Startup panelists – Tibo, Ridge Security and SlashNext

Mike Skurko, incoming president of the ISSA Silicon Valley Chapter, was the moderator.  Startup panelists were Daragh McGraph representing Tibo, Hom Bahmanyar representing Ridge Security and Patrick Harr representing SlashNext.

While ChatGPT and other AI tools promises to unleash productivity across coding to network troubleshooting, organizations are at risk of leaking confidential information to these engines. Tibo is pioneering the world’s first-of-its-kind platform to detect sensitive information sent to ChatGPT and AI tools, redact them automatically and/or prompt the user to be aware.

Penetration testing is critical to ensure the security of infrastructure of organizations and software and hardware products of tech companies. Ridge Security provides autonomous agents that mimic a white hat to identify exploitable vulnerabilities. It provides CISOs with kill chains so that they can prioritize which vulnerabilities to patch.

Since launch of ChatGPT, there is a 12.7x increase in Phishing emails. Generative AI can now create phishing emails that have context, are customized, and without the usual flaws like grammatical errors. SlashNext is pioneering next Gen AI Email+ Security.

Challenges of AI to Cybersecurity

Patrick shared that since the advent of ChatGPT, there has been not only a huge spike in phishing attacks and deep fakes. These phishing attacks have become “three-dimensional” and more sophisticated.  Phishing is now “polymorphic”, meaning they dynamically change.  Deepfakes across voice and video are easy to create.  Bad actors scrap photographs from the internet and create fake accounts in social media that can impersonate you and add your friends to these fake accounts.  It takes only 15 seconds of a person’s recorded speech to be able to impersonate his/her voice through deepfakes.

Meanwhile malware has also become polymorphic and evade traditional signature based detection.  Generative AI will further the automation capabilities of malware and ransomware as a service.

Daragh spoke about how Generative AI opens up a hole for organizations to lose their most sensitive data as their staff leverage engines like ChatGPT to enhance their productivity.  Many organizations have chosen to completely block out ChatGPT and others, but there are many work arounds.  Organizations need to embrace AI in a way that does not compromise the loss of proprietary information.

Opportunities for AI in Cybersecurity

Yet, AI can be for good.  Hom discussed how AI is critical for helping CISOs respond to attacks quickly.  In the shift-left paradigm, code and products need security and penetration testing at the same time as unit tests.

The panel and the audience exchanged many ideas on how Generative AI can be used in Cybersecurity. Generative AI is now used in coding.  It is used to create synthetic data for training detection engines, for example clones of phishing or business compromise emails.

Final Thoughts

As organizations embrace AI, one of the threats that FBI has identified is in the access that Co-pilots and Large Language Models (LLMs).  It is critical that CISOs vent Access Control Lists of AI engines.

Thank our startups Tibo, Ridge Security and SlashNext for their exciting sharing!

The post Impact of Generative AI on Cybersecurity appeared first on Oakseed Ventures.

Our panelists were Brian Goffman, Associate Principal at McKinsey where he co-leads the Generative AI practice in software, Harshini Jayaram AI strategist at Distyl AI, Nikos Georgiades, Senior Expert Advisor for McKinsey and Co-founder & Strategy Advisor of a startup CHOIR AI, David Van Bruwane, CEO of Fairly.Ai and Awah Teh, VP Data Governance & Privacy Engineering at Capital One.  I’m the founder of Oak Seed Ventures.

Generative AI – State of Affairs and Future

Brian kicked off the panel by sharing McKinsey insights on Generative AI.  70% of the enterprises have launched a Generative AI powered solution.  Though early adopters are adopting Generative AI to gain competitive advantage over competition, many challenges remain.  These include cost, tech integration, talent, reliability of output, but also ethics, compliance and IP risks.

Harshini shared with the audience Distyl their progress in taking enterprise clients through the generative AI journey.  The first step in this journey has been information retrieval, a customer service chatbot that can provide answers to questions.  The second step is being able to take action for customers.  This is where enterprises are now experimenting.  Where the future is headed is having autonomous agents that can make decisions on behalf of humans.

Nikos shared with the audience the pioneering work that CHOIR AI is doing to democratize the access and analysis of enterprise data.  Focusing on the Pharma Industry initially, CHOIR AI enables managers to perform analysis on business data in management meetings in real-time without the current several days to weeks lag, by which time often a certain analysis may no longer be relevant.  AI thus opens up new capabilities, not simply replacing human labor.  And this is done with (almost) no hallucinations, and without sharing enterprise internal data to Open AI, Microsoft or other providers of LLM models.

David shared the critical work that Fairly.AI is doing to enable financial institutions stay compliant to regulations, an area that Awah at Capital One concurs is critical because it is the foundation of trust.  Capital One is investing a lot into infrastructure and talent when it comes to AI.  An area that Awah is very concerned is avoiding bias. And data quality and understanding its lineage is crucial to the performance, utility and success of any AI system, because garbage in garbage out in the world of AI and computer science.

Challenges – Hallucination, ROI and others

The panel and the audience had a lively debate on many topics, including “hallucination”, return on investment in AI and others.  “Hallucination” is still unavoidable, and is managed by different methods.  This includes chain of verification, experimenting and testing the technology where it is further away from the customer and less risky first.  The panel and audience debated the humans seem to hold a very high standard for AI when humans make mistakes. May be its more appropriate to compare the accuracies of AI to human, but it seems like data is lacking for human performance.  Nonetheless, it is important to note that for application in social media, the standard required may be lower than other industries like finance and pharmaceuticals.

The audience and panel also debated about the return on investment on AI, whether enterprises have made money from AI or that investment in AI will wane.  The consensus view was that AI is now table stakes. Though enterprises are constantly evaluating the effectiveness of AI investments, they may be under pressure to continue investing to stay competitive.

Thank you Brian, Harshini, Nikos, David and Awah for your time, insights and lively debate!

The post Real-world Applications and Challenges of Generative AI in Enterprise appeared first on Oakseed Ventures.

Jonathan Rechtman

Hey, everyone, and welcome to the Essence of Investing where we explore the story, strategies, wit, and wisdom of investors from across the Asia region and beyond. I’m your host, Jonathan Rechtman. My guest today is the one and only Chee-We Ng, partner at Oak Seed Ventures, which invests in early-stage enterprise technologies from AI and cyber security to next generation compute.

In this episode, Chee-We shares stories from his early days as a coder in middle school, his strategy for evaluating technical founders, and a ton of wisdom about making hard tradeoffs, listening to our inner voices, and realizing distinctive value as human beings in the age of AI. Please listen, like, share, give feedback, and most of all enjoy. The Essence of Investing is powered by Next Level Communication, and by the World of Allocators. Next Level Communication helps investors and multinational executives in Asia tell their stories to their most important global stakeholders.

Alright. Thank you so much, Chee-We, for joining us, on the podcast. So excited to, to have you with us today. I wanted to kick off with a look at where you got started. When we were speaking earlier, you told me, you know, you’re a very technical fund. And you said that you started coding as a child. And I wanted to ask how you got into coding as a child. What coding was like then and what your early fascination with technology and programming was.

Chee-We Ng

In middle school, this was the first time our middle school decided that instead of learning woodwork, we would learn programming. To set the context, this is during the days of the IBM PC when Windows hasn’t showed up yet. We were learning to do interesting things with GW BASIC, to solve, simple problems.

One day when our programming teacher wrote a simple program to do class planning. This is a laborious thing if you had to do it by hand. There are a number of teachers in math, science, history, geography, and what have you, and they will teach class A and B and C. And then you have to figure out for when school starts to when school ends, you need to have three science classes a week and three reading classes a week, how do you slot all of that in? And I was fascinated.

I was like, oh, wow. You can use computers to do that. And it was a simple BASIC program that our teacher wrote to solve that.

Jonathan Rechtman

How old were you and where were you at that time?

Chee-We Ng

I was in Singapore. I was, twelve going thirteen, and this was, grade seven.

Jonathan Rechtman

And do you remember the first time that you wrote a piece of code or that you found that empowerment, the ability to create something or to save time or to you know, create value, even though maybe as a child, you didn’t think of it in those terms. But the realization that with just your fingers and this keyboard, you could make something that didn’t exist and do something that you couldn’t do before.

Chee-We Ng

Yeah. And so the first real challenge that I took upon myself was after having learned some programming, I observed that my mother was facing some challenges at home using WordStar and WordPerfect.

This is way before Microsoft Word. And some people may remember that you have all these funny keystrokes even copy and paste wasn’t that straightforward and the other editor that MS-DOS provided was an editor called EDLIN, which is command based. It’s just a nightmare.

And I looked at my poor mother. She’s like, “Okay, what do I do to copy and paste again?” You know, it was incredibly hard.

And I was like, “Okay. What can I do to solve that?” And then I realized that you couldn’t do that in GW BASIC, because GW BASIC is an interpreted language. I needed to learn a language that you can compile.

So I went to the bookstore. I asked my dad to buy me a book on Turbo C, and we bought a copy of the Turbo C compiler.

And I learned about how a screen works and how do you display things on the screen. And I learned about data structures and how do you capture input, like left key and right key. And I decided that I was going to write my mother a word processor.

It was very simple, but it allowed her to not have to do funny keystrokes, you know, to copy and paste and allowed her to save, make things bold and underline. And that was it, but I made the decision to really alleviate her from pulling her hairs.

There was a lot to learn, but I was motivated and spent many hours in front of a computer and figure out, this is actually how you would compile a program and then and there you go. It was probably second year in middle school that I got the whole project done and my mother never needed to use WordStar and WordPerfect.

Jonathan Rechtman

Take us forward now in the story. How do you take this early passion for technology and coding and bring it forward as you as you go on your journey and enter a career, in both working in technology and then in finance.

Chee-We Ng

Yeah. So, you know, a fast forward, I was, very thrilled and delighted that I got admitted to MIT. You can tell I was a very geeky boy and, you know, technology really excites me. I, like, I still remember another story, which is we, grew up playing with Texas Instruments Speak and Spell, and our Speak and Spell broke, and my dad’s a physicist, and he said, okay, well, let me take a look.

He soldered a piece of a calculator on to Speak and Spell. I think it probably was a microprocessor also that he basically piggy-backed onto the bus. And it worked. It magically worked. I was like, oh, wow. What is this technology?

And so when I went to MIT, I learnt this is how these things work. It was just mindboggling that all these things are capable of doing different things.

I did my undergraduate and was admitted to the PhD program. I had actually taken a scholarship from the Singapore government, and so, I couldn’t finish my PhD program and Singapore said come home and, I started my work in the area of information security.

I started, building cybersecurity products, you know, encryption, authentication devices, and, I led a team of software and hardware engineers.

And then years into that, I started being exposed to the business side of things, doing business development and creating partnerships with companies like, Schlumberger Sema, which back then, had a smart card company. And so I decided, it’s time to maybe go to business school instead. And so I went to Harvard Business School. And then this was what really led me into the business side of the world, I was first at McKinsey. And then, from McKinsey, I transitioned into investing.

Jonathan Rechtman

What was the thesis that you took in your transition from, practicing to investing?

Chee-We Ng

At, Harvard, this is when I made the decision that, eventually I would like to be an investor. Maybe not right away, but this would be something that I would feel incredibly passionate about. At Harvard, as you can imagine, many of my peers are drawn to an investing career because it’s very financially rewarding. A third of the class comes from Wall Street and a third of the class wants to go to Wall Street. It’s almost natural.

But I was very inspired by some of the people that have walked through the halls of Harvard. Georges Doriot and Arthur Rock in particular, they actually were the first venture capitalist as you would call it.

I was actually receiving financial aid, from the school in the name of Georges Doriot, who was a professor. He was a general in the US Army, where he was director of military planning. And later Dean of Harvard Business School. Between, Georges Doriot and Arthur Rock, they have created companies like Intel and Digital Equipment.

Venture capital is in the business of making the world better, because by allocating capital to these innovators, they create things that otherwise would not be created. It just would not.

And so venture capitalists, have an immensely important role in society.

Jonathan Rechtman

When, tell me about the beginning of your career in investment. How did how did you begin investing?

Chee-We Ng

I was recruited to help start the Shanghai office of Arsenal Capital, which is a New York based mid-market, private equity firm.

And this was a time that a lot of businesses and manufacturing had all these opportunities in China. And Arsenal needed people like me who had consulting background, I was at McKinsey, and understood cross border challenges.

And so I transitioned from McKinsey into investing with Arsenal Capital. And it was a very educational experience with, with our partners like Terry Mullen, because Arsenal is a very special private equity firm that values a lot about having focus and having value add. Investing isn’t just go pick a good opportunity, but actually knowing what to be investing, having industry know-how, and also having impact, having value add to the firm itself.

Now what typically a lot of people think about private equity buyouts is you acquire a company, and then you do financial engineering – you go flip it. Arsenal was not. And that had a foundational impact on me in terms of how I think about investing.

And then transition into venture capital, I was later recruited into doing venture investments at Cisco. And at Cisco, we wanted to be investing into all the areas across the enterprise technology stack, as an effort to broaden Cisco’s know how experience and exposure to other areas of enterprise technology other than computer networking.

Corporate venture is about identifying technology trends, disruptions, these technologies that are coming out, and where we should be investing.

And so that’s how I got into doing this. And that’s essentially what we are still doing today.

Oak Seed Ventures was founded with colleagues of mine, to look at where the innovations are. Today we focus exclusively on AI cybersecurity and next generation computing. And we look at the innovations that are coming up, the disruptions that are coming up and the pain points in organizations, and then backing and helping the new founders that we see.

Jonathan Rechtman

How is it different practicing this investment as a standalone fund as your own fund versus is doing it via a corporate. How is your practice at Oak Seed different from your practice at Cisco?

Chee-We Ng

So I would point to a few things. One, of course, in a corporate, you never have to worry about fundraising.

But, of course, at corporate like Cisco, we really cared about the technology. We cared about how is this relevant to Cisco? Now, at Cisco, there were things that are close to Cisco’s core businesses, which computer networking is a very big part. But we also have cyber security, collaboration tools, Webex and others.

And for things that are close to core, we tend to think about what is the synergy? Is there some sort of strategic fit?

But we also define areas that we think are important technology areas in general, but not necessarily having an immediate intersection with Cisco’s business. For instance, the areas of big data, next generation data warehousing and so forth. Areas that, were emerging and important to Cisco to understand.

So in those areas, we think pretty much like a venture capitalist. Where these new big things that are happening that will give rise to opportunities where new, potentially, huge companies will be created?

Now, of course, in a VC firm, you push that to even more, because our responsibility is to create outsized returns for investors, given the risk that is in VC. Investors are looking to venture capital to create those outsized returns. And that forces us to think not just about the technology, the market, the dislocations, but financially whether this would be, one of those investments that would deliver that outsized return.

Jonathan Rechtman

Tell me a little bit now about Oak Seed Ventures and the strategy and what is unique about your firm, unique about your point of view on the market, on these sectors that you talked about, and your edge?

Chee-We Ng

We bet companies in the enterprise technology space when they, have little or no product. And what’s our edge is we work very hard to have our own, perspective on things that is non-public information. And then we try to de-risk by helping, those companies. And we’re very, very focused.

As mentioned, we only focus on AI, cybersecurity and next generation computing. We’re very technical. Some of us are from investing background, some from industry, and we share different perspectives, from the technology, the business of technology, and the financial and investing perspective, and we put all of that together. And we are looking for founders that are highly differentiated in terms of their experience in the technology world.

And we do a lot of the DD ourselves in terms of, like figure out if these technologies are at the forefront, not just by looking for things in a checkbox, like they worked at a Google or they worked at a Qualcomm or, they have a PhD from Stanford or MIT. But actually that they have spent time really developing truly unique technology capabilities.

We spend a lot of time thinking about the business of technology, figuring out whether they are solving real pain points. In the technology world, oftentimes, one of the pitfalls is that you would be a better mouse trap or a mouse trap looking for the mouse.

You don’t want that. Steve Jobs once said, you want to start from the customer experience and figure out what the technology needs to be. It’s no different in the enterprise space. You have to find customer pain points, what pain points you’re trying to solve.

And a database seems to be a database, but it’s like you use different knives for different situations. You really have to find out the use case, you have to really find out the pain points. It takes a great startup team to realize where these new opportunities are, the new use cases that are not solved by existing technologies. And they create new products and solutions to solve it.

Jonathan Rechtman

I want to double click on what you described as non-public information. And what sort of information are we talking about and how do you get it? And why is it valuable?

Chee-We Ng

And let’s talk about technology bench of the teams we back.

There’s one approach that you can do, which is, you basically look at the resume, and you say, okay. This team has the credentials, have gone to the good schools, done a PhD and a graduate degree, and then have looked at the right companies.

That’s public information. Because that’s information that that everyone has access to. Right? The BP will say, the founders went to these schools. They work for these companies. You can go a bit deeper and then you can go interview colleagues at the company. You can try to find out what was their real experiences and those kinds of things.

But we go beyond that. We really quiz the founders in terms of their understanding of the things they are doing. Granted that we, obviously, even though all of us are very technical, we can’t be experts in in everything. Even though many of us had written code, or done engineering work when we were younger, we don’t do it as deeply now.

But we have access to friends, colleagues, and MIT faculty and others. I also spend time reading technical papers. We try to figure out, when do things get difficult and challenging, where are the tradeoffs that need to be made?

And so we have a conversation with typically, the CTO or the technical founders, what is difficult here? And why is this so special? And granted that sometimes founders also don’t tell us the true secret sauce, because obviously it’s proprietary and probably we won’t be able to understand all the details about it.

But we know fairly enough where are some of the really difficult challenges. And the founders that are working at that forefront of technology understand limitations of technology. They understand, oh, wow, this is really hard. And some of them have chosen to work on those very difficult things because they know if they are able to overcome them, those are huge barriers to entry.

And so we look out for those. We look out for a team that does not just look good on paper because often times the best talent need not have gone to the MIT’s and Stanford’s and what have you, the best talents are the ones that just love playing with technology, whether it’s software or hardware. They just enjoy doing that, since they were very, very young. And you get to know that by having interactions like these with them.

Jonathan Rechtman

It sounds like there’s this there’s this paradox for investors where investors want to invest in people that are smarter than them so that they can, you know, push the boundaries, the frontiers of science and technology and create things that don’t exist. If the investors were that smart and that innovative, they would probably, you know, invent technologies themselves.

So you want to be, you know, giving allocating capital to people that are really on another level. But at the same time, you wanna understand. you wanna be able to do diligence on them and make sure that that they really do have that intelligence. And so you need some sort of ability to check.

And the way that you approach sounds like is rather than by having all of the answers, you get really smart about what are the questions or what are the challenges or the tradeoffs that you described; drawing on your network of science experts to understand where the where the cutting edge gets blurry and then quizzing the founders not on how they solve it, but how they approach that tension or those difficulties, how they think about the hard part?

Chee-We Ng

That’s exactly right. We are not nearly as smart as them in what they do. My problem statement is not to be as smart or to be smarter, but knowing how to identify the smart ones.

And maybe smart is not even the right word. It is having those experiences, and the ability to do that creation, and being the best in in that area. And so that’s what we are looking for.

And there’re also other elements to it. And as I mentioned, it’s also things like passion. Like, this is their life’s work. So it’s not just, oh, this is just another gig. This is someone who’s like, yes, I’ve gone through this, I’ve learned all these things, now I see this problem that needs to be fixed. And I have all the skills to do it. And I this is my life’s passion now, and the world will be better.

And so we look for this drive as well because, end of the day, it’s really about a founder’s life passion, and they are there at the right time, at the right place, with the right sets of skills. And they’re like, yes, I want to do it now. This is the right time to be doing this.

Jonathan Rechtman

What’s the sort of non-public information that you can get that reveals something about a founder’s passion or their commitment or their, their drive or character?

Chee-We Ng

One of the things that we try to do that we don’t always succeed is we try to put them in front of new potential customers.

Now that’s an amazing win-win. And we do that early on, even without our investment, because it’s so value creating in many, many ways. Obviously, the founders would be very grateful that, you know, there’s a new potential customer that can speak with and develop business.

But for us, it’s always enlightening, to see founders interact with potential customers. Do they, receive feedback well?

This is always an amazing, delicate balance, because on one hand, you want to have the founders like Steve Jobs at Apple who says the iPhone should have one button and no keyboard. And that’s the right decision to make.

But on the other hand, you also want to be listening to your customers. And oftentimes, customers will tell you things that maybe you don’t want to hear. And so whether one has the maturity and experience to be dealing with those difficult situations, you can tell — and this is non public information — by seeing that conversation.

This you don’t get by giving reference calls. Everybody can make reference calls. That’s public information. So how do you get those non-public information? Uou do that by creating opportunities like this.

Jonathan Rechtman

You mentioned earlier the role of tradeoffs in evaluating founders and their perspective on a market. What have you learned about tradeoffs? Do you see common tradeoffs occurring across different categories? Are there tradeoffs that you become familiar with? It’s one of these, one of the familiar cast of characters. And what has it taught you about facing tradeoffs in markets in technology? And then, you know, may be afterwards we’ll talk about what does it taught you about facing tradeoffs in life.

Chee-We Ng

So there are different types of tradeoffs that technology founders have to make. They could be technology tradeoffs, or they could be business trade offs or even may be more broadly speaking business choices.

So let me go down this in different directions.

In technology, they are tradeoffs. So let me not use the computer science or electrical engineering examples because maybe that’s hard to understand. Let’s just talk about cars and trucks.

So a truck has an engine that can carry a huge load. It may not go very fast, but it has a lot of horsepower. A racing car, like a Porsche, is able to go from zero to a hundred miles per hour
in five seconds. And so that’s a tradeoff because you can’t get a Porsche to pull what a truck pulls.

In the technology world, there are lots and lots of tradeoffs. So we trade off performance, like throughput. We tradeoff what we call, latencies. We tradeoff with power these days. Power consumption is such a big issue. Because it’s not just climate change. Sometimes, it’s just not enough power to drive these things in datacenters.

So there are lots of tradeoffs and the most experienced architects and engineers are dealing with those tradeoffs. And it’s because these tradeoffs exist that there are different products, and different niches of different segments that you can go after. It’s not a one size fit at all.

And when you are at that forefront, you know what you’re trading off. Sometimes you can even try to break that barrier and have the best of both worlds and go beyond what people think of tradeoffs. And that’s obviously immensely powerful.

Sometimes a lot of that arises because there are innovations. So for instance, hard drives. Storage has gone through different transitions – when you transition from the hard drives, which is magnetic in nature and spin based, to solid state drives. Certain tradeoffs that you may have to do in the past may disappear when certain technologies become more mature. And so that again creates opportunities for startups to create new products.

Now in the business side of the world, it gets very, very interesting. Tradeoffs are around business choices. What customer segments do you go after. Do you go after the government?
Do you go after the telecom? Health care, manufacturing or utilities? Do you go after big enterprises, or do you go after small or medium businesses? Do you go direct? Do you go directly to the CIO, top down sale or you go through sort of the enterprise user, the consumer, or small teams, and then eventually you sell to the entire organization?

And those are tradeoffs. If you go after the CIO and do a top down sale, the sales cycles can be long. But maybe you have a big bigger ticket size.

Now if you choose to say, we’re going bottom up. We’re going to sell to departments and small teams. The customer decision is fast, they test it and it’s great. And then to sell to the company, you have to upsell. You have to create all the enterprise features that a CIO wants, but you can do that later. And, then as we mentioned, different customer segments are very, very different — selling the government, telecom, healthcare are very, very different. And each one comes with different tradeoffs.

And it’s particularly important for a startup because there’s only this amount of money, this amount of people that you get hire. And then also you have to make choices in terms of who to hire, because sales, BD and marketing become very specialized if you go out to different segments of the market.

Jonathan Rechtman

I find this fascinating, and I’m particularly fascinated by the idea that there are some tradeoffs that are just unavoidable and other tradeoffs that maybe you can innovate your way out of. One of my favorite quotes of all time is from a Vietnamese monk, Thích Nhất Hạnh, who talks about dissolving false boundaries as part of the pursuit of wisdom and the idea that many things that look like tradeoffs or look like dualities, that’s a limit of our perception.

And so as you said, sometimes through technological innovation – you give the example of hard drives – sometimes the value of innovation is dissolving false tradeoffs and allowing us to have the best of both worlds. That’s a great aspiration, but it’s also very risky to think, well, we can just innovate our way out of any having to make any choices and we can do everything. And especially for a startup, as you said, there really are limits to resources.

These are real choices. They are not false choices. And so there’s like a wisdom or a judgment that comes in in identifying which of these tradeoffs we need to make just a hard decision on. And which of them we can sort of innovate and wiggle our way into getting it all.

How have you seen founders develop that wisdom and discernment or and how have you developed it yourself? Where do you see it coming into play?

Chee-We Ng

That’s an amazing question and insight. I would say that sometimes it really boils down to challenging the assumptions.

A lot of people, we accept what is presented to us. We learn to use certain technology, and that’s also given to you, and this is it, and we were not part of building it. We were not there when certain choices were made.

But the innovators that love tinkering with things. They break things and they revisit assumptions. A tradeoff that was done previously may disappear, and people still don’t realize that because technology has improved. And you don’t need this tradeoff this anymore.

For instance, in the areas of databases, the first databases were designed in the seventies and computers were rather unreliable then. You’d have to do locks and a lot of innovation in databases continues to today because workloads are internet scale. And then so a lot of what innovators do is they go back and say, hey, let’s look at some of the assumptions, what were the tradeoffs or decisions they made in the past. And what can you give? How is the world different now if you can make the choices again. And that’s how you actually make breakthroughs.

And that’s why, it really has to be those people who are tinkering and playing with it that goes back and ask the question of why not? Not just the whys, but why not? Why couldn’t we do this?

And so those are ways that I see these innovators create. They really challenge those assumptions and those decisions that we’ve made in the past.

Jonathan Rechtman

What have you learned from this whole journey? You’ve been practicing I mean, in the technology space for decades in the investment space for a very long time. What have you learned from your experience that you think has more generalized applicability? What is wisdom that we can draw from your practice and technology and investing that we can apply in our lives? Not just as investors, but as human beings.

Chee-We Ng

As I invest in these technology startups, I see the business of selling the product of a company is really hard. And what’s really important for us to be focusing on is delivering a very distinctive value. And so venture capital and entrepreneurship is about creating not any value but distinctive value.

And so if I take a step back and think about life, I remind myself every day in any situation, how can I bring distinctive value to this situation? What can I do to leave the world in a better way, in a distinctive way? What other thing, based on my experience that I can give that maybe someone else is not in the best position or has not done? I’d say that that is the one thing that I really learnt looking at founders creating these companies, and that would be the one lesson if I were to generalize that and bring that to my life.

Jonathan Rechtman

You mentioned you have a daughter. Right? Yes. I have a daughter too. If you were to give advice to our daughters on how to find their distinctive value and cultivate distinctive value, what would what do you tell them? How does a young person uncover something special about themselves? In this world of many, many people who have many, many abilities, how do you find something truly special about yourself and create that distinctive value for the world?

Chee-We Ng

One of the unfortunate things that has happened, I don’t know for how long, is that people are conditioned to stop listening to the inner voice, which actually all of us had when we were young.

It’s that burning question. And we were asked to just ignore that, suppress that. Sometimes I look at Charlotte learning science and the way she’s taught, it stamps out the curiosity and wonder.

Wonder comes from that inner voice that somebody’s talking to you. And this is something that I couldn’t emphasize more, because it’s actually already there. You actually didn’t have to learn it. It’s already there.

All you have to do is to listen to it.

This is particularly interesting for me because when I when I first showed up at Harvard Business School, and we are all case method, the professors always start with the question, “What do you think?”

And it’s a really weird question.

But then I realized why that question was asked. Because it’s really about what do you think? Not tell me the answer that you prepared, but you what do you actually think.

And so what I would encourage children to do is to listen to the inner voice.

And with that, then they are really observant. Innovators need to be observant. They are always looking at things and it’s the inner voice that tells them, I think things could be done a different way.

Jonathan Rechtman

In my own business, I often find myself saying my business brain says this, but my heart says this or my inner voice has another view. And we’re absolutely trained to kind of try and squash out that subjective voice and apply the cold rational logic. And I wonder whether that is one of those real tradeoffs or should we be trying to marry the two or integrate the two or dissolve the duality between them?

You know, if we have multiple voices in our head, is one of them true and one of them false?
Is one of them, you know, an external projection of society, or our teachers and the other represents our true authentic, you know, higher self? Or is it possible that it’s all our thoughts are our thoughts? And they’re just different expressions that maybe we can resolve the perceived conflicts between them with just enough time and enough tolerance for them perhaps?

Chee-We Ng

Yeah. I think this is what the author, Daniel Kahneman of the book Thinking Fast and Slow said.

We do have the two sides of the brain. The slow thinking which is the analytical logical thinking and the fast thinking is that gut intuition.

Unfortunately, especially the engineers and most of us, we tend to spend a lot of time more on the slow thinking. As engineers, we deal with all the concepts and all the things that are so abstract. It’s not intuitive. And you learn to ignore that intuition.

But if you read books about how the real mathematicians think, you’d be surprised that the best mathematicians use intuitive thinking. You must be like, you got to be kidding me! We learn math without intuitive thinking. Step by step, this is the formula and this is the strategy and the methods you can actually use. And that’s what we end up with

But we need to use both brains. We need to actually use both thinking to look at every situation. We need to reconcile the differences. We need to understand the limitations. Certainly, even a mathematician, the fast intuitive way may give them a hunch. Oh, I think maybe you should head this direction. But when they, write out their proofs, it’s all the slow thinking they are doing.

Jonathan Rechtman

A formative experience for me was I played a lot of chess as a kid. And I would play a lot of blitz chess and then had a chess tutor.

This is like the classic, Searching for Bobby Fischer story. There’s the speed chess in the park and then the tutor that wants you to just study the world for twenty minutes before you make a move. And it does seem like a tradeoff. They reinforce each other. The fast decision making, the time pressure, it sort of forces out inspiration. It develops that intuition. You start to see things. You don’t even know why you see them. Your eye looks at places on the board that you wouldn’t otherwise think to look. And it goes there immediately, and you can’t explain why. It’s very black boxy. It’s a little bit like an AI. It’s just like where did that come from? Yes. But this also probably has a pretty high error rate. And the slow kind of methodical, diligent processing, helps round that out. So maybe it’s just it’s about finding a way to reconcile them.

Chee-We Ng

And I think it happens in business every day. In a business meeting, you have executives. You do the analysis. You have the CFO with probably very analytical, the numbers. But when all that slow thinking is done, when you communicate certain decisions, it’s more likely that it’s the intuitive way of communicating. Of course, you wanna have the support of the facts and the numbers and the logic be watertight. But when you boil it down, it is that intuition that’s like, okay, that that’s why we are doing this.

Jonathan Rechtman

Do you have any practices, personal practices for maintaining presence and balance and clear mindedness in a world and a business that can oftentimes be distracting and stressful. How do you find a balance and a peace and a presence to apply to your work?

Chee-We Ng

There are many things that I try. I guess it’s different tools that I pull up from the toolbox.

One is setting aside time for doing different things. If you wanted to do some serious thinking, I set aside time at night when it’s quiet to do some reading and do some reflection. Be aware that this is how I function best and creating those times to do it.

And then of course, a lot of everybody knows this, which is make sure you have time to rest and exercise. And that really helps the body cope.

And then, I constantly remind myself to take things in perspective. Also challenge assumptions. We already discussed a bit about challenging assumptions. So it’s like, let’s try to be really taking a different perspective.

And we all know this. Perception is everything and yet everybody has a different perspective of things. If three people saw something happen, everybody will have a different perspective. And so you have to put yourself in others’ shoes in looking at the same thing. Even though, after doing that, you can still say, okay, I still think this is my choice, but it really helps challenging myself. And also, hopefully whether or not you would still remain with the same decision as before, and you’ve actually gone through that exercise, so that you have the comfort that you are able to make that decision, having considered all different perspectives.

Jonathan Rechtman

That’s interesting. When you say put things in perspective, the first immediate intuitive question I have is put things in what perspective? There are an infinite number of perspectives to put things in.

But I think you followed through with a nice answer, which is it’s kind of put them in all the perspectives and then maybe come back to your own and say, has this journey has it has it changed my subjective perspective at all? Do I still believe what I believe? Do I still judge this the same way, having been around the circle? Yes. Having looked at all these other perspectives.
So it’s not so much about you’re trying to just shift your perspective. It’s more like your touring around perspectives and coming back to our own.

We thank you for sharing with us today. I learned so much from this conversation. I had a lot to go back and think about. Is there any other final words of wisdom that you wanna share with, with me, with our daughters or with our audience?

Chee-We Ng

I want to talk about AI. A lot is happening in AI and we invest in AI, and we follow the innovation. We also hear about the limitations and where the technology is today.

And we’ve seen the world go through different transitions, and how the world economy has changed. How competition has become very, very intense and how, as we discussed, for startups to survive, they have to deliver distinctive value. And humans have to do that as well. You’ve got to be ahead and have unique experiences and abilities that create value for others.

Going forward, AI as we understand it now, with these new innovations in foundation models and transformer models, we are in truly uncharted territory. In the next decade, I believe these technologies will be everywhere. And, it would start to create a very weird situation where a lot of information processing, things related to content, information, knowledge will be taken over by computers, which would actually challenge what it means to be intelligent.

And that’s a very scary thing. That’s a very scary thing because our children are completely, completely not prepared for the world that is coming, and it will come in the next five, ten years. All the school children today are just not well prepared because they are still in the mode of processing knowledge.

We are in the knowledge economy, and so kind of like knowing things and processing things is the focus. But going forward, a lot of this will become automated.

And it won’t be perfect, by the way. My prediction is, AI is not winning human beings because it’s perfect. In fact, it will still win the human, even though it’s imperfect.

And so that really pushes us to go figure out what it is to be human. What our children must do that computers will not be able to do. And that’s something that we have to be thinking. And instead of worrying, AI is bad and taking away jobs, running amok and we’re gonna fight AI, we should be thinking about what it truly means to be human. And to be focusing education and the work we do in areas that we are really creating, that we are really doing what is human. I think what we should be focusing our energies on are the many challenges that the world faces, right, climate change, and we can go on and on this.

Jonathan Rechtman

Well, it reminds me so much of the conversation earlier on distinctive value for individuals. But in this case, we’re talking about a distinctive value as a species as human. What is distinctive about human value? Yes. And I think the obvious or the low hanging fruit answers that are usually given in these kinds of conversations is creativity and imagination and maybe something spiritual or emotional.

And you get a vision of the future human economy as know, the robots are doing all the real work and we are painting beautiful paintings and, you know, being life coaches and yoga instructors for one another. And maybe that’s it. Maybe that’s endgame for human productivity.

But do you see anything, you know, when you think about this deeply, when you set aside time to read and reflect and go for walks and think about your daughter’s education, do you imagine something beyond that or some manifestation of that is not so easily trivialized or trivializable?

Chee-We Ng

I’m still figuring this out. Actually, everyday I think about this.

I would say one of the things is still uniquely human is conceptualizing.

At least, right now, ChatGPT and GPT-4 doesn’t conceptualize. They are very good at summarizing. They are very good at putting different ideas together. But I don’t see AI conceptualizing things.

Put it this way. If Isaac Newton had AI, AI could have predicted how the earth rotated around the sun with an incredible precision.

But it was Isaac Newton who said, there is a force. I don’t think ChatGPT would create the word force or the concept of force the way Isaac Newton did. I’m sure ChatGPT can write about force and all of that only now.

And so one of the things that I think is still uniquely human is being able to conceptualize. And this is not just physics. It’s business. It’s life. It’s about how we interact with each other. It’s about politics. Everything.

And it really is the inner voice that we spoke about looking at something, having that funny, what’s this thing? And then us as a civilization talking about it and conceptualizing and hopefully taking positive action. That is something that AI I hope can’t do.

But that’s what we should be focusing our energy on so that we work together, we tackle all the challenges that we are facing and will be facing.

Jonathan Rechtman

I’m beaming because I’m imagining my daughter who’s two and a half years old. I’m imagining her coming up with her first concept. It’s like we when we think about children speaking their first words, this big milestone.

Similarly would be like the first time that she conceptualizes something. She takes an abstraction and gives it a name. She observes something in the universe that exists, and then from it derives something that did not exist. She makes something up that captures that. And I just think that’s a really exciting idea.

Chee-We, thank you again so much for this conversation. I learned so much. And I’m so excited to kind of go back and reflect on it and apply it in my own life, and think about how I cultivate the ability to conceptualize, think about how I am able to articulate a distinctive value in a world still awash currently with human competition and increasingly with AI competition. And then maybe most importantly how we position our children to do the same. And find something truly unique about themselves and come up with unique concepts that push us forward as individuals and as humans. And I give you a lot of good credit for inspiring us along that journey.

So thank you so much for this chat. I really enjoyed, chatting and thanks for doing this. Thanks for listening.

To support, please check out the links to our sponsors in the show notes, Follow me on LinkedIn, and of course, subscribe to the essence of investing wherever you get your podcasts. With that, I’m signing off your happy and humble host, Jonathan Rechtman.
See you next time.

The post Essence of Investing appeared first on Oakseed Ventures.

I had the honor and privilege to organize and moderate a panel on “Business & Society in the Age of Generative AI, Large Language Models and ChatGPT” for the Harvard Business School Association of Northern California HBSANC.

Our panelists were Olaf Groth – renowned author and founder of think tank Cambrian Group, Zornitsa “Zori” Kozareva – co-founder CTO of enterprise AI startup SliceX AI and former professor of NLP at the University of Southern California, Emad Elwany – co-founder CTO of legal AI startup Lexion and David Wang – Chief Innovation Officer of tech law firm Wilson Sonsini.  I’m the founder of Oakseed Ventures.

Where are Generative AI, Large Language Models and ChatGPT headed?

Olaf kicked off the exciting panel by sharing insights from his upcoming book “The Great Mobilization: Strategies and Designs for a Smarter World.” The Cognitive Economy is one of the “Five C” tectonic forces shaping the global economy. As many as 300 million jobs will be impacted by AI, and it will be difficult to retrain such a large number of people.

Emad shared his vision for Lexion, to provide legal professionals with the tools to be more effective. As one of the first to incorporate Large Language Models (LLMs), Emad observed that “hallucination” is a real problem. In fact, as the models become bigger, the “explainable” problem becomes worse, and fixing the hallucination problem is like “whack a mole” – patch a problem and another shows up.

David shared his perspective on the technology and what it will mean for the legal profession. Referring to the book “Thinking, Fast and Slow” by psychologist Daniel Kahneman, David likened AI to “system 1” instinctive thinking. Human instincts can be unexplainable, biased, and wrong, and so can AI. David doesn’t think AI will replace lawyers but change the legal profession in unexpected ways. For example, he’s observed contracts become longer, as both sides of the negotiating table use generative AI; this is a continuation of a trend that really began with word processing. He also believes that there will be simply more lawsuits or litigations until the courts become the bottleneck, as the legal profession becomes more efficient.

Challenges with AI

Zori shared her perspective that a major problem exists in AI today that corporates are not ready to share their data with AI companies. Also, AI companies like OpenAI can kill the businesses of companies that offer services on top of their AI platform overnight. Zori sees a faster adoption of AI and LLMs in the consumer segment. In enterprise applications, marketing and consumer experience currently lead the way while segments like medical are slower.

On whether AI will surpass human intelligence and where the world is headed with AI, the panel had a lively debate. Zori noted that LLMs still fumble with basic math and Emad noted that AI is still good at doing specialized tasks, and does not have the general intelligence that humans have. Olaf quickly pointed out that humans often make the mistake of using ourselves as the model for intelligence, whereas other organisms are better than humans in other forms of intelligence. We cannot judge AI by comparing it to a human. Historically, capital markets have not been able to capture the value and reward companies for upgrading human capital, as compared to capital investments. Hence, Olaf believes that companies will be forced to use more and more AI in the companies.

What should CEOs do in Age of AI?

On the question of what CEOs should do in the age of AI, both Olaf and Emad opined it is important to not just work on AI for AI’s sake, but to figure out how companies can differentiate and solve real problems with AI. Olaf points to AI Readiness Self-Assessment Tool to help companies evaluate their Company AI Readiness Index (CAIR) and identify and prioritize areas for action and recognize potential harmful missteps.

The audience joined in a lively discussion with the panelists. On the question of what generative AI is best used for, Emad shared that generative AI has lots of applications across the creation of texts to images but there are many better, less computationally demanding AI techniques for language understanding and classification. For instance, generative AI would not be good at helping a doctor with diagnosis, but a good application would be helping doctors improve the tone of what they write to their patients.

On the question of whether companies can trust AI companies with their data, Emad pointed out that it will boil down to legal contracts and trust. Today companies already place their data in public clouds operated by Microsoft and others. Olaf opined that humans create by getting inspiration or combining the creation of others, and society will have to come to terms eventually that AI will do the same.

Thank Olaf, Emad, David, and Zori for taking valuable time off to participate in the panel and share their insights on where business and society are headed in the age of generative AI, Large Language Models, and ChatGPT.

The post Business & Society in the Age of AI appeared first on Oakseed Ventures.

Oak Seed Ventures recently completed the first closing for its new Core Tech Fund. Seeding early-stage core technology startups, the venture capital fund invests in companies that are developing AI, 5G, SaaS, Web3, cloud, as well as data and enterprise infrastructure.

The global venture capital firm was founded by Ng Chee-We, who has been leading investments in early-stage deep tech startups for over a decade. With a focus on providing seed funding to frontier tech entrepreneurs, Chee-We has invested in companies such as data intelligence company Kyligence, which has raised over nine figures since its formation.

“Our company aims to seed the tech world with oak trees,” said Ng, who holds an MBA from Harvard and a master’s and bachelor’s from MIT. “Oak trees support a huge ecosystem, and we are looking for the future oak trees of the tech world.”

KrASIA spoke with Ng to find out about his investment philosophy and why he believes this is the best time to invest in early-stage tech startups.

This interview has been edited for brevity and clarity.

KrASIA (Kr): Tell us about your career as a coder before you became a venture capitalist.

Ng Chee-We (NC): I’ve always been interested in computers. When I was 13, I learned how to write programs.

I first went to MIT for my undergraduate studies in electrical engineering and computer science. In 2000, I joined ST Engineering, where I led the team to build Asia’s first encrypted hard drive. Then I went to Harvard Business School. After that, I came to China with McKinsey, where I worked as a consultant for two years. I did that because I heard China was where the next big thing was. Eventually, I decided venture capital was what I really wanted to do because it lets me go back to my roots of loving technology.

Kr: How did you get your start in the VC world?

NC: I started my venture capital career at Cisco Systems, where I was actively looking at investments in enterprise tech startups to understand future trends of innovation, and for the company to diversify into other areas besides computer networking. This was around 2012, when cloud and big data were becoming a thing. This was when the technologies of big internet companies were seeping into the enterprise world.

For me, that was a very exciting time. I also love being in venture capital for various reasons: it keeps me “young” and forces me to continue to learn.

Kr: What are some areas Oak Seed Ventures is focusing on?

NC: One of the biggest areas we’re looking at is enterprise technology. At the top of this IT stack are the applications, such as software-as-a-service (SaaS). As you move down, there are more general technologies—fundamental building blocks that are data-related—including big data and data analytics, and infrastructure, such as storage, computing, networking, and DevOps.

Kr: Why does Oak Seed focus on enterprise technology?

NC: We are bullish on the enterprise technology market. We’re seeing a wave of enterprises that are transforming themselves. These enterprises want to be like internet companies and their transformation is enabling them to serve their customers digitally—in real time and intelligently—so they require lots of data and AI processes. We need startups to provide these kinds of technologies and services.

Kr: What does your startup portfolio look like?

CN: Ninety percent of our portfolio is in enterprise startups, and in areas such as SaaS, AI, data technologies, and infrastructure. Maybe 10%—one or two investments—is in semiconductors.

Kr: Deep tech startups often require massive funding. How capital-intensive are your investments?

CN: One great thing about enterprise tech startups is that they don’t burn lots of money. It’s not like in consumer tech, where you have to spend a lot on customer acquisition and provide subsidies, such as giving out free coupons. For enterprise tech, you don’t have these issues.

Having said that, there are sectors in enterprise that are capital-intensive, such as chips.

The other one that requires a lot of capital expenditure is AI. Some AI enterprises are quite capital-intensive. For example, when they have to acquire GPU farms or pay for that in the cloud, and require many engineers to train large neural networks with large datasets.

Kr: These are challenging times for VCs. We’re seeing the trend of rising KPIs and lower investment rounds. How do you decide which startups to invest in? 

CN: We look for truly world-class entrepreneurs who are building something unique and investing in them at an early stage. That’s our secret sauce. The key is going to them early. That takes sharp judgment.

The business of venture capital is very much about making the right judgment about risk when others are not able to. Otherwise, you are just making the market rate for returns. If you want to achieve more, you have to exploit information asymmetry. You have to have a better ability to pick out the right companies that will succeed. This means one has to have a better perspective of the risks than the rest of the market. And my job is to be on the right side of information asymmetry.

Kr: You recently said the public equity market is turbulent because of spiking inflation and supply chain disruptions resulting from the Russian invasion of Ukraine and COVID-19, and this is the best time to invest in early-stage venture sectors with robust long-term growth. Why do you feel this is the best time to be coming in? 

CN: Many people are worried about venture capital financing in tough times because consumers and enterprises spend less. But life goes on. Enterprise customers are still experiencing pain points that need to be solved, and startups are still being set up. Sometimes, in difficult market conditions, companies feel a need to upgrade their capabilities further and the ROI for acquiring good enterprise technologies could be even more compelling.

Innovation doesn’t stop because of turbulence in markets. The real entrepreneurs we’re looking for have a higher chance of success because there’s less competition for them during this time.

Also, there is less “noise” in the sense that during uncertain times, there are fewer entrepreneurs and startups competing with each other. This makes it a lot easier for us to cut through all that and identify the real innovators.

At the same time, there is less “noise” in financing in terms of the artificial valuations when markets are booming. Now, we can go in early and invest in these startups when they have lower valuations. Hopefully, in five to seven years’ time, we’ll exit, with good returns, assuming of course that there is no major depression that lasts for ten years.

Kr: How have US-China geopolitical tensions affected China’s startup ecosystem?

CN: China wants to become more self-reliant. The government is encouraging domestic firms to buy local technologies. Some startups are responding and rising to the occasion. There are also returnees who come back from the US and start businesses: they believe that for every product in the US, they can develop a regional version.

These entrepreneurs can take these products to Southeast Asia, a market that the US generally tends to ignore. In all, these factors have created a lot of opportunities for startups.

Kr: What advice do you have for startups looking for funding amid the “US-China decoupling”?

CN: It is a good time to be creating companies that would be favored by the environment; for example, making a domestic equivalent of technology that exists in the US.

With that said, I would encourage entrepreneurs to be mindful that the products they create must be world-class and differentiated. There’s no point in being the tenth maker of anything. Whatever you create, you need to have an edge over others.

This article was originally published in KrASIA

The post This is the best time to invest in early-stage venture sectors with robust long-term growth appeared first on Oakseed Ventures.

Adam: Welcome Chee-We, before we dive in… could you please introduce yourself and tell us more about how things got started.

Chee-We: Sure thing. I started Oak Seed Ventures to focus on enterprise and deep technologies. I’m a geek! I taught myself C when I was 14 to develop a word processor for my mum because WordStar, WordPerfect and Edlin were all too complicated for her. Going to MIT was a dream come true, where I participated in early research in AI and chatbots as well as integrated circuits for low-power communications. I interned at Xerox PARC, where almost everything we know about computing was invented, including object-oriented programming, GUI, mouse and Local Area Network; and Bell Labs, where UNIX and transistors were first created.

I started my professional career in cybersecurity where I led a team to build encrypted phone and hard drive which are still award-winning at CES after twenty years. Right before my investing career, I spent two years at McKinsey after Harvard Business School, where I advised telecom operators on mobile OS and Computing as a Service (before they called it Cloud).

I began investing in enterprise tech at Cisco. We were probably the only team solely focused on this in Asia. Our mandate was to invest across the enterprise stack from integrated circuits, storage, security, cloud, big data, AI, internet of Things and SaaS. We did so with a global perspective, looking for world class companies, and also with a value-added approach, where we sought to help our companies with our partner and customer access. I spent a lot of time taking our startups to meet our sales team, channel partners and customers. We were also value-added LPs in venture funds focused in areas of interest to us. After Cisco, I transitioned over to CRCM and Redpoint where I learnt portfolio construction and fund management. It was there I decided to focus entirely on early stage.

I founded Oak Seed to focus on enterprise technologies. Unlike elsewhere, there are few if any VCs focused on early-stage enterprise tech startups in Asia. Yet, when I was at Cisco, we began seeing truly world-class enterprise tech startups in Asia, for example Kyligence. Due to a number of factors, there are now world-class engineers and in particular technology architects and innovators in Asia, which are building the best enterprise technologies anywhere. This may not cut across every field yet, where Silicon Valley still has the lead, but in selected areas. Later stage funds and public markets are beginning to recognize the value of these startups, and I believe having an early-stage enterprise focused fund will be good for the industry and deliver great returns to investors.

Oak Seed’s Investment Approach

Adam: Clearly you’ve done a lot over the past 20 years and I think being a geek is super helpful for investing in some of these areas. In terms of Oak Seed Ventures, we’d love to learn more about your fund. Can you tell us a bit more about your fund’s overall approach to investing, what you focus on, what stage, what are some of the criteria you look for when it comes to interesting opportunities?

Chee-We: Oak Seed is looking for ambitious, talented entrepreneurs starting companies to tackle very difficult problems that enterprises face. Our promise to you is we will help you with introducing key partners and customers, advise on marketing and strategy, or simply being your cheer leader. You will not be dealing with a VP who’s trying to size you up, but a potential thought partner who understands technology and business in a deep way.

We are focused across the entire enterprise stack, from SaaS and tech-enabled business services on the top, 5G and IOT, to data infrastructure and information security. You don’t need to meet partners who would rather spend time with consumer investments because we don’t have any!

We like investing early, as early as just having a business plan or a prototype, because that’s where we can apply our technology understanding and market insight to identify potential winners and help make them successful. For our investors, this drives the upside potential which is important because the road for enterprise startups can be very long.

We apply a convicted approach to investing. This is possible because we can reduce market risk and technology risk through careful due diligence. This allows us to spend more time with companies to help them succeed. Our goal is to deliver 5 to 10x for our investors through patiently waiting for the right investment, working hard to win it, and committing to helping them be successful.

Enterprise Cloud Market

Adam: Can you tell us more about these areas you’re investing into… it’s a mix of cloud and enterprise, some deep technologies and some semis as well. There’re few large companies in Asia in the enterprise space. There is no Salesforce, for example. There are a few companies that are over $10B in market cap in Asia whereas in the U.S. there are many such companies and enterprise and cloud has been all the rage for the past 10 years in particular. How would someone who’s not here look at the cloud opportunity here? Where do we start first to understand this opportunity?

Chee-We: Indeed, the IT spending has been small in Asia even as a percentage of GDP. There aren’t that many big companies (in enterprise software), but there are in hardware, such as Huawei, Lenovo, Inspur, or HTC. There are also a whole bunch of system integrators, many of them listed domestically. But software in particular as a percentage of IT spending is only 3% to 4% whereas in the rest of the world is usually 15%. That explains why, historically, you don’t see that many software companies at all. However, what’s changed is that with the mobile internet, today you see mobile internet, big data, IoT and AI becoming the top agenda for many enterprises. This started with internet companies leveraging all these technologies and then encroaching on the markets of traditional companies, for instance, in finance and insurance.

And now enterprises have no choice but to reinvent themselves. They have to use state-of-the-art technologies to have a mobile and omnichannel experience and they also have to employ big data and analytics in order to stay ahead. So what you can see now in the startup space is a whole school of startups in enterprise space across SaaS, applications, business services, infrastructure services, data analytics and so forth.

There is actually evidence that there will be more and more of these companies listed on the stock market as well. You can already see, for instance, over the past two years, in areas of public cloud, other than AliCloud, two companies have successfully listed, Kingsoft and UCloud. We’re also seeing big data companies like Kyligence and PingCap that have gone from seed to Series C in less than 2–3 years. We expect these companies to become the next set of companies that will become public and gradually change the entire IT industry. Overall, it is true that IT market in Asia is definitely not as big, by any measure, compared to the U.S. or the west, and it is true that it’s largely hardware and system integration, but many many startups are now emerging to provide SaaS, analytics, cloud and infrastructure solutions to enterprises which are now under increasing pressure to stay ahead and facing increasingly competitive market environment.

Adam: There’s been a slew of Chinese enterprise cloud-based companies going public. Kingsoft has been doing well recently. Agora just went public a few weeks ago and their valuation is quite rich. I realize this is a very large topic. There’s a lot to tackle when it comes to cloud opportunities and we’ll probably spend multiple episodes (to cover them all). Perhaps today we can focus on a few specific areas that you’ve been looking at. You were just talking about databases like PingCap and Kyligence. I think you mentioned SaaS as well. These are two things that global investors and founders know very well. Can you talk us through what you’re seeing when it comes to SaaS and databases?

Chee-We: Yes, SaaS is a very hot topic. It’s driving the value of many companies from Microsoft to Zoom to Salesforce which eclipsed Oracle in its market cap, that’s amazing. Yet SaaS is very nascent in Asia but there are many startups that are trying to be the Salesforce of Asia. There have been many waves of SaaS companies in Asia. Waves that targeted SME’s.  SaaS companies offering “freemium” model. Some of these startups in the past have been challenged when tackling SME market. This is a market that, although it looks big because it counts for a significant part of GDP and there are a large number of SMEs, it turns out that they don’t have deep pockets and also often don’t have a long lifespan. The average SME only has a lifespan of 2 years. And with the freemium model, these companies face the challenge of converting free customers to paid ones; typically, the converting rate can be as low as about 2%.

But we’re seeing new types of SaaS. These type of SaaS companies do not just digitize a workflow. It’s not about recording or digitizing a workflow. These are really the SaaS of the past. The new SaaS really combines analytics, AI and external sources of data. They really engage and truly automate workflows. The boundaries between SaaS and tech-enabled business services are also blurring very quickly. Sometimes you’re won’t see a distinction between the two. I might even say that this is happening faster in Asia than in the U.S. where SaaS are usually software companies and business services is very distinct. Here it’s blurring very quickly.

We are also seeing new trends in what’s called low code or no code platforms. This really enables end users to build their own applications that enable the workplace of the future. This is what VCs are actively looking at and we’re seeing new companies in this area as well.

Talking about databases and data infrastructure. This is an area where a lot is happening. With data infrastructure, often times there will be significant bottle necks that show up when you have volumes of data increasing exponentially. New innovation is always required to keep up with large volumes of data: new ways of analyzing and making use of data whenever the underlying hardware changes. Our observation is whereas in the past, many technologies were imported from the U.S. by multinational companies, data infrastructure is an area that, going forward, there will be many more domestic companies, whether these are the big companies like Huawei and Lenovo putting together solutions or these are startups. For instance, data analytics have gone from using Hadoop to cloud and Kubernetes to the next thing which is called serverless. We see both big companies like AliCloud and small startups trying to offer AI on serverless architecture.

Data warehousing and databases are now seeing new growth areas around graph and time series databases. Compute storage fabric has gone from conventional to converged and hyper converged and now composable. Many of these areas will see new innovations. I do not anticipate startups in the U.S. being able to enter the Chinese market going forward. I expect many of these new disruptions to be led by other startups.

Adam: Got it. There’s a lot to unpack here. Just focusing on databases in China, we brought up Kyligence and PingCap and there’re many more projects. I’m trying to get a sense of how well these companies monetize. In the U.S. some of the database companies have done quite a good job with their open source open core approach where they offer up the code for free but they offer other services, could be security or something else, in order to monetize very well. In China, some of these companies I’ve heard aren’t really generating any revenue. How do you see them developing over time?

Chee-We: Different companies have taken different strategies. Companies like Kyligence have actually taken a rather similar approach, having open source version — the Apache Kylin — that everyone can use and extensions and enterprise versions that have more features like security, better performance and also working with end customers to deliver the actual commercial value of using analytics. That’s one strategy. Because Kyligence is delivering something that’s truly world-class, the company has also gone abroad and worked on not just the Chinese market but also opportunities elsewhere, leveraging a global traction to raise money and grow.

There are also other ways that many of these startups have succeeded. You’ll find, as you move from the more generic data infrastructure to providing a service, providing an actual business analytics that’s closer to the enterprise being able to generate revenue, then you will find it much easier to monetize. A lot of the spending these days in enterprises is held in hands of the business unit leaders, not so much in the CIO’s, so to the extent that a solution provided by a startup can actually drive the top line of a business unit, you will find much more willingness to pay on the part of the company.

Geopolitics

Adam: Since we’re on the topic of some of these companies that have world-class talent or are pushing products that could compete against solutions in the US or other countries, it gets me thinking about the elephant in the room, so to speak. There’s quite a bit of tension going on between the U.S. and China. There’s geopolitics going on and I was thinking, there are certain areas that seem to benefit from that. It could include some of the semiconductor companies, chipset makers. A lot of these public companies have seen their market cap skyrocket and have pretty incredible P/E ratios like 100x. Pretty ridiculous stuff. And not just semiconductors and related companies, but also even some companies that we’re talking about right now, databases and alike enterprise. Could you talk us through what you think about this continuous tension and how that might impact the growth of these companies that you’re looking at?

Chee-We: Sure. To set the context, China has been trying to be independent, or at least less dependent, on foreign technology for many years. This started out in, for instance, semiconductors, being one of the major causes of trade deficit. In fact, the trade deficit due to semiconductors has been larger than that of oil for many years. However, what has really happened in the last 2 years, starting with ZTE and now Huawei, is that the very survival of Chinese IT companies and even the entire Chinese economy has been threatened. When you have exports of certain critical components being entirely limited, when you have a blacklist of companies being drawn up, and now potentially limiting the ability of companies to list in the U.S. Basically, going forward, companies and government will try to independent on foreign imports if they can.

There is phrase coined many years ago called “自主可控”. It actually came about when Edward Snowden revealed Project PRISM but now it’s on hyperdrive, which means government really wants to have its own chips and…in the past there was a phrase called “removing IOE”, I stands for IBM, O representing Oracle, E representing EMC. I don’t think that’s so explicit these days, but you can see the government’s desire to be truly independent of foreign technology, and this really cut across the whole stack, from chips to basic software and hardware.

Now, not all of that is possible. It’s probably very challenging to replace Intel and ARM processors, Microsoft operating systems and Oracle databases from legacy applications, but for new applications you will find Chinese companies and the government very cautious of whether it is dependent on a foreign technology. You will find that Chinese government and enterprises want to use open source if they can or a Chinese vendor. So for every new innovation in the U.S., whether it’s a new type of database (for example a graph database) or a new deck of data infrastructure (for instance composable infrastructure), going forward its very clear that these markets will be entirely serviced by regional players.

Adam: Got it. Chee-We, how does that impact your investing? Or take a step back, not just import substitution but in general, given what you’re seeing, how does it impact your investing and how do you go about finding good investments before due diligence given the circumstances?

Chee-We: That actually has been a good change for us. It means there’s a protected market. It means there’s also a lot of talent coming into this sector, which in the past is considered very challenging, because you have dominance of foreign players. In the past, trying to create a new infrastructure startup is impossible; that’s entirely done in the valley or, to some extent, in Israel. Now, with the market opportunity and also with some Chinese talent that has been in the U.S., whether it’s working for startups or just doing their Masters and PhDs at Stanford or MIT types… they’re coming back, sometimes forced to come back. They will be starting startups in areas of enterprise technologies because this is an area that they feel passionate about and they have expertise on, so that’s actually very good for us.

Now, having said that, it does not mean that you can deliver good returns by just backing every company with an import substitution theme, because you still have to spend the time to do the due diligence and make sure that, indeed, this is a company that has the best technology, the best commercial team to execute and you’re going in at the right valuation. Often times, when something gets too hot, then their valuations go crazy and it may not be a good investment.

What Makes a Good Investment?

Adam: What else do you look at when it comes to investing? With regards to the team? With regards to the solution that’s being developed? How do you go about conducting commercial due diligence on very technical products?

Chee-We: Sure. If we take a step back, later-stage venture places a premium on two things: the ability to scale really big and the perceived scarcity of what’s being built. That means our entrepreneurs need to (1) be very ambitious and (2) have a world class technical background and has or is developing something special. I like the teams that have a combination of strong technical and commercial founders. The commercial aspect is often neglected, but it’s often needed because you need to build a clear marketing message for enterprise customers. The product managers need to make the difficult choices of what to be and what not to be, also what use cases to go after and what features to prioritize. This side of things has to be driven by a clear commercial plan, not so much of a technical plan.

I also place a strong emphasis on the team being at the forefront of technology and pushing the envelope. For applications, the team must understand the business challenges and have available at their disposal, the ability to implement state-of-the-art technologies with excellent user experience. For data infrastructure, it means the team understands the bottlenecks of conventional solutions and are making architectural choices that enable a solution that is orders of magnitude better. It is also highly crucial to link technology to the use case. One must never fall into the trap of a solution looking for a problem.

To complete commercial due diligence, it is important to spend time with the end-uses, the CIOs to understand use cases, but also partners, for example system integrators which are needed to put together solutions for end customers.

I often get asked a question, how do you know how strong is a CTO or founder technically? It really boils down to this. In every area for enterprise startup, there is an envelope of what technology can achieve beyond which there are serious trade-offs. Sometimes there is even a computer science theorem, for example the CAP theorem, CAP’s short for consistency, availability and partition tolerance, that says you cannot achieve all three at the same time; you must have a trade-off.

When I do due diligence for a company, I try to get myself educated at where that technology boundary is by talking to experts and learning myself. Then I spend time with the CTO or founder and see where his understanding is. There are CTOs that don’t understand the limitations of technology or where that “state-of-the-art” is or when things will get challenging, these CTOs are not the world-class founders who are pushing the envelope. They haven’t gotten there yet and that’s why they don’t see where the limitations are. That means, whatever he’s working on, unless there is another knowhow that’s required from outside of technology, it will be quite easy for a competitor to build exactly what he’s thinking of building.

Then there are the CTOs that appreciate the limitations and trade-offs that technology forces them to make. They are already thinking of solutions and are making architectural choices. These CTOs are at the forefront of technology envelope.

Then there are, now and then, CTOs that not only appreciate the limitations and trade-offs that I am aware of (after speaking to a host of experts), but also understand other challenges and issues further down the road. These CTOs are truly pushing the forefront of technology envelope. Startups that are founded by the latter two types of CTOs, in my mind, stand a higher chance of being successful because what they build will have fewer entrants or copycats.

Entrepreneurs in the Space

Adam: Could you walk us through some of the investments you’ve made prior and give us examples of some of these founders. Why did you decide to back them?

Chee-We: Sure. Let me share with you the stories of two entrepreneurs in the data infrastructure space, hopefully they serve as inspiration to future entrepreneurs. Luke Han with Kyligence was with e-Bay in Shanghai. E-Bay, as everyone knows, has no business in China, but they have an R&D team. E-Bay wanted to perform multi-dimensional analysis on very large sets of data, which were stored on Hadoop. Think of it like performing pivot tables on Excel, but for billions of rows of data. So, they got their Shanghai R&D team to work on it and build, initially, this internal tool for themselves. Then e-Bay decided the open source what they built, which became Apache Kylin, the first ever top-level Open Source project from China. What happened next was customers ranging from Citibank to China Mobile began to use it and began to ask Luke and his team at e-Bay for technical support. The team decided to quit and create Kyligence to build an enterprise solution around Apache Kylin and help customers with their most challenging analytical problems.

Another example, Chen Xi, the founder of Fastone, was with EMC. He was probably the youngest technical director at EMC, leading the team that built EMC’s Hyper-converged Infrastructure product line from nothing to becoming №1 worldwide. He paired up with his college classmate and former colleague who became a sales leader at Amazon Web Services to start Fastone, which provides a proprietary high-performance computing cloud solution. This is truly proprietary and world class, not just a Copy to China kind of strategy. He really thought through where the technical bottlenecks were and created an entirely new solution. Now the solution is now being used by industries cutting across genomics (which needs a lot of high performance computation to do genome sequencing) to semiconductors (for simulation and IC design) which is currently seeing a huge uplift, given the US-China tensions.

Luke Han of Kyligence and Chen Xi of Fastone, in my mind, represent a sample of world-class technology entrepreneurs. They are not doing a Copy to China strategy that many predecessors did. To me, what’s most surprising is that this is happening in the enterprise tech space in China, where what they are doing is not just best in China, but best everywhere in the world.

Adam: Definitely impressive founders. Having worked with some of these top-class founders, do you have any advice for other entrepreneurs looking to build businesses in these areas?

Chee-We: My first piece of advice is be different and choose a difficult area. The scariest thing about starting a company is after one year of diving into doing it, there are 5 to 10 startups trying to do the same. When that happens, you will find it very difficult to stand out and have to compete on price. I often hear entrepreneurs say “that’s okay, the market is big enough” and that’s one of the biggest fallacies — yes, the market may be, but the customers will get you and your competitors to outbid each other in RFPs and tenders. That basically means it’s a competition of price and a race to the bottom. This is very different in the consumer space.

My second advice is focus on commercial value that your solution brings to a customer. Technologists are too often inward looking. They try to make the world better, not a particular customer. But frequently, the world may be better, but nobody is willing to pay big money for it. Companies pay for someone to solve a pain point, not for removing inconveniences. Try to work on the top one to two priorities for your customer, which could be the CIO or, nowadays, could be the HR or finance department. You may be working on an analytical tool, but at the end of the day, there must be a commercial benefit to someone, e.g. the marketing department or the finance department. It must mean something to them.

Finally, move fast. Really fast. Be willing to make mistakes and learn quickly. The difference between a winner and the rest often boils down to being the first few and speed. In Asia in particular so because VCs will throw money at the first few quality teams and totally shun the later ones because they feel “the window is over” and there are players in front that have lots of money. Deliver quick results in short cycles, and always be in the market to raise money, which is a rather unique feature of the Asian startup/VC market.

Adam: Got it, that’s really helpful advice Chee-We. Thanks for sharing your views on what’s happening in this market to me, to the investors who are listening to this podcast and also the founders who look to draw inspiration from your experiences. Chee-We, thanks so much for your time.

Chee-We: Thank you!

Interview with Adam Bao of Harbinger, reproduced with permission from http://www.theharbingerchina.com/blog/investing-in-chinese-enterprise-and-core-technology-with-oak-seed-vc

The post Investing in Enterprise and Core Technology – The Harbinger appeared first on Oakseed Ventures.

Indeed, whereas four SaaS companies with more than $10b went public in the US this year, Sensetime, the second highly valued enterprise tech Unicorn after Alicloud, is roughly $7b while most of the other enterprise tech unicorns are less than $2b in value.

How is the enterprise tech market different between China and US and why?

Let’s look at the enterprise tech unicorns in China today. The big elephant, though one might cry out “not fair!”, is Alicloud, valued at $70b. Together in the category of public clouds are Tencent cloud, Kingsoft cloud and UCloud. The second biggest category of unicorns are in AI and Big Data. (I group them together because the boundaries are blurring though the recent renaissance in AI is arguably due to Deep Learning). Here we have the three deep learning giants, Sensetime, Megvii / Face++ and Yitu, but also big data companies that serve the government, financial services and retail like Fourth Paradigm and Tongdun. Security has a lonely giant 360 Enterprise, followed by market places with Zhubajie, a platform for jobs. Surprisingly but perhaps not surprisingly, Internet of Things, PaaS and SaaS each have a handful of unicorns but they are much smaller in size. 

A few observations jump out. First, the unicorns are much smaller in size. Second, there are several that are subsidiaries or spin-offs from larger corporations like Alicloud, Tencent Cloud and 360 enterprise. Third, other than Alicloud and Tencent Cloud that get to their scale by servicing many small and medium services, other large unicorns, especially the face recognition ones, get to the scale by serving the government and financial institutions. It may be fair to say, there are almost no unicorn that is in the fundamental IT infrastructure space like security, other than public cloud. And SaaS is still very nascent. 

Why?

As a historical context, IT spending as a percentage of GDP has been small in China compared to many parts of the world. Many who lived in China have the experience of receiving government official name cards with a personal 163.cn email address on it. Others will identify with the practice of needing a stamp on paper to be official and recognized. Yet others will tell you, if numbers can’t even be trusted, why bother digitizing things, it will only cause more confusion and worse still, embarrassment. 

IT market has been one that is mired by RFPs/SOWs/tenders and price competition and long sales cycles. Will that change?

I recently did a CIO survey and good news is, all of that is and about to change. CIOs are now asked to be profit centers to drive business, not cost centers where they are custodians of IT which is more like utilities or plumbing. CIOs are now tasked with deploying mini-apps in fast order, deriving insights from data and leveraging new technologies like 5G and IOT to transform businesses. 

What do enterprise startups need to do to succeed? Startups must have the courage to build unique offerings and work on the really difficult things. They must learn to sell based on value not cost plus that has trapped most of the ISV and SI market.

While Chinese companies may take a while to trust their data to be stored in a SaaS, and enterprise tech startups will continued to be challenged by the speed they can go to market and raise money compared to their consumer ones, I am hopeful that enterprise tech startups in China will get more attention that they rightfully deserve. Already there are enterprise tech startups in China that are truly world class, such as Kyligence whose team contributed to China’s first top level Apache Project Kylin and Oushu whose team created Apache HAWQ. China has some of the world’s most challenging enterprise problems due to its scale and diversity, and its engineers have and will be stepping up to solve these problems!

Really excited to have been investing solely in enterprise tech for the past 7 years. Looking forward to witnessing the next transformation.

The post Where are all the Enterprise Tech Unicorns? appeared first on Oakseed Ventures.