;color:#d40000;">merging</a> out of =
one dog, or a cat <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly95b3V0dS5iZS8tMm=
RhWGdsdHk5OD91dG1fY2FtcGFpZ249VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCs=
tK0FsbCtMRUFEUyslMjg3JTJGMTElMkYyNSUyOVx1MDAyNnV0bV9jb250ZW50PVRoZStIaWRk=
ZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcd=
TAwMjZ1dG1fbWVkaXVtPWVtYWlsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2U9Y3VzdG9tZXIuaW=
9cdTAwMjZ1dG1fdGVybT1mNmM2MDYxNWUzZDMwMWQ0OGQyOCIsImludGVybmFsIjoiZjZjNjA=
2MTVlM2QzMDFkNDhkMjgiLCJsaW5rX2lkIjoyMjY3MjM0fQ/0867a6da0f396d5419cde7402=
de9096113eca18a2469ab117a0cebddfb97dc1a" =
style=3D"text-decoration:underline;color:#d40000;">sprouting</a> random =
additional limbs. These generations are the result of massive =
statistical analyses=E2=80=94not an <em>actual</em> understanding of =
physics, or human hands, or cats.<br/><br/>To learn
how Runway is tackling this problem, I caught up with =
<strong>Anastasis</strong> <strong>Germanidis</strong>, the =
company=E2=80=99s C.T.O. and co-founder. This conversation has been =
lightly edited and condensed for clarity.</p></div>
</td></tr></tbody></table>
<table class=3D"heading_block block-2" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"pad" =
style=3D"padding-bottom:32px;text-align:center;width:100%;"><h3 =
style=3D"margin:0;color:#000000;direction:ltr;font-family:&#39;PuckSerifD=
isplay&#39;,&#39;Georgia&#39;;font-size:24px;font-weight:400;letter-spaci=
ng:normal;line-height:1.2;text-align:center;margin-top:0;margin-bottom:0;=
mso-line-height-alt:29px;"><strong>World
Simulators</strong></h3>
</td></tr></tbody></table>
<table class=3D"paragraph_block block-3" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;word-break:break-word;=
"><tbody><tr><td class=3D"pad" style=3D"padding-bottom:32px;"><div =
style=3D"color:#000000;direction:ltr;font-family:&#39;Inter&#39;,&#39;Ari=
al&#39;;font-size:17px;font-weight:400;letter-spacing:0px;line-height:1.5=
;text-align:left;mso-line-height-alt:26px;"><p =
style=3D"margin:0;"><strong><em>Ian Krietzberg</em></strong>: =
<strong>Runway is an
image- and video-generation company. How do you go from that to building =
world =
models?</strong><strong><br/></strong><strong><br/></strong><em>Anastasis=
 Germanidis</em>: We did a lot of the foundational research in image and =
video generation, and what we saw as we were building better and better =
video generation models is that, in order to solve video =
generation=E2=80=94to generate videos that are physically realistic, =
high quality, and high fidelity=E2=80=94those models essentially need to =
learn how to simulate
the world. They need to understand physics, and understand how humans =
interact in space, and to understand different aspects about the world, =
and the dynamics of the world. This created our initial interest in =
building world simulators, as we call them.<br/><br/><strong>Can you say =
a little more about the application of =E2=80=9Cworld =
simulators=E2=80=9D?</strong><strong><br/></strong><strong><br/></strong>=
There are, I would say, two broad areas of world simulators that are =
interesting from a use-case perspective.
One involves creating new forms of entertainment=E2=80=94and this is =
something we=E2=80=99re increasingly going to be doing on top of those =
models. Imagine gaming experiences where a game is generated as =
you=E2=80=99re playing it. We imagine most video generation will become =
real-time and personalized, and it will be generated on the fly as =
you=E2=80=99re experiencing it.<br/><br/>The other aspect where world =
simulation is very relevant, I think, is that simulation will =
essentially power most model training in the coming years.
Because if you want to build models and systems that can operate in the =
real world=E2=80=94like robots that can help you with household =
tasks=E2=80=94it=E2=80=99s much more effective to train them in =
simulated environments versus deploy them in the world. And that same =
[thing] applies in robotics and in building self-driving =
cars.<br/><br/><strong>Models today are limited in their capacity to =
consistently and reliably produce physical representations of the real =
world. Are you exploring other architectures? Do you think
the neural networks of today will become more =
capable?</strong><strong><br/></strong><strong><br/></strong>There are =
always algorithmic advancements being made, and we=E2=80=99re working on =
new types of architectures. So traditionally, on image and video =
generation, diffusion models were the architecture of choice, while in =
language models, it=E2=80=99s autoregressive models. What we=E2=80=99re =
increasingly seeing is a convergence between the two=E2=80=94the best of =
both of those worlds=E2=80=94and we=E2=80=99re working on some new
architectures along that direction.<br/><br/>But I would say, more than =
the architectures themselves, the way you=E2=80=99re training those =
models will be the thing that changes the most. So effectively, training =
models to perform tasks in simulated environments over long time =
horizons will become the way to further improve performance, more than =
any specific algorithmic improvements.<br/><br/><strong>You=E2=80=99ve =
said that one of the biggest bottlenecks involves ensuring that these =
model simulations are
physically realistic. How do you overcome that =
bottleneck?</strong><strong><br/></strong><strong><br/></strong>You =
overcome the bottleneck by essentially scaling those simulators with =
enough data and compute: finding a sufficient amount of data that =
captures the environment that you want to simulate, and then increasing =
the model and compute scale.</p></div>
</td></tr></tbody></table>
<table class=3D"heading_block block-4" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;"><tbody><tr><td =
class=3D"pad" =
style=3D"padding-bottom:32px;text-align:center;width:100%;"><h3 =
style=3D"margin:0;color:#000000;direction:ltr;font-family:&#39;PuckSerifD=
isplay&#39;,&#39;Georgia&#39;;font-size:24px;font-weight:400;letter-spaci=
ng:normal;line-height:1.2;text-align:center;margin-top:0;margin-bottom:0;=
mso-line-height-alt:29px;"><strong>The Bitter
Lesson</strong></h3>
</td></tr></tbody></table>
<table class=3D"paragraph_block block-5" width=3D"100%" border=3D"0" =
cellpadding=3D"0" cellspacing=3D"0" role=3D"presentation" =
style=3D"mso-table-lspace:0pt;mso-table-rspace:0pt;word-break:break-word;=
"><tbody><tr><td class=3D"pad" style=3D"padding-bottom:32px;"><div =
style=3D"color:#000000;direction:ltr;font-family:&#39;Inter&#39;,&#39;Ari=
al&#39;;font-size:17px;font-weight:400;letter-spacing:0px;line-height:1.5=
;text-align:left;mso-line-height-alt:26px;"><p =
style=3D"margin:0;"><strong>You mentioned self-driving cars as an =
example of how
world models can be applied. But the problem with self-driving cars is =
that it=E2=80=99s a physical impossibility to capture sufficient data =
for all possible edge cases. And that gets us to the root question =
around genuine machine understanding and generalizability: We=E2=80=99re =
trying to brute-force our way to simulating generalizability, but =
it=E2=80=99s not </strong><strong><em>really</em></strong><strong> =
generalizability, because it=E2=80=99s built on such a massive scale =
rather than on systems that can reliably
generalize based on a </strong><strong><em>small</em></strong><strong> =
dataset. Are you at all exploring methods of world modeling that =
don=E2=80=99t rely on massive =
scale?</strong><strong><br/></strong><strong><br/></strong>Are you =
familiar with =E2=80=9C<a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly93d3cuY3MudXRleG=
FzLmVkdS9-ZXVuc29sL2NvdXJzZXMvZGF0YS9iaXR0ZXJfbGVzc29uLnBkZj91dG1fY2FtcGF=
pZ249VGhlK0hpZGRlbitMYXllcitBY2Nlc3MrTm9uLVRITCstK0FsbCtMRUFEUyslMjg3JTJG=
MTElMkYyNSUyOVx1MDAyNnV0bV9jb250ZW50PVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vb=
i1USEwrLStBbGwrTEVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fbWVkaXVtPWVtYW=
lsX2FjdGlvblx1MDAyNnV0bV9zb3VyY2U9Y3VzdG9tZXIuaW9cdTAwMjZ1dG1fdGVybT1mNmM=
2MDYxNWUzZDMwMWQ0OGQyOCIsImludGVybmFsIjoiZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJs=
aW5rX2lkIjoyMjY3MjM1fQ/e9d905ced52e39049cc06c4cd2d4334962d8dae7f3d3a4cd83=
9986de6d047c31" style=3D"text-decoration:underline;color:#d40000;">The =
Bitter Lesson</a>=E2=80=9D? The thing that has repeatedly worked in this =
field has been finding the methods that can leverage more compute and
more resources, and increasing the scale that you apply them at. There =
are going to be improvements in data efficiency=E2=80=94learning from =
less data=E2=80=94but I don=E2=80=99t expect that to be the biggest =
driver of progress. We still haven=E2=80=99t trained on a sufficient =
amount of observations from the world. I think we=E2=80=99re still very =
early in leveraging all the data and all the observations that are =
available. So I don=E2=80=99t think we=E2=80=99re anywhere close to =
actually saturating=C2=A0 that available data.<br/><br/><strong>What =
does
this all mean for Runway as a business? Are you eyeing a push beyond =
simple image and video =
generation?</strong><strong><br/></strong><strong><br/></strong>Yeah, I =
think the potential of those models goes beyond content creation. I =
would say gaming is the most proximate area that we=E2=80=99re =
exploring. We have a new platform that we call <a =
href=3D"https://email.puck.news/e/c/eyJlbWFpbF9pZCI6ImRnVDJ4Z1lEQU5TTktOT=
05LQUdYLW02VDA2bmd1ZXBkZjFSN2Z5Yz0iLCJocmVmIjoiaHR0cHM6Ly93d3cuZW5nYWRnZX=
QuY29tL2FpL3J1bndheS1ub3ctaGFzLWl0cy1zaWdodHMtb24tdGhlLXZpZGVvLWdhbWUtaW5=
kdXN0cnktd2l0aC1pdHMtbmV3LWdlbmVyYXRpdmUtYWktcGxhdGZvcm0tMTkyMzUwMjk0Lmh0=
bWw_dXRtX2NhbXBhaWduPVRoZStIaWRkZW4rTGF5ZXIrQWNjZXNzK05vbi1USEwrLStBbGwrT=
EVBRFMrJTI4NyUyRjExJTJGMjUlMjlcdTAwMjZ1dG1fY29udGVudD1UaGUrSGlkZGVuK0xheW=
VyK0FjY2VzcytOb24tVEhMKy0rQWxsK0xFQURTKyUyODclMkYxMSUyRjI1JTI5XHUwMDI2dXR=
tX21lZGl1bT1lbWFpbF9hY3Rpb25cdTAwMjZ1dG1fc291cmNlPWN1c3RvbWVyLmlvXHUwMDI2=
dXRtX3Rlcm09ZjZjNjA2MTVlM2QzMDFkNDhkMjgiLCJpbnRlcm5hbCI6ImY2YzYwNjE1ZTNkM=
zAxZDQ4ZDI4IiwibGlua19pZCI6MjI2NzIzNn0/4f00dad4abd0f2a2683f2e626175fc411c=
49724ab3f28708da4f606a0960875a" style=3D"text-decoration:
underline;color:#d40000;">Game World</a>, where essentially anyone can =
generate a new world from a premise, and by kind of describing the game =
mechanics, they can then create a game they can share with others. But =
beyond gaming, there are applications that we=E2=80=99re exploring in =
robotics and in self-driving and a few other areas. We do think those =
models are very general, and so we=E2=80=99re going to be announcing =
some different collaborations and partnerships on many different =
fronts.<br/><br/><strong>That
opens up the highly contentious issue of automated media, which has =
already been resulting in job loss within these industries. Do you see =
this as something that will be associated with a reduction in the =
necessary workforce?</strong><br/><br/>I think that there=E2=80=99s =
definitely going to be a change in the roles and the kind of jobs that =
someone working in gaming, for example, would perform. Traditionally, =
with new technologies, they end up expanding what jobs are possible. We =
saw that with different
generations of creative software as well=E2=80=94there was the narrative =
that Photoshop would destroy all visual art or visual design. I think =
the same will happen with gaming.<br/><br/>There=E2=80=99s still going =
to be a big importance on taste and vision and coming up with the best =
ideas and designs for game experiences=E2=80=94but the creation of those =
games will not look the same as it looks today. You might not need to =
create every single asset and every single object in the game world. =
It=E2=80=99s more about designing the
overall rules of the system. Maybe the absolute number of games will =
increase, and the kinds of things that you can do as a game designer =
will change, but I don=E2=80=99t necessarily see it as a reduction in =
the amount of jobs that are available in this field. It=E2=80=99s more =
going to be a change.<br/><br/><strong>Artificial general intelligence =
is practically meaningless as a term, but is Runway interested in =
becoming an A.G.I. lab?</strong><br/><br/>To me, simulation goes beyond =
A.G.I., and I also think the
goal of getting parity on tasks with humans seems like it=E2=80=99s not =
the right goal to strive for. I think we should use A.I. techniques to =
go far beyond and augment human ability. So I wouldn=E2=80=99t call =
ourselves an A.G.I. lab., and I think even A.G.I. labs will move beyond =
this goal, because really what you want is to expand what humans can do =
to accelerate scientific progress, to solve all those different =
challenges. And that doesn=E2=80=99t necessarily mean that you need to =
get as good as humans in those
challenges. You need to build systems that go beyond what humans can =
do.</p></div>
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you enjoy this rainy weekend. I=E2=80=99ll see you next
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