Michael Li discusses his fund's investment strategy across seed to Series A stages, with typical checks of $1-2M from a $50M fund. He covers focus areas including environmental tech, water and energy, and an initiative linking China and African markets. Li also flags a critical shortage of technical talent for AI, IoT, and VR startups.
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Actually, my last question, then we'll open up to you guys. So we have 65% international students.
Yikes.
Have you thought about, given the close relationship between China and Africa, right? And China had bypassed the communication, the landline, and went straight to wireless. And Africa is probably going to bypass certain things, say finance or transportation, there are different things they can bypass. Have you thought about investing anywhere else in the world? You mentioned Israel, US. How about emerging markets like Africa?
That's a really interesting question. We have an initiative in South Africa. We're partnering with the largest sovereign fund in South Africa called the PIC. I think this is a little different. For investment in innovation, we want to target in countries where you see most of the innovation. But for African market, we do see that the mature market— it's a market that cry for low-cost and competitive products. For example, they are in severe shortage of water and energy. So renewable energy and the water treatment, water technology are something that can be applied, easily applied. And then for that, our portfolio company, by working with PIC, can serve as a link between the Chinese market, not only the Chinese market, can be the origination of competitive product into the African market.
Yeah, that's very clear. If China is the factory of the world and Africa's gonna ramp up on demand, So that bridge is probably going to become a pretty active commerce path.
Yeah, I think it's already pretty active. There's so many companies. I know quite a number of established Chinese companies like Hisense. They're setting up their factories in South Africa and doing really well. And Huawei is following suit.
Good. Any questions? Dominique?
Can you talk more specifically about your environmental project and how best to reach you if you want to connect with you?
Oh, okay. Well, for the environmental protection, that's a pretty big market. Initially, we focused on, you know, more on the terminal treatment like air, water, and solid waste. So we have made quite a few investments. For example, one of the earliest investments called Dongjiang Huanbao. That was doing the waste PC board, how you can recycle those. Later on, they moved into industrial water treatment sector. They're a public company now and doing very well. But as the industry grow, we actually sort of shift our focus from terminal treatment to process control. And even for more green material, the prevention of treatment pollution at all. So those are— it's a very broad area now.
And how best to What's the best place to reach you if we wanted to connect with you?
Oh, you know, you can email me. My email is michael@tsingcapital.com. T-S-I-N-G capital dot com.
Thank you.
Thank you.
So you mentioned that your capital fund invests in smart technology. And my question is, typically, What is your ground level or your most basic investment? What is it comprised of? What are you expecting of a fledgling technology company that has both hardware and software components to the technology?
Yeah, basically, let's— 2 questions. First one, in terms of stage, it's an early stage company. So we typically invest at seed, pre-A, or A stage, you know, probably more on seed and pre-A. What the thesis is, I forgot to mention, is we have very carefully selected our LP base. The idea is we want to create our own— everybody's talking about the ecosystem. We want to create our own ecosystem. So in the areas that I mentioned, We have about 10 public companies behind us. So they are, they are, they will be the one giving us money, and they also be the one that can help our companies, you know, try to localize, try to do manufacturing in, in China, try to get the supply chain expertise globally. So those are the value that we try to create in, in all the areas that I mentioned.
And you said Series A is where you come in as an investor.
How much do you typically— Oh, typical size would— the fund is only $50 million, so we want to invest probably $1 to $2 million per company.
You're speaking like a real Chinese VC, because the pre-A deals we do here are like $100,000 to half a million dollars. $1 to $2 million is a big check.
Well, that's, I understand. We can do less, but I think the typical is $1 million. It also is a consideration about the number of portfolio companies that we can manage.
You have a question?
Yes. So you talked about the investment fund that focuses on the Internet of Things, AI, VR, and these emerging technologies. Does your fund have any exposure to that? thoughts about the shortage of technical talent that will carry out what these businesses are proposing?
Technical shortage in terms of when we do the evaluation?
Of engineers.
You're thinking more like education training type of?
Yeah, I'm just interested to see how venture funds are responding to the fact that like these businesses will have a shortage of technical talent. Like for people focusing on machine learning, you talked about the $2 million per— yeah, or like even Even front-end engineers can still walk into $120K salaries, bounce between these large corporations while tripling your salary over 3.5 years because of the shortage.
Well, that's the fact. I think this is all— hopefully that's a temporary imbalance, right? Things will change over time. But obviously, you have to take that into consideration at the moment if you want to invest in AI technology. You know, the— not only the cost of the engineer, also the availability of the engineer is also a big issue. You know, for our investment in China, we tend to develop long-term relationships with known entrepreneurs long before, even before they decide to go out and start up their own company. So that's one way you can, you know, get an early ticket. Instead of having to face, you know, this is, you know, in China, AI companies are quite pricey already. You know, that's probably, you know, I've been in this industry for so many years, so this is always cycles.
So it's a good point because I remember 2 to 3 years ago, data scientists were $1 million per person.
Yeah.
And now it's come down because People, there are more people studying data science.
That's right.
Or at least more people claim they're data scientists.
We've actually seen a reduction. By like 2018, we'll have a shortage of 50% in the US. It's like, why do we have to outsource to other countries?
Yeah.
Just for data science, like we'll have 450,000 available jobs, but only 200,000 candidates.
Yeah. Well, that's a fact. And if that's the case, you really think You know, we are focusing on midterm, long-term potentials, not short-term. So you should not be too carried away by the short-term imbalance. If you believe in the long term, then you should find the— always be patient and try to find—
Take a 10-year, 20-year view.
Yeah, not, not, you know, if you look at 2-year, 3-year view, Then you're really facing a pretty embarrassing situation. Are you going to invest or not?
Oftentimes we say it's easier to predict the outcome but difficult to predict the timing. So you want to get the 10-year, 20-year, you know this will happen, AI or robotics, but it may take 7 years or it may take 12 years. You don't know.
Yeah, exactly. And besides, I'm— maybe call me conservative because I'm not a big fan of the AI companies, some of the AI companies on the market right now. I think really it's just a little bit outrageous. You know, AI by itself is not going to, you know, it's not going to Solve the whole world's problem. It's a technique. It's been around.
Sometimes people say the more you know, the harder it is for you to invest in the sector because you just, you know, there are all the different ways to screw up, right?
