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[Music]
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hello and welcome to SAS leaders Lounge
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your Premier podcast for insights into
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the tech World hosted by me Ramone today
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in our AI series we're excited to have
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Ela Haj haev the co-founder and CTO of
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real a with us El Journey from the
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University of Oxford to pioneering roles
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in a tech entrepreneurship including his
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transformative work at real eyes has set
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new benchmarks in Emotion recognition
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technology and its applications Ela it's
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a pleasure to have you with us today how
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are you and where are you joining us
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from hi Ramon thanks for the invitation
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uh great pleasure to to join you today
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as well I'm joining from Barcelona
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actually beautiful beautiful place I
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must say and also one of my teams I'm
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pleasure to have you here today oh I
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must say I think our guest and our
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audience is going to love what kind of
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you have in store for us so Ela to dive
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straight into it are you able to share
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your inspiration behind real eyes and
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the specific Market needs you aim to
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address with its
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Inception sure um well let's realize
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what we're trying to uh to do is we are
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we have a mission of um making
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technology more human
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um so that there's obviously a great
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technological development all all around
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um a lot of AI development as well um
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and I think we've always felt that one
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thing one important link that was
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missing in all of the applications and
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different kinds of Technologies is the
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ability for our devices to actually
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understand our
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emotions um and that's the mission that
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we set out with um and that's the
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missing link that we're working to solve
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and the technology that we're
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building brilliant I must say um a lot
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of our listeners are on a journey right
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now in careers or thinking to start
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something like yourself looking back on
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your entrepreneurial Journey what
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pivotal moments LED you to co-found real
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eyes and how have you seen the landscape
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of AI and emotion recognition evolve
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since
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then well I've always been interested in
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entrepreneurship uh because I don't know
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it's hard to say why I think my father
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is an entrepreneur um and I sort of
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liked uh the ideas behind it and and
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always wanted to do that realiz is uh
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not the first company that I've
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co-founded I had other um companies that
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were actually uh in the end uh turning
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out quite
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successfully as well so um there there's
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there's a number of different pivotal
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moments that led to um to uh uh this uh
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startup I think one of the pivotal
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moments was me meeting my uh co-founders
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obviously yeah um you know it's just uh
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people with uh some great ideas and
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clicking together um you know sometimes
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you do that intentionally sometimes it
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happens by luck uh for me was more of uh
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luck I think um yeah but um yeah I mean
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it was it was just one of those
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important moments where we we were
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talking about um technologies that were
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evolving that were able to uh better
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understand human behavior through um
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specialized devices or uh web cameras
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and uh we were fascinated about this and
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and kind of wanted to pull together to
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see what we could uh do about it um and
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then you know just throughout um the um
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the work that we had on uh realize in in
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you know at at the time when we were
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starting it I think the machine learning
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was was really uh taking off um and uh
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you know first um there were compute
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power that was kind of uh increasing uh
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and volumes of data that was uh being
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generated to to train machine learning
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models um and then and then and that
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enabled the ability to train deep neural
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networks um and then you know from from
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then onwards more and more uh different
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types of uh AI models have started to
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appear um and we've been just part of
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that Journey we've seen it all happening
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um and we were obviously within the
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space that we're working on uh which is
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reading faces reading facial
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expressions um
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uh we were we were kind of um riding the
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wave along with everyone
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else that's truly fascinating I must say
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and R as has recently introduced some
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groundbreaking features could you
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elaborate on these Innovations and the
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implications for emotion AI across
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various
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Industries uh yes absolutely so
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um uh first of all uh I'd like to kind
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of explain the the the differ features
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that that we have so we're we're we're
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focusing on faces and um we kind of find
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faces uh in the camera feed uh we're
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able to recognize faces we're able to
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recognize um things like age and gender
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uh of the phase and then uh we start
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tracking phase to see if we can read um
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facial
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expressions and uh depending on the
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context in which these facial
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expressions appear interpret them as
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certain reactions it can be emotional
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reactions or it can be an indication of
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uh levels of attention so are people
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actually paying attention or or they
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being
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distracted um and then you know this is
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just a generic technology and and then
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you can apply it in different
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scenarios uh one of the scenarios that
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we have been applying this technology is
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trying to gauge um audiences engage with
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content on their screen so we would show
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um people for example um movie trailers
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or advertisement videos uh or social
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media videos and kind of uh measure
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their reactions um and that can be very
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valuable to understand if uh these
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videos are of high quality if they're
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engaging the the audience correctly and
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so on um besides that uh of course the
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applications of this technology are are
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are much broader um we've been
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experimenting with use of this
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technology in online
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education uh where especially during the
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covid uh where a lot of education has
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moved to online um the the teachers have
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noticed um the challenges of trying to
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keep the audience engaged or trying to
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be to stay aware who in the audience is
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being engaged and who is not or how much
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the audience overall is engaged um and
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if you know and take take certain
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actions take certain corrective actions
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uh if necessary so again this kind of
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technology is is able to uh enable these
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type of uh this type of
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capabilities um One new area that we've
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been uh we've been working on recently
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is U fraud um fraud uh uh detection so
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um you know kind of trying to uh um um
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see if there is a real human uh behind
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the camera and if that human um is
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actually um really truly participating
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in for example an online uh research
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that might be being
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conducted um there are applications in
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gaming there are applications in
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security um there are there there are
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great applications in mental well-being
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um and we have worked on some of those
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applications as well so this kind of
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technology has very very broad
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applications of course their
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applicability depends on the maturity of
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the technology and how fine-tuned can it
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be um for the specific use
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case that's remarkable own I must say I
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was previously a math teacher before
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diving into recruitment I could
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definitely see the effect that would
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have on my classroom to kind of pinpoint
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who needs needs some further attention
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as well but overall I think it showcases
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how real eyes isn't just a participant
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but a leader in this emotion AI space I
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think your innovations that you've
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mentioned and including definitely that
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fraud detection element has the
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potential to revolutionize how we
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interact with technology on a um
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emotional level especially with security
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and the element is imported but your
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enthusiasm for the squirel sandr
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newsletter and its insights into Tech
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and product development is well noted as
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I have looked at previous post of yours
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as well how do these insights shape your
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strategy and product development at real
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I uh well I guess uh couple of words
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about uh squirrel Squadron so it's a
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squadron of um uh uh C Level Executives
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um a lot of whom are CEOs um uh cpos
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Chief product officers or CTO Chief
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technology officers uh but also others C
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se s um sea level um uh people and um I
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think for me everybody probably has a
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you know has something uh specific um to
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them to take away from being part of of
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such Community for me um an important
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aspect was um first of all um kind of
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confirmation that a lot of challenges
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that um I'm myself being a CTO a CTO in
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a startup um the challenges that we had
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are very similar across startups of of
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um all sizes particular similar type of
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sizes so this this is very reassuring
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because uh especially those who are um
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you know first time start Toppers they
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may um feel like oh my God you know this
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is only happening to me I'm doing
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something terribly wrong um and then
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there's a lot of a lot of great ideas a
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lot of great practices that are being
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shared by the community by by by people
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um who are part of the community um in
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in in how to address certain challenges
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that that do come up um and some
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challenges you know you resonate very
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strongly with them because they did come
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up or are actually coming up in your
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company some maybe something that would
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happen in the future but you haven't yet
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experienced that but it's still
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interesting to learn about it um so it's
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it's it's really being part of the
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community and uh you know being part of
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the like-minded people and kind of uh
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being the support group to each other
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this is this is an absolutely free
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community for anyone to join and I
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definitely highly recommend there's
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always something new to learn um even
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though I've been I've been doing this
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for for for many years I'm I'm always
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fascinated how um you know that there's
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there's so much to learn more
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definitely and I see the benefits of
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that Community as that's what we kind of
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foster on SAS leaders lounge and even um
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with two previous guests we've had so
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far and I've kind of identified what was
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their main concerns in the first six
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months and they've always said that the
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sales and marketing part like you've got
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this AI engineering brain but being a
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part of a community can actually allow
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you to find resources and how to boost
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those actual year sales and marketing
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aspects that will really drive your
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business further in terms of the
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exposure needs within that time so I
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think yeah it's inspiring to see how you
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leverage external knowledge to fuel the
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Innovation at real eyes in the realm of
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AI we did touch on this slightly
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previously but where privacy concerns
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are Paramount how does Real Eyes
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navigate the ethical implications of
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emotion recognition
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technology yeah privacy has always been
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super important for us um we are working
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uh with facial data um and that is uh
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personally identifiable data um and we
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kind of recognize the sensitivity of the
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data that we're working with even before
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the gdpr came came into Force um and um
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so we just follow certain rules and
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principles such as um uh making sure
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that we are fully legally compliant so
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100% gdpr uh
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compliance we're we're making sure that
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um we're always asking for explicit
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consent so we don't um access camera we
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don't um record people unless people
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explicitly agree um so um we obviously
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uh uh pay a lot of attention to security
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of our systems um and uh you know think
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things like um you know ensuring s SO2
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compliance um and having external
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parties to review uh from time to time
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the infrastructure uh from the security
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point of view uh we do we do open
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ourselves to external audits um so by
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you know one of the big audit companies
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um so these are these are um some of the
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critical critical items I think one one
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important thing for us um also from the
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ethical uh standpoint is that the
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applications that we're working on and
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the applications that we kind of enable
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our technology for um has to be an
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explicit consent on applications so that
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means that uh we wouldn't agree to to
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the kind of
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applications where um this would be used
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in security cameras where people
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obviously haven't been haven't consented
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they don't have a chance to give a
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consent and this software would be would
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be runting sort of secret Seely um
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behind the cameras there so no so all of
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the applications are um by Design such
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that there there is an explicit consent
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before um the technolog is being
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used I think I'm prioritizing those
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ethical considerations is definitely
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crucial and commendable and it does
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sound like you're setting a standard for
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this as well but considering the rapid
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advancements in AI I think especially
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considering your solution there's a risk
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of bias or misinterpretation in
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emotional emotion recognition how does
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real address these
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challenges uh yeah this is also a very
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important uh part of our work so one of
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the um uh areas that we very seriously
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look at is fairness of our models um and
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there are uh some uh specific segments
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by which we um try to um uh pay special
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attention uh and these are age uh gender
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and where possible we're also looking at
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skin tone um and measuring the
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performance evaluating the performance
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of models by these
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Dimensions um and then trying to adjust
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our models to uh ensure that there is no
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bias or that bias is kept to um minimal
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minimal levels um so this is this is one
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one area that's that's really important
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for us um another one is is kind of
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connected to that is the robustness of
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models uh we're also trying to um make
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sure that the model Works across
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different kinds of devices and different
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kinds of um environmental conditions so
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if somebody is um using for example a a
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lower quality device that they they
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would they would not uh be prevented
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from using this kind of technology so
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that's why our data set uh contains uh
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um data that that's been collected in
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all all from all kinds of camera uh
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camera devices so that's um that's
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another critical critical aspect um of
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what we do then uh I also mentioned this
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context uh specific awareness so um it
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is uh so what we're measuring uh uh is
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actually facial
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expressions and how you interpret these
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facial Expressions is very much context
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specific so you know if somebody is
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smiling in in in a scenario where you're
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showing them a funny video you know
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might have um a different interpretation
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if if if somebody is uh smiling in in a
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scenario where uh maybe they're
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expressing a doubt um because of uh some
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information that's being provided to
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them that they don't believe in um so it
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is very want to understand the context
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in which technology is being used um and
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and that's something that obviously
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depending on the scenario and
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application Um this can this can be um
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uh a difficult difficult subject but
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that's something that's always at the
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top of our mind and we try to make sure
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that we bring that into the
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interpretation element as much as
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possible brilliant brilliant I think um
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your approach to as you mentioned the
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context or mitigating the bias is
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essential for the creditability and also
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reliability of um emotion AI but it's
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clear real eyes is committed to these
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ethical and kind of accurate technology
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departments and as we look ahead to the
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Future how do you see emotion AI
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evolving and what role will R eyes play
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and shape in this trajectory across
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various
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sectors well one area that we're
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particularly fascinated um in the
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development of emotion AI um is
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uh AI
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avatars um so um you probably have seen
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um a lot of AI or starting to see an
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increase in AI avatars appearing out
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there and that particularly started to
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happen uh with the launch of Chad GPT
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kind of uh
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models um there is um another type of
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technology that not many people are
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aware of yet but you know it's gradually
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increasing is um a human realistic uh
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avatars uh so where um avatars are being
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visually generated and they look like
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real humans but they're 100% generated
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and and so uh pairing these two
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technologies together human realistic
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avatars and chat GPT kind of models uh
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enables AI avatars AI assistants yeah of
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totally different level and our vision
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is that there's going to be uh more and
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more of such assistants um that are
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appearing in in different kind of um
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applications it's going to start with um
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probably um customer support so a lot of
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the customer support is going to be um
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you know these uh not very useful uh
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chatbots are going to be replaced with a
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lot more um human fre friendly avatars
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um and I think I think this is one area
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that um is really fascinating for
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applications of our kind of Technology
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um because these AI human realistic AI
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avatars when they're interacting with
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another person uh obviously they're
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going to be a lot better if they um if
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they are able to sense humans uh not
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only by what they're saying but also by
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their behavior are they um uh enjoying
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the conversation or they're being um
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unhappy about it are they even paying
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attention to the conversation or they're
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being distracted and doing something
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else or is it still the same person I'm
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interacting with or has the person
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walked away and now another person came
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in in front of uh the Avatar so so
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that's that's one area that we're
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particularly
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excited uh about um uh but in general I
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think emotion AI techn is going to
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continue developing more and more into
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forms of uh
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nonverbal uh forms of communication so
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recognizing more of the gestures more
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nuanced um uh uh types of uh behaviors
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and of course
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multimodality so that's that's taking
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many aspects uh or you know many sensors
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uh be it audio be it video uh be it some
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the contextual information po it all
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together to make an even more accurate
00:22:02
understanding of of us humans in the
00:22:04
during the interaction
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process brilliant and I really like the
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answer I I say I spoke to the founder of
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deep AI called Kevin Baragon and one of
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the questions for him was what's the
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misconceptions about the future in Ai
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and he's kind of clearly mentioned what
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you said people think that AI is going
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to be very robotic but in fact it's
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going to be very human realistic and
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very humanlike to allow us to to kind of
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trust and work together more effectively
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so it's great you've pinpointed that as
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well in your
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answer if you could perfect an AI system
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to read and respond to one specific
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emotion which emotion would you choose
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and why uh I would uh I would choose
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um that's a that's an interesting
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question I I maybe I have two answers uh
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uh to it one answer is um I would choose
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um positive emotion so a happy or a
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smile um and the reason being because um
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you know one of the things that that uh
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part of our mission is to bring more
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Smiles uh into the world so a trillion
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more
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Smiles um and um um but uh the the the
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happy emotion is something that we're
00:23:29
we're already able to uh recognize and
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read quite well um The Challenge uh
00:23:36
right now is more on the um the you know
00:23:40
the negative emotions the um not very
00:23:44
explicit subtle especially if somebody
00:23:46
is maybe um subtly depressed or kind of
00:23:51
in a in a in a in a bad mood um and of
00:23:55
course I'd like to invest in enabling um
00:23:58
the the technology to to understand that
00:24:01
better so we're we're able to um help
00:24:05
with the initiatives of uh um emotional
00:24:08
well-being and uh and that way bring the
00:24:12
trillion more Smiles uh into the
00:24:16
world I agree with myself probably um
00:24:19
would help a lot of relationships as
00:24:21
well in solving problems I think there's
00:24:22
a lot of real life problems that could
00:24:24
solve I must say and I'm a very smiley
00:24:26
person myself and I think it's clear to
00:24:29
see um the opposite but some people you
00:24:31
can't really tell the difference in
00:24:33
their emotions so yeah that's a game
00:24:35
changer now we're going to move on to
00:24:37
our light-hearted quickfire section just
00:24:39
so our listeners could get a peek into
00:24:41
the person behind the Innovation
00:24:43
yourself um would you prefer to never
00:24:46
have to work again or love your work so
00:24:48
much that you never want to
00:24:51
retire never want to
00:24:53
retire brilliant would you prefer to be
00:24:56
the best player on a losing team or the
00:24:58
worst player on a winning
00:25:01
team oo that's a tough one I would go
00:25:04
for worst player in the in the in the
00:25:06
best
00:25:07
team would you prefer um a rainy day or
00:25:11
a sunny
00:25:13
day can I have any
00:25:16
day I like I like both so that's
00:25:21
positivity I must say um do you prefer
00:25:23
investing or
00:25:26
saving investing
00:25:29
brilliant brilliant and we're probably
00:25:31
past the times now so but I guess it's
00:25:34
still right to us would you prefer
00:25:36
handwritten letters or
00:25:38
emails depends but I'll go for
00:25:42
handwritten yeah I guess it depends on
00:25:44
the
00:25:45
content perly and last two questions do
00:25:48
you prefer a museum or an amusement
00:25:56
park hard I'll go
00:25:59
for
00:26:01
Museum nice nice Definitely I guess you
00:26:03
can learn a bit his history through that
00:26:05
as well without the froze um are you can
00:26:09
be like amusement parks yeah I agree
00:26:12
with your to be honest especially with
00:26:13
if you're with the kids as
00:26:15
well yeah
00:26:17
definitely so do you prefer DIY to do it
00:26:21
yourself or hire a
00:26:24
professional
00:26:26
DIY perfect I did say there will be two
00:26:29
more questions but I'll fit one more in
00:26:31
would you prefer to own your own private
00:26:33
island or a private jet Private
00:26:37
Island definitely um that's interesting
00:26:39
I must say got brilliant answers there
00:26:41
we definitely got more of a glimpse into
00:26:43
yourself elor and as we like to keep the
00:26:45
collaborative nature on the podcast we
00:26:47
always ask a question from one guest to
00:26:49
another so our previous guest is a
00:26:51
gentleman called Amin Rabino he's the
00:26:54
founder of gandro AI and he's asked if
00:26:57
you wake up one morning and you see your
00:26:59
bank balance on zero what's the first
00:27:02
thing you would
00:27:04
do I'd start um I'd start uh devising a
00:27:09
plan of um how do I get out of the
00:27:12
situation so um I think it will consist
00:27:16
of um initially like emergency uh reach
00:27:20
out to friends and family um who I I'm
00:27:24
fortunate to have um who would help in
00:27:27
the term and and then start uh making uh
00:27:32
my way towards how do I um uh you know
00:27:35
start bringing some money in into the
00:27:37
account um so how did it happen that I
00:27:40
have a
00:27:41
zero yeah I guess the emergency fun will
00:27:44
definitely be needed first but yeah the
00:27:46
planning's the right way to go um so
00:27:48
what would your question be for our next
00:27:50
guest who's a gentleman called Dan gaina
00:27:53
um he's actually we founded a company
00:27:55
called kelp and now they've been
00:27:57
acquired by signal AI where he is also
00:27:59
resumed control but yeah what would your
00:28:02
question be for
00:28:04
him well my question would be for him as
00:28:07
someone who is working on AI is um what
00:28:12
is he doing about uh AI
00:28:16
safety uh and ensuring responsible AI um
00:28:22
development um I think this is an
00:28:24
important uh question for anyone who's
00:28:28
working on AI to to think about
00:28:32
definitely and as they say great minds
00:28:34
think Al because I already had that
00:28:35
question to ask him but I'll be sure to
00:28:37
remove my one replace it and put your
00:28:39
one as the question to ask him
00:28:41
definitely before we wrap up Ela are you
00:28:43
able to share where our listeners can
00:28:45
learn more about you your work and real
00:28:48
eyes sure um well I'm I'm personally not
00:28:52
a very public person just from the
00:28:54
personality point of view um I do write
00:28:57
some s uh or or share some of our
00:29:00
company updates on LinkedIn um and uh
00:29:04
generally you know all my work goes goes
00:29:07
into the um the realize that that uh I'm
00:29:11
working with a great team on and so all
00:29:14
the updates that we are releasing as a
00:29:17
company are the ones where I tend to
00:29:20
think that I'm also contributing
00:29:23
to Brant Brant I'll be sure to include
00:29:26
your information in the about us and
00:29:29
below the podcast video as well on
00:29:31
YouTube and also on Spotify and apple
00:29:33
but thank you so much elor for joining
00:29:35
us today on a SAS leaders Lounge podcast
00:29:37
and sharing your insights into the
00:29:39
fascinating world of emotion AI it's
00:29:41
been a truly enlightening conversation
00:29:43
especially to myself to our listeners
00:29:46
thank you very much for tuning in be
00:29:47
sure to subscribe to the SAS leaders
00:29:49
Lounge on your favorite podcast
00:29:51
platforms and not miss out on episodes
00:29:53
like this stay curious keep exploring
00:29:55
the boundaries of innovation and
00:29:57
Leadership goodbye for now thank you so
00:29:59
much for your time Ela take care
00:30:01
pleasure pleasure talking to you morning
00:30:03
bye-bye thanks
00:30:12
[Music]
00:30:19
byebye
