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hello everybody David Shapiro here with,0.12,5.52
another video so today's video is about,2.46,6.0
uh measuring machine autonomy rather,5.64,6.12
than intelligence as a road map or set,8.46,6.96
of Milestones towards AGI uh you know,11.76,5.519
for a long time I've been using the term,15.42,4.08
autonomous cognitive entity Ace rather,17.279,5.281
than AGI because general intelligence uh,19.5,5.519
is one idea but you know general,22.56,4.2
intelligence doesn't necessarily apply,25.019,4.5
agency and what we're realizing is that,26.76,4.88
agency is actually very very important,29.519,5.341
to talk about and research and it's not,31.64,5.62
actually getting enough research uh,34.86,4.08
because a lot of people say oh well,37.26,3.36
either it'll never happen or we,38.94,2.939
shouldn't do it but the thing is is,40.62,3.119
people are doing it anyways so we need,41.879,4.381
to talk about it before we dive in I,43.739,4.081
just want to do a quick plug for my,46.26,4.139
patreon I give away all my code for free,47.82,4.98
all my videos are ad free and that is,50.399,5.64
because I am supported by a Grassroots,52.8,6.06
movement of support so if you want to,56.039,5.821
help keep the show alive keep it going,58.86,4.92
and support me so that I can keep doing,61.86,4.079
this work I would prefer to do this than,63.78,4.68
ever take a corporate job ever again so,65.939,5.521
jump over to patreon all tiers get you,68.46,5.519
access to the private Discord server and,71.46,3.72
then of course there's several higher,73.979,3.601
tiers but really every little bit helps,75.18,4.86
another quick update is the gato,77.58,5.34
community so as a decentralized,80.04,5.7
community uh we're right now one of the,82.92,4.32
biggest things is we're developing an,85.74,3.6
organizational roadmap so basically,87.24,4.14
we're setting up various Milestones such,89.34,4.459
as uh governments Community engagement,91.38,5.46
legal and financial Milestones so that,93.799,4.541
it can become fully autonomous and,96.84,4.319
therefore not even dependent upon me I,98.34,4.319
had a good talk with some members of the,101.159,3.541
community who were concerned that I'm,102.659,3.481
going to be like the benevolent dictator,104.7,3.779
for life but like I am phobic of control,106.14,3.839
like I actually don't want to control,108.479,3.78
something I want to create a system that,109.979,4.261
is self-sustaining without me I mean,112.259,3.601
heck that's what all my research does,114.24,4.199
around AI so I want to do the same thing,115.86,3.899
with people because if I can't do the,118.439,2.941
same thing with people then I sure as,119.759,2.82
heck probably can't do the same thing,121.38,4.32
with AI so the goal is for gato to,122.579,5.22
ultimately be leaderless and operate by,125.7,4.199
consensus as a you know as a dow and,127.799,4.141
that sort of stuff we're working towards,129.899,4.741
it uh the the doors are open for anyone,131.94,4.14
to join which we do have a steady,134.64,3.72
trickle of people coming in uh but yeah,136.08,4.2
so that's a quick update on gato and now,138.36,4.68
back to the show so I got this idea,140.28,4.92
after talking with a few of my patreons,143.04,3.839
who were saying like what's the road map,145.2,4.679
towards AGI and you know I I've I've,146.879,4.741
alluded to autonomy for quite a while,149.879,3.901
autonomous cognitive architectures but I,151.62,3.72
figured let me actually tell you guys,153.78,3.12
where I got that idea,155.34,4.74
and the idea comes from levels of uh car,156.9,6.18
autonomy so uh the SAE the international,160.08,6.06
uh what was it the the something of,163.08,6.42
Automotive Engineers anyways uh the SAE,166.14,7.26
uh created the levels of uh car autonomy,169.5,5.94
so level zero no driving all the way up,173.4,4.08
to level five full self-driving,175.44,4.98
capability uh to my knowledge we haven't,177.48,5.42
had anything get above level three yet,180.42,6.24
uh because there are numerous problems,182.9,7.119
around making executive decisions uh and,186.66,5.219
also there's a lot of sensory problems,190.019,3.3
like if you're driving in a whiteout,191.879,3.841
blizzard uh you know if there's a fire,193.319,3.84
right because there's very little,195.72,3.36
training data of like how to drive,197.159,4.8
around a forest fire for instance,199.08,5.22
um now that being said I do suspect,201.959,5.041
it'll be solved eventually uh some,204.3,4.62
people have have recently started saying,207.0,3.239
maybe you should integrate large,208.92,3.599
language models into the executive,210.239,4.201
function and I fully agree with that you,212.519,3.061
don't want it making all of the,214.44,2.28
decisions you want some things to be,215.58,3.9
just completely robotically automated so,216.72,3.9
for instance if you have a,219.48,3.119
forward-looking radar and it detects,220.62,3.8
that you're you know heading towards a,222.599,4.14
non-moving object at 60 miles an hour,224.42,4.12
slam on the brakes regardless of,226.739,3.36
whatever else is going on right there,228.54,3.24
are a few things that you can do just,230.099,3.301
fully automatically,231.78,3.48
but then for those higher order,233.4,4.14
executive reasons like say for instance,235.26,4.08
you hear that the occupant is like,237.54,3.66
screaming and gurgling and you know,239.34,3.66
struggling to breathe maybe the car,241.2,3.3
should make a decision to go to the,243.0,4.019
hospital instead of you know going to,244.5,6.42
Grandma's house not sure uh anyways,247.019,6.241
point being is that this is a very,250.92,4.8
useful framework for kind of tracking,253.26,4.8
our progress towards uh full stealth,255.72,4.019
driving cars and I realize let's use the,258.06,4.8
same thing for uh for uh the path,259.739,5.041
towards AGI or autonomous cognitive,262.86,2.94
entities,264.78,3.24
so we need this road map but there's a,265.8,5.1
few problems so first of all AGI means,268.02,4.98
different things to different people uh,270.9,4.799
there's no consistent definition a lot,273.0,4.259
of people assume that it means that it,275.699,3.421
has to be embodied or that it can do,277.259,3.72
things that humans can't do or this that,279.12,2.94
or the other,280.979,3.121
also a lot of conventional benchmarks,282.06,3.66
just don't apply to artificial,284.1,3.12
intelligence anymore they're actually,285.72,3.36
having to publish papers and research,287.22,4.8
new benchmarks in order to measure large,289.08,4.619
language models,292.02,3.78
the idea of you know oh well it'll be,293.699,4.741
AGI once it has self-improvement okay,295.8,5.399
sure but we can already automate some of,298.44,4.86
that anyways with reinforcement learning,301.199,3.841
and that sort of thing so it's like this,303.3,3.3
is all really squishy,305.04,3.659
uh so basically how do you get from chat,306.6,4.7
gbt to Skynet or something like that,308.699,5.28
intelligence is not necessarily the best,311.3,4.24
Benchmark and the reason that I say that,313.979,4.741
is because chat GPT or gpt4 rather is,315.54,5.52
already superhuman in a lot of respects,318.72,4.74
by any objective measure it's better at,321.06,3.96
test taking and a lot of other tasks,323.46,3.9
than humans and it's also faster which,325.02,4.619
means that depending on how you measure,327.36,5.7
its intelligence its IQ is like 145. uh,329.639,5.041
now that being said it does still make,333.06,3.78
some really brain dead mistakes those,334.68,3.66
are going to be solved if especially if,336.84,3.299
you look at the trend line,338.34,4.139
modality so another thing that a lot of,340.139,3.84
people point out is that it's just text,342.479,3.78
right but text is the best kind of,343.979,4.5
symbolic AI because you can literally,346.259,4.081
represent pretty much anything with text,348.479,4.021
that being said I've started to Pivot,350.34,3.9
and I believe that we're going to see,352.5,4.44
another gigantic leap as we introduce,354.24,5.399
more multimodal models and the reason is,356.94,4.68
because I got this idea when I was,359.639,3.361
thinking about the fact that if you,361.62,3.06
cross train a language model on multiple,363.0,3.539
languages it gets better at all tasks,364.68,3.66
and that is because different languages,366.539,3.481
have different strengths in terms of how,368.34,4.44
they represent uh facts of the real,370.02,5.22
world and you also get broader ideas,372.78,4.68
about how the world works that are,375.24,3.899
embedded in language because there are,377.46,4.079
terms that just do not translate from,379.139,5.28
one language to another likewise I think,381.539,3.901
that there's going to be some,384.419,2.701
information that just does not translate,385.44,4.02
from one modality to another where,387.12,5.699
whether it's images video text spatial,389.46,6.78
data audio data that sort of stuff and,392.819,5.16
so I think that by creating multimodal,396.24,3.239
models they're going to have a much more,397.979,3.421
nuanced under understanding of,399.479,3.56
everything that they're talking about,401.4,4.26
that being said a multimodal model is,403.039,4.061
still not going to be enough right,405.66,3.24
necessary but not sufficient because a,407.1,3.96
model sitting on a shelf doesn't really,408.9,4.019
matter,411.06,5.88
so the two primary uh ingredients that I,412.919,6.0
see to machine autonomy which is going,416.94,4.44
to be the best like proxy the best,418.919,5.761
Benchmark is agency and dependency and,421.38,6.06
so what I mean by agency is the ability,424.68,5.4
for an entity a self-contained entity to,427.44,5.66
set goals and objectives to task switch,430.08,6.3
and Implement cognitive control and,433.1,6.159
pursue self-determination because agency,436.38,5.34
or agentic behavior is the ability to,439.259,4.44
just be fully self-directed and,441.72,4.08
self-contained make independent decision,443.699,5.161
decisions and that sort of thing uh you,445.8,4.32
know whenever you think of like an,448.86,4.38
example of a of a robot right you might,450.12,5.579
think of uh the the robots from iRobot,453.24,3.66
where they don't really have that much,455.699,2.581
agency they just kind of wait they're,456.9,4.32
like the physical embodiment of chat gbt,458.28,4.979
um until they're given an update and,461.22,4.08
then they have a lot more agency,463.259,6.541
so agency is is a multi-dimensional kind,465.3,7.44
of proxy or Benchmark for level of,469.8,5.22
intelligence and of course you can,472.74,5.64
already give the reins over to like gpt4,475.02,5.34
and stuff like that uh that being said,478.38,4.2
there is a lot that uh in the cognitive,480.36,4.86
architecture that has to be figured out,482.58,4.739
in order for agency to make more sense,485.22,4.979
in the long run so for instance agency,487.319,5.041
implies that you remember what your,490.199,3.661
purpose is and where you are and where,492.36,4.32
you're going and then dependency so this,493.86,4.38
is the other dimension and remember it's,496.68,3.0
both of these you need both of these,498.24,4.799
ingredients so uh basically dependency,499.68,6.239
is how dependent uh on humans the,503.039,5.1
machine is so the more independent it is,505.919,4.981
for all needs and the more decisions it,508.139,5.101
can make the better the closer it is to,510.9,4.139
full AGI and so but when I mean,513.24,3.719
dependencies uh need for human,515.039,4.141
programming need for hardware and,516.959,3.841
physical infrastructure provided by,519.18,5.34
humans data architecture design patterns,520.8,6.18
and then finally solving problems and,524.52,4.439
just keeping itself going and,526.98,4.56
self-improving over the long run uh,528.959,5.94
without human Aid so as agency goes up,531.54,6.239
and as uh dependency goes down that's,534.899,4.021
how you know that we're going to be,537.779,4.201
closer and closer to AGI and we can we,538.92,4.32
can easily measure those things right,541.98,3.66
now because chat GPT for instance it has,543.24,4.2
to run on gigantic data centers that are,545.64,4.5
run entirely by humans uh or mostly by,547.44,5.1
humans rather so these are the two,550.14,4.199
primary ingredients that I think and I,552.54,5.76
uh I basically built it into a framework,554.339,6.781
uh very similar to the self-driving Cars,558.3,5.58
one so level zero is reactive basically,561.12,5.399
it has no agency it's a tool level one,563.88,4.56
is some autonomy so it has a little bit,566.519,3.601
of agency to make some executive,568.44,3.72
decisions Lang chain is a really good,570.12,3.96
example of this where it it basically,572.16,4.26
has the ability to choose between a set,574.08,4.62
of tools but that's about it still,576.42,4.56
requires significant human oversight and,578.7,4.86
is also still very very much dependent,580.98,3.859
upon humans,583.56,3.24
semi-autonomy is what a lot of people,584.839,4.661
are working on with like Auto GPT where,586.8,4.08
it can choose like what kind of,589.5,4.68
information it needs to go find uh or it,590.88,5.34
can also even start to rewrite some of,594.18,4.94
its own code or come up with other ideas,596.22,6.42
uh you know some directives then High,599.12,6.04
autonomy as far as I know has not been,602.64,5.4
achieved yet anywhere in the world which,605.16,4.739
is basically that,608.04,4.68
it is able to pick some of its own,609.899,6.721
directives uh and and more more,612.72,6.299
completely modify itself basically if,616.62,4.92
you if you were to have what baby AGI,619.019,5.281
and auto GPT tried to be which is they,621.54,5.1
can rewrite their entire code base and,624.3,4.62
change their their own directives and,626.64,4.8
are not dependent upon a whole heck of a,628.92,4.38
lot of human infrastructure that would,631.44,3.6
be level three and then level four is,633.3,4.56
full autonomy meaning they have,635.04,5.34
absolutely no need for humans uh,637.86,5.76
whatsoever they're 100 self-determined,640.38,4.92
in terms of what they do when where and,643.62,3.779
why and how they do it and then of,645.3,5.279
course on a physical level uh they will,647.399,5.281
continue to exist in perpetuity without,650.579,3.661
human intervention,652.68,3.06
all right so,654.24,5.4
level zero inner reactive agency zero,655.74,5.52
percent dependency one hundred percent,659.64,5.04
basically it's a wrench uh chat GPT as,661.26,5.04
it is right now mid journey and a whole,664.68,3.599
bunch of other AI tools they just sit,666.3,3.84
there waiting for a human to push the,668.279,3.541
button and they do their thing and then,670.14,3.54
they switch back off so these are Level,671.82,5.04
zero in terms of uh AGI score even,673.68,5.159
though they're intelligent so again like,676.86,4.08
I said intelligence is not necessarily A,678.839,4.44
good measure of AGI for something to be,680.94,5.1
AGI or an autonomous cognitive entity it,683.279,5.281
also needs agency and Independence which,686.04,5.58
chat GPT has none of so even even if you,688.56,6.6
have gpt5 right that could be a billion,691.62,5.159
times more intelligent than every human,695.16,4.14
combined if it doesn't have agency and,696.779,4.68
Independence it's not an AGI,699.3,4.14
so that's that's why that's why I'm like,701.459,4.32
AGI is not a good good measurement for,703.44,4.32
some of these things level one some,705.779,4.5
autonomy like I said Lang chain is a,707.76,3.96
really good example because it can pick,710.279,3.601
and choose between a few options and not,711.72,4.26
much else a few other examples are like,713.88,4.68
roombas Amazon's warehouse robots the,715.98,4.56
Mars rovers they have a little bit of,718.56,3.779
autonomy but basically they mostly wait,720.54,3.539
for a human command and then the human,722.339,4.201
command says drive over there and it'll,724.079,4.32
figure out how to get you know 10 feet,726.54,4.5
that way on its own uh some Advanced,728.399,4.921
chat Bots also have some autonomy,731.04,4.14
again anything that incorporates Lang,733.32,5.04
chain or similar uh very basic kind of,735.18,7.32
uh in uh obfuscated choices uh that's,738.36,6.96
gonna be that's gonna have some autonomy,742.5,5.72
um let's see next is semi-autonomy so,745.32,5.82
semi-autonomous is where uh its,748.22,4.78
directive still primarily come from,751.14,3.66
humans but it might be more of a mission,753.0,4.38
rather than like a directive or a rule,754.8,6.06
and so with a mission the idea is that,757.38,6.42
here's a general objective you have some,760.86,4.68
autonomy to figure out how to get there,763.8,4.32
or how to do it on your own and so this,765.54,4.32
is the autonomous drones that uh,768.12,3.3
militaries around the world are building,769.86,3.36
where it's like your mission is to,771.42,4.38
destroy you know that Sam site or your,773.22,4.26
mission is to get the passenger from A,775.8,5.219
to B or uh you know in video games the,777.48,6.479
NPC's Mission might be like uh you know,781.019,4.861
you're gonna try and you know capture,783.959,4.081
the castle or whatever so they still,785.88,4.56
operate within a relatively constrained,788.04,4.68
environment meaning they can't change,790.44,3.959
their own in environment or their own,792.72,4.2
fundamental operation they still have a,794.399,5.401
clearly defined uh they're not general,796.92,4.74
purpose put it that way,799.8,4.2
a full self-driving car no matter how,801.66,4.08
intelligent it is it's still just a car,804.0,3.899
a drone no matter how intelligent it is,805.74,4.68
is still just a drone in Ditto for a,807.899,4.38
video game and PC so this is kind of the,810.42,4.56
Midway point where anything above that,812.279,4.441
they're they're basically saying okay,814.98,3.659
given these constraints and given this,816.72,3.78
environment you have free reign to do,818.639,3.541
whatever it takes to get that job done,820.5,4.44
uh whereas you know the sum autonomy,822.18,4.62
they basically can only pick and choose,824.94,4.139
from a very short menu of options,826.8,4.68
whereas semi-autonomy is they can figure,829.079,6.06
it out themselves then High autonomy so,831.48,6.299
this is this is like uh Cortana in the,835.139,5.581
early days commander data and the Nestor,837.779,6.841
class 5 from iRobot so they're almost,840.72,6.9
entirely self-directing uh you know data,844.62,4.92
can make up his own mind on things but,847.62,3.54
he still has a lot of limitations just,849.54,4.02
due to the form factor that he's in,851.16,4.799
likewise Cortana at least in the early,853.56,5.339
days is basically designed to be a,855.959,5.221
weapon a military aid and So within,858.899,3.841
those constraints she still has a,861.18,4.02
tremendous amount of autonomy and able,862.74,5.039
to uh change the way she does things but,865.2,4.439
in both cases of data and Cortana,867.779,3.901
they're still very much dependent on,869.639,3.421
their human Companions and human,871.68,3.899
counterparts to continue operating so,873.06,6.959
most fictional examples of AI at least,875.579,6.421
many of the the friendly ones are what,880.019,4.081
we would call High autonomy and then,882.0,5.519
full autonomy so this is where the they,884.1,5.82
are they can can completely ignore,887.519,4.141
humans if they want to and are,889.92,3.3
completely independent of humans so the,891.66,5.46
examples here are Skynet Ultron the Geth,893.22,6.359
in Mass Effect Cortana after Guardians,897.12,4.74
uh the Reapers from Mass Effect so these,899.579,3.961
are these are the the kind of nightmare,901.86,3.599
scenario scenario where it's like okay,903.54,4.56
it has no need for us anymore so then,905.459,4.081
what does it do,908.1,3.0
and that's what we're kind of most,909.54,5.28
afraid of uh but again like this is the,911.1,5.22
work that I and other people are doing,914.82,3.0
and I one I think that this is,916.32,3.959
inevitable uh that it'll get to that,917.82,5.879
level of level four full autonomy uh but,920.279,5.761
I'm also not afraid of it because,923.699,3.961
I don't know I haven't seen any reason,926.04,3.84
to be yet now that that being said I'm,927.66,3.72
not saying that it is inevitable that it,929.88,3.48
will be safe no we could absolutely do,931.38,3.06
this wrong and it could kill everyone,933.36,3.779
I'm not denying that at all,934.44,4.56
um and I think it's coming sooner than a,937.139,4.741
lot of uh researchers realize uh that,939.0,4.62
being said I do have a few more videos,941.88,4.56
planned about okay if we're if we're,943.62,5.1
aiming for and building level four full,946.44,5.759
autonomous AGI how do we make it safe or,948.72,5.04
what will It ultimately choose to do,952.199,3.0
which you know you've seen some of my,953.76,3.06
other videos,955.199,3.901
okay so how do we get from where we're,956.82,5.34
at to level four because like I said the,959.1,5.22
the the best that we have is we're,962.16,5.46
approaching level two semi-autonomy in a,964.32,6.0
few cases right people are experimenting,967.62,6.6
with it uh but you know there's a lot of,970.32,5.579
problems so all the work that I've done,974.22,3.78
on cognitive architecture is going to,975.899,3.481
help get us there but there's still a,978.0,3.6
few other problems so first is,979.38,4.5
algorithmic breakthroughs that uh need,981.6,4.2
to happen namely like I mentioned at the,983.88,4.199
beginning multimodal models I think will,985.8,4.26
very very much Advance us towards that,988.079,3.0
just because they're going to have a,990.06,3.839
much more nuanced understanding of how,991.079,5.101
to pursue any goal they're going to have,993.899,4.081
a much better World model by being able,996.18,3.18
to integrate multiple kinds of,997.98,3.359
information and data,999.36,4.38
a contact size parameter count those,1001.339,4.74
those kinds of things uh Mesa,1003.74,4.62
optimization loss functions that's all,1006.079,4.141
the math which you know that's not to,1008.36,3.719
that's not to demean or diminish the,1010.22,4.859
value of mathematical researchers uh and,1012.079,4.68
and the computer scientists and the data,1015.079,3.721
scientists who really build these new,1016.759,4.621
architectures but like it's kind of it's,1018.8,5.399
kind of like Moore's law where like you,1021.38,4.439
can you can predict with a pretty,1024.199,4.74
regular Cadence how uh models become,1025.819,5.221
more sophisticated over time there,1028.939,4.321
doesn't seem to be any major blockers,1031.04,4.259
right if you pay attention to chip,1033.26,4.38
design every year people are like oh,1035.299,3.66
well this is going to be the end of,1037.64,3.419
Moore's law but then inevitably someone,1038.959,3.96
figures out another way of approaching,1041.059,3.841
the problem likewise I see the same,1042.919,4.861
thing the same pattern happening with um,1044.9,5.46
with language models,1047.78,4.98
um and then another big thing that we're,1050.36,5.1
seeing is online learning memory systems,1052.76,4.74
uh and and those sorts of things like,1055.46,4.68
recurrent neural networks and other ways,1057.5,5.46
of like in managing in context learning,1060.14,4.56
and that sort of stuff but one thing,1062.96,3.06
that people have started noticing for,1064.7,4.32
instance is that chat GPT with uh even,1066.02,4.62
even just over the last couple of days,1069.02,4.26
or a couple weeks rather,1070.64,5.46
because its data is uh two years old,1073.28,6.18
almost and and growing it's actually its,1076.1,5.939
utility is already dropping because it's,1079.46,4.68
more and more out of date and so we're,1082.039,3.901
realizing very quickly that you're going,1084.14,3.779
to need to have continuous learning in,1085.94,3.3
these models so that they can stay,1087.919,3.361
relevant uh and then there's the,1089.24,4.5
software architecture such as cognitive,1091.28,4.74
architectures orchestrating and training,1093.74,4.26
millions of models so one thing that,1096.02,3.84
I've started telling people is that AGI,1098.0,3.78
was never ever going to be a single,1099.86,5.76
model it is a huge gigantic Monumental,1101.78,6.24
mistake to think that one model whether,1105.62,6.12
it's gpt5 or GPT 18 or whatever is going,1108.02,6.0
to be responsible for AGI you're going,1111.74,4.679
to have at a bare minimum probably,1114.02,4.62
dozens if not hundreds or thousands of,1116.419,4.981
models required to achieve level four,1118.64,4.86
autonomy these are models that are going,1121.4,3.54
to be doing things like handling Vision,1123.5,3.96
handling motor control uh they're going,1124.94,5.099
to be performing task orchestration,1127.46,4.079
you're going to have models that are,1130.039,3.901
dedicated to ethics and reasoning,1131.539,4.861
long-term planning and you're also going,1133.94,4.619
to have multiple models of every single,1136.4,4.56
kind that work in conjunction this is,1138.559,4.74
called an ensemble of experts which is,1140.96,5.579
an old school method of basically saying,1143.299,5.641
okay you know you have a dozen models,1146.539,4.441
that are similar but there they might be,1148.94,3.119
slightly different architectures,1150.98,3.0
different training data that sort of,1152.059,3.601
stuff and so each one has strength and,1153.98,3.42
weaknesses and you get them all to work,1155.66,4.259
together and then you overcome any flaws,1157.4,5.159
or faults in any single model and so,1159.919,4.081
this is why I'm also really really,1162.559,3.36
skeptical of any research that tries to,1164.0,4.2
align a single model like that's kind of,1165.919,4.62
pointless no it's not pointless research,1168.2,4.14
but it would be a mistake to think that,1170.539,3.841
aligning a single model is going to be,1172.34,6.42
the solution because you know any any uh,1174.38,7.38
roboticist and old school ml data,1178.76,4.5
scientists will say oh yeah Ensemble of,1181.76,4.38
experts you know those this is very much,1183.26,4.62
the way and also there's an entire book,1186.14,3.24
about it called a thousand brains by,1187.88,3.12
Jeff Hawkins,1189.38,3.72
um yeah so the software architecture to,1191.0,4.44
do all this in a fully automated way,1193.1,5.1
that can that is you know stable and,1195.44,5.22
self-sustaining that you know the AGI,1198.2,4.14
can tune and manipulate and you know,1200.66,3.48
spin up another copy of itself and test,1202.34,4.26
it self testing and self-correction are,1204.14,4.26
going to be some of the hardest things,1206.6,5.939
to uh to achieve with uh with uh getting,1208.4,6.18
to level four full autonomy,1212.539,4.5
so anyways that's it for this video it,1214.58,4.32
was pretty short I just wanted to lay,1217.039,3.061
this out because I thought it was a,1218.9,3.3
really valuable idea uh to talk about,1220.1,4.68
like okay how do we actually get to AGI,1222.2,5.4
from here so I laid out five levels of,1224.78,4.68
of autonomy based on agency and,1227.6,4.079
dependency I hope this helps it make,1229.46,3.959
sense and kind of get a much clearer,1231.679,4.5
idea of what AGI or autonomous cognitive,1233.419,4.441
entities will actually look like so,1236.179,3.86
thanks for,1237.86,2.179