Morning Edition: 21st November 2023

CCNTV6

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Transcript

00:00:00 (upbeat music)

00:00:02 - And a very special good morning Trinidad and Tobago

00:00:07 and the rest of the world.

00:00:08 I'm Marlon Hopkins and welcome to the morning edition.

00:00:10 I know the set is looking a bit different this morning

00:00:14 and that's because we are at the Hyatt this morning

00:00:16 for the UN's Big Data Forum 2023.

00:00:20 But all the same, thank you very much for joining us.

00:00:22 I hope that you had a very good night.

00:00:24 So this morning we are going to be really discussing

00:00:28 what is in store at the Big Data Forum

00:00:31 and we are also going to be speaking about technology,

00:00:35 AI, robotics, you name it,

00:00:37 we are going to be speaking about that this morning.

00:00:40 But let me just tell you a little bit

00:00:41 about the Big Data Forum initiative.

00:00:43 So originally it was conceptualized in 2019

00:00:47 to create an environment that fosters research,

00:00:50 promotes discussion, strengthens partnerships

00:00:53 and advances strategies for harnessing

00:00:55 and integrating big data

00:00:56 as part of official sustainable development statistics.

00:01:00 Now the forum was originally proposed

00:01:02 as a two-day physical conference in Trinidad and Tobago

00:01:06 that brings together branches of government,

00:01:08 academia, civil society, business groups,

00:01:11 youth and the private sector to examine new methods,

00:01:14 tools and ideas and better understand the issues

00:01:17 to make effective use of big data

00:01:19 as part of the local data ecosystem.

00:01:22 Now the forum will act as an innovative change driver

00:01:26 and reinforces the importance

00:01:28 of high quality statistical services across the Caribbean

00:01:33 and key participants from across the region

00:01:35 will be invited to attend.

00:01:38 Now the objectives of the forum are to one,

00:01:42 create an enabling environment

00:01:44 that brings together all stakeholders

00:01:46 in the data value chain to exchange ideas and experiences,

00:01:50 innovative data practices and present case studies

00:01:53 and research on the harnessing and effective use of big data

00:01:57 to create public value.

00:01:59 And two, to explore the opportunities of big data analytics

00:02:04 and examine how the use of new and innovative data sources

00:02:08 and other data generated

00:02:09 outside the official statistical system

00:02:12 can be incorporated into mainstream statistics.

00:02:16 And three, to strengthen data partnerships

00:02:18 and collaboratives among stakeholders,

00:02:20 including youth to expand big data research and usage

00:02:25 and to expand big data projects and citizen generated data

00:02:29 through increased private sector investment mobilization.

00:02:32 So a lot is on the table this morning

00:02:36 and we are going to be discussing it extensively.

00:02:39 It's going to be, I suspect an education for a lot of us,

00:02:44 but it comes at an opportune time, at a great time

00:02:47 because of all of this talk about AI

00:02:52 and the concerns about AI.

00:02:54 So I suspect we are going to flesh that out today

00:02:58 and really give a bigger picture, a holistic picture

00:03:03 as we discuss AI in Trinidad and Tobago

00:03:07 and as Trinidad and Tobago gets ready for AI.

00:03:12 So again, we are at the HIRE today

00:03:15 and we are at the UN's Big Data Forum 2023.

00:03:20 All right, so we invite you to stay with us.

00:03:24 We are going to a very short break.

00:03:26 We are coming back.

00:03:27 (upbeat music)

00:03:44 ♪ We cannot take when they so ♪

00:03:48 - We are at the HIRE this morning

00:03:52 at the UN's Big Data Forum

00:03:55 and we are going to get right into the program this morning,

00:04:00 the day's proceedings as it were.

00:04:03 Allow me to introduce at this time,

00:04:06 Mr. Kishan Kumar Singh and Ruana Haynes.

00:04:10 All right, so these are my first guests.

00:04:13 Now, Mr. Kumar Singh is head

00:04:14 of the Multilateral Environmental Agreements Unit,

00:04:17 Ministry of Planning and Development.

00:04:19 He is an experienced environmental diplomat

00:04:22 and a prominent figure in the field

00:04:24 of international climate change negotiations and policy.

00:04:27 With a distinguished career spanning several decades,

00:04:31 Kishan has earned a reputation as a visionary leader

00:04:34 and influential advocate for climate action.

00:04:37 Mr. Kumar Singh, good morning

00:04:39 and thank you for coming this morning.

00:04:41 - Good morning and thank you for having me.

00:04:41 - And let me just tell you all,

00:04:44 this is just a little snippet of the gentleman's resume.

00:04:49 So just to tell you that,

00:04:50 we do have Ruana Haynes,

00:04:53 senior legal advisor at Climate Analytics.

00:04:56 Ruana is an international climate law

00:04:58 and governance specialist and TEDx 2020 speaker

00:05:02 with over a decade of experience in the UN climate process.

00:05:06 A former Trinidad and Tobago diplomat,

00:05:09 Ruana has negotiated for the Caribbean community

00:05:11 as well as the Alliance of Small Island States.

00:05:15 Ruana, thank you very much for coming this morning

00:05:17 and that's just a snippet also, all right?

00:05:20 So let's get right into what we have to discuss this morning.

00:05:24 So what role do you believe the Caribbean region

00:05:27 plays in international climate discussions

00:05:30 and having been deeply involved in the UN climate process

00:05:35 from your respective roles and positions,

00:05:38 are the concerns of small island states

00:05:40 adequately represented and addressed in these forums?

00:05:44 - Well, the Caribbean region is characterized

00:05:48 by small island states and low-lying coasts.

00:05:50 So that makes it very vulnerable

00:05:53 to the impacts of climate change.

00:05:54 And therefore the voices of the Caribbean

00:05:56 need to be heard globally in terms of what needs to be done

00:06:00 to address climate change.

00:06:02 So the Caribbean community, for example,

00:06:03 has been advocating over the years

00:06:06 for very stringent and strong action on climate change

00:06:11 to prevent any adverse impacts

00:06:15 that will undermine developmental objectives

00:06:17 in the Caribbean, for example.

00:06:19 The Caribbean region negotiates internationally

00:06:22 through the Alliance of Small Island States.

00:06:23 And we have been very influential over the years.

00:06:26 We have, for example, in the Paris Agreement,

00:06:29 true advocacy by the then Minister of Environment

00:06:33 of St. Lucia for getting in the 1.5 target

00:06:38 in the Paris Agreement when it was being set at two degrees.

00:06:42 Now you only hear about 1.5,

00:06:44 you don't hear about two degrees anymore.

00:06:46 So the Caribbean region and its voices have been heard

00:06:50 and continue to be heard as we advocate

00:06:52 for strong action on climate change.

00:06:53 - Yeah, and before I go to Rwana,

00:06:56 I think that there may be a perception

00:06:58 because countries are so small

00:07:02 that our voices are small too.

00:07:05 And there is a concern of how serious,

00:07:08 when we speak, how serious we are taken.

00:07:14 - But there is strength in numbers.

00:07:16 Under UN negotiating normative rules,

00:07:19 every country has the same voice.

00:07:21 So the largest and most developed OECD country

00:07:24 has the same voice as the least developed

00:07:26 island state, for example.

00:07:27 And under that premise, I think we have taken advantage

00:07:31 of that approach to let our voices be heard.

00:07:34 So there's strength in numbers

00:07:36 and the Alliance of Small Island States, for example,

00:07:39 collectively takes the views of small islands

00:07:42 and CARICOM region into consideration

00:07:45 when we advocate and we negotiate at an international level.

00:07:48 And we have been largely successful

00:07:50 in advocating for the needs of the region,

00:07:53 for small island states by extension,

00:07:55 and generally have had some success in that area.

00:07:59 - Yeah, and let's speak a little bit about climate change

00:08:02 because up to recently, just a few years ago,

00:08:05 climate change was denied.

00:08:07 People didn't think of,

00:08:09 well, they didn't think that it was something real.

00:08:12 And in recent times, we have seen a number of things

00:08:17 happening with the environment.

00:08:19 You feel now that there is a greater understanding

00:08:23 of climate change and the impact it is having

00:08:27 on countries worldwide?

00:08:29 - Definitely.

00:08:32 I think what we're seeing now is that,

00:08:36 well, it's two things actually.

00:08:37 First of all, we're experiencing impacts

00:08:41 in a much more extreme manner than had been expected.

00:08:44 And this is even based on what the Intergovernmental Panel

00:08:49 on Climate Change has been saying since 1992.

00:08:52 We knew that at that time,

00:08:55 they knew that the climate was going to change.

00:08:58 They knew that something was happening.

00:09:00 They knew that we would be in a situation where temperatures,

00:09:03 the average temperatures would be increasing globally.

00:09:07 But I think as we have seen technology progress

00:09:12 over the years, they've been able to see

00:09:14 in a much more specific manner

00:09:16 what exact impacts will be happening,

00:09:18 where they will be focused.

00:09:20 And what we understand now is even what they predicted

00:09:24 and modeled at that time was too conservative

00:09:27 based on what we're experiencing now.

00:09:28 So the impacts are actually,

00:09:30 they've actually been a bit more extreme

00:09:34 than expected at this time.

00:09:36 And they've been coming a bit earlier.

00:09:38 So we're actually in, I would say,

00:09:42 a more difficult situation than we had expected to be in.

00:09:45 And that is having an effect on, well,

00:09:49 I guess the level of global recognition of the problem

00:09:53 as to whether or not it's having an impact

00:09:56 on how quickly we move in the global negotiation process.

00:09:59 Well, that remains to be seen.

00:10:00 - Yeah. Hasn't it been a situation of,

00:10:03 as we say in Trinidad and Tobago,

00:10:04 you have to burn to learn, right?

00:10:07 And I think because we're seeing the effects of it now,

00:10:09 well, we are waking up.

00:10:12 - Waking up.

00:10:13 I would argue that we haven't yet started burning.

00:10:16 And this is maybe what is the biggest part

00:10:19 of the cautionary tale.

00:10:21 Even what we are experiencing now is a tip,

00:10:25 just a tip of the iceberg in terms of what we know

00:10:28 is coming down the line.

00:10:30 And the way the global climate system works

00:10:33 is that there's always a delay in terms of the emissions

00:10:36 that the atmosphere sees and the impacts that we feel.

00:10:40 So what that means is that the actions we take now

00:10:44 will not necessarily have an impact

00:10:45 on what we're experiencing now,

00:10:47 but we'll have a major impact

00:10:48 on what we will be experiencing in the next 30, 40, 50 years.

00:10:52 - Wow.

00:10:53 Kishan, as someone with such vast experience

00:10:56 in environmental diplomacy,

00:10:58 what do you see as the unique and most critical challenges

00:11:01 the Caribbean faces concerning climate change?

00:11:04 - Well, certainly climate change impacts will be an overlay

00:11:07 on the already existing challenges in the Caribbean region

00:11:11 for sustainable development, for example.

00:11:14 Because climate change touches

00:11:15 every aspect of human development.

00:11:17 It touches the biophysical environment.

00:11:19 It also touches more significantly

00:11:21 the socioeconomic aspects of development.

00:11:26 So the challenges not only speak

00:11:29 to those developmental challenges,

00:11:31 but it also exacerbates the existing challenges

00:11:36 of small islands.

00:11:39 Because you have limited land space, for example,

00:11:42 limited human capacity, limited financial capacity,

00:11:44 limited technological capacity.

00:11:46 And if you overlay the challenges of climate change,

00:11:48 which speak to every facet of human development,

00:11:51 then you can get a sense of how daunting the task is.

00:11:55 Overlayed on that as well is that the Caribbean region

00:11:57 is one of the most indebted regions in the world

00:12:00 in terms of its foreign debt, which continues to rise,

00:12:05 and the ability to pay that back,

00:12:10 which is serviced by economic growth and development,

00:12:13 which in itself is challenged by climate change.

00:12:16 So you can see it's a vicious circle.

00:12:19 All of these things have positive interactions.

00:12:22 And therefore, the Caribbean region is classified

00:12:25 as one of the most vulnerable in the world.

00:12:28 And therefore, to address climate change properly,

00:12:31 it not only takes a bottom-up approach

00:12:33 to build climate resiliency at the national level,

00:12:36 but it also takes that advocacy at the international level,

00:12:39 where you have global efforts, collective global efforts,

00:12:41 to actually mitigate against the impacts of climate change

00:12:45 on the one hand, but also to reduce emissions,

00:12:47 as Rwana said, to reduce the impacts

00:12:51 that will come in the future.

00:12:52 Because if we were to snap our finger

00:12:56 and the world were to shut down at this moment,

00:12:58 and not a single molecule of greenhouse gas

00:13:01 that causes climate change were ever to be emitted,

00:13:04 we will be committed to changes in sea level rise,

00:13:07 changes in precipitation, changes in temperature,

00:13:10 because of the past emissions.

00:13:11 And that is the level of challenge.

00:13:12 - But does it speak about or speak to our preparedness?

00:13:15 - The preparedness has to be an iterative,

00:13:18 continuous activity.

00:13:21 And built into that preparedness is the challenges

00:13:24 that come with the projections.

00:13:26 Because now we are seeing the rate

00:13:27 at which climate change is happening

00:13:29 has been underestimated.

00:13:30 I think Rwana made the point.

00:13:32 And so a continuous assessment will tell you

00:13:36 that if it has been underestimated,

00:13:38 it means that our preparedness now has to be ramped up

00:13:41 continuously, and that adds to the challenge

00:13:43 of our financial, technological, human capacity.

00:13:46 - Yeah, and Rwana, coming from your legal background,

00:13:50 have we in Trinidad and Tobago,

00:13:52 and regionally developed and implemented

00:13:54 and monitored the requisite key legal measures

00:13:57 to improve our responsibility

00:13:59 and resilience to climate change?

00:14:01 - I would say that it's definitely in train.

00:14:06 As Kishan described, it is an iterative process.

00:14:09 So the level of preparedness and the policy

00:14:14 and legal instruments that exist within a state

00:14:17 do not exist in isolation.

00:14:19 They exist in relation to the overarching legal environment

00:14:24 at the international level.

00:14:26 And we know that we've only had the Paris Agreement

00:14:29 in place since 2015.

00:14:31 It entered into force in 2016.

00:14:33 There's been seven years in between.

00:14:35 There's always a bit of a policy lag

00:14:36 in terms of when you have a global agreement in place

00:14:39 and the length of time it takes for states

00:14:42 to implement the policy and enact the legislation

00:14:46 in order to implement it.

00:14:47 So for example, I know that we have a few acts

00:14:51 throughout the region that address climate change issues

00:14:54 from different perspectives.

00:14:55 In Dominica, there's a Climate Resilience Act.

00:14:58 In Bahamas, they have an act looking at

00:15:00 structuring carbon markets and regulating carbon markets.

00:15:04 In St. Lucia, I think today they might be enacting

00:15:07 climate change, specific climate change legislation

00:15:10 in order to be able to implement the Paris Agreement.

00:15:12 I know that Kishan has done some work in Trinidad and Tobago

00:15:14 looking at draft legislation that would govern

00:15:18 the implementation of the Paris Agreement

00:15:20 in Trinidad and Tobago as well.

00:15:21 So what we are seeing is that there is a lot of movement

00:15:24 in the Caribbean from a legislative standpoint

00:15:26 in order to be able to implement the Paris Agreement

00:15:29 and respond to the rules that have now been established

00:15:32 at the international level.

00:15:34 And this work is on the basis of existing policy instruments

00:15:38 and there have been policy instruments in place

00:15:40 in the region for some time dealing with different aspects

00:15:43 of the problem, whether it be adaptation or disaster,

00:15:46 risk reduction, or any other area

00:15:49 that's related to resilience building.

00:15:51 - Yeah, Kishan, and I want you to help me with this.

00:15:54 I hope I pronounce it correctly.

00:15:56 There's an agreement called the Escazu Agreement.

00:15:59 Yeah, I got it right?

00:16:00 - You got it right.

00:16:01 - All right, good.

00:16:02 So can you tell us, let's speak a little bit

00:16:04 about this agreement and how it serves the interests

00:16:06 of the Caribbean specifically.

00:16:08 - So the Escazu Agreement, as the name implies,

00:16:11 was adopted in Costa Rica in a place called Escazu in 2018.

00:16:16 The correct name of, the full name of the agreement

00:16:18 is Access to Information.

00:16:21 It's an environmental agreement,

00:16:23 a regional environmental agreement

00:16:24 for Latin America and the Caribbean.

00:16:26 And it's access to information, participation

00:16:30 in decision making, and access to justice

00:16:33 in environmental matters.

00:16:34 And it is the first agreement that actually provides

00:16:37 for explicit mention of the environment as a right,

00:16:42 the right to a healthy environment,

00:16:45 as well as environmental defenders,

00:16:47 which is a first in the world.

00:16:51 It is the only agreement to come out

00:16:54 of the Rio+20 Sustainable Development Conference.

00:16:58 And what it speaks to is really one in which rights

00:17:01 of citizens at large are raised to prominence

00:17:05 so that their voices must be heard

00:17:07 in any decision that is being taken.

00:17:10 They have to be guaranteed their rights

00:17:14 in terms of environmental participatory decision making

00:17:18 and justice in environmental matters.

00:17:21 So how does this nexus with climate change, for example?

00:17:25 Climate change is increasingly becoming to be seen

00:17:28 internationally as a human rights issue.

00:17:30 So the Escazú agreement, with all its provisions,

00:17:34 basically serves to reinforce the need for everyone,

00:17:40 every citizen, to be involved in the decision making process

00:17:46 consistent with the human rights norms

00:17:49 that have been established,

00:17:50 including the right to a healthy environment,

00:17:53 evadication of poverty, things like that,

00:17:56 right to education, and so on.

00:17:57 So the Escazú agreement really serves

00:18:00 as a supporting instrument for addressing

00:18:04 and achieving some of the environmental

00:18:06 and climate change objectives

00:18:08 that we all aspire to in the Caribbean.

00:18:10 - Rana, you know, when we speak about climate change,

00:18:12 we immediately think about hurricanes and weather events.

00:18:17 Have there been, you think, successful strategies

00:18:21 that we have adopted in the region

00:18:25 to mitigate the effects of climate change?

00:18:29 - Well, to mitigate, or I guess to build resilience

00:18:34 and to adapt to the impacts of climate change.

00:18:36 So I would say yes, but I would say there still needs,

00:18:41 there's still a lot of work that needs to be done

00:18:43 in the realm of establishing climate services,

00:18:47 which would allow us in the region to be better able

00:18:51 to track, to predict, and to plan in order to ensure

00:18:56 that we have the proper building codes, for example,

00:19:01 in place in order to ensure that we have in place

00:19:03 the early warning systems that we need

00:19:05 to allow people to take measures

00:19:06 to remove themselves from danger

00:19:09 in order to allow us to understand

00:19:10 where exactly the impacts are going to be the worst

00:19:14 so that those people can be protected in those areas.

00:19:16 So there have been some strides made.

00:19:20 So for example, in Antigua and Barbuda,

00:19:22 they've done a lot in terms of their building codes

00:19:25 and planning in order to ensure that people can be prepared.

00:19:30 But with that said, when we think about extreme weather

00:19:34 events in the context of climate change,

00:19:37 what we are seeing and what certainly we have seen

00:19:40 in the recent past, in 2017, in 2018 hurricane seasons,

00:19:45 is that these extreme weather events

00:19:48 are getting to the point where it's actually difficult

00:19:51 to even be able to respond to them.

00:19:53 So that's not to say that there isn't still work

00:19:55 to be done to improve our resilience,

00:19:57 but for example, if we have category five

00:20:01 and some say hurricane Dorian, for example,

00:20:04 might have been a category five plus hurricane,

00:20:07 there's very little scope for adaptation

00:20:11 or for resilience building in the face of extreme events

00:20:15 that we had never even thought might be possible.

00:20:18 So what we're looking at, as well as the resilience building,

00:20:22 as well as the adaptation, is needing to make arrangements

00:20:25 to deal with loss and damage, which is what happens

00:20:28 when we get to the soft and hard limits to adaptation.

00:20:31 And that is a different kettle of fish.

00:20:34 - Dijan, we're just about two minutes again,

00:20:37 but a little birdie told me that you may be speaking

00:20:41 about climate finance today at the forum later on today.

00:20:46 If we could just touch on that and just give us really,

00:20:53 what else can we look forward to at today's forum?

00:20:57 What should be the biggest takeaways from the forum?

00:21:00 - Okay, so there's no adopted or accepted definition

00:21:04 of climate finance.

00:21:05 - Yes.

00:21:06 - Suffice it to say that any financial flows

00:21:08 from developed countries to developing countries

00:21:11 bilateral flows, loans, for the purposes

00:21:14 of building climate resilience or reducing emissions

00:21:17 can be loosely classified as climate finance.

00:21:20 Climate finance is one of the things

00:21:22 that have been the confidence maker

00:21:24 and the confidence breaker in international negotiations.

00:21:28 It has been a longstanding issue since negotiations began,

00:21:32 but actually came to a hilt in 2009 in Copenhagen

00:21:36 with the pledge of $100 billion by developed countries

00:21:39 for developing countries,

00:21:40 $100 billion by 2020, which was never met actually.

00:21:45 So you could understand how this now has eroded confidence

00:21:47 in the negotiations.

00:21:49 This goal expires in 2025.

00:21:51 And the process has been set in place

00:21:53 in the last COP26, two years ago,

00:21:58 for negotiations of a new quantitative goal,

00:22:02 climate finance goal to be adopted next year in 2024.

00:22:06 And so those negotiations are ongoing.

00:22:09 We are hearing of the quanta of finance

00:22:14 that would be required for developing countries

00:22:15 for adaptation.

00:22:16 It has moved very quickly in a matter of a decade

00:22:19 from billions, and we're now hearing trillions.

00:22:23 I think the UNEP recent report on finance

00:22:27 has gone into trillions.

00:22:28 And it will keep increasing

00:22:30 with the accelerated impacts of climate change.

00:22:33 So we hope that negotiations coming up in Dubai

00:22:38 later on this month and into next month,

00:22:41 that time and finance will be given the seriousness

00:22:44 that it requires and we can have hard decisions

00:22:47 that will lead to tangible delivery

00:22:50 of the kind of finance that are required

00:22:52 by developing countries,

00:22:55 but more so vulnerable countries,

00:22:57 such as small island states and Australia and the Caribbean.

00:23:00 In terms of what can be expected today

00:23:02 using the theme of big data,

00:23:04 I think given the complexity of climate change,

00:23:08 because it encompasses everything,

00:23:09 it can encompass the biophysical environment,

00:23:12 the oceans, the atmosphere,

00:23:14 the cryosphere or the ice-based ecosystems,

00:23:17 the land, everything, social and economic well-being,

00:23:24 the socioeconomics, for example.

00:23:26 To project and to predict the changes in the climate

00:23:31 and how we react to them requires the analysis

00:23:34 of huge datasets and very complex datasets.

00:23:38 And therefore, big data and big data analytics,

00:23:42 artificial intelligence, for example,

00:23:44 we see are now playing an increasingly important role

00:23:48 in how this large amount of information

00:23:51 that is needed to be assessed,

00:23:54 can be assessed to read down to the benefits

00:23:57 of not only predicting climate change

00:23:59 and what the impacts are going to be,

00:24:00 but certainly socioeconomic modeling

00:24:02 on how the human systems can now react

00:24:06 and plan for these large impacts of climate change.

00:24:09 - Kishan, Rana, thank you very much for coming this morning.

00:24:12 We do appreciate the information that you have given us

00:24:15 and it has also been an education

00:24:18 for I suspect all of our viewers.

00:24:20 We thank you again.

00:24:21 - Thank you very much for having us.

00:24:22 - So we are going to a very short break.

00:24:24 We are coming back.

00:24:25 (upbeat music)

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00:24:42 All right, so welcome back everyone.

00:24:43 So again, to our viewers are now joining us.

00:24:46 We are at the Hyatt this morning

00:24:48 and we are at the Big Data Forum.

00:24:51 Of course, there's going to be a major discussion

00:24:54 later today concerning data, concerning AI,

00:24:58 concerning robotics, concerning technology, you name it.

00:25:02 That is going to happen here today.

00:25:05 So we are now joined by Darren Muhammad and Adil Akbar.

00:25:10 Now Darren Muhammad is the director of Microsoft Azure

00:25:14 over a 14 year career at Microsoft.

00:25:19 Darren has served in many business development roles

00:25:21 across a managed customer segments,

00:25:23 industries and more recently cloud-based workloads.

00:25:27 And having always had a technical foundation,

00:25:30 Darren now leads a technical team of specialists

00:25:32 are focused on designing cloud solutions

00:25:35 and delivering technical proofs for managed customers.

00:25:39 Darren, thank you very much for coming this morning.

00:25:41 - Thank you for having me, pleasure to be here.

00:25:41 - And we do have Adil Akbar,

00:25:44 account executive and country manager

00:25:46 for Microsoft in Trinidad and Tobago.

00:25:49 He is an experienced professional and technology expert.

00:25:53 Now Adil's efforts as an account executive

00:25:57 and country manager for Microsoft in Trinidad and Tobago

00:26:00 are on delivering tangible results for the government

00:26:03 and citizens of the country.

00:26:05 Adil, thank you very much for coming this morning.

00:26:07 Yeah, all right, Adil, let's begin with you.

00:26:10 What are some of the most significant challenges

00:26:14 and opportunities that the region faces

00:26:17 in terms of digital transformation?

00:26:19 - Well, Amman, let's start with,

00:26:21 Microsoft is on a mission to empower every organization

00:26:25 and person on this planet to achieve more, right?

00:26:28 Challenges and opportunities come in the same breath, right?

00:26:32 So we've seen during the pandemic,

00:26:35 organizations, governments, citizens

00:26:38 having to change very rapidly to a new way of life,

00:26:42 a new way of work.

00:26:44 So the challenge and the opportunity that we have here

00:26:47 is not to let that go.

00:26:50 Let's keep moving forward with that piece

00:26:52 that we've been moving with during the COVID.

00:26:54 It's, you know, the world is moving quite quickly

00:26:58 and as a Caribbean nation,

00:27:00 we need to keep with that piece.

00:27:03 - Yeah.

00:27:04 Darren, let's bring you in here.

00:27:07 How can the region ensure that its workforce

00:27:09 is prepared for the jobs of the future?

00:27:11 And I wanna put it in a context,

00:27:13 because as you know, some of us in the region are very rigid.

00:27:17 We have rigid positions.

00:27:19 When we think about things like technology,

00:27:22 we always have a reason why we should not

00:27:26 implement technology at our organizations

00:27:29 because we are so accustomed to having things done

00:27:33 in a particular way.

00:27:34 And some of us are just afraid of coming outside the box,

00:27:37 of thinking outside the box, yeah?

00:27:39 - Yeah, yeah, absolutely.

00:27:41 Well, I mean, every organization,

00:27:43 including private and public sector is there to serve, right?

00:27:46 So the private, you would serve the customer.

00:27:48 In the public, you would basically be serving the citizens.

00:27:51 I think that the demand for change

00:27:54 is gonna be driven by who you serve.

00:27:55 So it would be driven by through the citizens

00:27:58 and from your customers.

00:28:00 Customers will demand more technology.

00:28:02 With the advent of artificial intelligence,

00:28:06 the statistic that they use is that by 2025,

00:28:10 over 50% of the workforce will need re-skilling.

00:28:14 And so we are encouraging governments across the region

00:28:19 to focus on re-skilling.

00:28:21 And then we're also encouraging everyone to focus on

00:28:25 not just the skills that they have today,

00:28:28 but actually the ability to learn

00:28:31 and the ability to be adaptive and change.

00:28:34 - Yeah, but Adil, let's really get into

00:28:37 artificial intelligence because I remember,

00:28:40 I think it was earlier this year,

00:28:43 or it could have been late last year.

00:28:45 It would seem that this term artificial intelligence

00:28:50 came out of nowhere.

00:28:52 And we were seeing things on international news telling us,

00:28:55 look, this is the end of us as humans

00:28:59 because of artificial intelligence.

00:29:01 So I can say that artificial intelligence

00:29:05 has gotten a lot of bad rap, all right?

00:29:09 But I think over the past few months,

00:29:11 we've been seeing what could be the benefit

00:29:14 of artificial intelligence to countries,

00:29:17 to business organizations.

00:29:19 You think that you're already seeing promising areas

00:29:25 of investment in the Caribbean, re-artificial intelligence?

00:29:29 - Yes, definitely.

00:29:32 You know, artificial intelligence has been,

00:29:35 it has been here for quite some time.

00:29:37 - Yes.

00:29:38 - It's definitely more prevalent now

00:29:41 in the eyes of the average of the citizens of the countries.

00:29:45 So, you know, we need to make sure that

00:29:52 investments are put in the right place

00:29:55 to keep promoting artificial intelligence across the nations.

00:30:00 Artificial intelligence is gonna make,

00:30:02 it's gonna make our jobs easier.

00:30:06 It's not necessarily it's replaced jobs.

00:30:08 It's gonna change the way in how we work moving forward.

00:30:12 And there's a need for both on the private side

00:30:15 and the government side to continuously invest

00:30:19 in the employees and in citizens as well

00:30:24 to take advantage of the technologies that are coming forward.

00:30:29 - Yeah, but Darren, how do humans compete with AI?

00:30:35 Because if you are, if an organization is adopting AI,

00:30:40 well, therefore that is being done

00:30:43 to make the organization a little more efficient, not so?

00:30:47 And I suspect profitable.

00:30:49 So how do I as an individual compete with that?

00:30:53 - Yeah, I mean, we see it differently.

00:30:55 I mean, we don't see it as competition.

00:30:58 You know, recently Microsoft invested

00:31:01 in a World Trend Index survey.

00:31:04 And in that survey, and when we surveyed workers,

00:31:08 when we looked at what they wanted,

00:31:11 it was to get away from some of the drudgery of work.

00:31:15 You know, some of the, you know,

00:31:16 they said that they were having ineffective meetings

00:31:19 and the meetings were going on too long and too many.

00:31:21 They said they had too many emails, right?

00:31:24 We're also in a very uncertain time globally.

00:31:28 You know, you have two wars,

00:31:29 you have a lot of inflation and so on.

00:31:32 And so the amount of resources,

00:31:33 let's say higher more resources,

00:31:36 is always, you know, is always being limited.

00:31:41 So we see artificial intelligence

00:31:42 as a way of actually making people more productive,

00:31:47 get helping them get through, you know,

00:31:49 the already the work that they have to do

00:31:52 to make more effective meetings, you know?

00:31:55 And so I'll give a simple example.

00:31:57 We launched a technology called Copilot.

00:32:00 At the end of your digital meeting,

00:32:02 Copilot would have transcribed everyone who spoke

00:32:05 and would already present a meeting summary.

00:32:08 So imagine if you had too many meetings

00:32:09 and you did not attend that meeting,

00:32:11 you could come back and then the summary would be there.

00:32:15 So we see it as a way of an enabler, you know,

00:32:18 to the productivity of humanity.

00:32:21 - Yeah, Adil, we are speeding this morning.

00:32:25 Unfortunately, I would have liked to speak a little more.

00:32:28 However, Adil, we have just about a minute again,

00:32:32 but as you look at, let's say, Trinidad and Tobago,

00:32:36 other countries of the Caribbean

00:32:39 and their efforts to adopt AI,

00:32:45 how do you see things, let's say, in the next few years

00:32:48 and further into the future?

00:32:50 - You know, there's been, we have seen an uptick in AI.

00:32:55 You know, we have lots of organizations

00:32:58 between all of us, for what Dara mentioned,

00:33:01 which is a co-pilot, right?

00:33:02 I think the uptake is gonna be quite serious.

00:33:09 I do think organizations, both in the private sector

00:33:12 and the government, are going to look

00:33:14 to take advantage of this because of the efficiencies

00:33:17 that this is gonna bring, ultimately the productivity,

00:33:20 ultimately the revenue, and the profitability,

00:33:23 the organization.

00:33:24 I don't think there's any other way to do it,

00:33:27 but to do it.

00:33:29 - Yes. - And move forward.

00:33:32 You have to embrace it.

00:33:33 - Yes, absolutely. - You have to embrace it.

00:33:35 - And I think our role as a provider of the technology

00:33:38 is to democratize it because you want to make sure

00:33:41 that the technology is inclusive

00:33:43 and that it could reach all those who want to use it

00:33:45 and that it does not create any differentiation in society.

00:33:49 And I think that that's really our role.

00:33:51 When you offer these services in very, you know,

00:33:54 sort of bite-sized, per-user type ways,

00:33:58 then an SME can adopt the same technology

00:34:01 as a big enterprise.

00:34:03 And that's our role, is to democratize it.

00:34:06 - And make it more palatable.

00:34:07 - Absolutely. - Absolutely.

00:34:08 - And that's an important point.

00:34:09 The important point is this is not geared

00:34:11 towards the enterprise or, you know,

00:34:14 the top end of the organization.

00:34:16 This is intended for every single business.

00:34:20 - Yes. - And every single person.

00:34:23 - Yes.

00:34:24 Gentlemen, it was a pleasure speaking with you

00:34:26 all this morning.

00:34:27 I wish that we had more time to flesh out

00:34:29 a number of other things,

00:34:30 but it was a pleasure speaking with you all.

00:34:32 Thank you very much. - Absolutely.

00:34:33 Same on it.

00:34:34 Thanks for the opportunity. - Same to you.

00:34:35 - Thank you.

00:34:35 - So we are going to a very short break again.

00:34:37 We are coming back.

00:34:38 Gentlemen, thank you.

00:34:42 (upbeat music)

00:34:46 (upbeat music)

00:34:49 All right, so welcome back, everyone.

00:35:08 So again, we are at the Big Data Forum

00:35:10 at the Hyatt Regency in Port of Spain.

00:35:13 Of course, as I said a little later,

00:35:16 there's going to be a massive discussion

00:35:18 concerning big data, artificial intelligence,

00:35:22 and a host of other topics.

00:35:24 All right, so let's welcome at this time

00:35:27 Dr. Letitia Addison and Dr. Fadra Mohammed.

00:35:31 Now, Dr. Letitia Addison,

00:35:33 she's the project officer lecturer at UBC in D'Augustine,

00:35:36 a Women in Data Science and TNT ambassador.

00:35:39 She's a tertiary level educator, statistician,

00:35:42 and researcher specializing in building statistical

00:35:45 and mathematical models for sustainability.

00:35:49 She holds a PhD in mathematics

00:35:51 and in statistics from the University

00:35:55 of the West Indies, St. Augustine.

00:35:57 All right, and we also have, as I told you,

00:35:59 Dr. Fadra Mohammed, lecturer, computer science.

00:36:02 She's a computer science lecturer

00:36:04 at the Department of Computing and Information Technology

00:36:07 at the University of the West Indies, St. Augustine campus

00:36:10 in Trinidad and Tobago.

00:36:13 Doctors, thank you very much for coming this morning, right?

00:36:16 All right, so doctors, let's jump into this right away.

00:36:20 So I'm told that you both can be considered

00:36:25 as pioneers in data science.

00:36:27 Can you tell us a bit about your current roles

00:36:30 and your thoughts on data science as a career path

00:36:33 for young girls and women?

00:36:36 Pioneer, doctor.

00:36:37 - I'm trying to be.

00:36:38 (laughing)

00:36:39 So thank you for that title.

00:36:40 - Yes.

00:36:41 So, well, in my current role,

00:36:43 I feel like I'm a woman of many hats.

00:36:45 I'm a statistician.

00:36:46 I'm also a lecturer, but I also hold the title

00:36:48 of the woman in data science ambassador.

00:36:50 And I feel in that space, through the global organization,

00:36:54 I've been able to sort of harness

00:36:56 this community building aspect

00:36:58 and bring that into our environment in Trinidad.

00:37:02 And I feel like that's very important

00:37:04 in the digital age we're in right now

00:37:06 to give girls and women that support,

00:37:10 something that I saw when I was going

00:37:12 through my trajectory to my career

00:37:14 was really that I needed more support,

00:37:16 especially from females as well, to feel that motivation.

00:37:19 And I think it's really crucial at this point in time

00:37:22 that we actually pave the way for others coming up.

00:37:25 - Yeah.

00:37:26 Dr. Mohammed, what has the experience been like for you?

00:37:29 - Well, I'm a lecturer in computer science.

00:37:32 So data science is a subset of that area.

00:37:36 And truly now data is oil.

00:37:39 - Yeah.

00:37:40 - So when I started, there was actually a lack of data

00:37:44 in the sense that the algorithms

00:37:45 and the things that we were building,

00:37:47 they were not able to work the way that they could have.

00:37:52 So now it's quite exciting to see things

00:37:54 that you would have learned in theory come out.

00:37:57 And so do we.

00:37:58 - Yeah.

00:37:59 Now, both of you have had substantial impact

00:38:01 through your work.

00:38:02 What inspired you to pursue a career

00:38:04 in data science and research?

00:38:06 And did you face any particular challenges

00:38:09 as women in STEM fields?

00:38:12 - In fact, I always like to say,

00:38:13 I think most people know I say that data science

00:38:16 is really a new term to really coin statistics

00:38:19 and the inclusion of computer science

00:38:21 and other digital mechanisms.

00:38:23 And for me, I think throughout my academic career,

00:38:28 I felt like statistics is really crucial to build a story.

00:38:33 I think we're all living different stories in our lives

00:38:36 in our different communities.

00:38:38 And in that way, it's really important for us

00:38:40 to harness the power of statistics.

00:38:43 And through data science, we're able to do that

00:38:44 in an even larger way now to connect with each other.

00:38:48 We have all these AI tools

00:38:49 and we're able to sort of build platforms

00:38:52 to really help with problems that have social impact.

00:38:55 So I think it's really crucial

00:38:56 to move into that data science age and embrace it.

00:39:00 - Yeah.

00:39:01 And Dr. Muhammad, how do we get more girls

00:39:03 and women involved in data science and computer science?

00:39:08 - I think we just need to connect with them.

00:39:10 It's seen as something difficult.

00:39:13 I think it's the same stigma for mathematics

00:39:16 that I don't know how to use these computers.

00:39:20 I can't do this computer thing.

00:39:22 And truly the field is so multidisciplinary now.

00:39:25 You can merge anything that you're interested in

00:39:28 with computing, fashion, science, biology, mathematics,

00:39:33 astronomy, language, anything that you can think of,

00:39:36 you can find some sort of complimentary facet

00:39:40 that involves computing.

00:39:42 So to let girls see that there is that connection

00:39:45 is the first step.

00:39:46 And I think the second step is to make it accessible to them.

00:39:50 Many times they say that computing is a boy's domain.

00:39:55 And this is true because in the '80s,

00:39:58 parents would have purchased a computer

00:40:00 for their boys as a toy.

00:40:02 And for a girl, they got something else.

00:40:05 So then when these boys or that generation

00:40:08 got into education at the tertiary level,

00:40:11 the teachers would say, "Huh, well, they know this already.

00:40:14 "So let's gloss over some things."

00:40:16 And then those people in society, not just girls,

00:40:19 but other men who did not have that exposure,

00:40:23 it became hard because things were assumed.

00:40:26 So I think we have to stop assuming things

00:40:27 and just start from scratch.

00:40:29 - But doctor, I suspect it takes a new approach

00:40:34 to the way that we deal with girls and women in our society,

00:40:39 open up as much opportunities to them

00:40:42 and also make them understand from a very early age

00:40:47 that everything that they think about can be achieved.

00:40:51 So it's a holistic approach by the entire society.

00:40:55 But do you think, just jumping off of that point,

00:40:58 but do you think that things have changed

00:41:00 and we as a country have taken steps

00:41:03 to make our girls and women feel that anything

00:41:07 and everything is possible and that can be achieved?

00:41:09 - And I like that you said that.

00:41:11 Anything is possible is really my mantra.

00:41:12 And I think now more than ever,

00:41:16 we are in a space where women feel more empowered,

00:41:20 especially with just the advent

00:41:22 of all these different communities.

00:41:24 I do think in Trinidad, we have a lot of different facets

00:41:27 of where we are able to see women shine in the arena.

00:41:30 Currently at the university,

00:41:31 we have many women in top roles, including our principal.

00:41:35 And I think that in itself is very inspiring.

00:41:38 And I believe that it's a growth mindset.

00:41:41 I think for us, just as a country, as a world,

00:41:44 to be able to give, as Dr. Mohammed mentioned,

00:41:46 girls that, you know, pass the torch and let them know

00:41:51 that they can achieve anything

00:41:53 that they set their minds to,

00:41:55 especially with respect to data science

00:41:57 and STEM field.

00:41:58 - Yeah.

00:41:59 And I know that today that you all will be participating

00:42:03 in a session focused on women and on data science also.

00:42:08 The session is called Building Capacities.

00:42:12 So from where you sit, we as a country,

00:42:16 and we did touch on the fact on this issue a little earlier,

00:42:20 do you think that we are doing enough policy-wise,

00:42:23 investment-wise, industry-wise

00:42:25 to develop greater capacity among girls and women

00:42:29 as data scientists and technologists?

00:42:31 - Something of a loaded question.

00:42:33 - Yeah.

00:42:34 (laughing)

00:42:36 - Can we ever do enough?

00:42:38 - Yeah.

00:42:38 - I think we need to, like I said, start small.

00:42:43 And definitely we need policy where computing knowledge

00:42:47 is just as important as mathematics and reading.

00:42:50 Because the world is changing.

00:42:54 And just to have basic literacy is fundamental.

00:42:59 And that sort of thing needs to be established

00:43:03 at a very high level.

00:43:04 So that's my perspective on things.

00:43:07 Start very early, because children are curious.

00:43:11 And they unfortunately lose that curiosity

00:43:14 as they are put into particular streams.

00:43:18 - Yeah.

00:43:19 - So--

00:43:20 - And boxes.

00:43:20 - Yeah.

00:43:22 - That's my thought.

00:43:24 - Yeah.

00:43:24 What does the future look like, Doctor,

00:43:26 for young women and girls in this field?

00:43:31 - I think the future is bright.

00:43:33 I think right now we have a lot of avenues

00:43:36 and a lot of opportunities have been opening up.

00:43:39 A lot of community-based opportunities, a lot of projects.

00:43:41 And I think that it's really to just continue

00:43:45 to mold and support.

00:43:47 Because aside from the technical skills,

00:43:49 I think we also need the motivation and support

00:43:52 to be able to understand that we can continue

00:43:54 to go and achieve in these areas

00:43:56 and make a difference in that sense.

00:43:59 So I think it's really, I see it as a positive path.

00:44:03 And I think it's growing.

00:44:04 And to be a part of that revolution right now

00:44:05 is exciting for me as well.

00:44:07 Because I think I can actually give people

00:44:10 those tools as well to be able to say

00:44:13 that you can do this, you can.

00:44:15 And I also want to say statistic literacy

00:44:17 is extremely important, mathematic literacy.

00:44:20 Understanding that math is the foundation of everything.

00:44:22 I could talk about this for days.

00:44:24 But that in itself is really giving persons that opportunity.

00:44:29 Not only women and girls, but boys, everyone,

00:44:31 all genders, underrepresented groups as well,

00:44:34 to understand how important it is to use these subjects

00:44:37 to be able to propel themselves

00:44:39 in all these different areas.

00:44:41 So I think the future is really bright.

00:44:42 And I think we could, as a country, I see us moving forward.

00:44:46 And it's a revolution that will continue to grow.

00:44:49 - And Doctor, you're seeing more and more young women

00:44:53 enrolling in courses such as these at the university?

00:44:57 - Oh yeah, we have, we recently had a few

00:44:59 programming competitions internally at the university.

00:45:02 And the girls are doing really well.

00:45:05 Really, really well.

00:45:06 And we just have to get them a bit more,

00:45:09 some bravery there, to be able to not feel

00:45:14 as if I don't fit in.

00:45:17 Because when you go to these competitions,

00:45:19 and you go to these for, it's mostly men.

00:45:21 And it's a very difficult thing for a girl

00:45:24 to get that bravery to say, hey, I can do this, I can fit in.

00:45:28 And that's pretty much the challenge

00:45:29 throughout the world for most women.

00:45:32 It's not that they're not intelligent enough.

00:45:34 It's not that they're not driven enough.

00:45:35 It's not that there aren't enough opportunities.

00:45:38 It's just that they don't feel as if they fit in.

00:45:41 - That's a major problem, eh?

00:45:42 - Yeah.

00:45:43 - I suspect it's culture.

00:45:45 - Intimidation too.

00:45:46 - Not so.

00:45:47 - Yeah.

00:45:48 And I mean, I felt the intimidation as well.

00:45:50 When I came on campus as an undergrad.

00:45:52 - Yeah, yeah.

00:45:54 - Dr. Mohammed and I were in a very male-dominated

00:45:57 department, mathematics and statistics.

00:45:59 So you would feel that intimidation,

00:46:01 but then you have that passion and the drive.

00:46:03 And I would like to say that I was very supported

00:46:06 in that realm because there were boys

00:46:09 who were very confident, they were very skilled

00:46:11 at the computer science aspect.

00:46:13 And I learned a lot from them.

00:46:15 So I think we could learn a lot from each other, you know?

00:46:17 And it's nice to have that support as well

00:46:20 from the boys who are confident.

00:46:22 So I think that in itself is really what will help

00:46:25 all of us to grow.

00:46:26 - Yeah, teams make a difference.

00:46:28 - Yeah.

00:46:29 - Once you have a good team, that makes all of the difference

00:46:33 'cause just like Letitia said, I have had support

00:46:36 from many strong male models within my ecosphere,

00:46:42 as well as women.

00:46:43 So it doesn't really impact too much.

00:46:47 It's just support wherever it comes from.

00:46:49 That's the important thing.

00:46:50 - Yeah, and you know, doctors, I suspect there's a reason

00:46:53 why you are described as pioneers in this field

00:46:57 because I think that's some of the responsibility

00:47:01 in imparting knowledge, in boosting our young women

00:47:08 and girls when it comes to this sector.

00:47:12 Some of that responsibility lies on your shoulders.

00:47:15 It's a heavy responsibility, doctors.

00:47:18 - It's worth it.

00:47:19 - Yeah.

00:47:19 - It's worth it.

00:47:20 - When they come back.

00:47:21 - When they come back and they say, you know what?

00:47:23 That name joke you told, you do tell a lot.

00:47:26 That really helped me to understand some heavy theories.

00:47:31 - Yes.

00:47:32 - It makes it worthwhile.

00:47:33 It's heavy, it hurts, but it's worth it

00:47:36 because you see them.

00:47:37 - Yes.

00:47:38 - No, I agree.

00:47:41 I think in that sense, being able to support them

00:47:44 in this realm where they can actually say, you know,

00:47:49 just as Dr. Mommet said, looking back,

00:47:51 I've had some students tell me, you know,

00:47:53 miss in the class right now, currently that I teach,

00:47:55 they're kicking and screaming about the statistics

00:47:57 and the project.

00:47:58 Just yesterday, they had a presentation.

00:48:00 And I said, you'll come back, you'll come back a year later,

00:48:03 at least one of you and say, you know what?

00:48:05 This actually, you know, helped me to grow

00:48:07 and to go into the work and work.

00:48:08 We want to create 21st century, you know,

00:48:11 individuals, professionals, you know,

00:48:13 well-rounded individuals as well.

00:48:15 So I think it's worth it.

00:48:17 - Yeah, doctors, it was a pleasure speaking with you all

00:48:19 and thank you for your contribution.

00:48:21 And thank you for inspiring so many girls

00:48:24 and young ladies in Trinidad and Tobago.

00:48:26 We do appreciate it.

00:48:27 Thank you very much for coming this morning.

00:48:29 - Thanks for having us.

00:48:30 - We are going to a very short break.

00:48:30 We're coming back.

00:48:31 (upbeat music)

00:48:34 (upbeat music)

00:48:36 All right, so welcome back everyone.

00:49:03 I hope that you're having a good morning.

00:49:05 Of course, over the past hour or so,

00:49:07 we have been speaking about what is to come

00:49:11 at the Big Data Forum, the UN's Big Data Forum

00:49:15 that is being held here later on today

00:49:17 at the Hyatt Regency.

00:49:18 So for the past hour, we have been discussing technology.

00:49:22 We have been discussing data, AI, you name it.

00:49:26 It has really been an education for all of us,

00:49:31 judging from the information that we're getting here.

00:49:34 But we are now joined by Professor Patrick Hossain.

00:49:39 And let me tell you a little bit about Professor.

00:49:42 He is, or he attended

00:49:44 the Massachusetts Institute of Technology

00:49:46 where he obtained five degrees, not one, five,

00:49:50 including a PhD in electrical engineering

00:49:53 and computer science.

00:49:55 And he has worked at Bose Corporation, Bell Laboratories,

00:49:59 AT&T Laboratories, Ericsson, and Huawei.

00:50:03 Professor, it's a pleasure.

00:50:04 Thank you very much for coming this morning.

00:50:06 - Thank you for having me.

00:50:07 - Of course.

00:50:08 And Dr. Letitia Addison, she's still with us.

00:50:10 So she's going to be chiming in

00:50:13 as Professor speaks this morning, all right?

00:50:16 So Professor, let's speak,

00:50:18 and if you could give us a little overview of TT Lab,

00:50:22 because I suspect to people that may be a new term to them.

00:50:27 And what led you to create such a powerful network?

00:50:32 - So TT Lab is not really any sort of legal entity

00:50:35 or organization.

00:50:37 It's an ad hoc group of researchers.

00:50:40 I wanted to get researchers together

00:50:42 from multiple disciplines, multiple stages in their career

00:50:47 to do research in various disciplines.

00:50:50 So we have people from computer science, data science,

00:50:54 statistics, mathematics, mechanical engineering,

00:50:57 economics, electrical engineering,

00:51:00 but we work on real world problems.

00:51:04 So we try to collaborate with our industry

00:51:07 and solve whatever problems they may have.

00:51:11 But we want to go further than that,

00:51:12 we want to publish.

00:51:14 So we publish at work as well.

00:51:17 And this helps the student either go on to grad school

00:51:21 somewhere else or at UE, or get options in industry as well

00:51:26 because of internships.

00:51:28 - But how long have you all been doing this?

00:51:31 - It started about, I would say about six years ago.

00:51:34 What happened is we have a lot of national scholars

00:51:39 and they return, having done their work

00:51:44 at some of the best schools abroad and at UE,

00:51:51 but we were not utilizing them efficiently.

00:51:55 So there was one particular case,

00:51:57 this guy did an internship at NASA,

00:51:59 he came back and he was doing some trivial stuff.

00:52:02 So I told him to come do some research with me,

00:52:04 he just had a bachelor's degree.

00:52:06 And within a year he had four publications.

00:52:09 And he went on to do great things,

00:52:11 he went to Cambridge and then Google, et cetera.

00:52:14 So after that I said, well, maybe I could do this

00:52:17 with other people.

00:52:18 So I started bringing in more and more people

00:52:20 to work under me to do research.

00:52:23 It's mostly some of my master's students, my PhD students,

00:52:28 but I do have people from other universities, UTT,

00:52:32 even people in industry, Diaspora.

00:52:36 So if you're interested in doing interesting research,

00:52:41 come and reach out to me, I can evaluate you

00:52:45 to see your interests and your background

00:52:48 and then go from there.

00:52:49 - Professor, I get the feeling that what you are doing

00:52:54 is to not only guide people in the right direction,

00:52:58 but there's a level of molding by molding of the individual.

00:53:03 Yeah, and streamlining them to have that laser focus.

00:53:08 - Yeah, it's sort of like a finishing school.

00:53:11 So they come out of UE and industry expects them

00:53:16 to have experience, they have no experience.

00:53:18 So this bridges that gap, but it also gives them

00:53:23 the confidence to do more than they think they could do

00:53:26 because some go into industry and they just do

00:53:30 regular stuff where they have the ability to do a lot more.

00:53:33 So by publishing and doing research,

00:53:35 presenting at conferences, it makes a big difference

00:53:37 in their attitude, their confidence, et cetera.

00:53:40 - Yeah, and Dr. Adesan, I see that you're shaking your head.

00:53:45 Let's look at some of the benefits of a professor's program.

00:53:50 What have you seen?

00:53:51 - I mean, I would first say that Professor Hussain

00:53:54 has been my mentor for many years.

00:53:56 And in fact, when I completed my PhD,

00:53:58 I approached him because I heard about TT Lab

00:54:01 and the great research that they were doing.

00:54:04 And I think it actually, as he mentioned,

00:54:06 it really built my confidence because we have so many

00:54:10 smart students who complete their degrees

00:54:12 and then they really don't know how to harness

00:54:15 their abilities, especially when it comes to research,

00:54:17 which is really important.

00:54:19 And I think because of the group's dynamic with research,

00:54:22 you kind of have bridged the gap between academia

00:54:25 and then if you want to go into industry

00:54:27 and have that support, that leverage,

00:54:29 to be able to go into different avenues.

00:54:31 And I think TT Lab has really successfully done that.

00:54:34 And Professor Hussain has really

00:54:36 harnessed that in a great way.

00:54:37 - Yeah, and Professor, if you have to look at some of the

00:54:42 achievements, as it were, derived from TT Lab,

00:54:47 what jumps out at you?

00:54:48 Anything in particular?

00:54:51 - Well, a couple of things.

00:54:52 Several people have gone on to do PhDs abroad and at UE.

00:54:57 And it's, I would say some of it has to do with TT Lab

00:55:04 because the publications that they did at TT Lab

00:55:08 were used to apply to universities

00:55:10 and that helps quite a bit.

00:55:12 In fact, I keep telling students,

00:55:13 if they want to get into a good university,

00:55:15 if they have a publication record,

00:55:17 that helps a lot more than even high grades

00:55:20 because they want to see potential.

00:55:21 So that's one aspect.

00:55:24 The other aspect is people who want to work in industry.

00:55:28 So for instance, one company, for instance,

00:55:32 an insurance company has been hiring my students as interns.

00:55:36 We have this internship program where for a six month

00:55:39 period, the individual would work within the company

00:55:43 under my supervision, solve a problem,

00:55:46 do a proof of concept, and publish.

00:55:48 And 12 of those interns have been hired

00:55:53 within this one company.

00:55:54 Another company, they've hired 10 of these interns.

00:55:57 So what happens is that the internship illustrates

00:56:01 to the company the potential of these students

00:56:04 and they hire.

00:56:05 Some of these students actually negotiate salaries.

00:56:08 They start off as interns and when they are given an offer,

00:56:11 they actually negotiate because they've shown

00:56:14 what they could do.

00:56:15 - Yeah.

00:56:16 But doctor, do you, I think that we can say,

00:56:20 when we look at countries, let's say China, India,

00:56:25 the United States, and there is a rush of young people

00:56:30 to get into this sector.

00:56:32 Are we seeing that in Trinidad and Tobago?

00:56:34 Because I know that we in Trinidad, that some of us,

00:56:38 I should say, we still like traditional routes to follow.

00:56:43 So you're seeing more and more people getting

00:56:46 into this sort of education.

00:56:49 - Yes, and I actually think that people who are

00:56:51 like data scientists are very expansive field.

00:56:53 I mean, you have data analytics, you have data engineering,

00:56:56 you have other, and even if it's not called data science,

00:56:59 business analytics, if you go into financial companies,

00:57:02 you could fit in anywhere, to be fair.

00:57:04 So it's a very, very versatile area.

00:57:06 And I think it's right now, currently, I mean,

00:57:10 even in the master's program that the professor's

00:57:12 been involved in at the UE, you see a lot more,

00:57:15 the enrollment is quite high.

00:57:16 So there's a lot of great interest in the area.

00:57:19 There are a lot of courses online, micro credentials,

00:57:22 et cetera, so it really is growing.

00:57:23 And in Trinidad, it's really, I've seen it grow

00:57:26 and there's a great interest in it currently.

00:57:28 - Yeah, but you know, professor, and you did speak

00:57:32 about that, that when, even for university students,

00:57:37 it is sort of difficult for them to really decide,

00:57:42 look, what I want to do with this boy?

00:57:45 So it's a problem when it comes to navigating.

00:57:49 But so then the question is, should we be exposing

00:57:54 students, children, to this sort of study at an earlier age?

00:58:01 Or it could be too much for them?

00:58:04 - No, no, I think some of these things we do

00:58:07 could be started much earlier, but that's, you know,

00:58:10 way above my pay grade.

00:58:12 So I start with the material I have,

00:58:15 which is MSC students and bachelor's students.

00:58:18 So some of the bachelor's students, in fact,

00:58:21 do even better work than some of the graduate students,

00:58:24 post-grad students, because, you know,

00:58:27 I would point them to online courses.

00:58:29 Once they have the interest, they would learn

00:58:32 whatever they need to learn to solve the problem.

00:58:34 And that's what you need, that attitude.

00:58:37 And so, yeah, they can start at an earlier age,

00:58:40 but we have to develop a sort of model

00:58:45 that would encourage that type of--

00:58:46 - Of course, of course.

00:58:47 And it takes me back to you, doctor.

00:58:51 At what age you think that you would have begun

00:58:57 getting an interest into this course of study?

00:59:02 - Well, I think I've always loved math.

00:59:05 And that opened up the realm for me to actually understand.

00:59:09 There were so many avenues at first I wanted to,

00:59:11 I always wanted to teach something related to math.

00:59:13 But I think I got really serious about it

00:59:15 when I reached a secondary level, completing A levels,

00:59:19 and then really understanding that I can go into a more,

00:59:22 probably a more compact field like statistics.

00:59:25 But I really wanted to add to that,

00:59:28 in terms of the younger generation,

00:59:30 I do believe it's important for us to sort of guide them

00:59:34 from way before.

00:59:35 And it's really interesting because I'm currently involved

00:59:39 in some women in data science activities

00:59:41 with the large organization,

00:59:42 through the Stanford University,

00:59:44 where we have a next generation initiative

00:59:47 that we want to begin with secondary students

00:59:50 and lower to actually give them activities

00:59:54 to inspire them to understand what data science is.

00:59:59 How do you learn from data?

01:00:00 How do you build a story?

01:00:02 And I think I would say,

01:00:04 as young as you can get them to understand

01:00:06 that this is important, I believe it's really young.

01:00:09 It will really be beneficial later on.

01:00:11 - Yeah. - Yeah.

01:00:12 - And professor, as you look at the young people

01:00:16 who are involved in this industry, this course of study,

01:00:20 what do you see for them?

01:00:22 And what do you see for countries

01:00:23 like Trinidad and Tobago and the region?

01:00:25 - Well, there's a lot of talk about AI, et cetera.

01:00:30 And our focus is more on data science,

01:00:33 which is kind of a subset of AI.

01:00:35 The nice thing about it is it applies to any industry.

01:00:41 It applies to government, it applies to academia, et cetera.

01:00:46 So potential for jobs is great.

01:00:50 Some countries are in desperate need of good data scientists.

01:00:55 So the thing is we produce very analytical students.

01:01:00 So they are prepped for this type of data science,

01:01:06 analytical stuff.

01:01:08 So we need to take advantage of that.

01:01:10 I know there's a heavy push for developing apps, et cetera,

01:01:15 but you have millions doing that stuff in India, China,

01:01:20 all over the world.

01:01:21 So where we could compete is at the higher level.

01:01:24 I always look at it as software engineering, et cetera,

01:01:27 app development.

01:01:28 But beyond that, development of the algorithms behind

01:01:32 is where we have an impact.

01:01:34 - I think it is safe to say it's a wide world

01:01:38 of opportunities available.

01:01:40 - Oh yes, yes.

01:01:41 I've had companies from abroad ask me

01:01:46 to supply them with data scientists.

01:01:49 So yeah, so there's a growing need for it.

01:01:51 - Yeah, Professor, it was a pleasure speaking with you.

01:01:53 Doctor, it was a pleasure.

01:01:55 Thank you very much for coming this morning.

01:01:57 I think our discussion has been eye opening

01:02:00 for a number of people.

01:02:01 So thank you again.

01:02:02 - Thank you very much. - So we are going

01:02:02 to a very short break.

01:02:03 We are coming back.

01:02:04 (upbeat music)

01:02:07 (upbeat music)

01:02:09 All right, so welcome back everyone.

01:02:30 So again, we are at the Hyatt, at the big data forum.

01:02:36 And joining us now, we do have Dale Wilson

01:02:38 and also Akash Hariram from Teleos.

01:02:43 Gentlemen, thank you very much for coming this morning.

01:02:45 - Good morning. - Good morning.

01:02:46 - All right, so Dale, let's look at your involvement

01:02:50 in this year's big data forum that zeroes in

01:02:54 on the prompt engineering.

01:02:56 Prompt engineering is a fascinating

01:03:00 and specialized field within AI.

01:03:04 - Yes, so prompt engineering came into the fore

01:03:08 late last year when OpenAI released ChatGPT,

01:03:12 which is a more publicly facing type of AI system

01:03:16 that people interface with natural language.

01:03:19 And so prompt engineering is the ability

01:03:21 to interface with these systems using normal English.

01:03:24 And there is a design to it that allows you

01:03:27 to maximize what the output from the system does.

01:03:31 So prompt engineering is about creating those inputs,

01:03:35 making sure that the system understands

01:03:37 what you're asking it so that you can get the best results.

01:03:40 - All right, Dale, so for people like me

01:03:43 who are not too tech savvy and so on,

01:03:45 give us an example, how is this going to be used?

01:03:48 - Okay, so let me start with a non-computer example.

01:03:52 If I told you, Marlon, go buy me a newspaper.

01:03:56 That is something you can do.

01:03:58 But I haven't given you any details.

01:04:00 You can go anywhere and buy any newspaper.

01:04:02 But if I say to you, Marlon, go down to Independence Square,

01:04:06 you will see a newspaper vendor in front of KFC.

01:04:11 I want you to buy me a Trinidad Express.

01:04:14 Then that prompts you to do something very different.

01:04:17 - And specific.

01:04:18 - Exactly, so I get exactly what I want.

01:04:21 You don't waste time having to look all over the place.

01:04:23 You go directly and you execute.

01:04:25 - A more focused approach.

01:04:26 - That's right, so that essentially

01:04:27 is what prompt engineering does for the AI systems.

01:04:30 You give it specific directions or specific instructions,

01:04:34 or you ask your question in a specific way

01:04:36 to get the answer or the response that you want.

01:04:39 - Yeah, Dale, that's good, Dale.

01:04:40 All right, so Akash, so the prompt engineering competition

01:04:44 seems like a fantastic way to engage students.

01:04:47 Can you tell us more about how it was conceived

01:04:50 and the objectives of this innovative competition?

01:04:53 - Sure, so at TELUS, we have a weekly recurring meeting

01:04:58 called Power Hour, and it's a meeting

01:05:00 where most of the company gets together

01:05:02 and we discuss the latest trends

01:05:04 and innovations happening in tech.

01:05:06 And it's at one of these Power Hour sessions

01:05:09 where the idea behind the prompt engineering competition

01:05:12 came about, and really we wanted to allow students

01:05:17 to experience the power of prompt engineering

01:05:20 in a very visual manner.

01:05:21 So that's where we came up with the idea

01:05:23 for an interactive AI-driven game.

01:05:26 So the students will innovate and create their prompts,

01:05:31 and they will see in real time their prompts being executed

01:05:36 before their very eyes.

01:05:37 - Yeah, what has the response been?

01:05:39 - It's been overwhelmingly positive.

01:05:41 So we had a couple sessions with the students

01:05:44 and we spoke to them,

01:05:46 and their response has been phenomenal so far.

01:05:49 - Yeah, if you say phenomenal,

01:05:52 so is it that they would have had

01:05:54 some experience with it before?

01:05:56 - Some of them did, yes.

01:05:58 So some of them would have used models like ChartGPT before.

01:06:02 They would have had experience with crafting their prompts,

01:06:06 but this gives them the ability

01:06:08 to actually go further than that.

01:06:11 So they will actually, we have a test arena

01:06:13 that is open right now that the students

01:06:15 are currently engaging with their battle bots,

01:06:20 providing prompts to them and seeing the results

01:06:23 of those prompts in real time.

01:06:24 - Yeah, and Dale, what Akash has told us,

01:06:28 I suspect to some people,

01:06:30 it may be surprising that so many young people

01:06:33 are involved in this sort of activity.

01:06:38 Why is this so important, you think,

01:06:40 to expose our young people to this?

01:06:45 I suspect as an early age too.

01:06:47 - Yeah, because remember, they are growing up in an age

01:06:49 where this will be normal for them.

01:06:51 So I guess the previous generation

01:06:55 would have grown up with the internet.

01:06:57 They don't know life without the internet.

01:07:00 The upcoming generation,

01:07:01 the same thing will apply for AI for them.

01:07:04 So they need to be able to be comfortable

01:07:07 with the technology.

01:07:08 They need to be able to interact with it

01:07:10 and to be able to grow with it

01:07:11 because it is going to continue to evolve.

01:07:14 It is going to continue to change.

01:07:15 So the sooner we get them involved in it

01:07:17 is the better for them.

01:07:18 - Yeah, and we have seen recent challenges locally

01:07:22 with respect to cyber security and ethical use of data.

01:07:26 With AI and big data becoming increasingly prevalent,

01:07:30 how does TELIOS ensure that their educational initiatives

01:07:35 keep ethical considerations?

01:07:38 - Oh, I guess the key thing there is awareness.

01:07:40 So one of the things we did,

01:07:41 we had a couple of sessions with the students

01:07:43 to introduce them to AI for those of them

01:07:46 who weren't familiar with it.

01:07:47 And one of these sessions dealt with ethics,

01:07:52 things like data privacy,

01:07:54 things like the capacity for fraud,

01:07:56 deep fakes and that kind of thing,

01:07:58 bias in AI,

01:08:00 because a lot of these systems are trained on existing data.

01:08:03 So if the data itself contains biases,

01:08:07 then the system will have a biased output.

01:08:10 So these are things that I guess all of us

01:08:12 have to be cognizant of.

01:08:13 So when we are designing systems,

01:08:15 we have to make sure that those systems are fair,

01:08:18 that they take all of these things into consideration

01:08:21 so that nobody is left disenfranchised.

01:08:24 - Yeah, and Akash, inclusivity I suspect

01:08:27 is critical in education,

01:08:29 especially regarding new technologies and so on.

01:08:34 Beyond Big Data Forum,

01:08:36 beyond the Big Data Forum and this competition,

01:08:39 how does TELIOS plan to ensure that students

01:08:42 from all backgrounds participate

01:08:45 and get the opportunity?

01:08:47 - Right, so with the latest advances in AI,

01:08:50 this actually has the ability

01:08:53 to break down a lot of barriers.

01:08:54 So instead of you having to interface

01:08:57 with software systems using your mouse

01:08:59 or your keyboard and stuff like that,

01:09:02 you can actually enact a language,

01:09:04 a natural language,

01:09:05 and thereby make things happen.

01:09:09 So you can control your programs,

01:09:11 you can do things just by you speaking

01:09:14 in your very natural way.

01:09:16 So that allows for anybody potentially

01:09:20 to use AI effectively.

01:09:23 So that's pretty much breaking down a bunch of barriers

01:09:28 that people would have traditionally with software systems.

01:09:32 - Yeah.

01:09:33 Dale, as we look towards the future,

01:09:38 what is the next big milestone for TELIOS?

01:09:42 - Well, I think we want to continue

01:09:43 to contribute to the economy,

01:09:47 to continue to make an impact on people's lives.

01:09:49 These are things that we are continuing

01:09:51 to discuss internally.

01:09:52 So we will, just the other day,

01:09:54 we'll be reviewing our mission and vision

01:09:57 and so on for the company.

01:09:59 And I guess at the core of who we are,

01:10:02 what we want to do really is to make people's lives easier.

01:10:05 And that actually is our new mission statement.

01:10:08 We make life easier.

01:10:10 And so therefore, as we continue to provide solutions

01:10:13 for our clients, that really is the core

01:10:16 of what we want to be able to do,

01:10:17 to solve people's problems.

01:10:20 It's not just about the technology,

01:10:21 but we want to provide solutions

01:10:23 and the solutions have to meet the needs of the people.

01:10:26 So that's our focus.

01:10:27 - Yeah.

01:10:28 And Akash, as we look at technology

01:10:31 and as we look at countries such as Trinidad and Tobago

01:10:35 and others in the region,

01:10:37 let's look at over the next five years,

01:10:39 what do you see?

01:10:41 - Well, right now AI is becoming very prevalent.

01:10:45 So across all of your different areas,

01:10:47 healthcare, education, everything is going to be touched

01:10:51 in some way by AI.

01:10:53 And that's just going to increase exponentially

01:10:55 over the coming months and years.

01:10:57 So I expect that many people will need to interface

01:11:01 with these types of technologies,

01:11:03 potentially on a daily basis.

01:11:04 It will affect your workplace,

01:11:06 it's going to affect how you learn things,

01:11:09 it's going to be very far reaching

01:11:11 and you're going to need to learn

01:11:13 how to use it effectively.

01:11:15 - Yeah.

01:11:15 But Dale, why is it that you think that AI

01:11:19 got just such a bad rap just maybe earlier this year

01:11:24 or until late last year?

01:11:27 Because to people like you in this industry,

01:11:31 AI would not have been something new.

01:11:35 - No.

01:11:35 - But I think to the general public

01:11:37 or people outside this industry,

01:11:39 it was something new.

01:11:40 And as I said earlier,

01:11:42 the reports that we were getting internationally

01:11:45 was that AI was not good.

01:11:47 And I think in recent months,

01:11:49 we have seen that narrative change.

01:11:52 So the question is, why was it given this bad rap?

01:11:57 - Right, I guess AI, as with any technology,

01:12:03 you have good uses and you have bad uses.

01:12:05 So AI, as you said, is not new.

01:12:07 It's been around for many, many years

01:12:09 and people interact with it daily

01:12:11 and don't know that they're doing it.

01:12:13 If you're shopping on Amazon,

01:12:14 if you're watching Netflix,

01:12:16 if you're using Google Maps,

01:12:17 always AI is behind that.

01:12:20 It came to the public for, like I said,

01:12:22 last year, late last year,

01:12:23 when OpenAI released ChatGBT.

01:12:25 So that was a very public facing thing.

01:12:28 And so it came to light in a more prominent way.

01:12:35 But as much as we are using it for good,

01:12:37 you have threat actors out there

01:12:39 who are using it for purposes that are not good.

01:12:44 So the whole issue of deception,

01:12:45 the whole issue of fraud,

01:12:47 we have threat actors that are using AI

01:12:50 to make their cyber security attacks much more complex.

01:12:55 So I think that is part of the reason

01:12:59 why it is getting a bad rap.

01:13:03 The other thing, of course, is,

01:13:05 I think a few months ago,

01:13:07 some of the subject matter experts in the space,

01:13:10 they came together and said,

01:13:12 "Look, we need to slow down a bit

01:13:14 on the rapid development that is happening

01:13:18 because this thing can go beyond

01:13:20 where we think it can go.

01:13:22 And there are dangers that we need to be mindful of."

01:13:26 And so there was a meeting of governments last month,

01:13:30 I think, to talk about the ethical

01:13:32 considerations and to develop rules

01:13:36 about how AI is developed.

01:13:38 So those are things that are going to be ongoing.

01:13:41 There'll be debates, there'll be discussions about it.

01:13:43 Those things are not going to stop.

01:13:45 Some people are afraid of a Terminator-type future

01:13:49 where AI takes over and launches nuclear weapons

01:13:52 and destroys humanity.

01:13:53 That is on the extreme side of it.

01:13:58 But what the experts are saying is

01:14:00 we do need to be careful.

01:14:02 Because it's advancing so quickly

01:14:06 that the systems will be capable of things

01:14:10 that maybe we didn't intend them to.

01:14:13 And so we need to ensure that the guardrails are in place

01:14:16 so that they don't take over, so to speak.

01:14:19 - Yeah.

01:14:19 So Akash, I think it is safe to say that systems,

01:14:23 protection systems, are being put in place.

01:14:27 So the narrative of AI destroying mankind

01:14:32 I suspect it's far-fetched.

01:14:35 - Yeah, so for the most part,

01:14:37 the guardrails that Dale mentioned are being put in place.

01:14:41 But of course, it's still a tool,

01:14:44 and a tool can still be used for good purposes

01:14:46 or bad purposes.

01:14:47 So at the end of the day, what actually needs to happen

01:14:50 is we need to instill in the young people, the students,

01:14:53 for instance, in the competition,

01:14:55 at an early age, about the potential for AI

01:14:58 to be used for good and be used for bad purposes.

01:15:02 So that needs to happen quickly

01:15:06 because we enter into a world

01:15:08 where they're going to be exposed to AI very, very young.

01:15:13 - Yeah, and you're seeing already, Dale,

01:15:16 where countries of the Caribbean are embracing the AI.

01:15:20 - Yeah, I think generally speaking--

01:15:22 - They're coming along.

01:15:23 - People are seeing the benefits of it.

01:15:27 So what we have to do now is to determine

01:15:29 what are the best use cases to be able to apply it

01:15:31 inside of our societies and our countries.

01:15:36 So that is coming along.

01:15:37 I think people have already jumped on the bandwagon.

01:15:40 We're starting to see applications popping up.

01:15:43 So we hope that it is a trend that will continue.

01:15:46 And like we said, we want the young people

01:15:48 to be able to be a part of that revolution.

01:15:51 - Yeah, for business organizations,

01:15:54 the use of AI or the implementation of AI

01:15:58 into organizations, is it expensive undertaking?

01:16:03 - Not necessarily.

01:16:06 I guess it depends on the use case.

01:16:09 So for example, we have a booth here at the Data Forum

01:16:14 demonstrating a use case for using AI

01:16:19 as part of a customer experience enhancing solution.

01:16:24 If you think about some of the websites we have

01:16:27 that have chatbots, based on what we've researched,

01:16:32 a lot of people aren't satisfied with the interactions

01:16:35 that they have with these bots.

01:16:38 But you can use AI to enhance that experience

01:16:43 so that people are able to get answers

01:16:45 to the questions that they're asking

01:16:46 without having to go to a human agent.

01:16:49 So it saves them time.

01:16:50 So that's a simple application of how AI can work for you

01:16:54 in a very short, short-term period.

01:16:56 So those things are happening.

01:16:59 And like you said, we have a demonstration of that

01:17:01 at our booth.

01:17:02 But then you have AI being used

01:17:04 inside of machine learning type of scenarios

01:17:08 where companies are looking for future casting,

01:17:12 trend analysis, business analysis, that kind of thing.

01:17:15 Those things are also happening as well.

01:17:18 And then of course you have those who are doing things

01:17:21 with weather and doing things like climate,

01:17:26 climate, sorry,

01:17:31 analyzing climate change and those kinds of things.

01:17:37 So yeah, it doesn't have to be expensive,

01:17:41 but it depends on the use case.

01:17:43 - Yeah.

01:17:44 Akash, I think it is safe to say it's here, you know?

01:17:47 So you're going to have to use it and embrace it, right?

01:17:49 - Yes.

01:17:50 - Yeah.

01:17:51 Gentlemen, it was a pleasure speaking with you

01:17:53 all this morning.

01:17:54 Thank you for all of the information

01:17:56 that you have given to us this morning.

01:17:57 It has been eye opening and we do appreciate it.

01:18:00 Thank you.

01:18:00 - Thank you for having us.

01:18:01 - Okay, of course.

01:18:02 We are going to a very short break again.

01:18:04 We are coming back.

01:18:05 (upbeat music)

01:18:09 (upbeat music continues)

01:18:12 (upbeat music continues)

01:18:16 (upbeat music continues)

01:18:19 - Hi everyone.

01:18:44 We are continuing our discussion from the Hyatt

01:18:46 this morning and on the big data forum

01:18:51 that we continue to speak about.

01:18:53 So we are now joined by Vijay Pradeep.

01:18:57 And Vijay Pradeep, he is the founder

01:18:59 and chief technology officer of Vertana.

01:19:02 Now he's a robotics engineer and angel investor

01:19:06 and has been involved in the robotics sector

01:19:08 for the past 15 years.

01:19:10 Now Vijay moved to Trinidad in 2017 to start Vertana,

01:19:15 a robotics software development and consulting company

01:19:19 aiming to grow the Caribbean's impact

01:19:22 in the global robotics ecosystem.

01:19:25 Vijay, it's a pleasure to have you here.

01:19:28 - Thank you for having me.

01:19:29 - When we think about robotics, Vijay,

01:19:32 we don't necessarily think about Trinidad and Tobago.

01:19:37 I suspect it is, how do I say, a new industry

01:19:42 that you and I suspect some of your colleagues

01:19:46 are trying to create in Trinidad and Tobago.

01:19:48 - Yes, that's totally, totally correct.

01:19:51 I mean, I wasn't necessarily thinking about Trinidad

01:19:55 and Tobago in terms of robotics as well.

01:19:57 What really sparked a lot of this was

01:20:00 when I first started learning about Trinidad and Tobago

01:20:03 as a country and as a tech ecosystem,

01:20:05 there were, what I got exposed to

01:20:08 were so many new graduates

01:20:10 that had such strong technical skills

01:20:12 that didn't necessarily have the opportunities locally

01:20:15 to really extend those skills and blossom it into careers

01:20:18 and continue to grow their trajectory of growth,

01:20:20 have that trajectory of growth in technology.

01:20:23 So I thought that starting Vertana was a really great way

01:20:26 to give these engineers opportunities

01:20:28 to work on cutting edge problems

01:20:30 in a cutting edge field like robotics

01:20:32 with advanced companies all across the world.

01:20:35 - Yeah, and you have been in this sector

01:20:39 for the past 15 years.

01:20:41 Is it that that is how long you have been in the industry

01:20:46 in Trinidad and Tobago?

01:20:48 - So I'm relatively new to Trinidad and Tobago.

01:20:50 - Yes, okay.

01:20:51 - If we rewind, like growing up,

01:20:54 I really didn't have any connection to Trinidad and Tobago.

01:20:56 I was born and raised in the US.

01:20:58 - Yes.

01:20:59 - My parents are from India.

01:21:00 - Okay.

01:21:00 - So I guess my connection to Trinidad was

01:21:02 when I was out in Silicon Valley in San Francisco,

01:21:06 I ended up meeting my now wife, who's Trinidadian.

01:21:09 - Yeah, that's a good reason, PJ.

01:21:12 Good reason.

01:21:13 - Yeah, and I mean, through her,

01:21:14 I ended up learning more about the country,

01:21:16 more about the ecosystem and all of that.

01:21:17 And that's what eventually led to both me and her

01:21:21 deciding to move here in 2017.

01:21:25 Me building out a tech ecosystem in robotics,

01:21:29 robotics and AI, and she's building out a tech ecosystem

01:21:32 in bioinformatics and biotechnology.

01:21:33 - Yeah.

01:21:34 But tell us a little bit more about

01:21:38 the work of your company.

01:21:40 Because when we think about robotics,

01:21:42 I believe that maybe we have

01:21:45 a sort of one-minded focus as to what robotics is.

01:21:52 We're seeing robots.

01:21:55 So I want you to just expand on knowledge this morning

01:21:59 and speak a little bit about how robotics

01:22:03 are being used in Trinidad and Tobago

01:22:06 and how it is being, it is playing out

01:22:09 in Trinidad and Tobago.

01:22:10 - Yeah, I think that's a great question.

01:22:12 You alluded to it already.

01:22:13 When we think about robots, we think about something

01:22:15 with two arms and two legs running around,

01:22:18 like doing chores in our house.

01:22:20 And I think robotics takes so many more forms than that.

01:22:24 Like a lot of the work that we do at Vertana

01:22:26 is robots that don't necessarily look like that.

01:22:29 And the robots that don't,

01:22:32 what those robots do that we work on is very much,

01:22:36 we work on drones that do delivery.

01:22:38 We work on robots that are helping to harvest crops

01:22:41 or work on manufacturing lines,

01:22:43 pick up parts off of shelves in warehouses.

01:22:45 But a lot of the projects that we're working on right now

01:22:48 are very international-focused,

01:22:49 working with international companies,

01:22:51 international projects.

01:22:53 And we're building that tech talent locally

01:22:55 that we hope can start working on more applications

01:22:57 in the local ecosystem as well.

01:22:59 - All right, so is it safe to say that most of the work

01:23:03 that you are doing, it's for international companies

01:23:07 and not necessarily companies in Trinidad and Tobago?

01:23:10 - At the moment, that's correct.

01:23:12 We're using our international clients

01:23:15 to build up the company, build up our team,

01:23:16 build up our expertise.

01:23:18 And now we have a team here, a team of 20,

01:23:20 all based in Trinidad and Tobago

01:23:22 that now have the expertise to start tackling problems

01:23:25 that can have local importance and local impact as well.

01:23:28 - But has the word and the message

01:23:31 about what your company is doing,

01:23:34 is it spreading in Trinidad and Tobago?

01:23:36 And I say that on the basis,

01:23:38 so if the word is spreading about the work that you're doing,

01:23:41 I think it is safe to say that more local companies

01:23:44 may be interested.

01:23:47 So is the word getting out?

01:23:48 - Yes, I think more and more companies are excited

01:23:52 about using the types of technologies we're working on,

01:23:55 especially in areas like manufacturing,

01:23:57 let's say, logistics.

01:23:59 These are things that are really interesting

01:24:01 to companies locally.

01:24:02 Making investments in some of these

01:24:05 more advanced technologies.

01:24:07 There are some technologies

01:24:08 that you can start using immediately.

01:24:10 There were some conversations that you were having earlier

01:24:13 today around chat GPT and prompt engineering

01:24:15 where companies can use it immediately.

01:24:16 Some of the other technologies are robotics.

01:24:18 It takes a little bit more investment,

01:24:20 a little bit more patience for it to come to fruition,

01:24:23 which we're happy to work on

01:24:26 and we're happy to support locally,

01:24:27 but it does take more time

01:24:28 and a little bit more investment to bring that to reality.

01:24:30 - Do you think that there is an interest

01:24:33 by local companies here to use robotics?

01:24:37 - I think the interest is there.

01:24:40 I think what's needed is both the expertise

01:24:45 that we are building,

01:24:47 along with expertise in the broader ecosystem as well,

01:24:51 to really start to build these systems at scale

01:24:53 in the Caribbean.

01:24:55 And I think that requires companies

01:24:59 that might be interested in robotics.

01:25:00 I mean, relying on companies like ours,

01:25:01 of Vertana would be great,

01:25:02 but also looking to invest

01:25:04 in building that talent themselves as well

01:25:06 to support these systems,

01:25:08 deploy them and sort of work together collaboratively

01:25:11 to build these, to deploy these types of solutions.

01:25:15 - Vijay, if people, businesses,

01:25:18 businesses, business leaders

01:25:19 want to get in touch with your company,

01:25:21 how do they do that?

01:25:23 - Yeah, if they happen to be here at the Big Data Forum,

01:25:27 please, please come out and reach out to me

01:25:29 in the next two days.

01:25:31 They can check us out online at vertanatech.com.

01:25:35 I would, we would be more than happy to check out,

01:25:37 more than happy to talk to them as well.

01:25:39 - All right, Vijay, stay with us for a few minutes more.

01:25:42 We are going to a very short break.

01:25:43 We are coming back.

01:25:44 (soft music)

01:25:47 (upbeat music)

01:25:59 And welcome back everyone.

01:26:08 And still with us this morning,

01:26:10 Vijay Pradeep, founder and chief technology officer

01:26:13 of Vertana.

01:26:14 Vijay, let's speak a little bit about some of the work

01:26:16 that you have been doing with the UN

01:26:17 in Trinidad and Tobago.

01:26:19 - Yeah, I was connected to the UN team

01:26:25 a few years ago, actually.

01:26:26 They were thinking about big data

01:26:28 in the context of the Caribbean

01:26:30 and also what it would take to build a robotics ecosystem.

01:26:33 So I'm excited to have helped be a part of shaping

01:26:37 that direction and the vision of what the UN

01:26:39 has been trying to do of creating a robotics ecosystem

01:26:41 in Trinidad and Tobago.

01:26:43 And I think Vertana is excited to be a part of that

01:26:46 and shaping the narrative around how we can have

01:26:48 more impact locally,

01:26:49 how we can build an export focused robotics industry as well.

01:26:52 I think all of these are key factors

01:26:54 to really making this a reality and a healthy ecosystem.

01:26:56 - Yeah, and I think Vijay that more and more information

01:27:01 needs to come out as it relates to how beneficial robotics

01:27:06 could be to a business organization.

01:27:08 If you had the opportunity to speak about that,

01:27:11 let's speak about the benefits to a business organization

01:27:14 using robotics.

01:27:16 - Yeah, I think a lot of the macroeconomic narrative here

01:27:20 in Trinidad around, let's say a manufacturing business

01:27:23 or other businesses or other export businesses

01:27:26 has been around, we're a low cost of operating

01:27:30 or a low wage economy.

01:27:32 So bring your business here, help build your goods here.

01:27:35 And I think I like to think of the flip side

01:27:38 of that narrative, which is maybe our wages

01:27:41 are actually not that low.

01:27:42 Maybe it's actually not that cheap to be producing

01:27:45 these goods and exporting these goods in Trinidad.

01:27:47 What we should be doing is figuring out

01:27:49 what are the highest value, most sophisticated goods

01:27:52 that we can be producing that can command

01:27:55 the highest retail prices.

01:27:57 So maybe that's aerospace, maybe that's advanced robotics

01:28:01 parts and things like that.

01:28:02 And I think those are the types of things

01:28:03 that we could be building here in Trinidad and Tobago

01:28:05 on exporting and doing that requires advanced technologies

01:28:08 like robotics and AI to make sure we're hitting

01:28:10 the right quality, the right consistency and reliability

01:28:12 to actually producing those parts.

01:28:13 - I think what you have done Vijay is to tell us

01:28:16 about the number of opportunities available

01:28:21 in this industry.

01:28:22 And when we as a country speak about diversification,

01:28:26 maybe that's a sector that we should be looking at.

01:28:30 - Yeah, I totally agree.

01:28:31 And this is one example of exporting physical goods.

01:28:34 I like to just remind people that we're also just,

01:28:38 we're a knowledge business, we're a services business

01:28:40 and we're exporting our services internationally, globally,

01:28:44 building local talent, providing good wages to our staff

01:28:49 and continuing to hire and producing foreign exchange

01:28:52 at the same time with nothing leaving the ports

01:28:55 for the goods and the services that we're providing,

01:28:58 which I think is a really powerful thing.

01:28:59 - Yeah, I would think Vijay that we,

01:29:04 robotics we're really at the infancy stage

01:29:08 in Trinidad and Tobago, right?

01:29:09 You would say so?

01:29:10 - Yeah, I agree, but I also think the future is bright.

01:29:13 I think there's a lot of room to continue

01:29:14 to grow the industry.

01:29:15 We're growing that ecosystem.

01:29:17 We've already shown that we can build a business

01:29:19 that's exporting these services.

01:29:21 And I think the next step from here is creating

01:29:24 many businesses that are focusing on specific verticals

01:29:27 and specific areas that are doing more

01:29:28 in the field of robotics.

01:29:29 And we are just one of many companies to come

01:29:32 to really build a mature, healthy,

01:29:35 and really blossoming ecosystem in robotics.

01:29:38 - But Vijay, how do we compete?

01:29:40 If we're talking about Silicon Valley,

01:29:42 if we're talking about the activities in China,

01:29:45 if we're talking about activities in other parts

01:29:48 of the world who are known to have a history

01:29:52 of robotics and technology and data and so on,

01:29:55 how does a small country like Trinidad and Tobago compete?

01:29:59 - Yeah, I mean, other ecosystems,

01:30:02 I mean, for the longest time,

01:30:03 China didn't have automation in robotics.

01:30:05 It was new for them as well.

01:30:06 And I think it's important to remember,

01:30:08 like we have the educational system.

01:30:10 We have a very trained, we have so many students

01:30:15 that have the expertise and the raw skills

01:30:16 to be working in these fields.

01:30:18 We just need to build a little bit more scaffolding

01:30:20 around it to let them blossom in their careers

01:30:22 and build these ecosystems.

01:30:23 - Right.

01:30:24 - One point I'll say is that when we talk about

01:30:26 like building parts, it's very normal for parts

01:30:29 to be shipped from China or let's say Seattle,

01:30:32 the West Coast of the US, to places like Miami

01:30:34 to assemble larger, more complex aerospace systems.

01:30:37 If parts are being shipped halfway across the world,

01:30:40 why can't they be shipped from Trinidad?

01:30:42 I think it's totally possible,

01:30:44 and we just need to have focus and patience

01:30:45 to build that ecosystem.

01:30:46 - Yeah, I think what it is telling when you're saying that,

01:30:51 I think that we do have the educational system in place

01:30:55 and certain infrastructure in place

01:30:58 to make the robotics industry possible.

01:31:03 I think that's what you're saying.

01:31:04 - Yeah, exactly.

01:31:05 I would add one piece to that,

01:31:06 which is that there are the raw skills,

01:31:10 the technical skills that are needed.

01:31:11 I think what we need is encouraging more of our youth,

01:31:14 more of our young professionals

01:31:16 to be willing to take more risks, be more curious,

01:31:18 be more entrepreneurial, be willing to take those big swings

01:31:22 at tackling hard problems,

01:31:24 and know that there's the beginnings of an ecosystem,

01:31:28 companies like Vertana and myself

01:31:29 that are willing to help them through that journey

01:31:31 and figure out how to navigate that

01:31:33 and build those new industries and companies.

01:31:34 - Yeah, some of us are not brave like you.

01:31:37 (laughs)

01:31:39 As you look at the future for your company,

01:31:44 what do you see?

01:31:46 - Yeah, I mean, I see, I'm excited that,

01:31:50 I mean, I was the sole founder of the company,

01:31:52 and I'm excited that as we're continuing to grow,

01:31:54 I've brought in more people into the leadership team,

01:31:57 we're continuing to grow.

01:31:58 We're 20 people right now,

01:31:59 but we see our growth continuing to happen.

01:32:01 And I see us going beyond just doing consulting

01:32:05 for international companies.

01:32:06 We alluded to it in the interview already,

01:32:08 but working on more local applications,

01:32:10 solving local challenges,

01:32:11 maybe around national security or infrastructure,

01:32:15 or helping other businesses become more effective

01:32:17 in providing more advanced goods to the rest of the world.

01:32:20 - Yeah, and you feel that the opportunities are there

01:32:23 and the future is bright.

01:32:25 - Yes, 100%. - Robotics.

01:32:26 - Yeah. - Yeah.

01:32:27 Vijay, it was a pleasure speaking with you this morning.

01:32:30 I think that it's an issue that we don't talk about

01:32:35 too much in Trinidad and Tobago,

01:32:36 and thank you very much for shining that light

01:32:40 on robotics in Trinidad and Tobago.

01:32:42 We do thank you very much.

01:32:44 Thank you for coming this morning.

01:32:45 - Thank you so much. - Yeah, okay.

01:32:47 So that's gonna do it, everybody.

01:32:49 As we have been for the past two hours at the Big Data,

01:32:55 the UN's Big Data Forum that is being held at the Hyatt.

01:33:00 Thank you to the UN for making this possible this morning.

01:33:03 Thank you very much to our technical team, our guests.

01:33:07 Thank you very much.

01:33:09 See you tomorrow, everybody.

01:33:10 Have a good day.

01:33:11 Bye for now.

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