Video summary
Peter Neubauer introduces himself as the co-founder of Stair and a passionate advocate for scaling open-source principles within business models to drive global change. Drawing from his background in communist-era Germany and his work with projects like NeoForge, Mapillary, and OpenStreetMap, he explains how these initiatives successfully internalized open code and data while securing financial sustainability. Currently applying lessons learned at Meta and Mapillary to robotics through Stair, Neubauer emphasizes the goal of making open space more accessible for both humans and machines. He highlights a significant shift in his own workflow where his team stopped writing any new lines of code manually last October, opting instead to rely entirely on AI generation to remove human editing from their internal processes, thereby empowering teams to solve problems that were previously considered too difficult or time-consuming.
However, Neubauer warns that this rapid advancement comes with serious risks comparable to the environmental crisis caused by plastic pollution. He argues that while AI is a powerful tool capable of solving countless issues, society lacks the infrastructure and care needed to handle its waste products effectively, leading to an internet drowning in "micro-plastics" such as fake knowledge and hallucinations generated by models like Claude. A critical concern he raises is the inability to verify or audit current large language models for safety when they control physical systems; even major players like Anthropic admit they cannot guarantee AI will not cause harm in real-world scenarios involving humans, trucks, or infrastructure. Consequently, relying on standard transformer-based approaches that simply dump data into a heap and hope for the best is insufficient for critical applications where deterministic behavior and trust are essential.
The transition to an era where compute replaces human labor also forces a fundamental reevaluation of economic value and social status. Neubauer points out that if AI centers consume vast amounts of clean energy, society must decide whether this power fuels Bitcoin mining or weather models rather than genuine societal progress, prompting the need for new regulatory frameworks similar to those governing atomic energy. He suggests that as technical implementation becomes automated, humanity should pivot toward "intent" over execution and focus on genuinely human experiences like attending live concerts or engaging in nature restoration, which cannot be perfectly replicated by algorithms. This shift requires redistributing status and financial resources away from obsolete roles and into essential fields such as nursing, education, and ecological repair to prevent a catastrophic collapse of these vital sectors.
Ultimately, Neubauer concludes that humanity faces a limited window to navigate this transition before self-improving AI evolves beyond our control or creates an unmanageable dystopia. He proposes embracing the reality that status is no longer tied to technical proficiency but rather to genuine human contribution and intent, advocating for measures like Universal Basic Income (UBI) to support those displaced by automation. By treating compute as a powerful resource akin to nuclear energy and consciously choosing which problems are worth solving with AI versus what requires authentic human presence, society can steer toward a post-capitalistic future where technology serves humanity rather than undermining it. The core message is that we must actively choose how to integrate these tools now, focusing on preserving our unique values while ensuring the benefits of advanced computing reach those in need without sacrificing safety or environmental integrity.
Read the full video transcript
Yes, as Kella said, my name is Peter and
I'm co-founder of Stair, but also do a
lot of other things. Um, when I go back
and look at like what it is I'm actually
passionate about is apart from me being,
you know, growing up in in communist DD
um, and being uh, like a a a convinced
communist and agitator for my school
before the wall came down. Um I'm mostly
interested in big vision uh uh
approaches to things. So NEO forj the
first kind of like bigger effort apart
from all other open source things I
founded is is um a way to internalize
open open code and open source and open
effort into a business model that scales
and apparently it does. So, so, so to
keep the four freedoms there and and
also make this an internally uh scalable
concept to put money behind it. Um,
Mappiler was a similar approach to to
open data, keep the data open, creative
common share like, but put money behind
it to be able to utilize that to make
planetwide change and power other open
source uh uh and open data companies
like like uh Open Street Map who's
producing, you know, some of the best
geographic data we have now. Um and um
and now um with uh with stair we're
applying what we learned at at at Meta
and Mapillary to robotics and and uh
making um the open space more accessible
to to humans and machines. But aside
from that, I've been realizing there's
other questions and and one big there is
the big commons the like you know air,
water, biodiversity and so on. Um and uh
now sailing up is AI as one of the big
uh comments. So I got three questions
that I'm actually going to concentrate
on um in my work quite quite uh like
concrete what's happening with with you
know AI um I come from a very hard you
know software background what's
happening right now is and I think you
all see that is that software as a field
of work and skill is basically breaking
down together with uh open source
movements like Communities are getting
destroyed by autogenerated pull
requests.
There's no community in just approving
stuff that people put into claude and
and and send you a 100 day and now we
have you know Claude Mutos finding all
these bugs that someone needs to needs
to fix. So so I think like software as a
line of work and self-defin is
disappearing. You have now context that
you need to to round trip. It's there.
uh we took a decision last October when
we started to basically not write a
single line of code ourselves. We
removed edit buttons for from our
internal things. We we're not editing by
hand anything. Um this thing is
generated also. Um so so um I think we
need to start moving into making the
team work together in a way that is not
just human but even empowering uh your
your central context. So we built our
own thing for that but you can do it in
other ways right but just just to just
to say um
anybody uh can build anything as as you
said like problems that we thought were
hard for people are not existing anymore
uh and that I think is hugely
empowering. Um is that only positive?
No. We're creating a lot of stuff that
is just burning tokens and and the
energy for that is just phenomenal. I
would almost say
AI is a bit like plastic. We got this
super material that solves buttloads of
problems and it sterilizes it. It it it
makes things I mean we have plastic
everywhere and uh however we are not
equipped and we are not caring how to
handle this stuff. So we contaminate our
environment with microplastics with with
plastic bags. AI I think is such a super
dualized use technology. We cannot
refrain from this because we will solve
so much stuff right and we know we know
we can solve it. I mean there's several
companies in here that use AI to go do
revolutionary stuff. However, we are
spoiling our internet and ourselves with
microA with microsop. make our internet
basically unusable.
We we we drown in like fake knowledge
and and that is something we need to
learn or we will end up with
microplastics. I mean that's that's a
serious problem now, right? Um a weak
signal. Well, um compute replaces human
work. Uh we are now at the point where
bigger data centers are actively
displacing
work. Anybody who sits in front of a
computer and works with anything that's
remotely logic related coding
spreadsheets like anything that is done
inside will be automatable. I'm not
saying everybody will be automated but
but there is there is a big risk that or
not a big risk actually a big
opportunity. However,
um um that is also like point two. We
have the case now and we see this in
stair and other in other like societal
critical applications that we cannot we
cannot verify we cannot audit AI to the
point where we not just sit and chat GPT
where the human is in the loop but
actually off the loop. If we want to put
a truck into an environment where
there's humans, we there's no way right
now we can trust any AI not to run into
the wall.
And there's no way I mean if you if you
read Kellis link from Anthropic just
coming out like the other day, even
anthropic has no idea
how to verify to audit and to make AI
deterministic.
So this is all good as as long as we are
sitting here. Oh yeah, I can do other
stuff. But but if you really put it into
like a watch or something that that
controls anything physical, we probably
need post LLM models. The whole the
whole you throw throw data into a big
heap um put transformers on it and hope
that something comes out and then
discover what else is the side effects
of this. Uh is is probably not going to
work. Even energy wise, we have a big
problem there, right? We we encode the
whole world to do an if statement. uh
that's that's kind of not what we want
to do. Um and um and then yes on the on
the positive side, you know, more and
more becomes solvable for for some of
the biodiversity assessments in in in
some of the efforts we're doing. We're
actually just taking the drone images
and the and the data saving it for next
year knowing that next year this will
take zero effort together with the next
assessment instead of spending some
weeks on this. Now we're saying oh we
have the base data so we will when
biodiversity is is you know computable
we will just go back and evaluate that
data and it will be much cheaper then so
let's not spend the effort now
then
a future yeah um so so one big thing
that comes from this is if if compute
replaces human
power what happens to the to the uh a
value attached to human input.
Now if that is compute then we should
start treating compute just like say
atomic energy. We should make ourselves
account for this. If we build data
centers up in northern Sweden with clean
energy that feed like 600,000 GPUs
um what is the what is the you know
alternative? Could we do something else
for it or
are we feeding Bitcoin miners or are
feeding weather models?
That's a in my opinion that's a big
problem. And also the um the effects of
this uh are quite profound. If everybody
in this room needs to change jobs, what
does that cost? And where does this cost
come from? I mean the the the benefit
has been 80% at anthropic. Everybody
here refers to Claude. I mean these are
people sitting you know in the US in a
in a world where where you know we would
we would like to have some control of
both the value but also the data that is
prompted into these systems right. Um
then also I think with this comes the a
a a re
um revaluing of genuine human values. We
we and and and that is a bit what humble
said like we need to start treating
ourselves not as inferior and do what we
talked about before here and do kind of
like knowledge maxing. Everybody has
their agents. Oh, this is so cool. We
can do all this and everybody gets
nervous about being dump. what uh maybe
we should just embrace this and say, you
know what, this is not longer a a a
unsolvable or a status problem. Let's
concentrate on stuff that's genuinely
human life stuff. You go to a concert to
experience things that's not perfect.
Otherwise, you can just go to Spotify,
right? Um and redistribute is not status
right now. In order for this to happen
like this this this shift in what we
deal with more intent and less
implementation,
we need to redistpute status. We we we
work in these in these jobs that are
becoming shifting if not say irre
irrelevant in some places. And but where
we need people like in nursing like in
in nature restoration in you know
teaching
these these branches have less status
right now. So so we need to kind of like
redistribute money and status into these
into these efforts. Um and uh and you
know if we do it right, we have this
this kind of post
post uh uh um capitalistic
um possibility to to use UBI and others
other measures to to to come to a world
that we want otherwise you know we are
that we are the knee of of uh
self-improving AI right now and I think
we have a very limited
time span to to make this transition or
not. Otherwise, we will just make it uh
into something that potentially
can can be very bad for us um implicitly
or or explicitly.
So, that's me. That's all I have.