- 2 days ago
Datuk Syed Haizam Jamalullail and Zubin Rada Krishnan, Partners at The Hive Global AI Fund, discuss how Malaysia can position itself as a global hub for AI-driven services. In this episode of The Economy with Ibrahim Sani, they explore the nation’s competitive advantages, talent readiness, and the strategic investments needed to accelerate AI adoption across industries.
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00:07Thanks for joining us. This is The Economy with me, Ibrahim Sani.
00:10We're going to be looking into investing into the AI space in my office right now.
00:16Two gentlemen that are pretty much clued in into this space so that we can learn a little bit more.
00:22To my right is Dato' Syed Haizam Jamalulayl, the partner of the Hive Global AI Fund.
00:26And his partner, Zubin Radha Krishnan.
00:31Maybe before we jump into the whole topic, maybe Aizam you can share a little bit in terms of the
00:36fund.
00:37Who are you guys all about? Where do you guys enter? What kind of geographies do you operate?
00:42Okay, so currently I run the Hive South East Asia which is a venture capital fund under right now is
00:48Jelawang Capital.
00:49The mandate in 2021 that we got it was to invest into companies that will digitize Malaysia into the fourth
00:54industrial revolution.
00:55We are fully invested right now. We've invested into 13 different companies, early stage, pre-series A.
01:02And now we are into our next fund. We're looking to launch and raise our next fund which is in
01:10the AI space, the Hive Global AI Fund.
01:12And Zubin joined me from, previously he was at BigPay, he was the CEO of BigPay and he's now joined
01:18me on the Hive Global AI Fund.
01:21As you know, AI is everywhere. It's become a general technology for everything.
01:25And it's a partnership between our Hive US and the Hive Southeast Asia to create this Hive Global AI Fund.
01:33So we will be investing into companies in the US as well as Southeast Asia that will really dive in
01:43to enable this AI revolution.
01:46And the point of entry will be pre-seed and pre-series AI, I suppose?
01:50Yes. We even co-create companies. So at this very moment in time, we'll talk about it a little bit
01:57further later.
01:58But we are building a company called Rakantani in the agri-tech space.
02:04And we are partnering with the likes of Brenas.
02:08And we are talking with the National AI Office.
02:12So we have a partnership with the National AI Office called the National AI Office Lab.
02:17And we're building a company called Rakantani, which I guess, Zubin, you can go a bit deeper.
02:22Well, Rakantani is an interesting one.
02:24So we have co-created this alongside a corporate partner, Brenas.
02:29What it is, is an AI co-pilot that a farmer can access via WhatsApp.
02:34So it's an AI brain, a multi-model kind of stack that we use to deliver all of the farming
02:41knowledge and expertise that Brenas and our universities and Mardi have aggregated over the years.
02:47But normally they find it very hard to communicate to the farmer.
02:51Because when you're a paddy farmer, the last thing you want to do is sit in a classroom for two
02:55hours and listen to an agricultural extension officer, you know, lecturing about how to do the farming.
03:02What we created is the ability for the farmer to essentially talk to a digital expert at any time to
03:09understand what they should do at any point in time.
03:11And so that's accessible via WhatsApp in Bahasa Melayu or any local dialects as well.
03:17So what in essence this does is enables a farmer to follow a schedule more accurately and do things to
03:25specification, which will enhance the yield and the quality of the rice, which improves food security for the country, for
03:31Malaysia.
03:32It improves outcomes for Bernas and for the welfare of the farmers as a whole.
03:38But of course, this is one of the items you're looking at.
03:42Zooming out and looking into AI per se, there's a whole host of issues when it comes to talking about
03:50AI.
03:50One of the big issues is, of course, is there an AI bubble, to be honest?
03:54How, what's your view on that?
03:57Yeah, I think bubbles are interesting ones.
04:02There's two kind of ways people look at bubbles.
04:04One is like, you know, a bubble that is a mean reversion.
04:08That means like asset prices go up and then they go back because of speculation like tulips.
04:13Like nothing really, you know, came out of that.
04:17But there are also bubbles which are inflection points where, yes, there's a lot of interest, there's a lot of
04:25investment going in and asset prices can go up.
04:28But at the end of the day, society will change because of this investment, because of this rush.
04:33And this is like the same as railroads in America in historical times, right?
04:38So I think, yes, maybe there's a little bit of a bubble.
04:40There's a lot of interest, but it will yield us great things from a societal perspective.
04:46AI has evolved into, from a tech trend, so the bubble related era, into a fundamental capability, similar to the
04:55internet, similar, go way back into like the steam engine, etc.
05:00So, you know, right now the advanced AI models are mainly helped by the largest players around the world.
05:05So the China is of the world, the US is of the world, and it's very high cost.
05:08But we can play in that application space.
05:10And, you know, with regards to the language models, etc., it's the winner or takes most, if not all.
05:20So that's the bubble.
05:22But with the application space, if you are going down into identifying problem statements and building according to that, then
05:31it can be very, very effective.
05:33What about AI services as a role and looking into players in this slither of the large AI landscape?
05:43Where do you see that AI services growth looking like?
05:45Do we have emerging players that might be of interest for you guys?
05:49And more importantly, do you think that some of these players are better off amalgamated so that they can actually
05:55share resources and scale better?
05:56So, the interesting question, I think, first, I think back to your point about kind of AI as a bubble
06:02and so on and the AI landscape, we are, I think, very, very early in the adoption curve, in the
06:11pathway to adoption.
06:13A lot of things now are really just, when people talk, people cite this MIT study that was done last
06:20year about how, you know, 90%, 95% of AI initiatives haven't yielded a return on investment.
06:26But that's because these AI initiatives have been very, very basic, almost very kind of not meaningful material.
06:34It's people using ChatGPT at work.
06:36It's people using Gemini at work.
06:38I think there's one scale of adoption there.
06:41The next part is where we use agentic AI and AI to kind of really automate and make existing workflows
06:49and value chains more effective.
06:51And then there's a stage where, you know, AI really can reinvent value chains.
06:58Like tabula rasa, we can rethink how we do business using AI.
07:01Now, in that context, and we were kind of very early in the curve, in that context, to deliver those
07:07things, you need, you know, what's known as an AI stack, right, of components.
07:11You need the physical infrastructure, you need the GPUs, the data centers, you need the model layer, right, you need
07:19the foundational models.
07:20You'll need, you know, kind of data components, data layers where kind of different types of software allow us to
07:28hold data in different ways.
07:30And so the application layer as well.
07:31But importantly in that stack will be this kind of services layer, this kind of AI operations layer, where you
07:38still need humans in the loop.
07:40You still need humans doing things.
07:43And that is things like, you know, annotating data to make sense of it, annotating images of the real world
07:48so that the AI can ingest it and make sense of what's happening.
07:54It's around kind of monitoring of how models outputs are, are they accurate or not, are they ethically right or
08:02not.
08:03There's a whole range of things where we still need kind of humanity to be involved, right.
08:08It's not as if instantly AI is going to give us everything.
08:13Yeah, this is where applied AI, you know, along with evaluation, monitoring, human oversight becomes vital in this services operational
08:22landscape.
08:22And of course, very recently you guys wrote a very interesting article in the Edge talking about Malaysia could potentially
08:30be a global AI hub for AI services.
08:36What was the thesis behind the understanding of this OP-AD and why this view?
08:45Because I think, I find it rather interesting, we haven't even argued that Malaysia should be an AI hub of
08:51sorts, but we want to.
08:52But at the same time, you guys took a very nice avenue that, forget about the rest of the, you
08:58know, the gamut of AI, but AI services global hub.
09:01That could be an area of win for Malaysia.
09:03Why that argument?
09:04Yeah, so for me, I'll let Zubin talk about the article.
09:07But for me, I was privileged to spend the last year at the Blavannick School of Government.
09:11And I wrote a paper on Malaysia potentially seeing this AI revolution as this catalyst for the country.
09:21I mean, in Korea and Japan, you had the automobile electronics.
09:26In India, you had business processes, the call centers.
09:31And then in Taiwan, you had semiconductor.
09:33And Malaysia can really take advantage of this AI revolution because we are right in the center.
09:39I think YB Liu Qingtong has always mentioned that we can be that indispensable middle.
09:44We can't compete with the likes of China in the US with regards to the LLM, the large, the big,
09:51high cap, capex investments.
09:54But on the application side, so we have a history specifically with Penang with the semiconductor industry, more on the
10:02manufacturing side.
10:03And then Selangor is going down into IC design and going a bit down, further down the supply chain.
10:10Exactly, with the likes of SIDEC.
10:12The talent side, we are trying to get that and supplement that with ASERM, the Advanced Semiconductor Academy of Malaysia,
10:20which the High South East Asia actually co-created with the Selangor State Government,
10:25supplemented by the huge amount of data centers that are being built within the country.
10:32All that put together, we have a significant opportunity to really use this AI revolution as a catalyst for the
10:43country,
10:43similar to those other countries that I mentioned before.
10:46What would be the highlight of that year that you spent?
10:51Do you feel that there could be some lessons that could be exported?
10:56Yeah, so what's interesting is the school is, their main thing is the Masters in Public Policy.
11:02So a lot of it is policy.
11:04And this is something with regards to Malaysia as an AI revolution.
11:08All countries around the world, they really need to look into really, really carefully is the policy governing,
11:15the governance side with regards to AI.
11:19You know, 40, 50 years ago, another revolution with regards to oil and gas.
11:24You had the Seven Sisters, the big oil and gas companies.
11:27But they move like an oil and gas ship.
11:30When they turn, it takes one day to turn, or a few, you know, one day is an exaggeration, but
11:35a few days.
11:36Then the government moves along with policy.
11:39But the tech giants nowadays, the AI companies, the NVIDIAs around the world, snap, snap, snap.
11:44They will, in terms of product, the product cycles are extremely quickly.
11:50And governments around the world are not built to move that quickly.
11:55They're built on policy cycles.
11:58They're built on bureaucracy, legislative cycles.
12:01So, you know, it's not a question of fast or slow in the abstract,
12:06but the question is whether the government can be adaptive without being too reckless.
12:11At the same time, sticking to the same policies so that no matter how fast or how intense changes and
12:19developments take place,
12:21if the policies remain consistent or at least the values remain the same,
12:25it is actually okay for us to be a little bit slower when it comes to policy creation as long
12:30as the policies stay the same.
12:31You need to, but you need to get a balance.
12:32So, as I mentioned, my time in the UK last year, you can see Europe being very, very careful,
12:39but then you can see a lot of the technological advances within the AI space is also lagging behind the
12:45likes of the US and China.
12:46But I guess we will see in the future.
12:48The US and China need to do no regulation, so there's that as well.
12:52Yes. So, you need to get that balance.
12:54Moving on to my early argument.
12:56So, what's with this possibility of us becoming a global hub?
13:01Yeah, so I think, as I mentioned, an important point around being the indispensable middle.
13:06I think it's a great point by YB Liu Chin Tong, and he's been talking about this a lot.
13:12It means that we don't need to be in the sexiest spaces.
13:14We don't necessarily need to be in the most cutting-edge spaces.
13:17But we need to be part of the value chain that is kind of indispensable, right?
13:23And be so important there as a plug in the global kind of supply chain for AI.
13:29And that's a space where, especially in this interim period, as we see adoption happening,
13:36that's a space where this AI services and AI operations space is really interesting.
13:40So, you'll still need, as I mentioned, a lot of humans doing things so that the AI can be developed
13:46at the core.
13:47And Malaysia has experience, right?
13:49We have established ourselves as a real global center for BPO and KPO and what's now known as global business
13:56services, right?
13:57We export services.
13:58We know how to export services well.
14:01Things like data labeling and automation, sorry, data labeling and annotation,
14:05those things are huge industries at tens of billions of dollars in size and growing very rapidly, right?
14:12There's no reason why we can't take the same skills that we learned as a country in exporting business process
14:19outsourcing and KPO
14:21and apply that to these AI, these kind of human-heavy AI businesses, right?
14:29And these things are not peripheral to AI.
14:33They're essential to ensure that AI behaves responsibly, AI works in favor of humans, and AI is safe, right?
14:42We still need these humans in the loop.
14:43So, let's take advantage of that.
14:46And the opportunities are manifold, right?
14:48There are things that we can do in terms of, let's say, radiologists, like reading imagery,
14:53providing that kind of clinical expertise there.
14:56There are spaces where we can leverage our multilingual capacity, right?
15:01To train models and nativize them and localize them, make sure that in certain cultural contexts,
15:06they're giving the right responses.
15:07So, there's a lot of things we can do and we are structurally set up and we've kind of succeeded
15:14in that space before, export of services.
15:16So, let's do this for AI.
15:18That's our view.
15:19Going back to the fund itself, what's the landscape looking like when you meet these founders?
15:27Are you happy with what you're seeing?
15:29And I'm not just talking about Malaysia, of course, the domicility that you're targeting, which is North America and Southeast
15:36Asia in general.
15:37Do you feel that there's some interest in terms of what they're going after?
15:42And perhaps if there's a gap, what are you looking for?
15:45What's that missing je ne sais quoi that you're looking for right now?
15:49Yeah, I think just quickly on that, I think the North America, the America divide with kind of countries like
15:57us, middle countries like us, Malaysia, not even Malaysia, Singapore, Indonesia, Thailand, wherever, is quite vast.
16:05And I think we're focusing on deep tech investments in America because for new innovation to come out, like deep
16:11tech innovation in AI, different kinds of scientific models, scientific foundational models, that kind of replicate the laws of physics
16:20using AI.
16:22AI, those things emerge as a result of decades of deep research, of funding between universities and the public sector
16:31in America, of access to high compute power, supercomputers before and now kind of GPUs.
16:37We don't quite have that yet.
16:40So I think the kind of investment landscape that we see in America is very different to what we'll see
16:44here in Southeast Asia.
16:45Here in Southeast Asia, we have a lot of, you know, very fast growing, profitable, mature and knowledgeable businesses with
16:55data sets, with knowledge and expertise of kind of workflows.
16:59If you look at our ports here, arguably our ports are far more advanced than, let's say, the port of
17:04Los Angeles, right?
17:05And because of that, we can take that vertical knowledge and use AI as a kind of catalyst to create
17:18businesses on top of that, right?
17:19To take the knowledge, ingest the knowledge using AI and then package this and sell this to the world.
17:25So it's more vertical applications we see here in Southeast Asia and the more kind of horizontal applications,
17:31the deep tech applications that could work across various industry domains.
17:36Those are the things we look for in America.
17:38So in terms of the Hive, so the Hive's model based out of their four funds, this is going to
17:44be their fifth fund.
17:45And then they also have Hive's Southeast Asia, Hive Brazil is, we're made on our co-creation model.
17:51So we work, identify problem statements, work closely with a corporate, for example, or government or ministry,
17:58and then we build accordingly, right?
18:02So Rakantani is an example.
18:04So a company that we built in the US, for example, a company, a large conglomerate, global conglomerate,
18:14identified that they wanted to use edge intelligence and AI and big data to build a software that will improve
18:24health and safety at the workplace
18:25using the video cameras, using data, et cetera, et cetera, but they couldn't find anything out there.
18:30So essentially, we, the fund, invested into the company, built it.
18:36This company was basically used the use case, like you can use it in three or five different factories, et
18:42cetera.
18:42Eventually, this company then invested into the company that we built.
18:47And we invested, you know, 1.5 million US.
18:51The company is now worth 150 to 200 million US with a lot of different customers at that hand.
18:57In the same way, as I mentioned before, investing into a lot of different companies, hoping for the best,
19:05is not the way to go in terms of AI.
19:07It needs to be targeted.
19:08You need to identify problem statements.
19:11You need to identify what areas you want to invest into.
19:13So working closely with the National AI Office, with the Ministry of Digital, for example,
19:18they've highlighted six different areas that they want us to concentrate on and look on
19:24and build companies on, invest into companies on healthcare, education, public services, SME, and transportation.
19:36So those are specific areas that is aligned with the government as well.
19:41And, you know, when you align yourselves with the policy that the government is going,
19:46that the market is going commercial, then that's the way to go nowadays.
19:51And, of course, the idea of still on your fund, is there any different kinds of pressures from your LP
20:01and family offices?
20:03Are they looking at a still a seven-year fund or 10-year fund?
20:07Are they pressed for time?
20:09Or it's more of, you know, nothing changes in terms of how the investment structure is looking like?
20:15It's just looking into specific sectors.
20:18For instance, right now, into AI and the risk appetite is still the same.
20:23And the tolerance for the timeline is also the same.
20:27Do you think that there's a change there?
20:28No.
20:28So, you know, obviously more capital will go into the AI because that is the buzzword right now.
20:32And this is the area that technological advances are going to happen.
20:37Growth is going to happen as well, right?
20:42In terms of the VC industry, I don't think I need to spell it out.
20:47But there have been challenges with regards to VC industry, not just in Malaysia, Southeast Asia, Indonesia, of course, and
20:53globally.
20:54In terms of the cycle, I think the seven-year cycle will not change.
20:58Because the market dynamics for a venture capital fund is that.
21:03But I think you need to show results earlier in terms of proof of concept earlier.
21:12And I think the LPs will demand that.
21:16You need to create the company.
21:18You need to show that this company is...
21:22Not necessarily pre-rev, I suppose, but results.
21:26Generally speaking, the rollout plan and stuff like that.
21:30And I think the reality is with the pace of AI, we're going to start to see distributions a little
21:36bit quicker.
21:37Compared to traditional tech, how we started off maybe three, four decades ago.
21:41And I think because of the pace of change and because of the appetite of some of the bigger players,
21:46we're focused on enterprise AI.
21:47You can see players like Anthropic or ChatGPT, OpenAI, wanting to get into that space to deliver the type of
21:58products that we invest into to deliver those same products to their customer base.
22:02So I think there'll be a lot more acquisition and it might happen a little bit quicker.
22:07But kind of rolling back, I think, as Hazem said, there definitely has been a lot more pressure around distributions.
22:14I think the general milieu climate around Southeast Asia-centric VC is where are the distributions, what happens to the
22:22distributions.
22:22And we come in at this point in time raising this fund at a very difficult point from a macro
22:29perspective.
22:30Because, you know, the funds that are coming up to the end of their life now have a kind of
22:36vintage of 2016, 27, 2018.
22:39Those are funds that were investing in very, very high valuation times, right?
22:44There were kind of zero interest rate times.
22:47And now coming down, you know, the distributions might not have happened, you know, for those funds.
22:54And so LPs are still kind of very, a little bit more diligent around deployment.
23:02And Anthropic is currently valued close to $400 billion.
23:05OpenAI is rushing to get its IPO done fourth quarter this year in a race to beat Anthropic.
23:12How seismic are these kind of players going to impact the industry as a general play?
23:19And of course, how will you help your portfolio of companies that intend to target right now?
23:24Is it going to have some effects?
23:26And what would that be?
23:28Definitely.
23:28I think the model, there will be, in the model space, the model layer, there will be a range of
23:33players.
23:34There will be these large utility type players, which are almost like the providers of the internet, you know, providers
23:39of intelligence.
23:40And they will continue to be large in Bahamas.
23:42There will also be smaller model players, scientific model players that are fit for purpose for certain spaces.
23:52And to be honest, in the next five or 10 years, as we move towards AGI and other, you know,
23:57real world AI models that people like Jan LeCun are looking at,
24:03nobody can tell, you know, where this is going to really go.
24:07But the foundational models and their investment there are going to be kind of pillars to the application layer.
24:15And then, of course, moving towards the macroeconomics.
24:19Ringgit is strengthening.
24:21It's getting interesting for local players to look outside.
24:27But seeing that you're a U.S. fund, the U.S. is weakening, bang for buck kind of thing.
24:35How do you view, say for instance, currency fluctuation impacting how you look at your fund size and the ticket
24:44size of your investments?
24:45And how do you see some interesting markets like Malaysia, for instance, or Southeast Asia as investment opportunity against the
24:53backdrop of economic growth,
24:55against the backdrop of policy volatility and the risk bandwidth widening,
25:03considering that Trump has various other issues that he has to deal with and content with people like us?
25:07Yeah, so, you know, the Hive Global AI Fund is a U.S. domicile fund.
25:13But we're building the fund based on the thesis of building this U.S.-ASEAN corridor, right?
25:20So, as Zubin mentioned, the deep tech stuff will be in the U.S.
25:25And then the application side, the applications of that and taking advantage of that will be invested into Malaysia, Southeast
25:34Asia.
25:35So, with regards to the macroeconomic side, it's specific to each region.
25:40And we will, to a certain extent, the macroeconomics will potentially help us, right?
25:47This is an upside for you guys.
25:48Yeah, and I think, look, you know, we can't predict big macro trends, currency trends and so on.
25:55But what we do see as an underlying thesis for our fund, this corridor that Haizan spoke of, is important.
26:03So, you know, our startups that we invest to in America don't have access just to American corporates and the
26:10American market,
26:11but also to the fastest growing region in the world, right?
26:14Southeast Asia is going to be, over the next five years, probably the most steady and, you know, bang for
26:20buck, risk return,
26:21the best space that you can invest into.
26:25And so, our startups in the States will have access to high-growth corporates out here in Southeast Asia and
26:32Malaysia.
26:33Not only that, they'll have access to kind of high-value and very highly cost-competitive labor,
26:41engineering, software engineers and AI engineers that we can source out here in the region.
26:46And then on the reverse side, you know, the startups that we invest into here can be battle-hardened by
26:51kind of technical expertise that we have out in the Bay Area.
26:54We can inject talent from the Bay Area and so on.
26:57There's a lot of kind of synergies there that we see beyond the kind of fluctuations of the currency.
27:05So, I think, yes, there will be considerations there.
27:07But I think the overall, the synergistic upside from that corridor is what we're looking at.
27:14And then, so, you know, we have to mention the Global AI Village.
27:18So, the Global AI Village was launched at the same time as the National AI Office and it is an
27:23investment under the Hive Global AI Fund.
27:27And the idea stemmed from the Hive 1, 2, 3, 4 from the US investing into companies.
27:34They've been hiring AI engineers from all around the world, from Colombia, from Ukraine, from Korea, from India, predominantly India,
27:43etc.
27:43It's basically where the best AI engineering team is to build.
27:47And we're saying, you know, why can't you just house it within a particular location within Malaysia?
27:54We have an increasing amount of AI engineering talent in Malaysia.
28:00And, you know, now with especially post-COVID and post-MCO and the digitalization stage, you can be anywhere in
28:09the world.
28:10So, the idea is that AI engineers from around the world can potentially be housed within Malaysia, can upscale the
28:19talent within Malaysia and work on projects from all around the world.
28:22So, the Hive is one of them. We have current companies in the Hive Fund 4 and Hive Fund 3
28:28that we're working on, we're building.
28:29There's one company that we're looking to work with a local, the local oil and gas company.
28:34So, on a particular project.
28:36We're building one. Well, now two if you think about Sarawak.
28:39Yeah. So, the engineering team will be built, will be, this company will be using AI engineering talent within Malaysia
28:49to service Petronaut.
28:51Yeah. And, and personal curiosity, how has the take-up been? Is it a bit too slow? Is it going
28:58according to plan?
28:59No, I mean, I mean, there's definitely a significant interest. I think based on the economics of raising this fund
29:10and setting up this fund,
29:11it's been a little bit slower than what we would have envisioned.
29:14But again, this Global Air Village, the AI engineers are the ones that's building Rakantani for us and also working
29:21closely on these different projects as well.
29:23And certainly a lot of, I mean, there's a lot of interest from our incumbent portfolio companies from previous funds
29:28in terms of utilising, you know, talent out here.
29:31There's a lot of interest from our previous portfolio companies in terms of expanding here and using the village as
29:37a distribution channel to get into Southeast Asia.
29:41And there's also a lot of interest from people, you know, everybody from universities to kind of businesses about building
29:48AI projects for them and how their village can help.
29:52Yeah, that's another area that I'm very keen on. So I also the deputy chair of the Malaysia Venture Capital
29:58Association. And, you know, the hive in the US, we've built a lot of companies with the University of Stanford.
30:05One company that we've built was on a paper from, from the University of Michigan, right?
30:11And I feel that the universities, we are looking at it, it did come across this problem statement, didn't come
30:20across with between the Venture Cap industry in Malaysia and in the budget engagement session with YBMK2,
30:29that the universities need to work more closely with the Venture Capital funds and vice versa.
30:34Because a lot of the talent and a lot of the research is coming out from universities, but it's not
30:40being gestated into actual viable products.
30:43We've been talking about that for quite some time.
30:45Yes, of course.
30:46Sweden did the Triple Helix 30 years ago.
30:50Yeah, I'm a bit pessimistic in that sense.
30:54Pessimistic, but we need to look at it.
30:56The rest, I'm rather interesting, you know, intrigued, a bit optimistic, all this.
31:01On that part, that last part, I don't know, I have my skepticism there.
31:06Final thoughts on 2026, is this going to be a very fun year for you guys?
31:10Well, year of the horse.
31:11Fire horse, apparently.
31:12Fire horse, yeah.
31:13So, that's exactly what you need with regards to, you know, your leap and bounce and fire to drive the
31:21jumping of that, right?
31:22So, we are very optimistic.
31:26We are, with regards to the Hive Global AI Fund this year, 2026 is the year when we make that
31:32leap.
31:34And, you know, inshallah.
31:35Your fundraising period stops?
31:37End of this year.
31:39Okay.
31:40So, full deployment maybe?
31:41We will start deploying.
31:42We are starting to deploy this year.
31:44And, it will be, it will start really, starting taking shape over the, kind of, the mid, the middle of
31:52this year.
31:53Yeah.
31:54I think with regards to the policy as well, with regards to the Malaysian Government, we are working very closely
32:00and speaking to the various stakeholders.
32:05the AI roadmap as well, to be aligned to that.
32:09I think, so, for this year, I think it's really a really critical point because I think people are waking
32:16up, enterprises, old and new, are waking up to the impact that AI will have on business.
32:23Not just as a tool, but because AI is becoming work, right?
32:29AI can do the work itself.
32:31I think that realisation is slowly dawning on people.
32:34And, in the conversations we've had with investors, family officers that have operating companies and a portfolio of assets, the
32:42idea of, or the notion of embedding AI to be radically more productive, radically more efficient, or to do radically
32:49different things, is really starting to become a reality.
32:52So, we've seen a really, kind of, market, kind of, change in the way, you know, family officers and owners
33:01of businesses have been talking to us about investing into us.
33:05So, I think it'll be an interesting year, but it'll be the year where, kind of, the world and Malaysia
33:13itself kind of awakens to the power of artificial intelligence inside a business, reshaping businesses, and kind of reinventing value
33:21chains, reinventing the way we do things.
33:23I'm getting the vibe that 2026 is the tipping year.
33:26If Malaysia really wants to get in, now's the time.
33:28And if we miss this boat, I don't think we'll ever get it back.
33:31I think that's the vibe I'm getting.
33:32So, when I was in the UK, exactly that, I said, you know, I use this as an opportunity for
33:39Malaysia, as I mentioned before, that this can be our catalyst, similar to Taiwan, Japan, Korea, India.
33:46We can't miss the boat.
33:47And then the professors, so, Haizam, stop talking about missing the boat.
33:51Malaysia needs to build the boat, right?
33:54You need to drive it.
33:56You need to build the boat.
33:57And, you know, whatever you want to take from that, that's where we need to think.
34:02I think that's right.
34:03I think, you know, we're interesting.
34:04We're a great economy.
34:05We're an open economy.
34:06We export a lot.
34:07But that means we're, you know, we are under pressure to adopt, right?
34:12So, if we don't, if our businesses don't adopt AI, don't embed AI, don't reinvent their value chains with AI,
34:18we'll be far less competitive than peers in other markets, right?
34:23So, as an open economy, we'll suffer, right?
34:25People, our exports will suffer, right?
34:27So, we need to be amongst the early adopters in this space.
34:31And while a lot is at stake, now is the time to see some of the opportunities presented to us,
34:35I suppose.
34:36Yes.
34:37Thank you very much.
34:38That was Zubin Radhakrishnan and early on Jesse from Dato' Syed Haizam Jamalul Lail.
34:44They are partners of DeHive Global AI Fund.
34:47Perhaps, you know, it would be good if you are interested, can reach out to them.
34:50Just reach out to them on their socials and their website.
34:53Until then, thanks very much for watching.
34:54Catch you in the next one.
35:08Catch you in the next one.
35:09Catch you in the next one.
35:09Catch you in the next one.
35:09Catch you in the next one.
35:09Catch you in the next one.
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