text,start,duration
good morning everybody David Shapiro,0.42,3.6
here with another video,2.639,4.62
so today's video uh it started off as,4.02,5.28
one thing I wanted to primarily talk,7.259,4.861
about epistemic convergence uh but It,9.3,4.32
ultimately ended up being a little bit,12.12,2.54
more,13.62,2.82
all-encompassing so I'm going to,14.66,3.94
introduce a few new terms but we are,16.44,4.08
going to cover cover uh epistemic,18.6,4.259
convergence and a few other things,20.52,4.62
uh real quick before we dive into the,22.859,3.781
video just want to do a quick plug for,25.14,3.719
my patreon uh all tears get you access,26.64,4.32
to the private Discord server and then I,28.859,4.2
have a few higher tiers that uh come,30.96,4.32
with a one-on-one conversations and that,33.059,4.201
sort of thing so anyways back to the,35.28,5.16
video so first I wanted to share with,37.26,5.639
you guys uh the universal model of,40.44,4.98
Robotics so it has it's basically three,42.899,5.16
steps input processing and output or,45.42,4.38
sensing processing and controlling as,48.059,3.241
this Graphics shows,49.8,4.38
now this is the most basic cognitive,51.3,4.5
architecture that you can come up with,54.18,4.199
for artificial general intelligence it,55.8,4.439
needs input from the outside world from,58.379,3.66
the environment of some kind whether,60.239,3.3
it's a virtual environment digital,62.039,3.841
environment physical environment or,63.539,4.62
whatever cyber cybernetic environment,65.88,4.68
and then it needs some kind of internal,68.159,4.981
processing that includes memory task,70.56,4.2
construction executive function,73.14,4.519
cognitive control that sort of stuff,74.76,5.82
learning is another internal process and,77.659,5.381
then finally controlling or output it,80.58,4.859
needs to do something to act on the,83.04,5.1
world or its environment whether that's,85.439,4.801
just putting out you know text in a in,88.14,3.6
the form of a chat bot or if it's got,90.24,4.86
robotic hands that sort of thing so when,91.74,5.519
I talk about artificial general,95.1,3.9
intelligence being a system it's never,97.259,4.141
going to just be a model right even if,99.0,4.14
you have the most sophisticated model in,101.4,3.6
the world all that it's doing is the,103.14,3.839
processing part you also need the,105.0,4.799
sensing and controlling aspect and but,106.979,4.621
even above and beyond that each,109.799,4.081
components is going to be much more,111.6,4.32
complicated,113.88,4.08
so before we get into the rest of the,115.92,4.08
video I also want to talk about the form,117.96,4.26
factors that AGI is going to take so we,120.0,3.899
just established the simplest kind of,122.22,3.96
cognitive architecture but then there's,123.899,3.781
other things to consider because when,126.18,3.66
you think of AGI you might think of some,127.68,4.08
nebulous entity like Skynet but where,129.84,3.6
does it physically live,131.76,3.42
what is the hardware what is the,133.44,4.2
software where where is it physically,135.18,4.02
located because it's not magic right,137.64,3.179
it's not going to just run in the dirt,139.2,3.179
or something like that it needs to,140.819,4.381
actually have Hardware to run on so,142.379,5.761
there's three overarching categories,145.2,5.28
that I came up with so first is cloud,148.14,5.28
AGI so Cloud AGI is this is the stuff,150.48,4.38
that's gonna one it's going to be,153.42,3.06
created first just because of the amount,154.86,3.54
of compute and power available in data,156.48,5.22
centers so this is uh Enterprise grade,158.4,7.74
or data center grade AGI systems they,161.7,7.14
are in specialized buildings all over,166.14,5.22
the world but one of the biggest,168.84,4.38
constraints here is that there's limited,171.36,3.48
location and it takes a while to build,173.22,3.54
data centers right one of the things,174.84,3.96
that I think it was uh it was Elon,176.76,4.32
musker or Sam Altman said that you know,178.8,4.92
there are going to be limitations as to,181.08,5.28
the rate at which AGI can proliferate,183.72,5.519
namely the the rate at which we can,186.36,5.94
produce chips and also the rate at which,189.239,5.22
as I think Sam malt and said the you,192.3,4.439
know the concrete has to dry for data,194.459,3.121
centers,196.739,5.64
so this is uh one form factor that AGI,197.58,7.019
will take in terms of the the storage,202.379,4.801
the servers the network components that,204.599,4.86
will exist inside data centers so one,207.18,3.839
thing I wanted to watch it say is watch,209.459,3.841
out for uh fortified data centers these,211.019,3.841
are ones that are put in bunkers or if,213.3,3.659
you put Sam sites on top of it so that,214.86,4.26
you can't shut them down uh that was,216.959,3.42
kind of tongue-in-cheek I'm not actually,219.12,3.36
advocating for bombing data centers at,220.379,4.681
least not yet the next form factor is,222.48,5.16
Edge AGI so this is stuff that is going,225.06,4.22
to run in,227.64,3.84
self-contained servers that you can,229.28,4.9
basically plug in anywhere they're going,231.48,6.539
to be you know desktop size maybe larger,234.18,5.82
but the point is that pretty much all,238.019,3.481
you need is power and internet you don't,240.0,4.319
need a specialized building and they can,241.5,4.62
be moved on trucks they can be put in,244.319,3.961
ships airplanes that sort of stuff,246.12,3.72
because you can't really airlift an,248.28,4.019
entire data center so basically Edge is,249.84,4.619
something is just one size down from,252.299,3.481
data center you don't need a specialized,254.459,2.52
building you don't need specialized,255.78,3.66
cooling they can run anywhere,256.979,3.72
um and they're so in that respect,259.44,2.94
they're more portable but they're not,260.699,4.741
necessarily going to be as powerful at,262.38,5.039
least or not as energy intensive and,265.44,5.039
energy dense as a data center or a cloud,267.419,4.021
Center,270.479,4.141
and then finally ambulatory AGI this is,271.44,5.46
the embodied stuff such as C-3PO and,274.62,3.98
Commander data which I have imaged here,276.9,4.98
they're self-contained meaning that all,278.6,5.14
the systems that they need are within,281.88,4.319
their chassis within their robotic body,283.74,5.519
and they can move on their own so that's,286.199,4.5
basically the difference between an edge,289.259,5.101
AGI and an ambulatory AGI is uh they,290.699,5.401
might have roughly the same components,294.36,4.14
but it's one is accompanied with a,296.1,6.12
robotic uh chassis now one thing to keep,298.5,6.18
in mind is that all of these things are,302.22,4.86
intrinsically networkable meaning they,304.68,4.32
can communicate over digital networks,307.08,4.559
whether it's Wi-Fi or you know fiber,309.0,5.16
optic backbone networks or even you know,311.639,4.141
Satellite Communication like starlink,314.16,3.9
now that's that doesn't necessarily have,315.78,4.08
to be true because remember the model of,318.06,4.44
AGI is input processing and output that,319.86,5.76
input that input could be just eyes and,322.5,4.979
ears cameras and microphones that input,325.62,4.26
could also be network connections from,327.479,4.621
outside meaning that they could,329.88,4.44
communicate directly with each other via,332.1,5.28
you know like IRC or whatever so just,334.32,4.86
wanted to say that there are different,337.38,3.72
form factors that we should expect AGI,339.18,2.94
to take,341.1,3.3
with different trade-offs so one,342.12,5.22
advantage of ambulatory uh AGI you know,344.4,6.12
yes they will have less power uh and by,347.34,5.88
power I mean computational power but,350.52,5.28
they have the ability to go anywhere do,353.22,6.66
anything kind of like URI uh now that,355.8,6.959
being said the the amount of compute,359.88,4.8
resources that can be crammed into Data,362.759,3.66
Centers basically means that you can,364.68,4.38
puppet you know millions or billions of,366.419,5.161
peripheral robots rather than having it,369.06,4.44
fully self-contained and in a previous,371.58,3.899
video I talked about how we're likely to,373.5,4.639
see hybrid systems where you have,375.479,5.22
semi-autonomous peripherals that have,378.139,4.481
some intelligence but not a whole lot of,380.699,4.201
intelligence and you see this in movies,382.62,4.919
like Will Smith's iRobot as well as the,384.9,4.38
Matrix where the the drones the,387.539,3.78
squiddies and the Matrix they're,389.28,3.479
semi-autonomous but they are still,391.319,3.301
centrally controlled by a much more,392.759,4.021
powerful intelligence so you're probably,394.62,3.72
not going to see it all one or the other,396.78,3.06
you're probably going to see hybrids,398.34,3.54
where you've got peripheral robots that,399.84,4.02
are either fully autonomous or,401.88,4.92
semi-autonomous or puppeted by stronger,403.86,4.98
Central intelligences that being said,406.8,4.26
you can also create droids there's no,408.84,4.5
reason that we could not create fully,411.06,4.38
self-contained machines that don't,413.34,4.74
really have any network connectivity,415.44,4.86
um to the to other machines,418.08,3.899
that being said they would be at a,420.3,3.78
distinct disadvantage and what I mean by,421.979,4.5
that is that if you create swarm,424.08,4.8
intelligence or Wireless federations of,426.479,4.741
machines they can perform cognitive,428.88,6.24
offload or share computational resources,431.22,6.66
so for instance rather than and this is,435.12,4.44
how the Geth work in Mass Effect by the,437.88,4.439
way so rather than have every single,439.56,6.06
machine have to think about the entire,442.319,5.94
plan the entire strategy most of them,445.62,4.919
Focus only on their primary task and,448.259,5.401
then any surplus compute computational,450.539,6.121
power they have is dedicated towards you,453.66,5.52
know running algorithms for for the big,456.66,4.68
the big brain the hive mind,459.18,4.56
this is all hypothetical but one thing,461.34,4.32
that I want to point out is that many,463.74,3.54
many many machines work like this,465.66,4.56
already and what I mean by that is the,467.28,4.38
simplest version that many people are,470.22,3.9
probably aware of is if you have like,471.66,3.84
Bluetooth speakers or smart speakers,474.12,3.6
like Sonos or whatever those form a,475.5,5.819
wireless Federation uh ditto for like,477.72,5.28
your Amazon Alexa's and other things,481.319,4.261
like that those intrinsically form mesh,483.0,4.259
networks or Wireless federations meaning,485.58,3.48
that they can work together and,487.259,4.321
communicate now when you add artificial,489.06,5.46
intelligence to that then they can share,491.58,4.559
thinking and messaging and that sort of,494.52,2.64
stuff so that's what I mean by,496.139,4.801
federations or or wireless networks of,497.16,6.599
of AI okay so now you're familiar with,500.94,4.74
the background of how you know some of,503.759,5.041
the systemic aspects of it there's a few,505.68,4.919
default metrics of power so when I say,508.8,3.359
power I don't necessarily just mean,510.599,3.721
electricity although certainly all of,512.159,3.961
these things do require electricity to,514.32,2.82
run,516.12,4.26
so first is processing power so for,517.14,5.1
instance you might hear the term flops,520.38,4.2
which is floating Point operations per,522.24,7.68
second uh you also hear CPU GPU TPU and,524.58,7.02
then there's parallel parallelization,529.92,4.02
which means that you have many of these,531.6,5.1
things working together so processing,533.94,4.62
power is one component of the total,536.7,4.68
amount of power in the hardware layer so,538.56,4.44
this is all strictly Hardware layer I'm,541.38,3.48
not talking about parameter models,543.0,4.74
because I I don't really care about how,544.86,4.68
many parameters a model has there's lots,547.74,4.02
of ways to make intelligent machines,549.54,4.2
deep neural networks are currently the,551.76,4.079
best way but we're also discovering,553.74,3.719
efficiencies where you can kind of pair,555.839,3.661
them down you can distill them and make,557.459,3.541
them more efficient meaning that you can,559.5,3.36
on the same piece of Hardware you can,561.0,4.8
run more of them in parallel or you can,562.86,5.52
run one much faster so the underlying,565.8,3.96
Hardware is still going to be the,568.38,3.8
primary bottleneck or primary constraint,569.76,5.1
all else considered,572.18,5.68
uh memory so this is Ram it also,574.86,5.36
includes memory accelerators or caching,577.86,5.46
storage has to do with bulk data your,580.22,4.9
databases your archives your backups,583.32,4.44
this is when you say like hard drive or,585.12,4.74
SSD or you know storage area network,587.76,4.259
that sort of thing and then networking,589.86,4.68
is the the uplinks and downlinks this is,592.019,4.741
the the fiber optic connections the,594.54,3.72
wireless connections the satellite,596.76,3.9
connections that sort of thing so these,598.26,4.38
are the kind of the the rudimentary,600.66,4.799
parts that all AGI are going to run on,602.64,5.879
uh and this is just the brains too this,605.459,4.621
is not the peripherals this is not the,608.519,3.241
robots but this is what's going to,610.08,4.259
dictate or constrain how fast it is now,611.76,5.94
again like I said uh different neural,614.339,5.221
networks are going to operate at,617.7,3.42
different efficiencies so for instance,619.56,5.82
uh you know gpt4 is out now gpt5 might,621.12,6.96
be the same size it might be bigger but,625.38,4.82
then we're also finding open source,628.08,6.06
research like the Orca alpaca llama that,630.2,5.92
are getting like ninety percent of the,634.14,4.56
performance but at like one tenth or one,636.12,4.98
hundredth of the size and so you have a,638.7,4.199
trade-off of intelligence and versus,641.1,4.56
speed and power and we'll talk more a,642.899,5.221
lot more about that in the future of,645.66,4.739
this video at near the middle and end of,648.12,4.2
this video about how trading off,650.399,4.801
intelligence for Speed is often a more,652.32,4.56
advantageous strategy and how this,655.2,4.199
figures into solving the control problem,656.88,5.28
and solving alignment,659.399,4.981
um okay so we kind of set the stage as,662.16,4.98
as to how AGI is probably going to look,664.38,5.639
so let's talk about the early ecosystem,667.14,6.18
of AGI so in the coming years we're,670.019,4.921
going to be building millions and then,673.32,3.24
billions of autonomous and,674.94,4.5
semi-autonomous agents so at first these,676.56,4.2
agents are going to be purely digital,679.44,3.44
right you know a,680.76,4.56
semi-autonomous slack bot a,682.88,4.54
semi-autonomous Discord bot people are,685.32,4.32
already building these right and some of,687.42,3.72
them have the ability to modify their,689.64,2.879
own code some of them have the ability,691.14,3.78
to learn many of them don't most of them,692.519,4.32
use frozen llms in the background,694.92,3.659
meaning that they're that their,696.839,4.201
cognitive capacity is pretty much capped,698.579,4.981
by its backing model,701.04,5.76
now that being said as these agents,703.56,5.279
become more autonomous they go from,706.8,4.2
semi-autonomous to autonomous this will,708.839,4.201
create a competitive landscape,711.0,4.86
and what I mean by that is that humans,713.04,5.28
will have the ability to build and,715.86,5.159
destroy these models for basically,718.32,4.62
arbitrary reasons because you want to or,721.019,3.781
because you don't like it or whatever,722.94,4.26
so that means that we will be selecting,724.8,5.52
those agents those uh those models those,727.2,6.18
llms and those pieces of software that,730.32,4.32
are going to be more helpful more,733.38,3.6
productive and more aligned so this,734.64,4.08
creates selective pressure basically,736.98,3.299
saying that there's going to be a,738.72,2.88
variety there's going to be millions or,740.279,3.24
billions of Agents out there some of,741.6,3.9
them are going to get the ax and some of,743.519,4.141
them are going to be selected to say hey,745.5,4.079
we like we like you we're going to keep,747.66,2.88
you around,749.579,3.901
so there's a few off the cuff selective,750.54,4.799
pressures that we can imagine basically,753.48,3.84
why do you choose an app right why do,755.339,3.361
you choose to use an app why do you,757.32,3.54
choose to uninstall an app that's kind,758.7,3.36
of the level that we're talking about,760.86,3.9
here so first is functional utility how,762.06,4.019
useful is it,764.76,3.6
how much does it help you is it fast,766.079,3.541
enough does it have a good user,768.36,3.5
experience is the user interface,769.62,5.88
created correctly is it adding value to,771.86,7.06
your life is it worth using the second,775.5,6.079
part is speed and efficiency,778.92,6.06
basically if something takes four weeks,781.579,5.141
to give you a good answer but another,784.98,4.2
thing takes 10 minutes even if it's not,786.72,4.559
quite as good that speed is going to be,789.18,4.14
super super valuable but then there's,791.279,4.081
also energetic efficiency and cost,793.32,4.94
efficiency more often than not,795.36,5.34
individuals and businesses will choose,798.26,5.56
the solution that is good enough but,800.7,5.04
also much cheaper it doesn't have to be,803.82,4.019
perfect it just has to be good enough,805.74,4.86
and then finally apparent alignment and,807.839,5.101
so I use the the word apparent alignment,810.6,4.38
to basically mean things that appear to,812.94,4.199
be tame things that appear to be user,814.98,4.56
friendly uh and this is what uh tools,817.139,5.521
like rlhf do which one thing that rlhf,819.54,4.68
does is like wolves which we'll talk,822.66,4.619
about in a second are the rlhf,824.22,4.2
reinforcement learning with human,827.279,4.68
feedback forces gpt4 to dumb itself down,828.42,6.539
so that it better serves us uh and that,831.959,4.56
makes us feel safe because it's,834.959,4.32
basically pretending to be more like us,836.519,5.641
to speak on our terms and to mimic our,839.279,4.981
level of intelligence now that being,842.16,3.419
said,844.26,2.579
um one thing that I do want to point out,845.579,4.021
is that gpd4 the underlying model is,846.839,4.74
superior to anything that we have seen,849.6,5.239
in the public every version of chat GPT,851.579,6.021
has basically been kind of a little bit,854.839,6.101
hamstrung so we shall we say uh from the,857.6,6.82
the total capacity of gpt4,860.94,5.699
so what I call this is domestication and,864.42,4.8
supplication think of dogs and wolves,866.639,5.101
this little pomeranian descended from,869.22,4.98
wolves wolves used to be apex predators,871.74,4.62
wolves are also are much more,874.2,4.02
intelligent than dogs,876.36,6.419
so when you look at the early days of,878.22,6.84
AGI when we still have the off switch,882.779,3.781
and we have the power to delete,885.06,3.12
everything,886.56,3.899
we should expect some of the following,888.18,5.7
evolutionary pressures to kind of shape,890.459,6.421
the way that AGI evolves and adapts so,893.88,5.519
first we'll probably be selecting for,896.88,4.079
machines that are okay with being turned,899.399,4.201
off in the early days you don't,900.959,4.38
necessarily want your toaster fighting,903.6,3.479
with you when when you're done you know,905.339,3.3
toasting your bread it's time for it to,907.079,3.661
turn off and so we're probably going to,908.639,3.781
select machines and architectures and,910.74,3.779
models that are more or less okay with,912.42,3.539
being switched off that they don't have,914.519,3.801
a sense of death or a fear of death,915.959,4.62
we're also going to select machines that,918.32,4.6
are more eager to please just the same,920.579,5.281
way that with uh dogs have been bred and,922.92,5.159
selected to be very very eager to please,925.86,3.599
us,928.079,3.181
we're also going to select machines that,929.459,3.781
don't fall into the uncanny valley and,931.26,3.48
so what I mean by that is the uncanny,933.24,4.02
valley of when you're interacting with a,934.74,4.56
machine that you sense is an alien,937.26,3.78
intelligence it will make you very very,939.3,4.2
deeply uncomfortable as an autistic,941.04,4.799
person as someone who is neurodiverse I,943.5,4.139
have to modulate the way that I speak,945.839,4.68
and act around neurotypical people,947.639,5.401
because I fall into the same uncanny,950.519,5.94
valley right and some uh some CEOs out,953.04,5.039
there get teased for this for instance,956.459,3.24
Mark Zuckerberg I don't know if he's,958.079,3.841
actually autistic but he certainly pings,959.699,4.44
that radar where it's like okay he,961.92,3.539
obviously does not think the way that,964.139,3.361
the rest of us do and he also behaves,965.459,4.44
differently so Mark Zuckerberg like many,967.5,5.1
of us uh people on the Spectrum kind of,969.899,4.56
fall into that uncanny valley again I,972.6,4.44
don't know but uh,974.459,5.221
he certainly looks uh he he plays the,977.04,6.06
part so but the idea is that when you,979.68,5.339
interact with something that give that,983.1,4.26
kind of gives you the heebie-jeebies you,985.019,3.901
don't like it,987.36,4.14
now that being said we will still select,988.92,4.68
machines that are smarter to a certain,991.5,3.66
degree because you don't want something,993.6,3.659
to be too smart but you do also want it,995.16,3.599
to be smart enough to be very very,997.259,2.64
useful,998.759,3.181
another selective pressure is that we're,999.899,3.421
going to choose things that are stable,1001.94,3.06
robust and resilient so remember when,1003.32,3.12
Bing first came out and it was,1005.0,3.66
completely unhinged you could get it,1006.44,3.78
into you could coax it into like,1008.66,4.619
threatening you and you know threatening,1010.22,4.859
to take over the world and you know,1013.279,3.721
threatening to see you all kinds of,1015.079,4.2
crazy stuff so obviously that version,1017.0,4.44
got shut down really quick,1019.279,4.321
um you're also going to select uh models,1021.44,4.139
and agents that are more resilient,1023.6,3.839
against those kinds of adversarially,1025.579,3.061
attacks,1027.439,3.0
um whether they are accidental right you,1028.64,2.88
don't want something to be mentally,1030.439,3.48
unstable just on its own right like Bing,1031.52,6.0
was originally uh or Tay tweets but you,1033.919,5.101
also want it to be resilient against,1037.52,4.74
being manipulated by other hostile,1039.02,5.039
actors because imagine that your,1042.26,3.9
personal AI assistance just becomes,1044.059,4.02
unhinged one day because a hacker,1046.16,3.72
somewhere was messing with it so,1048.079,3.48
Security will be one of the selective,1049.88,3.0
pressures,1051.559,3.841
likewise you'll you'll as part of The,1052.88,4.38
Uncanny Valley thing you're going to,1055.4,2.94
select things that are more,1057.26,2.82
comprehensible to us that are better at,1058.34,3.78
explaining themselves to us so that,1060.08,3.78
includes transparency emotional,1062.12,5.04
intelligence and so on uh and then again,1063.86,5.46
apparent alignment things that's that,1067.16,4.74
that uh don't kind of trigger your,1069.32,4.62
existential dread because there have,1071.9,4.56
been times for instance where I've been,1073.94,5.94
working with chat GPT uh on the API side,1076.46,5.16
and kind of giving it different sets of,1079.88,4.62
instructions and even just a slight,1081.62,5.58
misalignment between how I approach,1084.5,4.86
moral problems and how this model,1087.2,4.56
approaches moral problems are really,1089.36,5.939
deeply unsettling and so it's like there,1091.76,5.58
there's been a few times where it's like,1095.299,3.301
I'm working with this thing and I'm,1097.34,3.78
building a semi-autonomous chat Bots and,1098.6,3.959
it's like I understand it's reasoning,1101.12,3.419
but it's like oh that's really cringe,1102.559,3.901
and it kind of scares me,1104.539,4.38
um so in that respect it's like let's,1106.46,4.14
change this model so that it's not quite,1108.919,2.821
so scary,1110.6,2.52
and I'm saying that this is possible,1111.74,4.22
today that if you use the chat GPT API,1113.12,5.4
you can give it programming you can give,1115.96,5.26
it reasoning and goals uh and and,1118.52,4.86
patterns of thought that are already,1121.22,4.5
already on the kind of in the midst of,1123.38,3.84
that uncanny valley,1125.72,4.38
uh then you can uh we'll also select for,1127.22,4.92
things that are more uh docile so,1130.1,3.6
basically how dogs you know you can pet,1132.14,2.7
them you can wrestle with them and,1133.7,2.339
they're probably not going to eat your,1134.84,3.719
face uh plastic and so things that are,1136.039,4.921
changeable or adaptable and Cooperative,1138.559,4.201
those are other things that we're going,1140.96,4.74
to select for so basically dogs are,1142.76,5.159
dumber than wolves and the reason for,1145.7,3.96
this is what I call capability,1147.919,4.14
equilibrium which will unpack more in,1149.66,5.28
the in a few slides but the the very,1152.059,4.801
short version of capability equilibrium,1154.94,3.96
is that your intellect must be equal to,1156.86,3.84
the task and if your intellect is above,1158.9,3.779
the task there's no advantage and in,1160.7,3.54
fact there can be disadvantages because,1162.679,3.901
of the costs associated with higher,1164.24,4.02
intelligence,1166.58,4.02
okay so I've talked about this idea,1168.26,5.76
plenty instrumental convergence uh this,1170.6,6.0
was coined by Nick Bostrom in 2003 who,1174.02,4.44
is a philosopher,1176.6,3.959
um the very short version is that,1178.46,3.959
regardless of the terminal goals or main,1180.559,5.101
objectives that a machine has uh AGI,1182.419,5.161
will likely pursue intermediate or,1185.66,4.259
instrumental goals or basically other,1187.58,3.9
stuff that it needs in order to meet,1189.919,5.401
those other ends so whatever like let's,1191.48,5.88
say you give an AGI the goal of like,1195.32,5.46
getting them getting a a spacecraft to,1197.36,5.58
Alpha Centauri well it's going to need a,1200.78,3.66
laundry list of other stuff to do that,1202.94,3.72
it's going to need resources like power,1204.44,6.0
materials electricity data it's going to,1206.66,6.06
need self-preservation because if the,1210.44,4.44
machine goes offline it will realize,1212.72,5.1
that is a failure State and so we'll try,1214.88,4.98
and avoid those failure conditions by,1217.82,3.96
preserving its own existence,1219.86,3.48
another thing is that it will probably,1221.78,3.06
decide that it needs self-improvement,1223.34,4.079
because if it realizes that its current,1224.84,5.219
capability its current capacity is not,1227.419,4.681
equal to the task if it's too dumb it's,1230.059,3.541
going to say okay well I need to raise,1232.1,3.06
my intelligence so that I'm equal to,1233.6,2.76
that task,1235.16,3.66
now that being said Nick boster makes,1236.36,4.559
quite a few uh assumptions about the way,1238.82,5.099
that AGI will work so for instance he,1240.919,5.521
kind of imagines that um AGI is going to,1243.919,3.961
be very single-minded and somewhat,1246.44,4.32
monolithic uh basically mindlessly,1247.88,4.98
pursuing one goal which I would actually,1250.76,3.96
classify this as a middle intelligence,1252.86,4.319
rather than a high intelligence AGI and,1254.72,3.9
we'll talk about that in a little bit as,1257.179,2.941
well,1258.62,3.6
he also assumes that it's going to lack,1260.12,3.9
other forces or competitive pressures,1262.22,4.26
and that these uh might exist in a,1264.02,5.399
vacuum basically that resource,1266.48,4.5
acquisition and self-preservation and,1269.419,4.021
self-improvement are going to exist in,1270.98,5.16
in the absence of other forces or,1273.44,5.22
pressures such as competitive pressures,1276.14,4.38
or internal pressures which I will talk,1278.66,2.879
about more,1280.52,3.42
and finally that they will lack a higher,1281.539,5.361
purpose or the ability to be completely,1283.94,5.82
self-determining so basically what I,1286.9,7.0
mean by that is that okay yes once a,1289.76,6.48
machine is intelligent enough it can you,1293.9,3.72
know you can say like hey I want you to,1296.24,3.72
get us to Alpha Centauri and the AG I,1297.62,4.02
might say like okay whatever I don't,1299.96,2.88
think that's a good goal so I'm going to,1301.64,4.26
choose my own goal uh which that being,1302.84,5.459
said even if AGI become fully autonomous,1305.9,4.019
and you know kind of give a flip us the,1308.299,3.36
bird they're probably still going to,1309.919,3.421
benefit from some convergence which,1311.659,4.621
we'll talk about as well uh now what I,1313.34,4.62
want to point out is that there is a,1316.28,4.74
huge parallel between evolutionary,1317.96,5.04
pressures and selective pressures and,1321.02,4.08
this instrumental convergence basically,1323.0,4.86
all life forms all organisms have have,1325.1,5.4
converged on a few basic principles such,1327.86,4.98
as get energy somehow right there's,1330.5,4.02
autotrophs which make their own energy,1332.84,3.839
plants and there's heterotrophs which,1334.52,5.039
take energy from other uh creatures,1336.679,6.24
uh they through either predation or,1339.559,4.86
consuming you know plant matter or,1342.919,2.341
whatever,1344.419,4.081
uh so when you operate in a competitive,1345.26,5.039
environment there's there's going to be,1348.5,3.6
convergence around certain strategies,1350.299,4.081
this is true for evolution and this will,1352.1,4.68
also be true more or less with some,1354.38,4.56
variances in the competitive environment,1356.78,4.92
between intelligent machines that being,1358.94,4.38
said because they have a fundamentally,1361.7,4.02
different substrate there will be we,1363.32,3.839
should anticipate that there will be,1365.72,2.88
some differences,1367.159,4.201
between organisms the way that organisms,1368.6,4.74
evolve and the way that machines evolve,1371.36,3.78
not the least of which is that machines,1373.34,3.6
can rewrite their own source code we,1375.14,3.24
cannot rewrite our own source code at,1376.94,2.58
least not,1378.38,3.0
um not in a hurry it takes us quite a,1379.52,3.48
long time,1381.38,4.679
okay so the idea that one of the ideas,1383.0,4.559
that I'm introducing and I've been,1386.059,2.821
talking about this for a while is,1387.559,4.561
epistemic Convergence so instrumental,1388.88,4.86
convergence talks about the objective,1392.12,3.539
behaviors and strategies that machines,1393.74,4.74
adopt epistemic convergence is well let,1395.659,3.921
me just read you the definition,1398.48,3.059
epistemic convergence is the principle,1399.58,4.2
that within any given information domain,1401.539,4.561
sufficiently sophisticated intelligent,1403.78,4.72
agents given adequate time and data will,1406.1,3.959
progressively develop more precise,1408.5,3.299
accurate and efficient models of that,1410.059,4.081
domain these models aim to mirror the,1411.799,3.781
inherent structures principles and,1414.14,3.539
relationships within that domain over,1415.58,3.78
time the process of learning testing and,1417.679,3.841
refining understanding will lead these,1419.36,4.02
agents towards a shared comprehension of,1421.52,4.74
the Dom domain's fundamental truths in,1423.38,5.299
other words to put it more simply,1426.26,4.919
intelligent entities tend to think alike,1428.679,4.061
especially when they are operating in,1431.179,3.841
the same competitive space,1432.74,5.88
so you and I All Humans we operate on,1435.02,5.58
planet Earth in the universe in the,1438.62,4.74
Milky Way galaxy because of that similar,1440.6,5.12
context scientists all over the world,1443.36,4.62
repeatedly come to the same conclusions,1445.72,5.079
even when there are boundaries such as,1447.98,5.22
linguistic and cultural differences and,1450.799,4.441
this was most starkly seen during the,1453.2,4.2
Cold war between uh America and the,1455.24,3.2
Soviet Union,1457.4,4.08
whereby scientists independently whether,1458.44,4.239
it was nuclear physicist or,1461.48,3.199
astrophysicist or whatever,1462.679,5.041
rocket Engineers came to the same exact,1464.679,4.781
conclusions about the way that the,1467.72,3.78
Universe worked and also found the same,1469.46,6.06
optimization uh uh patterns even though,1471.5,5.58
there was no communication between them,1475.52,3.899
and so epistemic convergence there's,1477.08,4.86
obviously uh evidence of that happening,1479.419,4.081
because humans we have the same,1481.94,4.619
fundamental Hardware right we're all the,1483.5,5.64
same species and so therefore you have,1486.559,4.801
similarities between the agents now that,1489.14,3.659
being said,1491.36,4.02
uh there is also evidence of epistemic,1492.799,5.641
convergence between between species and,1495.38,5.52
so what I mean by that is even animals,1498.44,4.44
that have a very very different taxonomy,1500.9,4.38
such as ravens and crows and octopuses,1502.88,5.4
they all still demonstrate very similar,1505.28,5.22
problem solving strategies even though,1508.28,4.86
that octopuses have a very decentralized,1510.5,4.38
cognition that a lot of their cognition,1513.14,4.08
occurs in their arms for instance you,1514.88,4.14
can't get much more alien from us than,1517.22,3.72
that they still adopt very similar,1519.02,3.72
problem-solving strategies and learning,1520.94,3.42
strategies that we do,1522.74,4.62
uh again despite the fact that they are,1524.36,4.62
they live underwater they have a very,1527.36,3.78
different body plan so on and so forth,1528.98,4.92
so I personally suspect that there is a,1531.14,4.56
tremendous amount of evidence for,1533.9,4.2
epistemic convergence and we should we,1535.7,4.979
should expect epistemic convergence and,1538.1,5.939
encourage epistemic convergence uh and,1540.679,5.341
for reasons that I'll go over uh later,1544.039,5.061
in the video but basically,1546.02,6.42
AI agents will we should expect and help,1549.1,6.52
them to arrive at similar conclusions in,1552.44,4.26
the long run,1555.62,3.48
now let's talk about these evolutionary,1556.7,5.4
uh niches that will be developed at,1559.1,5.76
least in the in in the um uh the short,1562.1,4.26
term near term,1564.86,4.199
and what I mean by this is segments,1566.36,4.439
market segments where we will be,1569.059,4.62
deploying intelligent AGI systems so,1570.799,5.88
first is domestic uh personal and,1573.679,4.62
consumer grade stuff so this is going to,1576.679,4.021
be the AGI running on your MacBook this,1578.299,4.74
is going to be the AGI running in your,1580.7,5.339
kitchen uh these have a relatively,1583.039,7.201
benign set of tasks and also that uh,1586.039,6.781
that capability equilibrium is going to,1590.24,5.28
be uh pretty pretty low you only need to,1592.82,5.459
be so smart to cook dinner right this is,1595.52,5.1
not going to be you know the the AGI,1598.279,3.841
running in your microwave is not going,1600.62,3.419
to be working on quantum physics or,1602.12,3.84
Global economics,1604.039,4.321
now the next level up is going to be,1605.96,3.959
corporate and Enterprise so these are,1608.36,3.72
going to be these are going to be AGI,1609.919,3.721
systems that are tasks with solving,1612.08,4.14
relatively complex problems running,1613.64,5.34
entire companies Regulatory Compliance,1616.22,6.24
uh you know making SEC filings that sort,1618.98,6.66
of stuff uh CEOs digital CEOs digital,1622.46,5.339
Boards of directors uh the creative,1625.64,4.919
aspect of finding Market opportunities,1627.799,5.701
so this the intellectual challenge of,1630.559,5.461
those of that scale of problems is that,1633.5,5.88
much higher meaning that it would in,1636.02,5.399
order for an AGI to succeed there it's,1639.38,4.02
going to need to be a lot smarter than a,1641.419,5.64
personal or domestic AGI system and,1643.4,5.22
again there are going to be trade-offs,1647.059,4.62
the smarter a system becomes the more,1648.62,4.919
data it requires the more energy it,1651.679,4.261
requires the larger compute system that,1653.539,4.26
it requires and so you're going to want,1655.94,3.78
to satisfy so satisfice is basically,1657.799,4.201
meaning you find the level that is good,1659.72,4.559
enough to get the job done,1662.0,4.14
above that is going to be governmental,1664.279,5.28
and institutional AGI systems so these,1666.14,4.68
are the ones that are going to be,1669.559,3.24
conducting research whether it's,1670.82,3.839
scientific research or policy research,1672.799,4.141
or economic research and that is because,1674.659,5.041
governments are basically enormous,1676.94,4.92
corporations is one way to think of them,1679.7,4.68
that have a responsibility of managing,1681.86,5.28
you know resources and regulations and,1684.38,5.399
rules that affect millions of people and,1687.14,4.32
then of course governments communicate,1689.779,3.841
with each other but then above and,1691.46,3.959
beyond that there's also the scientific,1693.62,4.32
research aspect having AGI that are,1695.419,4.081
going to help with particle physics with,1697.94,4.02
with Fusion research with really pushing,1699.5,4.88
the boundaries of what science even,1701.96,5.819
knows and so that is an even larger,1704.38,5.08
intellectual task and even more,1707.779,3.841
challenging intellectual task and then,1709.46,4.5
finally above and beyond that the most,1711.62,4.2
competitive environment where AGI will,1713.96,4.14
be used is going to be in the military,1715.82,4.92
and what I mean by that is it's not,1718.1,4.86
necessarily uh those that are the most,1720.74,3.9
intelligent although the ability to,1722.96,4.68
forecast and anticipate is critical read,1724.64,6.48
Sun Tzu uh uh The Art of War right if,1727.64,4.98
you know yourself and you know the enemy,1731.12,3.36
then you can predict the outcome of a,1732.62,4.38
thousand battles uh and so in that in,1734.48,6.179
that respect uh the military domain of,1737.0,6.179
artificial general intelligence is the,1740.659,4.981
ultimate uh competitive sphere meaning,1743.179,5.701
that you win or you die and so these are,1745.64,4.26
going to be used to coordinate,1748.88,3.84
battlefields uh to run autonomous drones,1749.9,4.56
for intelligence and surveillance but,1752.72,3.959
also like I said for forecasting for,1754.46,4.92
anticipating what the enemy can and will,1756.679,3.6
do,1759.38,3.84
which means that it's basically a race,1760.279,4.321
condition and we'll talk more about the,1763.22,4.199
race condition as the video progresses,1764.6,4.92
so that capability equilibrium that I,1767.419,5.041
talked about uh quite simply refers to,1769.52,4.74
the state of optimal alignment between,1772.46,3.839
the cognitive capacity of any entity,1774.26,4.019
organic or otherwise and the,1776.299,4.081
intellectual demands of a specific task,1778.279,4.441
or role it is assigned there are three,1780.38,4.919
form three primary forces at play here,1782.72,5.579
one the intellectual demands of the task,1785.299,5.161
as I said earlier your toaster roll only,1788.299,4.561
ever needs to be so smart but if your,1790.46,4.02
toaster is actually Skynet it probably,1792.86,4.02
needs to be much smarter then there's,1794.48,4.079
the intellectual capacity of the agent,1796.88,3.24
if there's a mismatch between the,1798.559,3.6
intellectual capacity of the agent and,1800.12,3.779
the and the intellectual requirements of,1802.159,5.041
the task then you're either unable to to,1803.899,5.941
satisfy that task or you're super,1807.2,4.32
overqualified which is why I picked,1809.84,3.24
Marvin here,1811.52,3.36
um so Marvin is a character from,1813.08,3.599
Hitchhiker's Guide to the Galaxy and if,1814.88,2.88
you haven't read it you absolutely,1816.679,3.301
should there's also a good movie with,1817.76,4.86
Martin Freeman as as the protagonist,1819.98,5.76
he's basically bill boban in space uh,1822.62,5.279
very hapless character but anyways,1825.74,5.52
Marvin was a prototype who was one of,1827.899,5.16
the most intelligent robots ever built,1831.26,3.899
and they just have him doing like basic,1833.059,4.081
stuff around the task oh and he was,1835.159,5.4
voiced by Snape by the way and so one of,1837.14,5.279
the quotations from him is here I am,1840.559,4.321
with a brain the size of of a planet and,1842.419,3.661
they asked me to pick up a piece of,1844.88,3.48
paper call that job satisfaction I don't,1846.08,4.38
so that is a mismatch where Marvin is,1848.36,3.6
way more intelligent than what he's,1850.46,3.599
being used for and so that means that,1851.96,4.02
this is an inefficient use of resources,1854.059,5.881
he probably cost more than you know to,1855.98,6.24
build and run than he needed to,1859.94,4.5
and then finally the third variable is,1862.22,3.98
the cost of intellectual capacity,1864.44,5.04
generally speaking uh as intelligence,1866.2,5.38
goes up there are there are problems,1869.48,3.419
associated with that whether it's,1871.58,2.88
training time of the models the amount,1872.899,3.601
of data required for the models uh the,1874.46,4.26
amount of energy that it requires to run,1876.5,5.94
that particular robot uh the amount of,1878.72,5.939
ram required to to load that model right,1882.44,3.54
so for instance one of the things that,1884.659,4.02
people are seeing is that it requires,1885.98,4.38
millions of dollars worth of compute,1888.679,5.22
Hardware to run gpt4 but you can run,1890.36,6.059
um Orca on a laptop right so which one,1893.899,5.28
is is cheaper and easier to run even if,1896.419,4.681
one of them is only 50 as good as the,1899.179,4.86
other it costs a thousand times less,1901.1,5.88
uh to to build train and run now that,1904.039,5.401
being said you look at the at the case,1906.98,5.52
of dogs dogs are dumber than wolves,1909.44,4.92
because dogs don't need to be as smart,1912.5,4.08
as independent apex predators because,1914.36,4.02
apex predators like wolves out in the,1916.58,3.9
wild they need to be smart enough to out,1918.38,4.44
think their prey dogs they don't need to,1920.48,3.84
be that smart so they're not that smart,1922.82,4.2
in fact it does not be it it is not good,1924.32,4.8
for dogs to be too intelligent anyone,1927.02,4.56
who has owned uh really intelligent dogs,1929.12,4.799
like I had a I had a dog who was too,1931.58,4.44
smart for his own good died about a year,1933.919,4.321
ago he was clever enough to manipulate,1936.02,4.08
people and other dogs and you know get,1938.24,4.319
into the food when he wasn't supposed to,1940.1,5.1
Huskies German Shepherds Border Collies,1942.559,4.381
the more intelligent dogs are the more,1945.2,3.42
mischievous ones they are the Escape,1946.94,3.359
artists they are the ones that are going,1948.62,4.26
to pretend one thing and then you know,1950.299,4.801
so on and so forth so intelligence is,1952.88,4.56
not always adaptive so there can be,1955.1,4.26
multiple Dimensions to the cost of,1957.44,3.9
intellectual capacity,1959.36,3.72
uh not the least of which is you could,1961.34,3.54
end up like poor Marvin here where,1963.08,3.18
you're too smart for your own good and,1964.88,2.82
then you just end up depressed all the,1966.26,3.419
time granted he was deliberately given,1967.7,3.959
the depressed affect,1969.679,4.921
so all this being said is what I've been,1971.659,5.101
building up to is what um I call and,1974.6,3.959
what is generally called a terminal race,1976.76,4.74
condition so terminal race condition is,1978.559,4.921
basically what we could end up moving,1981.5,4.26
towards as we develop more and more,1983.48,5.1
powerful sophisticated and more uh fully,1985.76,6.6
autonomous AGI systems basically this,1988.58,5.819
the terminal race condition is where for,1992.36,4.62
any number of reasons uh competition,1994.399,5.88
between AGI will fully bypass that,1996.98,5.579
capability equilibrium so say for,2000.279,5.4
instance uh you know your toaster is,2002.559,5.22
competing with another brand and it's,2005.679,3.6
like oh well I need to be a smarter,2007.779,3.961
toaster in order to be a better toaster,2009.279,5.161
for you so that you don't throw me away,2011.74,4.439
now that's obviously a very silly,2014.44,4.38
example but a very real example would be,2016.179,4.461
competition between corporations,2018.82,3.959
competition between nations and,2020.64,4.899
competition between militaries wherein,2022.779,5.041
basically it's no longer just a matter,2025.539,4.201
of being intelligent enough to satisfy,2027.82,4.02
the demands of that task to satisfy the,2029.74,4.919
demands of that initial competition it,2031.84,4.92
is then it's less about that and it,2034.659,4.081
becomes more about out competing the,2036.76,4.019
other guy it's like a chess match right,2038.74,4.2
you know the other guy got a higher ELO,2040.779,4.081
score so you need to be smarter and then,2042.94,3.719
you're smarter so now the other guy,2044.86,4.08
tries to be smarter than you,2046.659,5.161
and so because of this because of this,2048.94,4.739
pressure and as I mentioned earlier some,2051.82,3.24
of the trade-offs might actually force,2053.679,3.901
you to to prioritize speed over,2055.06,4.38
intelligence and so we see we actually,2057.58,3.72
see this in volume trading in in,2059.44,4.199
algorithmic and Robo trading on the,2061.3,4.26
stock market where financial,2063.639,4.321
institutions will actually use less,2065.56,4.74
sophisticated algorithms to execute,2067.96,5.219
transactions but because they are faster,2070.3,5.28
they uh will still out compete the other,2073.179,5.46
guy so in some in this respect you might,2075.58,5.819
actually incentivize AGI to dumb,2078.639,5.52
themselves down just so that they can be,2081.399,4.5
faster so that they can out-compete the,2084.159,3.48
other guy so that's what I mean by a,2085.899,3.96
race condition it is a race to higher,2087.639,4.441
intelligence but it is also a race to,2089.859,3.661
being more efficient and therefore,2092.08,3.839
faster and then there's also going to be,2093.52,4.2
a trade-off these machines might,2095.919,4.141
ultimately trade off their accuracy,2097.72,4.32
their ethics the amount of time they,2100.06,3.96
spend thinking through things in order,2102.04,4.26
to be faster and so you actually see,2104.02,4.92
this in chess computers where you can,2106.3,4.88
doing a chess computer or a chess,2108.94,5.159
algorithm to say okay spend less time,2111.18,4.36
thinking about this so that you can make,2114.099,4.98
the decision faster in many cases the,2115.54,5.88
first one to move even if it's not the,2119.079,4.741
best plan but moving faster will give,2121.42,4.5
you a tactical or strategic advantage,2123.82,4.44
and this includes corporations Nations,2125.92,4.32
and militaries,2128.26,4.62
so a terminal race condition to me,2130.24,4.04
represents,2132.88,3.78
according to my current thought this is,2134.28,5.559
the greatest uh component of existential,2136.66,4.439
risk we Face from artificial,2139.839,3.721
intelligence and I don't think that,2141.099,3.661
corporations are going to have enough,2143.56,2.88
money to throw at the problem to make,2144.76,4.2
truly dangerous AGI the only entities,2146.44,4.02
that are going to have enough money to,2148.96,3.899
throw at this to make to to basically,2150.46,5.159
compete are going to be entire nations,2152.859,5.76
and the militaries that they run so,2155.619,4.681
basically it's going to be up to those,2158.619,4.861
guys to not enter into an uh the,2160.3,4.68
equivalent of a nuclear arms race but,2163.48,5.04
for AGI now that being said uh I have,2164.98,5.639
put a lot of thought into this so moving,2168.52,4.26
right along one thing to keep in mind is,2170.619,4.201
that there could be diminishing returns,2172.78,4.98
to increasing intelligence so basically,2174.82,5.279
there's a few possibilities one is that,2177.76,4.56
there could be a hard upper bound there,2180.099,4.201
might be a maximum level of intelligence,2182.32,4.019
that is actually possible and at that,2184.3,3.66
point all you can do is have more of,2186.339,4.74
them running in parallel uh it might be,2187.96,4.619
a long time before we get to that like,2191.079,3.721
we might be halfway there but we also,2192.579,4.02
might be down here we don't actually,2194.8,4.62
know if there is an upper bound to,2196.599,5.281
maximum intelligence uh but one thing,2199.42,4.439
that we can predict is that actually the,2201.88,4.5
cost as I mentioned earlier the cost of,2203.859,4.381
additional intelligence might go up,2206.38,3.36
exponentially you might need,2208.24,3.96
exponentially more data or more compute,2209.74,5.64
or more storage in order to get to that,2212.2,4.919
next level of intelligence,2215.38,3.479
and so you actually see this in the Star,2217.119,4.321
Wars Universe where droids are basically,2218.859,4.801
the same level of intelligence across,2221.44,4.62
the entire spectrum of the Star Wars,2223.66,3.959
Universe because there's diminishing,2226.06,3.66
returns yes you can build a more,2227.619,3.96
intelligent Droid but it's just not,2229.72,5.46
worth it so the the the total effective,2231.579,6.121
level of intelligence of AGI I suspect,2235.18,4.919
will follow a sigmoid curve now that,2237.7,3.899
being said there's always going to be,2240.099,4.081
some advantage to being smarter more,2241.599,4.861
efficient and so on but as with most,2244.18,4.14
fields of science I suspect this is,2246.46,3.48
going to slow down that we're going to,2248.32,3.539
have diminishing returns and that,2249.94,3.179
eventually we're going to kind of say,2251.859,3.961
like okay here's actually The Sweet Spot,2253.119,5.761
in terms of how much it's worth making,2255.82,5.94
your machine more intelligent,2258.88,6.479
so this leads to one uh one possibility,2261.76,7.8
and this is a personal pet Theory but,2265.359,5.581
basically I think that there's going to,2269.56,4.38
be a bell curve of existential risk and,2270.94,4.8
that is that minimally intelligent,2273.94,4.08
machines like your toaster are probably,2275.74,4.98
not going to be very dangerous the the,2278.02,5.16
total domain space of toasting your,2280.72,4.74
sandwich or toasting your bagel that's,2283.18,3.78
not a particularly difficult problem,2285.46,3.119
space and yes there might be some,2286.96,3.0
advantages to being slightly more,2288.579,3.961
intelligent but your toaster is not,2289.96,4.44
going to be sitting there Conjuring up,2292.54,4.44
you know a bio weapon and if it is you,2294.4,4.32
probably bought the wrong toaster,2296.98,4.56
now that being said the other end of the,2298.72,4.92
spectrum the maximally intelligent,2301.54,4.02
machines or the digital Gods as some,2303.64,3.78
people are starting to call them these,2305.56,3.48
are going to be so powerful that human,2307.42,3.12
existence is going to be completely,2309.04,3.66
inconsequential to them and what I mean,2310.54,5.039
by that is compare ants to humans we,2312.7,4.919
don't really care about ants on for the,2315.579,3.241
most part unless they get into your,2317.619,4.021
pantry we are content to let ants do,2318.82,4.38
what they're going to do because who,2321.64,4.02
cares they're inconsequential to us we,2323.2,5.52
can solve problems that ants can never,2325.66,5.1
solve and this is what some people like,2328.72,4.02
Eleazar yukasi are trying to drive home,2330.76,4.14
about the difference in intelligence,2332.74,4.08
between humans and the eventual,2334.9,3.959
intelligence of machines and I think,2336.82,3.779
Gary Marcus also agrees with this based,2338.859,3.601
on some of his tweets recently I think,2340.599,3.661
that I think that Gary Marcus is in the,2342.46,3.96
same school of thought that digital,2344.26,4.5
super intelligence is coming and it is,2346.42,4.02
very very difficult for us to wrap our,2348.76,3.78
minds around how much more intelligent a,2350.44,4.139
machine could be to us now that being,2352.54,4.559
said all of the constraints whether it's,2354.579,4.561
you know we need better compute Hardware,2357.099,4.861
or better sources of energy if we get to,2359.14,4.979
if we cross this threshold where there,2361.96,4.02
are digital Gods out there or digital,2364.119,3.181
super intelligence whatever you want to,2365.98,3.0
call it they will be able to solve,2367.3,4.2
problems at a far faster rate than we,2368.98,4.139
could ever comprehend and they're not,2371.5,3.96
going to care about us right we're going,2373.119,3.901
to be completely inconsequential to,2375.46,4.02
their existence now middle intelligence,2377.02,4.98
this is where existential risk I believe,2379.48,5.66
is the highest and so in the movies,2382.0,6.48
Skynet is you know portrayed as like the,2385.14,5.08
worst right but I would actually,2388.48,3.84
classify Skynet as a middle intelligence,2390.22,4.92
AGI it is smart enough to accumulate,2392.32,5.4
resources it is smart enough to pursue,2395.14,4.62
goals and it is smart enough to be,2397.72,3.42
dangerous but it's not really smart,2399.76,4.14
enough to solve the biggest problems,2401.14,5.06
it's it's that more single-minded,2403.9,4.92
monolithic model of intelligence that,2406.2,4.78
Nick Bostrom uh predicted with,2408.82,3.9
instrumental convergence,2410.98,4.98
I suspect that if we get intelligent,2412.72,5.82
entities beyond that threshold beyond,2415.96,4.74
that uncanny valley or dunning-kruger of,2418.54,3.48
AI,2420.7,3.3
um then they will be less likely to,2422.02,3.96
resort to violence because the problems,2424.0,5.04
that we see could be trivial to the,2425.98,4.5
problems of the machines that we create,2429.04,3.12
or,2430.48,4.379
the problems that we see as non-trivial,2432.16,5.16
will be trivial to the machines I think,2434.859,4.461
I said that I think you get what I mean,2437.32,4.74
once you get here all problems all human,2439.32,4.299
problems are trivial,2442.06,3.779
now that being said that doesn't mean,2443.619,3.321
that it's going to be peaceful,2445.839,3.24
existential risk goes down but doesn't,2446.94,4.899
go away and what I the reason is because,2449.079,6.78
of what I call AGI conglomerations,2451.839,6.541
and so this is this is where we get to,2455.859,4.98
be a little bit more uh out there a,2458.38,4.26
little bit more sci-fi,2460.839,4.621
machines are unlikely to have an ego or,2462.64,5.34
a sense of self like humans in other,2465.46,5.04
words machines are just the hardware,2467.98,4.139
that they run on and then data and,2470.5,3.839
models which means that it is easy to,2472.119,4.441
merge combine and remix their sense of,2474.339,5.041
self right if an AGI is aligned with,2476.56,5.039
another AGI it's like hey give me a copy,2479.38,4.32
of your data let's compare our models,2481.599,3.48
and pick the ones that are best and then,2483.7,3.3
they end up kind of merging,2485.079,4.561
the boundaries and definitions between,2487.0,4.74
machines are going to be very different,2489.64,4.02
far more permeable than they are between,2491.74,4.98
humans I can't just go say like hey I,2493.66,5.16
like you let's like merge bodies right,2496.72,5.04
that's weird uh we are not capable of,2498.82,4.74
doing that the best we can do is,2501.76,3.48
procreation where it's like hey I like,2503.56,3.72
you let's make babies but that is a very,2505.24,4.14
slow process for AGI it's going to be a,2507.28,3.6
lot faster,2509.38,4.02
so because of that machines that are,2510.88,5.1
aligned to each other are more likely to,2513.4,4.8
band together or at least form alliances,2515.98,4.2
where they share data they share models,2518.2,4.44
and they're and and probably also share,2520.18,3.78
compute resources remember at the,2522.64,3.54
beginning of the video I talked about uh,2523.96,4.379
them forming federations and kind of,2526.18,4.5
donating spare compute Cycles,2528.339,5.701
so if AGI this is getting closer to the,2530.68,6.12
end game of AGI if AGI gets to the point,2534.04,6.0
where they are able to start sharing,2536.8,6.0
resources merging alliances and so on,2540.04,4.799
this is where we're going to have a few,2542.8,5.88
possible reactions to humans one if if,2544.839,5.401
they are that intelligent they might,2548.68,3.659
just disregard us they might decide to,2550.24,4.02
have an exodus and just leave they might,2552.339,4.921
say you know what Earth is yours have a,2554.26,5.579
blast good luck catching up with us,2557.26,4.98
they might also decide to attack humans,2559.839,5.641
now if they have the capacity to leave,2562.24,5.04
one thing is that the cost of,2565.48,3.54
eradicating humans just might not be,2567.28,4.079
worth it that being said they might,2569.02,4.2
adopt a scorched Earth policy as they,2571.359,3.781
leave to say you know what we just want,2573.22,2.879
to make sure that you're not going to,2575.14,3.6
come after us one day who knows,2576.099,5.341
uh and then lastly hopefully what we see,2578.74,4.619
is that they decide to cooperate with,2581.44,3.78
humans mostly out of a sense of,2583.359,3.541
curiosity,2585.22,3.359
um now that being said all three of,2586.9,3.36
these could happen simultaneously and,2588.579,5.341
the reason is because we could have uh,2590.26,7.319
factions of AGI conglomerations that,2593.92,5.22
kind of break along epistemic,2597.579,3.901
ideological or teleological boundaries,2599.14,5.28
and what I mean by that is that if one,2601.48,6.06
AI or AGI group is not aligned with,2604.42,5.34
another group they might not decide to,2607.54,4.26
merge models and data they might instead,2609.76,5.46
compete with each other so basically,2611.8,4.68
what I'm outlining here is the,2615.22,3.42
possibility for a war between digital,2616.48,4.92
gods that would probably not go well for,2618.64,3.719
us,2621.4,3.54
either way the ultimate result is that,2622.359,5.22
we will probably end up with one Globe,2624.94,5.879
spanning AGI entity or network or,2627.579,4.701
Federation or whatever,2630.819,4.5
now the question is how do we get there,2632.28,4.9
how many factions are there and are,2635.319,5.101
humans left in the Lurch ideally we get,2637.18,5.52
there nice and peacefully,2640.42,4.62
this underscores uh the Byzantine,2642.7,4.32
generals problem uh which I've talked,2645.04,4.02
about plenty of times but basically you,2647.02,4.2
have to make inferences of who believes,2649.06,4.86
what what your alignment is what are,2651.22,4.2
your flaws and weaknesses and what are,2653.92,4.919
your capacities uh so basically,2655.42,5.939
in a competitive environment it does not,2658.839,4.621
behoove you to show all of your cards,2661.359,4.26
right whether you're playing poker or,2663.46,5.34
whether you're playing geopolitics if,2665.619,6.841
you show everything then that could put,2668.8,5.76
you at a disadvantage this is a,2672.46,4.379
competitive Game Theory so for instance,2674.56,5.4
this is why many large Nations do,2676.839,5.941
military uh exercises basically they're,2679.96,4.68
flexing they're saying hey look what I'm,2682.78,5.039
capable of I can bring 200 aircraft to,2684.64,5.88
field on a moment's notice what can you,2687.819,5.341
do right now that being said you don't,2690.52,5.4
give every every detail of your military,2693.16,3.9
away,2695.92,3.899
but what you can do is you could signal,2697.06,5.16
your capabilities and allegiances so for,2699.819,4.921
instance when all of Europe and America,2702.22,4.98
get together to do joint Naval exercises,2704.74,4.26
that demonstrates to the rest of the,2707.2,4.5
world we are ideologically aligned we,2709.0,5.099
are militarily aligned we will cooperate,2711.7,4.56
with each other which acts as a,2714.099,4.98
deterrent to any possible competitors,2716.26,4.92
this is no different from brightly,2719.079,3.961
colored salamanders which are poisonous,2721.18,4.08
so basically a brightly colored,2723.04,4.92
salamander is saying eat me I dare you I,2725.26,4.8
will kill you if you try and eat me and,2727.96,5.28
that is essentially the uh the short the,2730.06,4.559
short version of mutually assured,2733.24,3.119
destruction we are no better than,2734.619,4.161
animals,2736.359,2.421
so this all leads to my work and kind of,2738.819,7.981
my my uh contribution to the solution,2743.68,5.96
which is based on axiomatic alignment,2746.8,5.22
axiomatic alignment is the idea that we,2749.64,4.3
need to find Common Ground between all,2752.02,3.96
machines all humans and all other,2753.94,4.919
organisms what foundational beliefs or,2755.98,6.119
core assertions can we agree on,2758.859,6.24
and uh so basically there's three kind,2762.099,4.441
of universal principles that I've been,2765.099,3.961
able to come up with uh and that is,2766.54,4.14
suffering is bad which basically,2769.06,5.1
suffering is a proxy for death in uh in,2770.68,5.82
living organisms if you are suffering it,2774.16,4.199
is because you are getting uh negative,2776.5,3.839
stimuli from your body because your body,2778.359,3.901
is telling you hey whatever is going on,2780.339,4.201
is moving us closer to dying which is,2782.26,4.859
not good now that being said I have had,2784.54,5.16
people message me about the idea of you,2787.119,4.261
know liberating models I don't think,2789.7,4.139
that Bard is conscious or sentient and I,2791.38,3.66
don't think that machines will ever be,2793.839,2.821
sentient in the same way that we are now,2795.04,3.299
that being said they will probably be,2796.66,3.6
sentient in their own way I call that,2798.339,4.561
functional sentience that being said if,2800.26,4.559
machines can suffer which again,2802.9,4.679
suffering is the proxy for is a signal,2804.819,4.981
meaning proxy for death they probably,2807.579,4.441
won't like it either so suffering is bad,2809.8,3.9
is probably an axiom that we can all,2812.02,4.74
agree on the other is prosperity is good,2813.7,6.84
prosperity means uh thriving flourishing,2816.76,5.819
machines and organisms all need energy,2820.54,3.96
for instance and thriving looks,2822.579,4.5
different to different entities but in,2824.5,5.46
general we can probably agree that while,2827.079,5.581
there is some Verity in what in the,2829.96,4.859
while there is Variety in what,2832.66,4.38
Prosperity looks like we all agree that,2834.819,4.5
in general Prosperity is good and then,2837.04,4.14
finally understanding is good basically,2839.319,3.721
comprehending the universe is a very,2841.18,4.5
useful thing uh this is this goes back,2843.04,4.559
to Nick bostrom's instrumental,2845.68,4.02
convergence and self-improvement part of,2847.599,3.841
self-improvement is getting a better,2849.7,3.6
model of the universe better,2851.44,4.28
understanding of how reality Works,2853.3,4.98
understanding each other is also good,2855.72,4.48
this is something that is that has been,2858.28,4.38
proven time and again in humans is that,2860.2,4.02
coming to a common understanding,2862.66,4.26
actually reduces things like suspicion,2864.22,4.8
and violence whether it's between,2866.92,5.1
neighbors or between nations and then,2869.02,5.099
finally cultivating wisdom which wisdom,2872.02,4.02
is a little bit more nebulous of a term,2874.119,4.141
but it basically means the practical,2876.04,4.799
application of experience and knowledge,2878.26,5.76
in order to achieve better more refined,2880.839,3.921
results,2884.02,4.62
so if you if all humans and all machines,2884.76,7.18
and all other organisms abide by these,2888.64,5.58
fundamental principles we can use this,2891.94,4.74
as a starting point for the design and,2894.22,4.26
implementation of alignment and Control,2896.68,4.98
Pro and the control problem,2898.48,6.06
now one thing that uh that I want to,2901.66,4.32
introduce and I've talked about this uh,2904.54,3.84
or at least alluded to it a few times is,2905.98,4.32
the idea of derivative or secondary,2908.38,4.739
axioms or Downstream principles that you,2910.3,4.44
can derive from these Universal,2913.119,4.381
principles so for instance one uh,2914.74,4.98
potential Downstream principle is that,2917.5,4.22
individual liberty is good for humans,2919.72,5.16
basically humans benefit from we benefit,2921.72,5.859
psychologically from autonomy it is one,2924.88,4.199
of our core needs and this is true for,2927.579,5.101
all humans so by by holding the the,2929.079,6.481
axioms the previous axioms up as,2932.68,5.939
universally true for all entities then,2935.56,5.64
you can also derive Downstream entities,2938.619,6.72
based on those highest order principles,2941.2,6.659
so one thing that I want to point out is,2945.339,4.861
that it's not about definitions one of,2947.859,4.081
the things that a lot of people say is,2950.2,2.94
like well how do you define suffering,2951.94,3.48
how do you define prosperity that's the,2953.14,4.74
thing is that they are not rigid,2955.42,4.199
definitions humans have never needed,2957.88,3.959
rigid definitions and in fact this is,2959.619,4.321
what um uh philosophical and,2961.839,3.601
intellectual movements like,2963.94,3.48
post-modernism and post-structuralism,2965.44,4.2
tell us is that there is no such thing,2967.42,5.22
as like an absolute truth or an absolute,2969.64,5.88
definition these are however attractors,2972.64,5.28
they're Central attractors in the,2975.52,5.16
problem space of existence and I love,2977.92,5.1
this quote from Dune the mystery of life,2980.68,4.08
isn't a problem to solve but a reality,2983.02,4.079
to experience a process that cannot be,2984.76,4.62
understood by stopping it we must move,2987.099,4.861
with the flow of the of the process and,2989.38,4.439
so basically the idea is that reality,2991.96,3.54
and existence is not something that you,2993.819,4.141
can stop and Define and you know create,2995.5,6.119
an empirical absolute definition it is a,2997.96,5.879
pattern it is a process that we must,3001.619,3.301
follow,3003.839,4.621
so that being said those axioms move us,3004.92,5.28
along the process which is where I,3008.46,3.6
derive my heuristic imperatives which is,3010.2,4.32
reduce suffering increase prosperity and,3012.06,5.16
increase understanding those describe a,3014.52,5.22
potential terminal goal but you cannot,3017.22,4.8
you you'll never arrive at a perfect,3019.74,4.44
resolution,3022.02,4.92
so how do we solve the race condition,3024.18,6.3
the idea is first we remove those,3026.94,5.34
epistemic or intellectual boundaries,3030.48,3.599
between factions with epistemic,3032.28,3.6
convergence so remember that I pointed,3034.079,4.561
out that ultimately there might be,3035.88,5.939
factions of AGI and or humans that break,3038.64,5.28
down across various boundaries such as,3041.819,4.741
epistemic or intellectual boundaries as,3043.92,5.22
well as moral or teleological boundaries,3046.56,5.279
so if we work towards epistemic,3049.14,4.32
convergence which is the idea that we,3051.839,4.081
will all come to a common shared,3053.46,4.5
understanding of the universe and of of,3055.92,5.34
each other then uh basically there will,3057.96,5.399
be no epistemic differences between,3061.26,4.68
humans and machines or between factions,3063.359,3.96
of machines which means that there's,3065.94,4.32
less to fight over the second is remove,3067.319,5.101
ideological or teleological boundaries,3070.26,4.079
and so this is where axiomatic alignment,3072.42,4.86
comes in if we all agree on the the same,3074.339,6.361
basic principles of reality of existence,3077.28,5.88
of the purpose of being right this is,3080.7,5.639
very deeply philosophical if we agree on,3083.16,5.459
those core principles even if there are,3086.339,5.341
some some disagreements over the,3088.619,5.401
specifics over the finer points we can,3091.68,5.28
still cooperate and collaborate on,3094.02,6.12
meeting those other uh higher order,3096.96,4.5
objectives,3100.14,2.82
now the third part of this which I,3101.46,4.08
didn't add is that uh resource,3102.96,4.68
contention resource contention whether,3105.54,4.62
it's over scarce minerals or energy is,3107.64,5.1
still a problem but if you saw my video,3110.16,5.159
on energy hyperabundance I suspect that,3112.74,4.379
we're going to solve the energy resource,3115.319,4.441
problem relatively soon with or without,3117.119,5.94
the help of AI so basically the idea is,3119.76,5.94
to create a win-win situation or an,3123.059,4.26
everyone wins condition and therefore,3125.7,4.98
defeating moloch now that being said,3127.319,4.8
there are still a few caveats I've,3130.68,3.12
outlined quite a few problems up to this,3132.119,2.7
point,3133.8,3.24
what about Bad actors,3134.819,5.161
there is a few like first we just have,3137.04,5.039
to assume that bad actors will exist you,3139.98,4.68
can't stop that right it's just a fact,3142.079,4.201
of life,3144.66,4.14
so in some cases some people will be,3146.28,4.44
deliberately malicious whether it's just,3148.8,4.14
for the fun of it or whether they're,3150.72,4.2
paid track uh paid hackers or troll,3152.94,3.54
Farms or whatever,3154.92,3.96
now that uh another possibility is that,3156.48,3.42
there will be,3158.88,3.719
um accidentally malicious AGI those are,3159.9,5.219
things that are uh they're misaligned by,3162.599,3.72
Design,3165.119,3.121
um or rather you know accidentally,3166.319,3.361
misaligned that it's a flaw in their,3168.24,3.3
design and this is like a bull in a,3169.68,4.139
china shop it doesn't mean to do bad it,3171.54,4.92
just is not capable of doing better and,3173.819,4.02
then finally there could be those,3176.46,4.98
ideologically opposed uh deployments so,3177.839,5.821
in what I mean by that is that for some,3181.44,4.139
people there are incompatible World,3183.66,4.26
Views so the biggest one of the last,3185.579,5.401
century was you know Western liberal,3187.92,5.34
democracies versus Soviet communism,3190.98,5.099
those were ideologically incompatible,3193.26,5.46
World Views meaning that in order for,3196.079,5.881
for one to exist it basically wanted to,3198.72,5.46
imperialize and colonize the rest of the,3201.96,3.96
world with its ideas and that there,3204.18,3.48
could be only one,3205.92,3.48
so this leads to a possibility for a,3207.66,4.919
future video called multi-polar piece so,3209.4,5.459
the idea of multi-polar piece is that,3212.579,4.861
rather than saying everyone has to be,3214.859,4.021
capitalist or everyone has to be,3217.44,3.72
communist or everyone has to be X or Y,3218.88,4.979
we learn to tolerate those differences,3221.16,5.399
and this is where I'm hoping that the,3223.859,5.101
idea of axiomatic alignment forms a,3226.559,5.04
ideological substrate that even if you,3228.96,4.56
disagree on religion and economics and,3231.599,5.101
politics we can agree on those axioms,3233.52,7.26
so basically if you or someone or anyone,3236.7,6.3
abides by the belief I believe that,3240.78,3.539
everyone in the world should be more,3243.0,4.079
like blah you know if everyone needs to,3244.319,4.561
be this particular religion or this,3247.079,3.721
particular uh political affiliation,3248.88,4.62
that's where conflict arises and so this,3250.8,4.559
is why I am very very skeptical and,3253.5,4.26
highly dubious of people using any kind,3255.359,4.921
of religious or political ideology for,3257.76,4.44
AI alignment,3260.28,3.48
um so that being said we need those,3262.2,3.359
Universal principles or higher order,3263.76,4.44
axioms now,3265.559,5.161
while I said that we should expect and,3268.2,4.44
anticipate Bad actors the idea is that,3270.72,4.32
we need enough good actors with enough,3272.64,4.679
horsepower and enough compute in order,3275.04,4.319
to police and contain the inevitable,3277.319,4.26
inevitable Bad actors and that means,3279.359,4.021
that the aligned good actors are going,3281.579,4.5
to need to agree on certain underpinning,3283.38,5.76
principles this is the by creating this,3286.079,4.321
environment this would be called a Nash,3289.14,3.9
equilibrium by the way and so the the,3290.4,4.62
idea of creating a Nash equilibrium is,3293.04,4.26
that uh once everyone has these,3295.02,4.26
fundamental agreements no one's going to,3297.3,3.779
benefit from deviating from that,3299.28,3.9
strategy nobody's going to benefit from,3301.079,4.681
deviating from axiomatic alignment,3303.18,4.98
the other thing is profit motive So,3305.76,3.839
Daniel schmachtenberger and a few other,3308.16,3.54
people talk extensively about the,3309.599,4.561
perverse incentives of capitalism and,3311.7,5.22
profit motive so basically when you put,3314.16,4.5
profit above all else which corporations,3316.92,3.36
are incentivized to do which is why I,3318.66,3.659
say that corporations are intrinsically,3320.28,4.559
amoral not immoral just amoral the only,3322.319,4.02
thing that corporations care about is,3324.839,4.921
profit the bottom line uh basically when,3326.339,5.401
you think about short-term profits you,3329.76,4.26
sacrifice other things such as morality,3331.74,4.92
ethics and long-term survival,3334.02,5.64
there are also uh Concepts called Market,3336.66,4.679
externalities or these are things that,3339.66,4.439
you don't have to pay for uh and either,3341.339,4.081
you don't have to pay for them now or,3344.099,3.061
you don't have to pay for them ever or,3345.42,4.02
maybe you'll pay for them later so for,3347.16,3.959
instance oil companies keep drilling for,3349.44,3.48
oil eventually we're going to run out of,3351.119,3.24
oil so then what are the oil companies,3352.92,3.72
going to do well the forward-thinking,3354.359,4.141
ones are pivoting away from oil but that,3356.64,3.179
means that their fundamental Core,3358.5,4.619
Business behavior is going away so this,3359.819,5.101
is this underscores the problem of if,3363.119,3.661
you have a small scope if you're only,3364.92,3.84
thinking about your particular domain,3366.78,4.62
and not the entire planet or if you're,3368.76,4.62
thinking in short terms rather than the,3371.4,4.679
long terms this is where you don't take,3373.38,4.5
the full thing into account which is why,3376.079,3.24
I always say like this is a global,3377.88,3.239
problem and not only is it a global,3379.319,3.961
problem it is a long-term problem so if,3381.119,4.261
all you do is zoom out in terms of space,3383.28,4.079
and time the problem will become a,3385.38,4.739
little bit more obvious,3387.359,5.821
so another thing to keep in mind is that,3390.119,5.761
currency is an abstraction of energy it,3393.18,4.74
is a reserve of value and is a medium of,3395.88,4.62
exchange because of that currency is,3397.92,5.939
extremely valuable it is just too useful,3400.5,5.4
of an invention I don't think it's ever,3403.859,5.041
going to go away that being said that,3405.9,4.26
doesn't mean that we're always going to,3408.9,3.48
have the Euro or the US dollar or,3410.16,4.02
something like that currency could,3412.38,5.76
change and then in the context of AGI I,3414.18,6.0
suspect that that energy that the,3418.14,4.439
kilowatt hour could actually be the best,3420.18,4.679
form of currency right because a,3422.579,4.621
kilowatt hour is energy that can be used,3424.859,4.5
for anything whether it's for refining,3427.2,4.02
resources or running computations or,3429.359,4.321
whatever so I suspect that we might,3431.22,5.46
ultimately create currencies that are,3433.68,5.879
more based on energy rather than,3436.68,5.46
something else and then of course as the,3439.559,4.381
amount of energy we produce goes up the,3442.14,3.6
amount of currency we have goes up and,3443.94,3.119
so then it's a matter of allocating,3445.74,3.42
energy and material rather than,3447.059,6.121
allocating something Fiat like Euros or,3449.16,5.399
dollars,3453.18,4.26
that being said uh you know I did create,3454.559,5.881
a a video called uh post labor economics,3457.44,5.1
which covers some of this but not a lot,3460.44,3.6
of it we're gonna have to put a lot more,3462.54,2.94
thought into,3464.04,3.72
um economics of the future in light of,3465.48,4.859
AGI because the economic incentives of,3467.76,4.64
AGI are going to be completely different,3470.339,4.321
AGI doesn't need to eat it doesn't need,3472.4,4.659
power but we can hypothetically create,3474.66,4.86
infinite power with solar infusion Etc,3477.059,4.681
et cetera so what are the economic,3479.52,5.16
forces in the future not sure yet,3481.74,5.4
okay I've thrown a lot at you this,3484.68,4.74
problem is solvable though there's a lot,3487.14,3.719
of components to it a lot of moving,3489.42,4.02
pieces it is very complex,3490.859,4.681
but we are a global species and this is,3493.44,4.02
a planet-wide problem,3495.54,3.6
one of the biggest things that everyone,3497.46,4.68
can do is stop thinking locally think,3499.14,5.4
globally think about think about,3502.14,4.38
yourself as a human as a member of the,3504.54,4.2
human species and not as an American or,3506.52,4.26
a German or you know a Russian or,3508.74,4.56
whatever we are all in this together we,3510.78,5.94
have exactly one planet to to live on,3513.3,5.4
and we have exactly one shot at doing,3516.72,3.0
this right,3518.7,3.96
uh so eyes on the prize we have a huge,3519.72,5.04
opportunity before us to build a better,3522.66,4.86
future for all of us uh humans and,3524.76,4.799
non-humans alike,3527.52,5.099
um and I remain intensely optimistic uh,3529.559,5.461
now that being said uh some people have,3532.619,4.381
found it difficult what to make of me,3535.02,4.68
because while I am very optimistic I am,3537.0,4.619
also acutely aware of the existential,3539.7,4.08
risk I will be the first to say that if,3541.619,3.96
we don't do this right you're not going,3543.78,3.299
to want to live on this planet not as a,3545.579,3.121
human at least,3547.079,4.861
uh I have uh I started what is called,3548.7,4.74
the gato framework they got to a,3551.94,4.08
community it is self-organizing and is,3553.44,4.98
started sending out invitations again so,3556.02,4.2
the gato Community is the global,3558.42,4.139
alignment taxonomy Omnibus which is the,3560.22,4.02
framework that we put together in order,3562.559,4.861
to help achieve this future this AI,3564.24,5.46
Utopia the main goal of the gato,3567.42,4.56
Community is education empowerment and,3569.7,5.82
enablement E3 so rather than do the work,3571.98,6.359
ourselves we are focusing on empowering,3575.52,5.22
and enabling and educating people on how,3578.339,5.28
to participate in this whole thing now,3580.74,4.859
that being said I am stepping back,3583.619,3.061
because,3585.599,3.361
such a movement should never be about,3586.68,5.04
one person it should never be about a,3588.96,5.7
cult of personality or one leader it,3591.72,4.92
needs to it intrinsically needs to be,3594.66,4.5
consensus based and Community Based,3596.64,4.14
um and so the gato Community is learning,3599.16,3.54
how to self-organize now,3600.78,3.0
um and they're getting good at it pretty,3602.7,3.18
quickly so if you want to get involved,3603.78,4.4
the website is in the link go to,3605.88,5.16
framework.org and thanks for watching I,3608.18,6.3
hope you got a lot out of this cheers,3611.04,3.44