Let's move back a bit to the self promo and why it is
difficult instead. Do you think it's difficult for
female founders more in general because to?
Build a company. Not to to build a company, but
also to do promotion for the company.
Definitely. I feel like from what I've again
observed from my experience, what I've seen with my female
colleagues, they feel more pressure to prove that they're
as capable as their male colleagues, right?
I, I feel like we have watched a bit more closely how we speak,
how we dress, how we show up, do we smile enough?
Are we nice enough how present we are?
So, you know, we're judged more on the tone, on our appearance,
on the attitude. And actually, if I've personally
experienced that because I've received comments, I need to
smile more before. So, well, actually competence
alone isn't often enough for women.
So I think that that adds a layer of pressure as well.
Welcome to women disrupting tech my name is dear Kanupkas and on
this podcast I give the women who work in tech the platform
they need to inspire and empower each other.
Join me on a journey into the world of entrepreneurship,
funding biases and role models to discover the strategies for.
Success in the tech industry. In other words, how women can
disrupt tech. Are you ready to listen?
Hey, welcome back to Women Disrupting Tech, and thank you
for tuning in to episode 109. My guest today is Julia
Yakimenko. Julia is the founder of Cyber
Ed, a startup that's building a platform to detect deepfakes
across video, audio and images. But as you'll hear, she's doing
much more than that. Julia Yakimenko studied human
rights law. She shifted into tech because
she saw the potential of technology to simplify, support,
and protect people's lives. And now she's on a mission to
restore trust in what we see and hear online.
In this episode of Women Disrupting Tech, Julia and I
talk about what makes deepfakes so dangerous, how you can spot
them, and why building transparency into AI isn't
optional. It's urgent.
What I loved. Most about our conversation is
that Julia not only goes deep on the tech part, but also shares
her take on what it means to be a female founder in
cybersecurity. She opens up about the
challenges of self promotion, how she's redefined success for
herself, and we cover the emotional work behind staying
true to your vision, especially in the space where for female
founders, competence alone is not enough and where the number
of role models is still too small.
So when you're ready to listen and learn how Cyberrat battles
deepfakes so you can trust what you see, please welcome to women
disrupting. Tech Julia Yakimenko Welcome to
Women disrupting. Tech Julia, good to have you
question. Question I always ask at the
start is how you got into your current job or current position
and as the founder of Cyber IT? That is a good question.
There's a long answer and then there is like a short answer.
Which one do you prefer? Well, I prefer the loan because
this is going from content to our.
OK, so I started completely in a different industry because cyber
rat is it's a tech company, right?
It's a cybersecurity tech company.
But I started my career in law. My first degree was law and I
was planning to become a lawyer, very passionate about it.
I was very interested in law and European Union law and actually
human rights law. That was my favorite subject in
my bachelor's degree. So and then I moved to England.
I'd completed my law degree, European Union law degree in
Poland, moved to England, and then I started working in HR and
compliance. It's more business oriented, but
still legal. And I ended up working in a lot
of tech companies, startups, and that's it.
OK. There, there was no way back for
me. The once I've seen the tech once
I've seen what systems can do, how they can automate, how they
can simplify our lives. There was no other any other
industry for me anymore because I was just that's it.
I found myself. I want to be in tech Yeah.
And just, I guess I manifested it in a way as well a little
bit, but then I also sort of tried to shift my career.
COVID hit and then. So that is a good time to change
careers into tech. I was already working with
systems, but I was on the user end rather than actually
development sites. And then I moved to the
Netherlands, started working at Rabobank, and yeah, a few years
later I ended up finding Cyberat.
OK. And what does cyberat do?
Good question as well. So we are building pretty much a
platform to detect deepfakes across video, audio and images.
Very simple. Well, very simple, but it
sounds, yeah, it sounds really simple when you pronounce it
like that. But it sounds also to me like
really technically complex, because I think I read somewhere
that 8 out of 10 people cannot detect deep face.
So how can you? How can you deploy tech to do
that? Yeah.
So we actually, you're right, we have quite complex, quite
advanced technology behind it. So we build our own deep
learning models and we use multiple combined multiple
detection approaches. So it's like pattern based fraud
detection, neural forensics analysis and then provenance
verification. Many more approaches.
OK, so. So there is actually advanced
tech behind it, yeah. So I won't go into all the all
the terms that you just mentioned because to to keep
things simple, but it wouldn't be fair to say that you want to
bring trust back to the Internet or enable.
Trust on the Internet with that. Yeah.
So our goal is not really like to stop on AI, but just to bring
that confidence back to the Internet, keep people and
companies confident and what they're seeing online and help
help to set that boundaries around how AI generated content
is flagged, identified and responded to.
So yeah, I guess the goal is to make that verification process
of the media a default. You know how you have 100% you
have like utilizing 2 factor authentication or antivirus.
So what we want, we want to, in an ideal world, make that
default for the media as well. So any content that you see on
social media, online or that companies, organizations,
governments share should be verified and people should see
that that there should be a level of transparency around it.
So people can make the distinction between what is real
and what is deep fake. Exactly in the most approachable
way. Possible.
So. So maybe can you clarify for us
what types of deep fakes there are and what makes it difficult
for people to, let's say, distinguish them from real
content? So what is deep fake?
Deep fake? It's either AI generated or AI
manipulated or changed by the AI media, which is image.
It can be voice recording, it can be a video that you see
online. It can be a phone call.
So fake video or like a phone call or audio recording.
It can damage your reputation on like practically overnight, but
it can also be utilized by scammers to get someone to send
you money to trick you into sending money.
They can easily pretend to be someone's daughter or
grandparent and then ask for help using different techniques
like push in urgency and then get you to share your personal
sensitive information and that can be seen online that can be
used in a phone call. So there are different ways to
do it. They can clone the voice and
they only need like 30 seconds of someone's voice to be able to
clone it. OK.
So basically what I'm hearing you say is that, for instance,
the the CEOCFO fraud that would be done via e-mail is now moving
to phone calls because they can actually clone your voice as
ACEO or as ACEO. And then if they have a little
clip or 30 seconds of your voice, they can, well, they
could of course spoof as they call it, the OR mask the number
that they're calling from with the number of that particular
person. And then they call you to say,
hey, you need to wire that money and you need to wire it now.
Yeah, correct. It's a form.
Yeah, exactly. That's one of the forms.
It's not the only form, but that is one of the forms.
And what they often do, they try to get you off e-mail or off
Teams, off Zoom, try to get you into WhatsApp, into phone call,
because that is easier for them to clone.
There's still no perfect way to clone video real time to go on
like a FaceTime call, but on The Voice call they can do it.
So that's actually one of the probably one of the signals to
watch out for is they're going to try to get you off the e-mail
into the phone call or yeah, WhatsApp call saying they're
busy, they're on the move. Can we, can you give me your
phone number? I'll call you something like
that. That is.
Something that definitely employees should watch out for,
yeah. OK, that's good to know just as
a questionnaire because I I was browsing the Internet yesterday
and I saw that Google has the option to create videos from
images. Is that also?
A form of deep fake that is deployed.
That is synthetically generated deep fake.
That's one of them. So it's not just changing
cloning. So we have voice cloning, we
have image altering. You know, all those Photoshop,
Photoshop like Pixie changes where you put on face filter to
prettier or whatever you want to see, you know, in in your
picture. But yeah, also you have those
where you can generate really cool videos actually.
Yeah, I was experimenting yesterday with it, but now that
I hear from you, I'm like, OK, maybe not such a good idea,
although it's. But that's fine, right?
Not everything. The AAI is not only for harm,
it's also, you know, it's also for fun.
Yeah, true. Yeah, like every technology, I
think it's sort of it doesn't care if it's used for wrong or
right. And let's let's take that, take
that on a bit bit later. So you talked about a few ways
to to to spot the deepfake like really taking care or being
mindful that if people want to take you off e-mail into
WhatsApp, that's yeah, red flag. Are there any other red?
Flags to that you can use to to spot deep fakes.
Definitely. So the pressure to act fast,
that is probably ultimate signal.
I would say any security awareness trainings will
definitely mention that. So, and in any sort of social
engineering, even by e-mail, if you see someone is trying to
push you to do something fast, that is the first and the
biggest rut flag. But if we're talking about the
video or yeah, if we're talking about video deep fakes, just
look for any like unnatural blinking or weird light that
falls on the face, on the skin, any stiff facial expressions,
any weird poses, robotic tones in the voice.
Also a background noises that do not match the picture that you
see if you've seen someone at the office but then you see some
car in the background. Like I don't know some
construction or actually construction noises is
realistic. But if I don't know, if you see
some completely opposite noise to what it should seem like,
then it's better to ask or question that.
And that's already like a small flag.
Why is that noise? It's completely opposite to
yeah, what I'm seeing. So I think it's just like a
combination of multiple red flags.
Then that should raise questions in your head.
Yeah. We call it zero trust in
cybersecurity, zero trust approach, zero trust.
OK, so I'm still of the generation of trust but verify.
But then your approach is more like don't.
Yeah, I think millennials are zero trust.
Bit more skeptic, yeah. Yeah, our our generation is.
Just to add to that, because if you look at the AI and also at
video for that matter, the platform that we're recording
this on Riverside does actually does a pretty good job in
creating clips, etcetera, and help you with putting together
really nice looking video clips. So it, it, it, it works really
fast or it progresses really fast, I should say.
And also already described how difficult it is to, to spot
deepfakes, especially if you're not paying attention.
How can how can we ensure also taking that zero, maybe taking
that zero trust approach, how can we ensure that we keep using
AI for good? Well, I would say bringing that
transparency around the AI because if now we go into social
media or read some news, the only reason we can't suspect
that the source is verified is just by looking, OK, this is
Bloomberg. It must be real, right?
Or I don't know, some new news daughter.
Now that must be real, right? But we don't know because they
also getting their media, you know, from some witnesses or
journalists and how did they know that what they're sharing,
it's 100% true unless they've taken that picture themselves or
you know, taken that video. So I think bringing that
transparency to the next level, because people should always
know what's like when content is generated and when it is real,
especially when it, when, when it comes to politics or
journalists or something very serious, even general, even
regulations is not enough. We have AI act now in US.
We have some bills passing through, I think in California
around deepfakes. But then in Asia, there's still
nothing, right? And we read Asian news, right?
So we still, we Earth, Earth is not that big.
We're still all, you know, open to, you know, absorbing new
sources from all over. And so I think having
standardized regulation globally, that would really
help. And of course, clear boundary
boundaries, part of that regulation, how AI can be used
to manipulate everyone and deceive people.
I mean, these days, personal data is not personal anymore.
Any like social media platforms, they just have access to
anything you signed up on, like, you know, that's how we all
know. But now also we have AI models
that can just with a tiny bit of input, they can guess things
like your location, your income, your gender, and yeah, so we all
watched Black Mirror. So we actually entering the era
where AI can learn human behavior, predict and influence
the decision making process. So yeah, I think the focus
should be. How do you look?
At that yeah so it's I wouldn't I wouldn't say we should panic
and be scary we should definitely utilize the potential
of AI for good because there's so much good it can bring you
know in Med tech and in longevity as well helping people
you know especially like in medical fields.
And then we're talking about data, we're talking about
genetics. So it has a lot of views, right?
It can also help us progress and all kind of developments.
That's also I would say. So the way I look at it that we
just need we should, you know, benefit and enjoy the potential
that AI can bring while also, you know, bringing that
transparency regulation and enforcing those regulations
where there's clear boundaries between what can we can do and
what we cannot do. So I think just that openness,
transparency and enforcing the boundaries would definitely
help. So the focus should not be on
like building hype, you know, but also to protect people,
support people and bring that long term stability.
Yeah, and teach people how to use it.
And that as well, yeah. And that that's.
Probably at the front of it all. Yeah, I think that's, that's
really important to to especially teach people how
things work, what they see, how to detect deep fakes, but also
how to deploy AI for really good causes because they are, as you
said, a lot of them. So is cyber and AI.
Are those still very male dominated fields?
Work fields? Yeah, still quite male dominated
industry, I'd say. Yeah.
OK. So would it then also be good to
have more women in those fields? Also to make sure that we're
mindful of the dangers, that we just not go ahead blindly
because it's good. But then also really think about
the ethics part of it, the impact part of it.
Definitely. I mean we all know what gender
diversity brings so and how it helps to build systems.
We need diverse, you know, points of view, diverse
backgrounds to build the best, most efficient systems.
So of course. Of course, gender diversity,
cultural diversity, it definitely helps to diversify
and bring that aspect into cybersecurity 100%.
But I, I, I wouldn't just see it as cybersecurity, I would see it
as tech in general. Tech itself, as an industry,
it's expanding. We see that digitalization in
more small aspects of our everyday life.
So it's not just tech, it's just integrated in our daily life.
And I mean, what, roughly 50% of population is women, so it's 50%
of customer. Yeah.
But do you also see that because you've been working in tech for
quite a quite some time, do you also see that change?
So do you see more women come into tech, for instance as a
gabo or? Definitely, if organizations are
more conscious of diversity and inclusion and actually in their
conscious and integrating that into the whole workflow into
completely changing everything you know from the start.
And yeah, if if diversity and inclusion is not just a policy
and a box they took, but actually they are generally
interested in it and they see a benefit of it.
So yeah, then I definitely have observed that change.
Let's say Rabobank, certainly they put a lot of effort into
diversity and inclusion. I think it's like one of the few
employers that I work for where I've really seen, you know,
genuine interest, genuine dedication to bringing that
diversity and inclusion into the company, not just on a policy
level. Yeah.
Out of curiosity, how does that show?
Well, can you give an example? Of course, it's just it's
enabling initiatives. So for example, like they have
women in tech community and setting that up.
I wouldn't say it was difficult because everyone was very
excited about it, passionate. A lot of people are willing to
join and just do the work that needs to be done.
Where what I've heard from some of female colleagues at
different organizations where they face more hurdles, you
know, setting up a community from from above HR trying to
sort of manage them a bit and slow them down.
Where I have not experienced any of that at the Rabobank,
everyone was actually enabling, pushing, given space.
And so that that was just the most basic example that I can.
So you you received a lot of support also in practical terms.
100%, yeah. OK.
Do you? Experience the same as as a
founder of Cyber Ed. As a founder, you're bit more
isolated, so I had to consciously build a community of
people around me or join communities.
I, I see a lot of, I see a huge gap, gender gap in, in
entrepreneurship, in tech entrepreneurship.
And actually in the last four or five years, there's been a drop
in female founders versus before 2020.
I've actually spent a whole day researching the other day and I
was a bit concerned. So actually before 2020 has been
a bit higher number of female entrepreneurs and in Europe
especially and that number dropped.
And I started looking more into the data and I've seen the
reason. The reason behind it is that
women receive a less funding at a startup stage.
It's only up to 2% globally. Regions like Europe, I think
it's a one point half percent if I'm not mistaken, but it's up to
2% globally. Of all VC funds, you know of all
VC money women receive, which is.
Actually, well, now less than 1% globally and less than half a
percent in all lands. Wow.
It has dropped and there are there are several factors that
play a role in this. So funding is one of the causes
that there are less female founders.
What are other causes? I think another reason is just
because there's much less role models, so women struggle to
push through in between start up into scale up.
So that's where I've seen the gap.
So when women move from start up into scale up, there's a huge
drop in female founders that's make it through and that's.
So that make it to the second stage.
Yeah, make it to the second stage.
Yeah, exactly. So that's where the the issue
because, yeah, you get the first initial investment, maybe
friends and family maybe, yeah, maybe not VC itself.
It doesn't always make sense to get VC at the very early stage.
Maybe you get some grants, but then at the next stage, actually
women then that their women struggle to get funding, get
support, Yeah, there's not enough role models.
Maybe they feel isolated and I have to say every now and then I
do feel isolated as well. But I'm so consciously not wired
that I know OK, I have my best friend, she's very successful
entrepreneur. So I can text her, call her
anytime, 24/7. And then I'd say most of my
close friends are entrepreneurs or either ex entrepreneurs or
current entrepreneurs. Maybe not all of them are tech
entrepreneurs, but they all entrepreneurs.
So I'm just surrounded. But then even even then, I feel
every now and then isolated. There are communities.
So I think that is very important to be part of some
community and you know, go to the meet ups and have those
people around you that support you for sure.
How How difficult is self promotion?
That is challenging. And actually, funny thing, the
other day I went to the amazing event and there was a dinner and
someone was sitting across the table, someone that works at, I
think an investment firm. And he of course found out I'm a
founder. And he asked me the first
question. So tell me why your product is
better. And then I started giving them
him reasoning like, OK, so it's not a straightforward answer.
And I started going into like a bit of statistics and explaining
the product and he's like, you know, only females give me that
kind of answer. When I asked the same question,
when I asked a male the same question, they go straight away
into, oh, we're the best here, we're the best there, we're the
best there. And only female tries to be not
just more analytical, but tries to give that, you know, ego less
answer. And that made me think it's just
on such a core level where I don't want to go like as a woman
right into self promotion. I want to try to stay humble and
also just give benefits of the products and also give the whole
background, you know, help him understand the whole industry
products, so then he can understand how that looks.
Yeah. So that that was very
interesting. So 2 questions.
So. So if I understand you
correctly, what he basically told you is give me less less
context. I think, yeah, what he was
trying to tell is don't. He mentioned that.
Don't be afraid to put on a bit of ego.
That is OK. OK, so how did that make you
feel? Oh, that is a great question as
well. So I agreed with him partially,
and then partially it just made me question like, why that was
not my first reaction. Why did I not right away started
giving the benefits? And I thought, and then my next
thought was, well, because something that I'm building is
bigger than me, is bigger than you or him, You know, it's for
the world. So I want him to see that, you
know, from my standpoint rather than just, you know, giving a
sales pitch. You know, all our accuracy is so
high. We have descendants approaches
that no one else has, detection approaches that no one else has.
So I think, yeah, I think it is just having that mission above
anything else. And that's how I'd see that.
And maybe not everyone is like that.
Yeah, true, but let's do some shameless self promo then.
So why is why is Cyberrat better?
What makes it better? What makes it unique?
Let me put it that way. We have explored multiple
detection approaches that I've mentioned earlier.
I think So. What we're trying to build is
all in one defect detection platform.
So we don't just take one architecture and that's what I
know quite a few competitors do. They have one architecture that
they use and a couple of detection approaches.
We explore multiple detection approaches and our accent is on
forensics, forensics detection and giving that forensic
reporting, forensic explanation and comprehensive overview of
what is real, what is not. So it's not as simple as OK, the
image, the video is real or not. It's giving the full
explanation, the background behind it.
And we're going as deep as giving the metadata information
where, for example, the media was created, maybe even details
like date, like locations. So it's not high level insights,
but we focus on deep level insights while also ensuring
that we diversify our detection methods because Gen.
AI is improving. And with I would say the light
speeds, every day I open my Instagram and then I see some
new Chinese, you know, Gen. AI.
So we build our own data sets from the scratch.
So we have a whole team of people that are sitting and
building data sets and we make sure that we our data sets
quality is impeccable. So that is also a huge part in
in building a great product. Your data sets have to be
impeccable. And we have privacy first
approach as well. So there are multiple factors
Going back to that question that you asked, it's not about why we
are the best, it's about how we build a great product that is
very good quality product and it's, you know, meets the needs
of our customers. OK.
So it's more holistic in terms of the detection, but also in
terms of approach, it gives more analytical data to users.
So they can actually can they actually use that?
How can they use that data? Because if you give more data,
there's probably use case for that data with customers.
Exactly. So those kind of reports,
they're very helpful in forensics investigation.
It's aimed at the government's law enforcement, public sector
defence customer who really want to see, you know, the nitty
gritty details. I know what we offer on our our
dashboard as well is multiple views.
So whether you want to see more technical details or if you want
to test different approaches, we give that option that you can
see how that how different detection approaches look like
actually visually because I am very visual person.
So I believe and actually testing everything with my own
eyes. Yeah.
And the last thing I heard you say is that you focus on
building like an impeccable data set.
Maybe let's dive a bit deeper into why that is important, both
from a detection point of view, but also from a yeah, from a
customer point of view. Well, from the technical point
of view, actually now if we just make a little step back, having
a great data set is probably about 80% of your win.
Well, maybe I'm being a bit yeah, generic, but I would say
it's 70 to 80% of win in building a great detection
product, at least in our industry.
Because the better your data sets are, the better you can
train your models to, you know, differentiate and spot those
differences between real and what is real, what is vague and
spot those anomalies and patterns.
So actually those data sets, well, I foundation 2 great
models. So that that is, that is one of
the reasons. And of course our job is to
maintain them and update them on a regular basis.
So it's a lot of work, but it's a fun work.
We enjoy it. OK, well, that's important to
enjoy the the work that you're doing.
At least in my experience, it keeps you going.
Definitely, yeah. And of course, from the customer
perspective, we want to deliver clean, high quality product and
we want to make sure that our product is privacy first as
well, hence, you know. So why is that important?
Because we, we, we, you just highlighted.
So your customers are mainly law enforcement, law firms, forensic
firms who want to pick part. Let's say we need more data to
to detect deepfakes or is it is your product or that's.
Not our main customer, but that is a customer for whom we build.
We're building the forensics dashboard for sure, but we have
a more user friendly versions for media or maybe a bit less
techie type of customer. So it's not all very technical,
but we have an option for it to be more advanced.
OK. Because I was the like the more
technologically advanced people usually care a lot about today
getting as much data as possible and maybe less about privacy
because especially in law enforcement, you want to enforce
law. Correct.
Yes, but also. There's the balance with
privacy. DRS is different from, let's
say, if you're a regular company where you at least have to want
to report privacy rights of your employees and customers.
Exactly that is the case, yes. But also what I also tried to
say with the privacy first approach is it's really
important to me make sure that the way you collect data to
train your models, because we all know, you know, we put the
personal data into ChatGPT and that's not your data anymore.
That belongs now to everyone except you.
So we do not retain the data. So that is one of the probably
also very important bits that I'd say everyone in our industry
should be very conscious of that we do not retain any data from
the customer without permission. It's, you know, privacy first
built at its core and the way the data sets are built as well.
We do not, you know, utilize public data that does not belong
to us and we do not have, you know, if you, we do not have a
permission to use it, we're not going to use it.
So, so then we had to go through a few, you know, rounds of
really manually collecting and gathering the data and putting
quite a bit of effort from the team members who, you know,
created those data sets. So that's what I'm also
mentioning when it comes to collecting data, you have also
have to be very privacy first minded like it has to be at the
core of the mindset. Is that something you support in
in mil Co founders as well that they have this privacy first
approach? I think our industry is still
very new. It's not very sadly not very
transparent right now around, you know, defect detection
products. The companies are not are not as
transparent as I think we should be around, you know, knowledge
sharing and maybe having one united platform for benchmarking
and also for, you know, also regulating who's regulating us.
This whole AI regulating AIAI companies is still, you know, up
and coming those regulations. So I think until that is set, we
actually don't know who is doing what.
We can only trust their word. There's no organization that
can, you know, come and audit our data sets.
Let's say that doesn't, well, it exists, but not to the point
where it's widely used and widely utilized and widely
known. And I think it's, you know,
should not be the case because you have common standard audits
and compliancy and that should be applicable for AI companies,
you know, companies that build models and it's up and coming,
but we're not fully there yet. So we can.
Only trust the word of what the people say, right?
And you know, anyone can say anything really.
Yeah. But then still I would think
that they would have to comply with ISO type of standards.
Of course, yeah. Those are the sort of.
Starts are are really the basics about at least the organ, how to
build up the organization. Of course, those are the basics.
Yeah, ISO. Yeah, so let's move back a bit
to to self promo and why it is difficult for is that do you
think it's difficult for female founders more in general because
you. Build a company.
Not to to build a company, but also to do promotion for the
company. Definitely.
I feel like from what I've again observed from my experience,
what I've seen with my female colleagues, they feel more
pressure to prove that they're as capable as their male
colleagues, right? I feel like we have watched a
bit more closely how we speak, how we dress, how we show up, do
we smile enough? Are we nice enough how present
we are? So, you know, we judge more on
the tone, on our appearance and the attitudes.
And actually, if I've personally experienced that because I've
received comments, I need to smile more.
So while actually competence alone isn't often enough for
women. So I think that that adds a
layer of pressure as well for us, you know, all the all the
norms, older social standards. Again, when we start, you know,
going to school and studying what is, you know, normal for a
girl to be like for a guy, that where we end up, you know, a lot
of females end up not being very driven about building their own
business in the end because it requires a lot of masculine
energy to push through. OK, I'm a bit silent now because
what? Why does it require more
masculine energy? Because it's competitive.
Let me, let me rephrase this. There's always going to going to
be competition of sorts. So that's, that's I think a
masculine value that is really difficult to to evade.
But other than that, is there a way for a woman to build a
business on her own terms? There is, but I think we need to
understand what it takes to build a business.
First. It it takes a lot of self belief
if you don't especially come from a family of successful
entrepreneurs or parents who are financially well off to support
you in any journey that you take.
Where if you don't come from that money or those role models,
you have to have the blind belief that you are capable.
And also your upbringing will be a, you know, very core factor on
how on yourself image of yourself.
And if you grow up in an environment where you bullied a
lot, you judged a lot, you you're questioned a lot,
everything you say is used against you, then yourself
belief is going to be somewhere at the rock bottom.
So it takes a lot of self preservance and self belief and
sometimes a little bit of delusion.
But I'm capable, you know, of doing this and maybe a little
bit of ego as well, while healthy ego.
So how do you do that for yourself?
Yeah. How do you keep yourself?
I wouldn't say delusional, but how do how do you keep your
spirits up, especially when times get hard?
For me it took a lot of inner work, so I don't come from
money, I come from a very normal family of working class parents.
I also went through, like most of you know, I think females in
the 90s where it's been still, you know, post Soviet as well,
environments where you know as a woman you are more taught to be
compliant, be nice, be. To smile.
To smile to, you know, be a pleaser rather than, you know,
standing up for yourself and having that healthy rage maybe
or healthy, you know, boundaries, boundaries, what is
boundaries? So that's something that I had
to learn. So doing a lot of self work
definitely helped me to stop trying to fit into who I thought
I am supposed to be and actually helped me shape the idea of what
success looks like. Because in my head that was
something else. And then I would say after
really taken a few years to focus on my mental health, I've
come to my Zen. Then I realized, OK, this is not
what I see success as. And that helped me to step into
my power, into my potential, accept that the inner potential,
and then just, you know, act from it, speak from it.
So it's a journey. Yeah, so how has your definition
of success changed? It definitely changed before I I
thought it's, you know, having a stable job and, you know, having
your own house, maybe, you know, having like a family and
settling in one place and that that is definition of success
now changed. Now, for me, success is
something more holistic, something that comes from
inside. It's all those external values,
you know, I cancel them and transitioned into more, you
know, finding my own peace, my happiness that, you know,
doesn't rely on that portrait image of what success is like.
It's for me. It's just, you know, acting from
my inner voice. It's trusting my intuition, it's
feeling. Every day I wake up and I'm
grateful for being alive. That is what success for me, you
know, being happy to be where I am and it doesn't matter where
it is, it can't be anywhere. So you said you also worked or
lived and worked in different, let's say, cultures because you
come from a Soviet post Soviet background, Ukraine I think.
Yeah, that's correct. Yeah, I was born in Ukraine.
OK. And you lived in London and now
you live in the Netherlands. How does that help you as a
founder or as a human? That definitely helps me to be a
bit more adaptive. So where I had to, you know,
switch between different cultures, different systems and
that definitely helped me learn to accept people maybe more the
way they are, except differences and you know, feel at home
anywhere really. So that is probably one of the
things that's definitely helped me and that adaptability I bring
with me to, you know, to business where you all, you
know, start up environment. It's all about being agile.
And that is in me. I strive in change.
I love change. We moved around a lot as well
when I was a child. So that's it's completely fine
for me. I'm very minimalistic.
I don't need much. I need one suitcase to be happy
and have my things. It fits in the one suitcase and
that is enough. And I think it also helped me to
be a bit more perceptive. So because I've met so many
people in my life and travelling, I've been to 38
countries, I've lived in like over 7 countries.
So yeah, I think being perceptive and just seeing
through, you know, the surface level or performative dynamics
and that again really helps in career and business.
Also psychology degree helps with that as well.
Yeah. That I can imagine, because that
I think you're then also taught to observe.
Definitely made observe and make decisions really fast.
And I think as an entrepreneur, that's something that is a must
because the more decisions we'll make, the more mistakes were
made make and then, you know, we can improve faster.
So I, I think it's, yeah, from my experience, it's, that's
definitely helped. Just don't overthink.
Sometimes. Sometimes I also end up falling
into a pattern where I overthink and then I'm like, wait a
minute, why does that matter? You don't know?
So just make a decision and and that really helps, you know.
So basically also being able to intercept your head running
away. Exactly.
So I want to move back to to success for a moment and I want
to move forward in time to 2032 and let's imagine that cyber AT
is really successful. I was wondering what is if
you're really successful building a business and and
selling your products or giving yeah enabling people to work
with your product and detect deep fakes.
What has changed for companies and the people working for them?
Well, first of all, people no longer have to waste their time
questioning whether content is fake or real, so they can spend
their time on doing something more productive.
And that means that that verification process is fully
embedded into devices, work flows like 2 factor
authentication, you know, antivirus, it's just there so it
becomes a standard. I think that's the first thing
that really comes to my mind. And then people don't have to
then second guess. Or am I looking at a real
message? Is that it or like real, you
know, image video, is that a, is that a deep fake or am I
receiving call from my mother or is that someone pretending to be
her? So it should be embedded into
systems, into devices. Secondly, I would say global
standards and those providers of global regulations around media
authenticity like C2 PA or there's a global united body
that regulates AI and those regulations are in force and
companies are held accountable for the content that they share.
And then, of course, employees are trained to work with and
their fights good than the everified privacy for systems.
And people understand AI. They know how to work with AI.
They're not afraid of AI. Yeah.
So in a nutshell, you know. Is that also the ultimately what
you want to achieve is make people less afraid of AI because
AI is used for good? Definitely.
Because you know what? We are usually afraid of
something that we don't understand, but if we
understand, we know how to utilize it and there is
boundaries around it that's safe to protect us.
There's digital, you know, digital safety.
I think people will be less scared of the AI and its
potential if it's regulated in a transparent, you know, globally
enforceable way. Digital safety becomes a default
for our society, not something that we have to ask for, Send an
e-mail to cancel my, I don't know, don't use my data.
But it's, it's a default. You know, systems have to be
able to guarantee that safety by default.
And, you know, governments should really support that.
Yeah, fully agree. I'd say that's the very end
goal. Bigger mission?
Yeah, cool. So my bigger mission is to make
inclusion in tech to new normal by the end of 2032.
What is one thing that we need to do to get there that I would
need to do to get there? Wow.
I think they're already doing so much right.
The role models visibility promoting that and I think we
really need more role models. I mean, I've mentioned that
already a few times. If you don't have those role
models, you know, growing up, how can you know that someone
that looks like you can be successful?
So I think that is essential, you know, people who break the
mold and show that there isn't just one way to succeed in tech.
We need to accept everyone for who they are.
And I think that comes to my second point is stop forcing
everyone to fit in the same box. Like let people lead and build
and show up as who they actually really are, and that gives space
for everyone you know to show their real talents and step up
as their full potential without being scared to show it.
Yeah, SO also gives back trust. Yeah.
So inclusion can't just, you know, tick a box.
It has to be integrated into into everything, into our minds,
how we think, into products, how they designed, the way teams are
formed and the way decisions are made.
It has to be a default as well. Sounds like a great place to
close. Julia Yakimenko, thank you very
much for an amazing conversation.
If people want to learn more about you and Cyber Ed, where
would you like to send them? They can check our website, it's
www.cyberrat.ai or my LinkedIn or LinkedIn of Cyberrat.
OK, cool. And we'll include those links in
the show notes, of course. So once again, thanks very much
for a great conversation, really insightful, learned a lot about
deepfakes and how to detect, but also what detection does in the
bigger scheme of things. And this time, thank you very
much for listening. And until the next episode, keep
being awesome. Well, that's a wrap for episode
109 of Women Disrupting Tech with Julia Yakimenko on how
Cyberat battles deepfakes. So you can trust what you see,
Julia. And I hope that you found your
conversation as insightful and inspiring as we intended it to
be. And if you have any questions
for Julia or for me, please leave them in the comments on
Spotify, Apple, or YouTube. I do read all the comments and
I'll make sure they get answered.
If you want to learn more about Julia or Cyber Ed, please check
out the links in show Notes. And as usual, you can find show
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