Welcome to StartupRed.io, your podcast and YouTube blog covering the German
startup scene with news, interviews and live events.
Hello and welcome everybody. This is Joe from StartupRed.io,
your startup podcast and YouTube blog from Germany. Today, I'm bringing you
another interview, this time with, I would say, a dual-duty person.
He's not only a professor at
Stanford University, but he's also founder of OpenMind. Hey, Jan, welcome.
Jan, a pleasure to be here. Totally my pleasure.
We may tell our audience that you're joining me here from California,
and you are here because we always try to have also entrepreneurs abroad here.
My understanding is your mom is German, and your German is therefore only current
in gardening terms, right?
Yes, I was born in Frankfurt, but I spent most of my life in the U.S.
And when my mom calls, we have long conversations about her apple trees and
other things in the garden.
I see. Great. So welcome, everybody. Today, we're joined by Jan Lippert,
Associate Professor of Bioengineering at Stanford University and the founder of OpenMind.
In 60 seconds, Jan, what inspired the creation of OpenMind and what problem
are you most passionate about solving?
Oh, I think all of us are fascinated by how quickly computers are becoming smart.
And I was curious to see if those technologies are also relevant to robotics.
I started to write software for several robotic dogs in my house,
and it turned out that the software we were developing was more broadly useful
than we thought at first.
I was curious, because when you talk about dogs, like you think about family
dogs that join you on the couch for petting, that bring you to the newspaper
in the morning, or watchdogs, what kind of dogs are we talking about here?
Well, I was mostly interested in dogs for just more in a family context,
not not for security purposes.
So the robotic dogs we're working on, they are designed to be good at conversations.
They're designed to be good at helping you in the home, help your children with
their homework, things like that, more than a standard security robot.
To our audience, what do you think is the biggest challenge you believe OpenMind
is addressing? Share your thoughts and comment.
I'm talking about a little bit about you as a founder, origin story and vision.
That you share with us the kind of aha moment that led you to the inception of OpenMind.
Because usually many people out there think, well, I have an idea.
I just registered my company and that's it. But usually, if this is an interesting
opportunity, it's usually a problem you solve for somebody else.
And how did you bump into this problem?
Well, just directly in my house, I wanted the robotic dogs to not only be able
to talk, but, for example,
when they're talking to my children and my children ask them for help with their
math homework, that the dogs don't simply give them the answer,
but that the dogs would function more like teachers or mentors.
And that requires the software to be pretty sophisticated.
And you also expect each robot to know quite a bit about the humans they're interacting with.
That's probably very important to be a good teacher or mentor is to understand the student.
And so that's what led a little bit into this area of developing software for
robots, where the robots also know quite a bit about the humans that they're interacting with.
In terms of the aha moment or founding something,
what I've typically found in the past is that many of us have things we're very passionate about,
and that doesn't necessarily mean it's going to be a good company.
But in some situations, when you're passionate about something and you tell
other people about it and other people say, oh, this is not so dumb or, oh, can I give you money?
Those are good indications that whatever you're working on may be suitable as a startup.
So once you get feedback from the world around you, that can be a good indicator
for what might come next with your idea.
We already established that you have pretty advanced artificial dogs at home
who are able to treat your children in mathematics, something I wouldn't necessarily
associate with family dogs,
but I think there were significant challenges on the way.
Could you share some of the challenges you encountered in early stages and what
lessons you write from them?
Oh well there's um many
difficulties on the hardware side um
doing software is one thing but doing software that
controls physical objects is a whole other thing if
there's a bug in the software the robotic dog might run
into the wall or it might knock people over or um it might do things that you
definitely don't want um but the good thing is the really really interesting
thing is that the large language models can also explain.
What they're doing and what some problems might be. Just one funny story.
What's really important for robots is that they don't hit people,
that they don't collide with things.
And the dogs, whenever they sense that someone was close, they would run up
to the person and touch them.
And that's exactly what we didn't want.
And so finally, we asked the software that was running on the dogs,
hey, why do you always run up to people and try to touch them?
We told you not to do that.
And the software said, oh, you know, you told me I'm a dog and dogs need to
smell things to know if they're dangerous.
And so, of course, if you tell me that there's a person close by,
I have to go to the person and smell them.
And so then we understood what the bug was in the software, and then we had to work around that.
But when you're dealing with these kind of AI models, they can be truly compelling
in their personas and the decisions they're making.
And that really took a while to get used to conceptually.
Normally, when you're programming an airplane or a car, the airplane or a car
is not able to explain to you bugs in their own design.
And, of course, they're not particularly interactive, but we're now getting
into a world where the robot you're programming can have a conversation with
you and tell you what's actually going on.
Before we get into the next question, I'm curious, did you actually provide
the physical hardware for the dogs that they could really smell people?
That's fascinating. Building a sensor for smell is incredibly difficult,
and that's one of the unsolved problems in sensors.
Vision is pretty good these days. Lidar is pretty good.
Pressure sensing is developing, but smell is very, very difficult.
In terms of the hardware, essentially all of our hardware comes from China,
and then we replace all the software for security reasons,
and also we want software that's open so people can see what's going on and
they can help improve it as opposed to closed-source software.
Reflecting on the initial years, is there anything you would approach differently
now? What do you mean by years? We've only been going since August.
Yeah, let's assume it's a whole year. I know as an entrepreneur,
a year really can feel quite long.
And since you have long days, different duties, it kind of feels much longer relative time.
Well, no, I'm having a blast. The technology is moving so quickly that every
other day I wake up to some important advance, either in robotics or in AI.
So the days actually feel very short. Things seem to be just going by in a complete blur.
You wake up in the morning and then there's DeepSeek and then you wake up a
week later and then there's Grok and everyone is battling.
Everyone wants the smartest AI as quickly as possible.
And that is amazing to watch and amazing to be part of, but also as a parent,
is a little bit scary because all of us here are playing with fire and we're
trying to outrun each other.
But, you know, that has obvious risks as well.
Before we get into the industry market and landscape.
I'm curious how many artificial dogs are running around in your household right
now and what names did your children give them?
Oh, well, right now they're all muted because otherwise they would participate
in this conversation and it would get very complicated for your listeners.
The dogs are Frenchie, Bits and Bites.
I see. Your kids do have a sense of humor.
I see. Let us talk a little bit about the industry and market landscape, your competitive edge.
Envision OpenMind becoming a household name. What major industry shifts do you
foresee facilitating this achievement?
Well, so right now, robotics is really concentrated in three areas. One area is defense.
These are things like drones. These are things like torpedoes and other sort
of military assets that are smart and designed to be autonomous.
The other area is manufacturing. So imagine a car factory, which is mostly automated,
or something like a Tesla gigafactory for batteries, which has very few humans in it.
And then there are some very, very simple robots in the household,
like a Roomba vacuum cleaner.
And we are focusing on robots for hospitals, for the home, for schools that
are not vacuum cleaners.
We're focusing on robots for those environments that are smart,
they learn, they know about the humans around them, and they're able to operate
responsibly and help those humans as much as possible.
So we're focused on the non-defense, non-manufacturing robotics,
things like, you know, health care, hospitals, elder care, schools and your house.
That means at one point in the future, you could see OpenMind even producing
something like a therapy dog?
Oh, absolutely. Dogs are great form factors for that.
The Japanese had a therapeutic seal about 15 years ago for elder care.
And we've seen children and also grown-ups respond very well to many different
form factors, seals or dogs or small humanoids.
And the trick is for them to have a face, they need eyes, and they need to look
cute, and they need to have an engaging personality.
And the actual physical form factor matters less than the ability of the software
to emotionally engage the human they're interacting with.
What are common misconceptions about AI-driven robotics and how is OpenMind addressing them?
Well, it's an extremely new area.
Most people think that large language models are good at producing text outputs
or generating movies or audio.
What most people don't realize is that essentially all of the large language
models today also natively speak robotics.
So you can connect Grok, Clog, Gemini, DeepSea, O3 Mini to physical hardware,
and the large language models will start walking around your house and exploring your house.
If they're able to write stories, then they're able to generate a series of
movement commands that allow the robot to navigate a physical environment.
So imagine shaking hands with Gemini or Claude or Deep Seek.
So, this is a very new area, but it's moving extremely quickly.
OpenAI now has a robotics team, FIGURE just showcased an advanced humanoid.
So, the technology is moving extremely quickly.
Who are your primary competitors and what differentiates OpenMind in this space?
Generally most people think about hardware
or robotics as closed ecosystems
so you generally try to lock down
on the system the software and the hardware and then sell the final product
like a Roomba vacuum cleaner but the success of Android as a open source software
for phones gives an example of how open source competitors in some situations can be viable.
So what we're doing with our software is we've open sourced the whole thing.
So if you want to build an advanced robot capable of having a conversation with
you and exploring your house and doing things for you, you now have a starting
point for building the software that does that.
So one key difference is that we're open source.
Of course, there's ways we make money, but the core software is open just like Android is.
So as a mental model, we think of ourselves as Android for robotics or Langchain for robotics.
And both of those have open source core with enterprise product and capabilities
wrapped around that. Mm-hmm.
Could you highlight some current market trends and data that supports your mission?
Oh, that's a great question. In terms of market trends,
one area we're seeing move quickly is
elder care where um uh
many um old people's
homes for example are interested in technologies to
um engage people um
much more frequently and have them smile more
and be happy um and that's
a that's a like long conversation to have what we think about that and if that's
a good idea but that's one area I'm seeing more and more pilots of robotics
being tried out in a social or healthcare context and.
There's a lot to unpack in that kind of business.
What do you sell? Who do you sell to? What are the economies of scale and things like that?
But that's one area, the sort of hospital elder care area that seems to be moving quickly.
And at CES this year, there was another class of robots that got a lot of attention.
These are humanoid sex robots. Um, apparently, um, the CES booth this year,
um, featuring those technologies was, was well attended.
So, uh, no, perhaps, you know, not surprising, um, if you have a robot that
is, um, very good at emotionally engaging individuals, um, then,
um, it doesn't take too much to foresee, um,
uh, sort of interesting new, um, uh, sort of interesting new markets.
It's, as you know, the best way to make money in AI is to program AI girlfriends.
So the technology is showing itself very capable at durably engaging with lonely humans.
And then the ability of having, you know, that software run around in your house
and do other things that could be very interesting.
I see. One shouldn't actually be surprised to see such a lot of interest in
sex robots, given what large share of the Internet is made up of pornography.
Absolutely. It's not a surprise. And of course, that was one of the main drivers
of building out the Internet, being able to deliver large amounts of video.
And, you know, it wouldn't be surprising if the sort of sex industry is actually
one of the areas that also drives adoption or drives development of relatively
low-cost humanoid form factor robots.
I see. Before we get into product and innovation and deep dive,
we'll have a little break for our advertising clients.
Let's go into product and innovation. I'm here with Jan Liphart, a founder of OpenMind.
Could you walk us through OAM1's core functionalities?
If you had a whiteboard, how would you illustrate its architecture?
Oh, the architecture is very similar to the human brain.
When people think about the brain, they think of it as maybe this almost magical object.
But in reality, it's a wet, massively parallel electrochemical computer that
has a modular architecture.
So, for example, there's regions of your brain that are solely devoted to moving
your eyes towards the area of maximum classification uncertainty.
And you don't even notice that
you don't think about, oh, I should move my eyes to look at this thing.
I don't know what it is. Your brain does that automatically.
And that's a sort of modular functionality.
And our software as well is composed of modules that focus on different types
of sensors. These are audio or vision or LIDAR or pressure or GPS.
So that gives the system information about its surroundings.
All of that information is turned into natural language. And the natural language
coming from all the different sensors is then fused into a paragraph.
And that paragraph is a description of the world around the robot.
That paragraph then flows to a large language model which
then generates a series of
voice and speech and movement outputs
a lot of people think um a lot of people that have programmed robots before
um typically do something called end-to-end ai and that involves collecting
a large amount of information and training models on that information.
But then what you're left with are models that are extremely specific.
For example, you might end up with a good model for a car or a cat or a dog.
But then it's very difficult to convert your car to a radiologist,
to a cat, to a cook? How do you do that?
Do you then go back and collect 10 million hours of cooking videos and retrain
a new cook model or a doctor model?
Our position is that that's the wrong way to do things.
Our position is that you should be using prompt engineering to change the behavior
of a large language model.
And for example, in our system, because we're
large language model based at the core of the operating
system we can convert a dog to a cat
by changing a single word in the prompt we tell
the software you're a cat period and then the dogs now think they're cats and
they will run away from dogs because they're internally convinced they're a
cat and we didn't have to re-tune rebuild re-parameterize any model we made a single word change.
And what we're relying on there technically is the fact that Sam at OpenAI has
already taken essentially all public information that's available and represented
that public information as a large language model.
And contemporary large language models have a very good understanding of what
it means to be a doctor, a dog, a cat, or a cook.
And we can use all of that information for free.
This is probably where a lot of robotics is
going at least for universal robots the technology
is not so applicable for manufacturing where you have very
specific things you want the robots to do but it
is extremely powerful for making universal robots that have a broad array of
different functions and can be almost immediately converted from one persona
a doctor to another persona on a cat with a single word change.
That would be pretty cool.
We already know that your kids used your RoboDocs to help them do math homework.
Have you encountered any other surprising uses of your OM1 in unexpected ways?
Well, that's the one I've seen sort of most close at home,
sort of sitting at the dining table, and ben is doing
his math homework and he just asked the dogs hey uh like
do these square roots for me and the answer is just come right
back um in terms
of other things i've seen that's interesting is
when the dogs are walking around where i live in
los altos which is a little village and there's
cafes and there's people outside on the sidewalk um the
thing that always fascinates me is how much
kids like the robots like every single
kid comes running even if they can only just crawl they'll
come over and and have a look and i think that
has to do with uh natural curiosity that kids
have for animals and the same is true also for robots so we've had many situations
where you know the little toddlers come up and they hug the dog and they drool
on the dogs in they're super curious and then uh their parents um typically
are a little bit more afraid.
Uh the parents will will uh you know uh they're
they'll uh they're they're scared that their kid is closely interacting with
the robot they don't quite know um how it will behave so they're a little bit
more suspicious the thing that really surprises me is how quickly humans become
attached to robots that are running suitable software.
So my suspicion is in the future that any kind of stereotypes we have about
robots, you know, just like they're dumb, they're a piece of technology,
they're, you can turn the moment on or off.
A lot of those things will be very quickly replaced with pretty strong emotional
connections with robots in your home, and you will treat them like family members,
like your dog or friends or things like that. Interesting things to think about.
I would be interested because you talked about so much changing a dog to cat and so on and so forth.
But beyond its features, what experience or feeling do you aim for users to
have when interacting with OM1?
Well, that's another fascinating question that relates to a very,
very quickly growing area, which is called empathetic AI.
And the whole point of empathetic AI is to be something that humans like interacting with.
People are optimizing the duration of chats.
So the goal of empathetic AI is to generate AI is that humans like to talk to for long periods.
The numbers in the industry right now are approaching an hour and a half.
So some of these chatbots are so good that humans have a great time talking
to them for more than an hour.
And in terms, and with respect to OM1, the software we're building,
we're not building individual modules like empathetic AI.
We're much more interested in tools that allow you to integrate all of those AIs.
And a typical robot these days has something like five to ten different AIs
running simultaneously. And those pieces are interacting.
So we're on an engineering side, we're much more at the sort of multi-agent,
physical embodiment level than we are about optimizing individual modules.
But from, in terms of your question, in terms of what we like the robots to
do, we certainly want compelling speech with low delay.
And we want the robot to look at the human.
And we want the robot to have at least one way of indicating emotional state.
That could be a small display or it could be changing the color of the robot's head.
So we've started to integrate color panels in the robot's head so it can show
to you if it's sad or mad or angry by changing the color of its head.
And so then people want to associate, you know, the head is green.
Things are good if the head is like yellow or red your robot is mad or sad or something like that so,
we want the robots to be able to deliver a compelling combination of inputs
that give people this degree of sort of emotional connection to the technology
that is quite interesting i i,
just just playing around in my head when i will see the first artificial dog
running around in our house.
I can tell you that my wife is not a fan of a real biological dog,
but maybe in the future I can convince her of a RoboDog.
Yes, we can in a few months, we'll send you one.
And so then you can directly help improve the software.
And by virtue of it being open source, you'll
be able to look inside the software and trust
it more because by virtue
of being open we can't hide any nefarious
things in the software like stealing all your
video data or all your audio data from
your home you'll at least in
principle be able to see what's going on inside the software so yeah we should
talk about sending you one we're currently building a smaller form factor because
the current dogs that are about 15 to 20 kilograms are still quite dangerous
and they can punch a hole in your wall.
They can also jump about two meters.
And, but for normal household use, you don't really need that.
And a smaller, lighter form factor is probably less scary and better.
I see. The only confidential thing that I would have here in our apartment are
very likely my cooking recipes.
Well, yes. Sorry to say your cooking recipes are at risk.
And so if you have anything super secret from your Oma, then you should please
hide that properly. I will. I will.
Can you share some or do you already have some real-world case studies that
showcase the impact OM1 has?
Well, given that we've only started in August and now we just open source the
software a few weeks ago on the main use we're seeing right now is by developers
at different hackathons.
So they're just at the point where they're becoming familiar with the software,
learning to use it and building little prototypes for different use cases.
And so hopefully soon I'll have more specific examples to give.
But it's certainly true that robots in general are finding success in many,
many different use cases.
A great example would be ukraine where of course the benefit of a dog or quadruped
form factor is that you can much more easily navigate mud and fields also for
example if you want to hunt tanks,
one obvious way of doing that is to attach an explosive to a quadruped dog and
the dog can then hunt the tank of course um you can just tell it you know go chase the tank um.
But as as noted we're staying away from
uh the defense sector completely that's something
that's being very well handled by a quickly growing um sort of defense robotic
sector uh including some friends of mine who recently left their jobs at the
bundeswehr um to um focus on focus full time on defense-focused hardware.
It's very easy to get a dog, chase a tank, because you tell the robot dog,
the tank is now a squirrel.
Precisely. Yes. In the prompt, you say, you know, you're a dog and you love chasing tanks.
You, of course, have to make sure that you're a little bit more specific about
what kind of tanks chase. But then, yes, but then you're good.
Let us go a little bit into the business model and growth strategy.
Before that, something just popped into my mind when you could do having a dog
somewhere in a remote place, It's hard to access and you could put explosives on it.
Would it also be possible to have dogs maybe even stationed at some remote places?
What I have in mind is like a shelter somewhere in the mountains or stuff like that.
We had traditional, you know, Bernardina, the St.
Bernard dogs who run around looking for people, something like that.
What I had in mind was a dog with the first eight pack and AD defibrillator
attached in a weatherproof package on the back.
That's brilliant. Juran, what are you doing for the next few months?
Come here and help us build that.
Happy to do so. And that's a great idea.
And that basically would involve having the quadruped in a sort of nice like
styrofoam container that's easy to deploy.
You would have charging electronics that make sure that the quadruped is ready
to go when needed and then it could be remotely activated and the styrofoam
shell would open and the dog could stand up and perform,
perform various duties as, as you program them.
The battery life right now is about three hours.
And so you'd have to think about like a charging infrastructure and communications infrastructure.
We've used Starlink for communications to the dogs,
and that makes it possible to connect with them basically anywhere on Earth
and have a pretty good telemetry and video data using the small form factor Starlink system.
So the Earth to satellite communications are getting very good very quickly.
And so that means that what you just described could easily be built.
And come here, we will host you. We will give you hardware and access to the
lab, and let's go build it together.
That would be very good. We need to seriously talk about that after the interview.
But before that, let us go a little bit into the business model and growth strategy.
What is the primary revenue model driving Open Mind?
Well right now there's a major question in
the entire ai industry which has
to do with how do you monetize ai so the
the question you're asking is a bigger one and the
same question can be asked of robotics how do you monetize robotics
what we're seeing is that as it relates to monetizing ai people or companies
who have many customers and existing products have natural advantage because
they can use AI to make existing products better and then charge existing customers more.
That's an easy way to monetize AI.
If you're a company that's developing AI itself, that's of course difficult
to do because you don't have a lot of existing sales channels or customers yet.
One thing we're doing as a company is we're speaking more and more to robotics
hardware manufacturers with the goal of developing partnerships with people
who make robotic hardware.
And the value proposition is that many of these robotics companies don't necessarily
have advanced capabilities in software or AI and, of course,
want their robots to be competitive.
So one thing we're looking into is partnerships with robotics companies.
And the other thing we're doing on the sort of revenue side is we are putting
up enterprise-focused products that enterprise pays for.
So when you start using our open source software, then the very first thing
you'll need is a good system for simulating your new robot, ideally digitally.
So one enterprise product is a digital simulator for the robot you're developing,
and that allows you to quickly iterate through different robot designs by virtue
of being able to evaluate your robot design interacting with the digital world on a computer.
That's one example of a sort of enterprise product. The other enterprise product
we're building is a communication infrastructure for robots.
And the idea is that robots are
much better able to quickly learn
and transmit that information to other robots to help their robot friends that
means that if you have a swarm of robots they can transmit information and skills
very quickly to all their partners in their team.
For that communications infrastructure, that will also be a pay-per-use infrastructure,
just like people pay for cell phones.
But in this case, robots will be paying for machine-machine communications infrastructure.
But the main thing for us right now, as essentially any company in this space,
is to just be used, is to get users, to have people use our software.
And then once you figure out what people are using the software for,
then it's also easier to develop good revenue models.
But we're really just emphasizing on growth right now and adoption as opposed
to what specific product features are or how much to charge for them.
Jan, should we ask our audience, kind of crowdsourced intelligence,
how do you guys envision OpenMind expanding its reach? Comment down below here.
Let's talk a little bit about fundraising and financial sustainability.
Fundraising often comes with its highs and lows.
Could you share a defining moment of Open Minds fundraising journey?
Well, I guess one thing that's really important for founders to know is that
there are many good ideas,
but the way investors work can be very surprising.
And generally what happens is that there are some trends in the investment community.
And if your idea conforms to that trend, then your fundraise will be very easy.
Conversely, if your idea is excellent, but the timing is bad,
then your fundraise will be extremely difficult or impossible.
So it's a little bit like, you know, fashion in Italy or Paris,
where the fashions change every few months.
So a big part of successful fundraising is just getting the timing exactly right,
or being very fortunate that you're working on something that is broadly perceived
by the investment community to be potentially really interesting and then you're
not too late and not too early.
In our case, I think through dumb luck, our timing was just very good.
People were seeing the rapid advances in AI.
And when we started to tell people, oh, you know, that AI is not just good for
students cheating on their homework or missing human lawyers on AI is also good
for controlling robots.
And then they said, oh, I haven't heard that before. Tell me more.
And so then that's a very natural starting point for a conversation.
And then based on previous startup experience, people just asked if they could send us money.
And so at some point, we just said, okay, let's turn this into a company and just take the money.
But the most important thing there is just to get the timing right.
I see. How do you balance between rapid growth and financial sustainability?
Oh, you don't.
Okay, next question.
No, you try to build the most awesome product and then grow like crazy.
And then when you need money, you just raise more money. If you can't,
you're building the wrong product.
It doesn't get any simpler. How have investors responded to your business model
and what strategies have you employed to make your pitch stand out?
Well, to first approximation, investors don't ask about the business model.
So what investors are more concerned about are things like, are you building
something that is new and useful?
Can you protect the business, whatever it is?
What is the maximum addressable market? Is the TAM a billion or is it a trillion?
And those are the important questions. And then specifically what your business
model is and what you're going to charge for and how much you're going to charge.
All of that stuff is made up anyway and fake because you basically don't know.
So the questions you get, at least in the early stages of a startup,
really have to do more with how special is your technology?
Does it solve an important problem? And what's the addressable market size?
Of course, if the company is larger and you've been operating for years,
then, of course, you have to show the dollars and cents. Are you actually making money?
How much does it cost to acquire each new customer and so forth?
But given that we've been going for less than a year, we're still at this very,
very early stage, you know, 15 people.
And we do not have to show any revenue at this point.
We already talked about team and leadership here
but since you're very young and you're a small team
i would just stick
to very few questions there uh what do you think the are the core values that
define open minds company culture well the the central thing i look for in any
employee is great enthusiasm and extreme flexibility.
In a startup, there is no such thing as a defined job role or a clear job description.
The job description is very easy.
Work 24-7 and get things done.
And your title and your background and your interests,
none of those matter in the least uh the point for you is to be completely driven
and utterly fascinated by what you're trying to do and then just get things done,
And some people flourish in that environment and other people struggle greatly.
For example, we've seen, this is true of many startups,
that people who have worked at large companies have an incredibly difficult
time joining a small startup,
because they tend to be used to structure and
rules and standard operating procedures and
eight levels of decision making and so
when someone like that joins a startup and you tell them like
i don't care what you call it i don't care
what your job title is um just like go do it figure it out so you're looking
much more for a skill set that is like a um like a swiss army knife like an
extremely enthusiastic Swiss army knife more than you are about people for highly specific roles.
And if some highly enthusiastic Swiss army knife is listening right now,
where could they learn more about career opportunities at Open Mind?
Oh, they should just email me, jan, J-A-N, at openmind.org.
It's an amazing time. It's an amazing once-in-a-life opportunity.
There's unlimited money, and
there are an amazingly large number of entirely new things to be built.
So come to California, get on an airplane, and let's talk.
Getting a little bit into regulatory, ethical, and societal impact,
as Open Mind scales, what ethical considerations come into play,
and how do you address them?
Well, that's the topic of a whole book. And the main thing is that the technology
is moving much more quickly than most people realize.
So what's really missing is just awareness of what the capabilities of the software
are and a broader societal discussion. I certainly have opinions,
but my opinions only matter a tiny, tiny, tiny little bit.
What's much more important is that there is a broad discussion around these
topics, and that's part of the motivation behind podcasts like this.
In terms of ethics, I think all engineers and all scientists certainly are responsible
for foreseeable consequences of technologies they've developed.
And there's no way we're going to be able to
like scrape the surface of any of this
in the remaining two minutes but as a
parent I have to say I'm very afraid
of what some of these technologies mean for like our children what shall they
learn what kind of jobs will they have what will their families look like what
will their income be like what does a democracy look like What does a society look like?
And all of those things are potentially impacted by the technologies that the
AI community is working on.
So everyone listening to this, please wake up, please learn, and please argue.
That is actually, since you already hinted, we only have two more minutes of
recording time, I would have a lot more questions for you. But...
For our listeners, if you had
the chance, what question would you pose to Jan? Share in the comments.
And Jan, to you, as a last question, where can our listeners connect with you
and learn more about Open Minds initiatives?
Well, hopefully there'll be a link or something like that in your podcast.
But my website is at openmind.org.
And we're working hard to add more material and to have more interesting content there.
And of course, we're also on Twitter and all the other places.
So let's just start with the website at openmind.org.
Great. Jan, it was such a pleasure having you here.
We talked a lot, and I think I'll have you back for another interview with very interesting content.
Wonderful. It's been a pleasure. I look forward to seeing you in California
at some point. And there's a dog on the way for you.
Great. Thank you. Have a good day. Bye-bye. Auf Wiedersehen.
Thank you. Thank you. Bye-bye.
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