TVCNEWS — broadcast
20260808 090000 UTC
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[00:00:01] one can open the door to respect, sound, are you
[00:00:03] ready, and the other close it with
[00:00:07] fire, two perspectives, but one big
[00:00:12] of issue, are you good? yes, I'm good to go, so do
[00:00:15] we argue to fight or disagree to understand? three,
[00:00:19] two, one, real life, this is
[00:00:22] the
[00:00:24] of big.
[00:00:31] of of
[00:00:36] of in At TVs news, wherever the of big news stories happening, we're get up to
[00:00:37] of agg it, TVs news, first with
[00:00:42] of breaking
[00:00:42] news,
[00:00:49] of
[00:00:57] artificial intelligence is rewriting the gl. economic
[00:01:00] playbook, but while the west builds massive data centers
[00:01:04] and
[00:01:05] of silicon valley debates trillion dollar computations, a
[00:01:09] of quiet revolution is taking place right here in the African
[00:01:13] of continent. hello and welcome to technifire i
[00:01:17] of am, today we're mapping
[00:01:20] in out the rise of African AI, opportunities, challenges
[00:01:24] and the road
[00:01:24] ahead.
[00:01:30] of Nigeria stack ecosystem
[00:01:34] has crossed major
[00:01:36] of valuation benchmarks driven by booming fintech and
[00:01:40] digital
[00:01:41] of infrastructure.
[00:01:42] of Nigeria of has killed its 3 million technical
[00:01:46] talent initiative to position the country as major
[00:01:50] exporter of tech skills, strict safety,
[00:01:55] of transparency and bias audit compliance
[00:01:57] of
[00:01:59] of of rules are now legally enforced. for global tech firms,
[00:02:03] nextjen AI has moved beyond pattern margin
[00:02:06] to system to
[00:02:08] of agentic reasoning for complex problem
[00:02:11] solving. medical regulators have approved the
[00:02:14] first fully autonomous AI
[00:02:17] of systems to
[00:02:19] of independently diagnose medical conditions. tech giant
[00:02:23] have deployed small modular
[00:02:26] of reactors to meet massive AI computer energy demand.
[00:02:30] of of multi billion dollar investment have searched into
[00:02:34] local
[00:02:35] of sub-sea cables, data centers and regional AI
[00:02:39] computer
[00:02:41] of apps.
[00:02:46] to help us navigate the metrics, we have guest who lives
[00:02:50] of exactly at the intersection of business strategy and high
[00:02:53] impact machine learning. he has over
[00:02:57] six years
[00:02:58] a of of
[00:02:58] of experience building financial and analytics
[00:03:00] of models has trained nearly 3000 data
[00:03:04] professionals worldwide and is taking
[00:03:07] African grown ar research all the
[00:03:11] of way to the University of
[00:03:12] of Cambridge this
[00:03:14] of year.
[00:03:15] of Please welcome data scientist, lead analyst and AI
[00:03:18] researcher David Balugu. David, good to have
[00:03:22] you. Let's get to meet you, who exactly is
[00:03:26] David. I
[00:03:27] of did of a little bit of introduction of you, but let let's hear. from the horse's mouth, who is
[00:03:31] David? yeah, thank you so much for that question, yeah, see
[00:03:34] David Balogon,
[00:03:34] it's um, I've been in the data space for a couple of years and have the opportunity of
[00:03:38] working
[00:03:39] of across the fintech space, the tech
[00:03:41] of a space, renewable energy space and couple of other sector within the
[00:03:45] tech industry and outside of my
[00:03:47] of of work typically I'm also AI researcher and
[00:03:52] of I have couple of you know amazing paper I've written and you know some are
[00:03:54] of you for publication yet and some are still yet to be published and outside of my work
[00:03:57] also I'm also into mentoring and coaching. and
[00:04:00] i h the opportunity of you know mentoring and coaching over a couple
[00:04:04] a of two 3ous people across africa and across you know the
[00:04:07] global large basically i'm also someone who is driven by
[00:04:11] impact also right so most of what i do by getting to
[00:04:15] you know mentor and teach and tut people within a data space it's just born from the place of
[00:04:19] making impact here basically you build predictive
[00:04:22] of cash flow models for fintex and also
[00:04:26] of AI that can detect crop or diseases
[00:04:30] so tell us about it, so one
[00:04:31] of the first um fintech company had to work with one
[00:04:34] of the major because
[00:04:35] of the
[00:04:36] a kind of business we do that because it was peculiar to um disposing of cash so we
[00:04:40] have to build like
[00:04:40] of a model which can help us predict the accuracy
[00:04:42] of the disborsment and help us you know predict the accuracy
[00:04:45] of the pit back time of our customer right so we don't get
[00:04:49] of to over this b and we don't get to you lose money or we don't get to lose our return
[00:04:53] on the money so after putting the model into perspective to you make
[00:04:57] accuracy and may to make exact disbosement and know what our
[00:05:01] return on interest is going to be and it was very amazing and you know that was just it
[00:05:05] basically and also for the
[00:05:09] of um crop disease stuff i think couple of years ago two the years ago i was speaking to a
[00:05:11] of friend and he had major project project was working on at that time so he was trying to
[00:05:15] build something around crop dictation that is just a bit about deep
[00:05:19] learning right so maybe to use images to dictate diseases
[00:05:22] across
[00:05:23] scr and youside the conversation we had like a project to work on it took us
[00:05:27] like two the months and after then recently had a conference i was privileged to
[00:05:31] write about
[00:05:32] you know being able to track diseases with c images and all that using
[00:05:36] deep learning right and one the major thing we did basically was to you know put
[00:05:40] that into a research perspective and put it into a practical approach so what do mean by
[00:05:44] that? so farmer a small scale farm can make use these
[00:05:47] applications to you dictate crop diseases and also
[00:05:50] mitigates r against it know well that the word
[00:05:54] basically leaves on food right so i don't have to go to farm you don't have to go to
[00:05:58] farm but we literally eat and we get our food phogies from the
[00:06:02] farm right so that and about 40%
[00:06:06] of farm food is are being um disrupted because of this
[00:06:09] sp and all that in the farm how did you move from? to
[00:06:13] agriculture, yeah, so I would say the whole context is
[00:06:17] about problem solving right, so what problem are you able to solve, when you're able to solve
[00:06:21] problem, you would have money would come which ultimately star to value right, so
[00:06:25] everything at the end the day is just bottling down to problem solving and food is
[00:06:29] major in as much we are all in the old AI of ten
[00:06:32] ecosystem, food isn't a major problem or
[00:06:36] major solution right, so having like a right
[00:06:39] solution towards it, having like a putting a proper infrastructure towards it, i think we
[00:06:43] would have reduced number of disruption to our plant produce and
[00:06:47] all that basically, so it's just decision of trying to solve a
[00:06:51] problem right, you convince a farmer in the village
[00:06:55] that using application can help
[00:06:58] him to prevent crop diseases, so when you speak to average
[00:07:02] farmer most times they will tell you and from the research we did right, did
[00:07:06] and for the paper the conference i spoke about in university of one the
[00:07:10] major issue we saw was that 40% of farm food is being destroyed
[00:07:14] right, that is a yearly basis across west africa and east africa and
[00:07:18] africa at large right, so 40% of 50% and for it
[00:07:22] to be destroyed that means they've kind of putting lot of work to
[00:07:25] you know trying to plant and trying to water it and taking it
[00:07:29] to a particular point in time and everything just goes over so one the major thing we are selling to them
[00:07:33] is problem we are trying to solve x y z problem for you right so if i'm coming to you you
[00:07:37] have this problem i'm trying to solve it and also make it economical for them right it's something they
[00:07:41] will buy into basically at the end the day,
[00:07:43] in as much you still have instances of um best
[00:07:47] distruction, but at least it should be a very reduced and control rate
[00:07:51] right? so if you are planting let's say 100 100 crops
[00:07:55] and let's say 40% or 50% have been destroyed because of
[00:07:58] fampest, it's not a good business deal and no one is going to be
[00:08:02] willing to invest in the agricultural space right, so when those problem are
[00:08:06] being solved right, we would then open way for investors to keep coming
[00:08:10] into the agricultural space. tell me about your trip to the
[00:08:14] university of ibado, what did you take from there? first conference,
[00:08:18] international conference of competing university of ebado right, so the paper we
[00:08:22] delivered was trying to solve corb diseases right, so using deep
[00:08:26] learning to solve corp diseases, so one the major takeout there was the
[00:08:29] problem is being recognized, there is a problem of cop diseases, so trying to put
[00:08:33] it out there into implementation, so that is where we are moving towards now, right should
[00:08:37] trying implement it out there and making sure everyone is fully about is fully
[00:08:41] aware about this solution right and trying implement it to their businesses so that was the major
[00:08:45] thing,
[00:08:45] it was very fantastic conference we spoke about and it was very nice because we
[00:08:49] saw a couple of other problem,
[00:08:52] you know people are trying to peach some other problem to their research paper and all that and yeah
[00:08:56] just showing full that the african ecosystem is also coming to the center
[00:08:59] the world right we are not left behind in
[00:09:02] the in the whole conversation of um data and technology
[00:09:06] so which these two worlds actually represents the future of tech
[00:09:10] in Africa uh fintech or that's a very nice
[00:09:13] question i would say fintech currently have like um would i
[00:09:17] say a track record of doing so well right the ag pace is still very
[00:09:21] evolving i would say right so in as much you would give credit anacoly to
[00:09:25] the fintech space and one other thing we should not forget to
[00:09:29] mention is there a lot of investment going into the fintex space so in as much there was
[00:09:33] being a little slow sloopy investment
[00:09:37] you know investment willingness from investor to invest in the
[00:09:40] fintech they've had lot of... investment over time right and compared to the
[00:09:44] greek space, one thing i would say again is uh in the agreic
[00:09:48] space there should be need for you know investors to coming into the space but
[00:09:52] because of some the issues they
[00:09:53] are noting to come so i would say fintech is going and you know it's doing
[00:09:57] well but if opportunity has been given to the quick speech would also have
[00:10:01] during the coming years i would say your edge
[00:10:05] AI research is going to cambridge this i know you're
[00:10:08] excited so tell me about it yeah
[00:10:12] um so we worked on data collection um pipeline right so
[00:10:16] for computing cloud computing and also internet of it right
[00:10:20] so shout out to my quarter i have three quarter one the
[00:10:24] quarter to be a professor um of AI system in
[00:10:27] honoBC OnBC
[00:10:29] on banja university and two the other couple guys um working on the project with
[00:10:33] me right so what we are trying to solve is data collection process right
[00:10:36] so there is this conversation of data is not properly well collected
[00:10:40] in Africa right so because of some abnormally so we are trying to correct
[00:10:44] that so also trying to collect the data and showing like there's a proper cloud
[00:10:47] infrastructure right in putting in the data into
[00:10:50] implementation so that's what the paper is all about and it's going to
[00:10:54] be conference when you present this paper, so what's the the
[00:10:58] biggest misconception about Africa that you want to shutter? yeah, so I
[00:11:02] think one the major issue going to be around data collection system or not having like a
[00:11:06] proper centeric means of collecting data, so there is this might african
[00:11:10] k keep data, and as much that is 100% true right, so I think they've been
[00:11:14] some new regulations across some countries in Africa right, so when you look
[00:11:17] at like of Kenya and what's the minister of digital technology
[00:11:21] is doing in Nigeria yeah right, so you've seen the have been a kind of improve
[00:11:25] in the means of collecting data, but in as much is not 100% accurate, i
[00:11:29] would say or 100% reliable, they've been intentional
[00:11:33] effort towards it, so that is one the minds are trying to correct that
[00:11:37] AI infrastructure can can can come into Africa and they can really
[00:11:41] do well if you have the right data and that's the mind we are trying to correct or shutter basically
[00:11:45] a constrained a resource constrained environment
[00:11:48] like power and internet how possible can that be
[00:11:52] yeah that's
[00:11:52] a major issue i would also say so one the implication of that is
[00:11:56] it can kind of slow down the pace of air across africa right so think
[00:12:00] i saw a post recently someone was complaining that she walks for one
[00:12:04] customer care successful but guess one these company in the US or
[00:12:08] eastern western world and
[00:12:10] you know they have to lay off because of internet right so something as simple as internet
[00:12:13] can be so frustrating right and i'm sure every one of us have our own
[00:12:16] fair um fair of that basically so one the major issue will
[00:12:20] be having is internet connection and also lights right we know how light can
[00:12:24] be of nigeria and i think there's a vcent development
[00:12:28] or solar and to ver extent some people
[00:12:32] cannot afford it right because the old heavy investment and
[00:12:34] there are a couple of guys doing a bit of
[00:12:36] you know pay buying now pay later but in as much to sustain in places
[00:12:40] if we don't um tackle the basic issue of internet
[00:12:43] right and also making it affordable to people right so in as much you would say
[00:12:47] there is internet and it's good sometimes is not affordable to people right so you have
[00:12:51] person who is trying to do the remote job about probably spent
[00:12:55] chunk the money trying to buy internet and after buying it you still have to struggle with
[00:12:59] having like a good connectivity right
[00:13:01] so what that would do basically just to slow the pace of air across
[00:13:04] africa and nigeria as a whole so if you can talk those two button like right
[00:13:08] so we can start leveraging on
[00:13:11] that and start building basically you've trained 300
[00:13:14] data professionals what's the biggest mistake an
[00:13:18] African uh an African that wants to learn data what's
[00:13:21] the biggest mistake they make uh when enting to that field
[00:13:25] one the major mistake i've seen people make in general it's they want to start learning the
[00:13:29] big thing and i also did that mistake i can remember vividly a couple of years ago
[00:13:33] i was talking to a mentor of mine is a partner now at pwc so
[00:13:37] told him i was moving to the dat analytical space and he had me kind can you
[00:13:41] use excel in my head i'm like i'm learning python i'm learning pandas
[00:13:45] nopi machine learning what do need excel for but luckily enough i
[00:13:49] stumbled a video by someone and reached out to her for advice and she told me to
[00:13:53] go back to the basics right to learn the basic stuff, so
[00:13:56] most the mistake most people make most times is they want to start learning the
[00:14:00] big stuff and leave the basic right, and most times you need to learn the basic before you
[00:14:04] go into the add stuff, so for instance you want to build the house, you can't start putting the
[00:14:08] roof in right, you have to start from the foundation right, you have to put the blocks and
[00:14:12] make sure they are well cemented right, so make sure you're doing the underground work,
[00:14:16] make sure you are learning the basic stuff and you can start building from there, so when
[00:14:19] coaching uh students across the world across all the continents
[00:14:23] because I know you've trained. uh across uh the continent,
[00:14:27] what's the biggest advantage an African has over
[00:14:31] these people? so I would say from a place of pain and frustration right, so I've had
[00:14:35] instances whereby some of my students will tell me um they having issues with
[00:14:38] lights, no internet connectivity, sometimes you just have to
[00:14:42] understand them and you know you in this position at some time right, maybe just
[00:14:46] send them money to get um you know data and all that
[00:14:50] right, so most them take it from a position of pain right, I don't
[00:14:54] like this my presence. situation all the respect to the folks in the western world
[00:14:58] right, they have all this infrastructure, light, internet right,
[00:15:02] so they just have this kind of child mindset of that me just learn,
[00:15:04] but someone from Nigeria or African is coming from a place of
[00:15:08] pain right, so they are ch you are using your pain right, you are changing your pain
[00:15:12] to a good story right, so that is one the advantage they have over
[00:15:16] them, are we really being trained for local impact or just to pass
[00:15:19] remote jobs, the two works and in hand, so there have been a
[00:15:23] vcent debate, i think you are probably tos in um team
[00:15:27] are it app um moneypoint CEO he was saying something about talent and all that right so in as
[00:15:31] much you saying pass remote job it should have impact also right no one would
[00:15:35] want to h someone who do not have value right so both work and hand
[00:15:39] basically so make sure you have impact and make sure you're also chasing the money right,
[00:15:43] chasing the good job right, for one major thing i would see most times is most people are
[00:15:47] gradually moving towards the remote job because it makes your life
[00:15:50] comfortable, you stay
[00:15:51] at home, but at the end of it we are leaving the important part
[00:15:55] right, the important part of trying to build locally made stuff for ourselves across
[00:15:59] africa, silicon valley assumes everyone around there has problems with
[00:16:03] internet and problem with power, so to break through with...
[00:16:07] in this part the world, in this continent, africa, what's the first thing to
[00:16:11] break, mean to do? so yeah, the first thing we have to do, i think we spoken a bit
[00:16:15] about
[00:16:16] it is to solve the basic problem, right? so i'm taking it back to the question you
[00:16:20] asked me about the mistake most people make when they stand trying to
[00:16:23] make start the journey out the data scientist, one the major mistake i said
[00:16:27] was they don't want to learn the basic stuff so we have to fix the basic
[00:16:30] issue basic issue like light light light issue we have to
[00:16:34] fix it internet of it in right we have bad internet. you have to fix
[00:16:38] it, make it also affordable for people, right? i was speaking
[00:16:42] to a friend of mine, that person was telling me when you buy
[00:16:46] internet in their place in the western world right, they use it for a month, it
[00:16:49] doesn't unlimited, but when you buy unlimited here in Nigeria with all you respect, it's
[00:16:53] not even unlimited, you get
[00:16:54] what i'm saying right, one the major thing we have to fix is our data center, three
[00:16:57] issues are being fixed, you would see like rapid growt in our air
[00:17:01] ecosystem, so data sovereignty, we must
[00:17:05] have our own data, is that what you're saying?
[00:17:07] do you believe in sovereign data? i think last year i spoke at
[00:17:11] pycon a python conference, one the topic i spoke about
[00:17:15] was data sovent who really own the data of africa right? so one
[00:17:19] the major thing or one the major highlights i'm just going to retate on that is let's
[00:17:23] try and lokalize our data let's try and build for africa in in africa right
[00:17:27] we are not building for africa in the western world we are building for africa in africa right so i want to
[00:17:31] build the products a product that someone in ubumoshore can
[00:17:34] actually use right and that's one the major issue we have. so i'm going to give
[00:17:38] a quick illustration now right so when you use some of this ai to when i
[00:17:42] say um money now europa money means o
[00:17:46] right that's a th letter word and there's a place in indo state that is
[00:17:49] awo right so we have instances of that that's where i'm
[00:17:53] from oh right yeah i'm from some around there too right so we have on that
[00:17:57] place - right so still the same letter
[00:18:01] word but different pronoization right so sometimes when you look at this ai
[00:18:05] um tools or stuff the really can't get
[00:18:09] what we mean by this, they just generalize it most time, so we have to build ai for
[00:18:12] ourselv right, so data sovereignty has to start with us, we have to localize our
[00:18:16] data right, so making sure everything has been put into context
[00:18:20] right, so we are not leaving anything out for the western world to develop for us and
[00:18:24] then we ship it back, all the respect everyone doing a bit of data notation, you
[00:18:28] see companies areing data people to do a bit of data notation for them and all
[00:18:32] that, but we have to start localizing our data, we have to own our data,
[00:18:36] and one the major challenge have i was speaking to couple of um my
[00:18:40] um ment couple of months years back i think last
[00:18:43] year the lady was from kenya oround that she was talking she raised the question around
[00:18:47] this and one the major concern she said again was something
[00:18:51] around trying to assets data right try to access data is a
[00:18:55] bit hard and you recently ce of ch was talking about how they
[00:18:59] are using data to make decision how people will order for chicken in the first week so that's a very
[00:19:03] powerful inside the are sitting a lot of data right so this data have to be made
[00:19:07] public to for um for individuals to make decision
[00:19:10] and there is a b of data privacy of people not wanting to release their data because some people would
[00:19:14] do x right but if for every place there's a rule there's always
[00:19:18] regulation right and there's always a punishment right so i feel we should have more
[00:19:22] or less like and this appeal
[00:19:23] to the government right we should have like our data being made available for public use right
[00:19:27] for right use not for any fudulent or whatsever use right and
[00:19:31] anyone that has been cut in cut in the out of trying to use for something that is not rightful the
[00:19:35] person is being dealt with right so if that is being are good, we can start building for
[00:19:39] Africa in Africa right, so
[00:19:41] we don't have to shipping what is being built by the western one to Africa because they are not
[00:19:45] 100%, they don't fit, they don't fit what we are trying to do basically
[00:19:49] right, we are just using it, but it doesn't 100% fit in for the Africa
[00:19:53] ecosystem, one of that thing I'm going to say is in Nigeria we have over,
[00:19:56] I'm not entirely sure, but I'm sure we have over 20 to 30 languages right,
[00:20:00] so different languages, and when you go to the eastern um African
[00:20:04] for instance, more than yeah, when you go to eastern African you see. you see different type
[00:20:08] of languages, different type of culture, so we have to build air that can actually
[00:20:12] understand who we are, right? who we are, our
[00:20:16] problem, and from there we can make start making impacts globally,
[00:20:19] and as we own our data, we should own our tech
[00:20:23] also, definitely, and we on this show, we we we claim
[00:20:27] for sovereign innovation, mvps to
[00:20:30] mvps, we look at our technology or
[00:20:34] speaking our language, do you think we ready cuz I'm still
[00:20:38] on the move looking for intelligence that are native
[00:20:42] uh tech that speaks our languages do you think we're ready for we are actually
[00:20:46] ready for it one the major block I would say is maybe founding.
[00:20:50] right so for you to build um ai um product
[00:20:54] that
[00:20:54] is well used that people use you have to have quite a number of money right resources
[00:20:58] right um there
[00:20:59] was
[00:21:00] guy accident i think he built a product right in 20 yeah
[00:21:04] youngbit right so it scared
[00:21:06] to very i think um blue chips um um acquired it and all that
[00:21:10] right so we have folks building stuff when you go to your lag
[00:21:13] you see their the
[00:21:15] i think they have up right yeah innovation up the build stuff there right
[00:21:19] so we have guys doing stuff, but one the major issue we have is founding
[00:21:23] right
[00:21:24] and
[00:21:28] yeah d you like right so we have folks doing stuff
[00:21:32] but one the major issue we're having is funding right there is no funding and there's no government
[00:21:36] intervention i would say again right so when you are building most times people need
[00:21:39] govern government intervention right so government intervention is some areas
[00:21:43] of data collection to right you can actually build the model to be 100%
[00:21:47] accurate or let's say 90% accurate or 9 5% accurate if
[00:21:51] you are not actually fitting it with the right data set right and those
[00:21:54] are the issues some these guys are facing over there but the big question is is
[00:21:58] africa ready for the global AI race we are ready right if
[00:22:02] this issue being mentioned are being fixed here we are 100% ready for the AI race
[00:22:06] and we've been seen a bit of implementation towards that and a bit of product
[00:22:10] or a bit of services that have been launched that have been AI driven right so we are 100% ready
[00:22:14] for it we just need to put some check in place some checks in
[00:22:18] place right to make sure that it's been done fintech, agritech
[00:22:21] or logistics, where will the real
[00:22:24] african first african unicorn come from from
[00:22:28] these three? fintech um is like the big brother to every every
[00:22:32] other sector, let's be honest, fintech is like the big big brother, so fintech has been
[00:22:36] doing well right, so i think it's most likely come from
[00:22:39] fintech or maybe very
[00:22:42] very, i think fintech to be honest right, that is
[00:22:46] fully of that because the every investment in fintech the lot of... innovation that is going
[00:22:50] on into fintech right and recently i think pas launched a
[00:22:54] product where you can just chat they have a chat box you can chat the
[00:22:58] boss you want to make a transaction it's going to run it for you you want to please an order
[00:23:02] on child you want to do x y z right so i think it's going to come from
[00:23:06] fintech basically and that's because the infrastructure and the road
[00:23:10] map um fintech has already and now to matter that
[00:23:14] concerns everybody the brain drain the jakwa syndrome
[00:23:18] is it affecting us are we? training people for
[00:23:22] the world or or what do you think? one the major
[00:23:25] issue we have most times when people get to leave the country is the
[00:23:29] ecosystem right is not encouraging and outside of one the major influence again is pear
[00:23:32] pressure right so when you see someone - maybe you're working a
[00:23:36] project to someone person is telling you oh i'm going on vacation to
[00:23:39] grease and you're literally maybe you know this
[00:23:43] person is not quoton quote is not literally better than you
[00:23:46] just um what you call a limitation of government like
[00:23:50] person is telling i'm going on vacation to grace like you can't even take like you can't
[00:23:54] fly from legos to abuja for five days and stay in the five star hotel your
[00:23:58] bank your bank um what is it called account will be crying right so
[00:24:02] these are some the issue right we have the peer pressure issue and when when they feel they are good
[00:24:06] they apply for international job and most times you actually do get it right
[00:24:09] so it's just b down to the ecosystem and the the
[00:24:13] development the country we since uh we keep having people
[00:24:17] moving out the country because of this ch syndrome and the way other
[00:24:21] country are opening their door for talent right, so it's it's going to be very
[00:24:25] big opportunity for most people to leave, but if you can fix our issue
[00:24:28] predominantly, we would have lot of jakwad right, and most the jakwad are
[00:24:32] always coming with the innovative idea, and for you
[00:24:35] to jakwa that you must have jakwa and you must have maybe seen some one or
[00:24:39] two places to make improvement for in Africa and you would come back to your country and start
[00:24:43] making
[00:24:44] the innovation, yeah exactly three words,
[00:24:47] what's the biggest lie? have been told about AI in
[00:24:51] africa so i think the biggest line they told us about africa um
[00:24:55] AI basically is african don't collect data we
[00:24:59] don't collect data i think that's like biggest and i'm saying that because for you to have a
[00:25:03] good ai system or machine learning model
[00:25:07] whatsoever you have to have a good data what you call collection process right your data has
[00:25:11] to be accurate so i think that is one the biggest line
[00:25:13] to the african don't collect data and as we random
[00:25:17] award for someone listening today a word of motivation,
[00:25:21] someone that wants to be like you, but wondering maybe okay, maybe you
[00:25:25] were born with silver spoon,
[00:25:29] okay, so or basically a word for them a message, so i think
[00:25:32] resilians keep building, just keep building, that's the honest,
[00:25:36] anything you are doing, just keep building and be being optimistic right, so you might not
[00:25:40] get it right now, but just keep building and also have right set of people
[00:25:44] around you to inspire you and to guide you right, or just keep building anything
[00:25:48] you're doing regardless of even not even in the tech eco system, anything you're
[00:25:51] doing, just keep building, making sure you're building and you're building, don't be tired, it gets
[00:25:55] tired, and one other thing i would say again, think i had it from someone one time is
[00:25:59] you know when you are in the gym you are tired, you tell yourself let me just go... more
[00:26:03] right, let me just push one more, just that one more try can actually be
[00:26:06] like we defining moment right, just that one more push, let me
[00:26:10] just push one more time right, you can be tired, but let me just do this one more
[00:26:14] time and that might be where your results will be, no pain, no gain, no pain, no gain,
[00:26:18] yeah definitely, so so lastly uh, what's
[00:26:22] next for you, i know Cambridge is later this year, so what's the big thing
[00:26:26] again you working on,
[00:26:27] yes i have couple of other research paper i'm working on, one is supposed to be on the 10th international
[00:26:31] conference um a artificial intelligence in London, um another
[00:26:35] one internet of teams in Parkok University with the partnership the university
[00:26:39] in I think Manchester, so two of those people are actually being out
[00:26:42] there, but we are yet to get a responder feedback from them, but hopefully we would
[00:26:46] get and and one of my go again also is to make sure we have like lot
[00:26:50] of African researcher right, so predominantly building and
[00:26:53] researching for Africa right, and we can also leverage on that to um push Africa
[00:26:57] on the global map for AI basically, so thank you so much David
[00:27:01] pleasure is my... Thank
[00:27:02] you so much, thank you for showing us that the road to
[00:27:06] the African AI is not only full of opportunities, but
[00:27:10] paved with codes, yeah, thank you so much, and good luck representing the
[00:27:13] continents, thank
[00:27:16] you so much, thank you so much, the take away today is
[00:27:20] clear, African AI shouldn't try to copy the blueprints of
[00:27:24] western tes, the true power of innovation lies in
[00:27:28] constraint driving engineering, building lightweight high
[00:27:32] in
[00:27:32] at systems that work flawlessly where infrastructure is
[00:27:36] tough and that's our package today, i
[00:27:39] am keep innovating
[00:27:43] and see you next time on technique
[00:27:45] fire.
[00:28:25] I ride to request the kind approval the national
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[00:29:26] News. the
[00:29:30] Inspector General of Police has met with senior officers to review the state of
[00:29:34] security,
[00:29:39] we are continuing a coverage the rest of
[00:29:42] godwin
[00:29:43] and
[00:29:47] the senate has summoned the governor the central bank of nigeria to
[00:29:51] properly brief the senate regarding the state the
[00:29:55] economy.
[00:30:02] Let's now bring you more development from ibadan the year state
[00:30:05] capital where an explosion has taken place, tell us about this
[00:30:09] incident.
[00:30:13] TVC news, first with breaking
[00:30:16] news.
[00:30:22] At TVs and wherever the big news stories happening,
[00:30:25] we're get up to aggregate. News, first
[00:30:29] with breaking news.
[00:30:50] cardinal state government believes health care is central to human capital
[00:30:53] development, that is why governor Ubasani has
[00:30:57] placed it at the heart of Kaduna state development agenda for the
[00:31:01] Ubasani administration. Strengthening healthcare delivery is more than a policy.