In this episode I speak with Mikhail Taver about investing in deeptech and AI.
Mikhail’s background in investing and interests in AI
Deeptech/AI and why he loves those investments
GenAI, why it is a bit hyped, how it might change the investing landscape
Fields he’s most exciting investing in and how they will benefit from AI
Fund's website: https://www.taver.capital/
Mikhail's Linkedin: https://www.linkedin.com/in/mtaver/
Mikhail's Twitter: https://twitter.com/TaverMikhail
Fund's Linkedin: https://www.linkedin.com/company/taver-capital-partners/
Fund's Twitter: https://twitter.com/TaverCapital
Welcome everyone to another episode of PromptPod, an open-ended
exploration into the field of AI and my quest to document conversations with
bright minds in the space. I'm your host, Danny Kirk, and today I'm joined by
Mikhail Taver. Mikhail is a seasoned career investor with over 20 years of
experience in venture investments.
Mergers and acquisitions and strategic consulting. As the founder and managing
partner at Taver Capital, an international venture capital fund based in
Delaware, he focuses on investing in artificial intelligent companies worldwide,
with a diverse portfolio of over 20 companies spanning various verticals
including cybersecurity, mineral mining, tech.
Health tech, agritech, legal tech and sports tech. Taylor [00:01:00] Capital has
achieved four successful exits throughout his executive roles in major financial
groups in industrial companies. Mikhail has successfully closed over 250 m and a
and private equity deals. Mihail, welcome to the show. Hi, Danny. Thanks for
Excellent. Well, would you tell, um, our audience a little bit about your
background and how you got into investing and also how you got first got
interested in ai? Right. Well, I'm, uh, I am what you might call a career investor.
I've always been interested in doing this sorts of thing. Uh, I was born and grew
up, uh, at the very.
North of Russia, sort of polar zone. So there was really nothing to do there,
especially during the long winter nights. I had this, uh, Huge, uh, sort of wall of
bookshelves in my room, and I just, well, literally, there's nothing to do but
read, uh, yes. I, I, I got a computer when I was about, 10 or 11, [00:02:00] but
before that, I was reading that when I was about six or seven years old.
I read a book, uh, by Theodore, uh, a series of books. There's a three film, uh,
uh, I did not understand most of it as I see from now, but I got interested in
securities and. Investments and markets and, you know, those, those, uh,
difficult to understand pieces of paper, they apparently managed to, you know,
uh, Drive the world in a way.
Uh, and this is how I got interested in investments in general. And since then
I've been, uh, teaching myself to do that. Uh, I went to college to do that. I went
to the university to do that. And then, uh, I became an investor. I've been
investing ever since. And, uh, hope I'll be doing that for some time. So that's
how I got into investments.
Very interesting. Did you know other people, um, in the town you came from
that were interested in investing or was it until you got to uh, university? Uh,
well, I mean, no university I went to, [00:03:00] uh, my, I did my gcss in the uk
and that's when I, uh, started hearing the word investments from other people.
So, no, no, no, no.
Before that it was only me. Some, I dunno. Excel tables and it's, and a 2 86 pc.
Amazing. And how about ai? When did you first come across that, uh, Uh, this
is interesting cuz I mean, the first time I actually, uh, came across that and the,
the first time I've, I've learned something called a neural net, uh, was back in
1999, I think, when I was, uh, at the university.
And I, I, I actually tried to create a, a neural net, but uh, it was just, uh, with a
pen and paper, so I was just studying the concept. Uh, I understood how that
works. It was interesting. But other than that, you know, I mean these were the
times that, you know, things like data digging. Were not fashionable and were
almost a swear word cuz I mean, you know, the more you look at data, the more
patterns you [00:04:00] see and that's not something you should be doing with
That's what they used to say at the time. As as we're all now, now, you know,
this is the bread and butter of uh, ai. Starting. So this is when I first tasted that,
uh, after that, mm, I don't know. I suppose the, uh, closest sort of real AI for me
to touch was Siri as, uh, with the majority of people, I would say, this is when I
got interested in that.
but as an investor, well, uh, our fund's first deal was something called
masquerade. Uh, that's the company that you know. You might remember all of
a sudden everyone started, you know, wearing those, uh, dynamic masks. Um,
it, it was a quick, pretty quick deal. We sold it to Facebook, uh, three months
after, after it all sort of started.
they weren't strictly speaking, they weren't using ai. There was something called
ris, but it doesn't matter. It was, it was still something AI ish. So this got me
thinking and when, when we started planning, uh, a fund,[00:05:00] the real
reason to be honest was that I'm not that good at delegating, so I knew that the
actual, uh, team is not gonna be that large.
So we needed something with good potential, but manageable. Something
niche. this is where we made a mistake of thinking that this is gonna be ai.
apparently it wasn't that niche as we all now know, but yes, that's how I started
investing. And yes, this is how the current portfolio came to be. Our, uh, second
investment was a company made Prisma that you all might know with the
Uh, last year was December and so on and so forth. Now we're proud. I'm a
proud owner of, uh, portfolio of, uh, almost 20 companies. in all sorts of AI
applications, just like you said, from cybersec to health sector, to legal tech to
sports, you name it. Did you know masquerade was gonna be such a hit, or was
most of that just timing that Facebook was interested in buying them three
you know, when you invest in something, [00:06:00] if you're a venture
capitalist, uh, you always sort of try to look for something that is, looking in
interesting and having the potential. I mean, obviously, uh, there's lots of luck,
but, you know, luck favors those who do something. So I suppose it was, you
know, a great team, a great application, uh, very novel at that time.
It was a good timing with Facebook. it was a perfect storm and I'm, I was lucky
enough to be in the middle of it. Yeah, that's a great storm to be in the middle
of. let's talk about, uh, deep tech and ai. I know that you love investing in deep
Tech. Could you tell the audience, um, what deep tech, your definition of it and
why it's of interest to you?
I would say that the best definition of deep tech I would, I've seen is that, I
mean, it's something very boring. it's something that takes a long time and it's
something that does not have, uh, market risks off the bat. You get lots and lots
of tech risks, technological risks for, I don't know, five years, seven year, eight,
[00:07:00] eight years.
You, you, you're doing something that does not exist. And, you know, even
before you start trying to find the product market feed, it is something very
complicated. uh, it involves lots of, bright minds coming together in a perfect
storm. so I would say it's one of the, well, I wouldn't say, yeah, it is a pinnacle
of venture investing.
You know, it's, it's not the. prone to fashion and trans and, uh, human attitudes,
B2C stuff. It's something like, say, I know, take prescriptive, prescriptive
maintenance, for example. That's, that's, uh, something where, you know, you
diagnose, uh, machinery and try to, you know, see. If it's gonna fail before it
fails to, to make sure, you know, you do it in time in order to do that, you know,
you, you, you, you need to take a multi-discipline approach.
You need, you know, a specialist in, in vbro diagnostics, in mechanics, in
modeling, in signal processing, and in machine learning. You just can't do that
in, you know, in a few months. [00:08:00] And, you know, that's, that, that,
that's what I find interesting about this, uh, as an investor. I love that. You know
it. You know, given the amount of time and effort and money often that, you
know, uh, goes into such a project, it it does create, uh, some difficulty for
someone else to get and, and compete with you.
So it is a bit of a protective, uh, environment as well. If you manage to find the
right companies, it, it's very hard to replicate. So an investor, that's where I love
plus, uh, I mean, from my sort of private equity, uh, background, I've always
loved, you know, uh, varying industrial stuff that other people seem to find to
find not interesting.
And, you know, uh, not many people know about this, but they use the, uh,
products of that. Indeed. Yeah. It's so, it's so true. And on, on the deep tech side
of things, do you have, you know, it seems like, um, in a lot of venture capital,
it's at least [00:09:00] eight years till liquidity in deep tech. Is it even longer
Do you have a kind of lifespan on your funds as far as like your expected return
date? Well, uh, my current fund, uh, as you can see for the portfolio is a bit
different. I'm sort of get trying to focus my second fund around the, uh, deep
tech industrial ai, but yeah, from what I've seen for a portfolio, yes, this is
correct, it's about seven to eight years to, you know, till you see the company
But I mean, I, I think it's not just the dip tech companies, you. Any good
company takes at least eight, 10 years to, you know, to become something.
Other than that, it's all luck and, you know, circumstances on the tech side of
things, what, what particular types of tech are you interested in from an AI
Either ones that you're currently invested in or problems yet to be solved that
you would love to see. Um, companies being built for. Well, uh, from both
current portfolio, [00:10:00] uh, I loved my, uh, mineral mining company. The,
the Austral. They're bunch of Australian guys that use AI to, uh, find minerals.
What love about them?
I mean, yes, it is ai. Uh, yes it is, you know, orders of market magnitude faster
and cheaper to find those. It does a lot less damage to the environment. And
what sort of got me interested in that is that they, they can, you know, they are.
fuel. The ultimate goal was, uh, operating outside the planet Earth. And that's an
ambition I see, I see in some startups.
And you know, it, it's a long shot, but you know, well the future is tomorrow, so
why not bad on it today. Uh, so that's the, that's one thing I'm interested. I mean,
I'm quite used to mineral mining and, That's probably a bit of a competitive
advantage on my side, cuz I mean the, in general, the general sort of SARS fans
often don't understand or don't speak the same language as those guys, uh, do.
This is just a different sort of, uh, beast for them.[00:11:00] So that's where I got
an H. I also love food tech. food tech is great food tech. you know, as they say,
software is eating the world. So, you know, why, why not feed the world? Uh,
I've got some, some food and agritech in my portfolio as well. It, apparently, it
is, a deep tech year sector as well.
It takes a long time to develop something that, you know, uh, works, is tasty and
is economically viable for the potential clients to purchase. And I assume that
you do like deep, deep tech, just becau as of that defensibility, if you're gonna
take time to invest in something, you might as well make it hard for others to
copy it or do something competitive.
Is that correct? Exactly. Yeah. I mean it is just, it's not something you do, it's
something, uh, it, it is an inherent feature of a deep tech project. It's hard to rep
replicate cuz it involves, it involves a law of, uh, knowledge and work. And
that's fun. I mean, it is probably the same fun as, you know, watching the paint
dry or the grass grow [00:12:00] as, uh, I think Warren Buffett's put it.
But I mean, you know, like I said, I'm a career investor. I, I'm used to it. I love
it. That's why I like to see. Yeah. And also it seems like anything that is
connected to the internet, uh, is easy for an AI to help, um, compete against or
to replicate. But for a lot of this deep tech, it's offline, it's in the fields, it's in the
So that's also defensible from ai, even if it's using it. Is that right? Yep. Plus,
you know, uh, well, if it's not connected to internet, not that many people know
about this. Not, not until the acquisition happens. Exactly. Even then, they
wouldn't know what, what's happened. You know, they'll probably read it, you
know, just flip the page with the news and you know, go, go to something like
With all due respect to masquerade, I love you.
Let's, let's talk about generative AI a bit. You seem very uninterested in
[00:13:00] generative ai. Tell me, tell me why. Oh, no, not at all. I'm not
uninterested. Uh, I, I am interested in, in it. I'm, uh, I'm even grateful to it in
some respects, cuz, I mean, I, I like, uh, happy things. They take the, uh, Noise
of my markets.
it, it is a, it is an interesting thing. Uh, it is fun to play with. It is. Hyped at the
moment, I would say, I mean, it, it, it's easy to understand why it's, uh, sort of,
uh, immediately understandable by people, you know. It is something they
Unlike detect it's, it looks a alive, uh, it, you know, the very name, uh, artificial
intelligence. It, it suggests something from this sci-fi. Uh, excessive and people
think, oh, whoa, at last, you know, we have some, an AI we can talk to. You
know, AI and AGI in their minds are something similar to me. I'd say it looks a
bit more like a Chinese room, if you will.
You know [00:14:00] what that is, right? It's, it's a experiment. No. What is the
thought experiment? you got a room. You got a person sitting in the inside bed.
He doesn't speak Chinese, but he's got lots of instructions that, correspond, say
English words to Chinese words. So get, see, he gets an set of instructions.
He takes the necessary say, I don't know, uh, book from the shelf, composes a
phrase, and, you know, returns it back. Does he speak Chinese? No. Does he do
the job of translating? Yes. I'd say that at the moment Genia is, uh, a bit of a
Chinese room, so, mm, I wouldn't put, put that much trust in it. It's fun to play
with, T that's a different, uh, thing that, that's not chat.
D p t it, it, it does demonstrate some, uh, more interesting features, but it is still,
uh, an automated agent. It is still a Chinese room, but you know, on steroids if
you will. Yeah, I force getting very wide. Yeah, [00:15:00] and I mean, you
know, you, you know, the, the, the common uses of, uh, gen Geni at the
moment are co-pilots, which are helpful, but, you know, knowing how people
operate, uh, chances are these are gonna be used as scapegoats.
You know, you, you kind of, Transfer responsibility for, for your decisions to
them? You know, it's the geni that, that told you that it's not my responsibility.
Yes. I took a sort of destructive action and, you know, lost all my funds on the
stock market cuz they told me to do that. And yes, I probably prompted it
Speaking of prompting, I mean, uh, I keep thinking whether prompting is more
like cooking or like baking. Cuz uh, you know, like with cooking, you, you
know, you, you learn the basics, the sort of, you know how to cut the five
mother sauces and so on and so forth. And then you're on the old, you can
generate, you can synthesize and create new things with baking, you can't really
You have to take a precise recipe and follow it, otherwise you get a mess. I
think [00:16:00] at the moment prompting is more like baking, which means
that, you know, everybody is gonna learn it and then, you know, you are gonna
start losing competitive advantage. How do you, um, what rules do you have for
investing around hype bubbles and, um, investing for the long term?
I, I don't, I try not to invest in high bubbles. Uh, sometimes I manage to get in
them after I've invested, which is fun to watch. But, you know, uh, Fellow,
pretty much the same sort of Gartner cycle partner, if you will. You know, they
peak, then they, you know, uh, plateau a bit and that's when you start to realize,
you know, what you've got yourselves into.
I've seen that with Prisma twice now. So, I mean, no, no, I, I don't invest in
hypes. Uh, I, I am grateful to hypes cuz like, like, like I said, they, they, they
take the noise off my markets. Uh, like it, it was the same with the, you know,
the first AI was, uh, starting to pick up was around 20 16, [00:17:00] 17.
Everyone started put putting AI in their, uh, uh, investment decks.
Everyone was starting, you know, saying that they use it. You, you, you poke
them a bit and you know, is that necessary or not AI at all. But then crypto came
about. And everyone became a crypto guy. That was good. That was a fantastic
time. Cause you had, you know, proper, pure companies. Now the hype is
offered it, but Yeah, I mean, everyone's AI again, but they're gen ai so, you
know, they, they, they're different kind.
So, you know, my, my startups are now clear of noise again, which is good. So
when I'm not, I'm not saying I'm, I'm, I'm, I'm, I'm, I'm not saying investing in
hypes is a bad strategy. It's just not something I tend to do. I prefer, you know,
the fundamental things that are always going to be there. The, uh, Jeff Bezos
quote, invest in things that don't change isn't, isn't that what he said?[00:18:00]
I don't know the quote, but I completely agree with him. Yeah, I, I think, I think
he quoted that around, um, investing in things that don't change and that was
why he spent 20 years investing in two day shipping for Amazon. Cuz he is
like, people will never want slower shipping, you know? So I invest in the faster
shipping possible and they, you know, exactly.
Spot on. So, I mean, you know, people are always gonna eat. So I am investing
in, you know, agritech and food tech. People are always gonna require some
sort of materials, which is why it's good to invest in mineral mining. Yeah. You
might change from, I don't know, metals to composite materials, but that's still,
you know, the same thing basically around, around mineral mining and mining
How do you, um, how are you looking at investing in mining as it is relevant to,
the kind of changeover to green energy and sustainability? Well, I, I don't see a
contradiction here. Like I said, one of, well, I mean the, the, [00:19:00] the
portfolio company I was referring to is doing the same job, but you know, it's
much less damage to the environment.
And if we move to space, yeah, we're still gonna be polluting, but it's gonna be
some, not the earth.
It's, it's certainly true. What, what other, types of investments or, industries or
fields that are using ai, are you excited to invest in these days? Metals, I mean
like steel furnaces, things like that cuz, they pollute environment, but you know,
they're gonna be polluting less if they used effectively.
You know, you, you put some advanced AI in sales, say, and it's still fair
fairness to. Change the, uh, proportion of fer composites. That's the stuff you
use in iron to make steel, you know, while keeping the quality, you use less of
them, bam. You got immediate returns, you got, you know, growth and
capitalization and you, you, you do less damage to the environment cuz you use
Are you, um, seeing any deals around people using AI for optimizing direct air
[00:20:00] capture or anything like that? I'm not competent on that topic. I'm
afraid. I, I, I, I don't think I know that deals. No. Yeah. No, no worries at all. I
was just curious. Yeah. Um, any, any other tech and as far as, um, kind of AI
goes, anything kind of in the agritech space, what's, what's exciting about that
Oh, well, in agri, uh, yeah. Well, again, I, I mean, I, I don't, I don't. Enjoy
selling myself on a podcast, but I mean, alright. Right. Let's look at my portfolio
again. We got a robot that collects, uh, tomatoes, harvest tomatoes at the
moment and they got, you know, plans for cucumbers and bell peppers and so
on and so forth.
Uh, it's fantastic cuz I mean, you know, 2020 showed everyone that, you know
how Frazier. Supply chains are how fragile humans in journal are. And you
know, if you got your workers ill, that's it. You've got a problem. If [00:21:00]
you got a robot, you know, it just works 24 7. It doesn't get covid. Uh, I don't
know, it doesn't.
Drink. It doesn't get sick, it doesn't form trade unions.
So that's one example. Another one is, uh, another one where portfolio
companies that uses AI to, uh, grow plants. So, I mean, you know, there's an,
there's an inside joke that when we need a third startup, you know, got one that
bro stuff, they got one that have a sit. We're not, we need a third one that eats it.
I'm sure AI could figure that out, I'm sure like that too. Yeah. Um, any people or
books or blogs that you enjoy in the space that you would recommend to others?
That's a bit of a problem cuz I'm, I don't really follow any particular authority.
Uh, I've always tried to do things by my own, [00:22:00] uh, by my own mind,
cuz I mean, following someone's mind is not the right thing to do, I think.
Cuz you never know what made them do a particular thing, even though they
translated by a book which you paid them to, to read. Even you, if you get that
thatk, you don't really know why they acted the way they acted. So, following
someone is, uh, Not the best idea. It's like using chart G B T. Yeah. What, how
do you, how do you digest information and then come to your own conclusions?
What's your model for that? Well, you just, you know, read and read and read a
lot, read a lot of news, um, read a lot of, uh, books in general and just, you
know, live longer than, I don't know, 30, 40 years. And then you start to. Kind
of see how things operate and then you develop some kind of, uh, I dunno, uh,
intuitive feeling of, you know, where you feel comfortable investing, where you
want to invest and where it [00:23:00] might, you know, uh, work that's your
kind of strategic asset allocation, if you will.
You, you, you figure out the sectors that have the, this potential, then you drill
down that sector and stop, you know, actively. Just talking about it to people,
you know, searching for things. And that's where you find the particular
companies in that sector. That's your, uh, tactical asset allocation. And then you,
you know, you start negotiating.
Any, any other, it's easy. Six to six. Yeah. Yeah. As long as you do that. Any,
any other keys to success for, uh, long-term investing in venture capital? do
your thing, you know, do what's right and you know, eventually if you do the
right thing long enough, you're going to get it right. Yes. Don't, there are may
there, there may be some short term bumps along the way, but, you know, just
make sure you have enough, uh, dry powder to go through these t tranches and
[00:24:00] Bang, you'll be there. Always. Our final question, what interaction
with AI have you laughed the hardest at? I've asked Chad, g p t who ta is
fact. Oh, no, no, no. It was, it was such a weird mix of wrong facts, but it was,
uh, I laughter not what the facts, it was the confidence was that it was, I mean, if
I didn't know myself, I would've trusted it. That's the problem with chat gpt.
Was it, uh, was it impressive? I mean, was it better than the truth or what, what
Uh, it, it was very impressive.
Yes. That's, that's the problem. It knows how to, you know, uh, make sure you,
you'll, well, I mean here humans, you know, fall for that. That's Nate here and it
bloody knows how to use that. Oh, that's amazing. Well, Miha, thanks very
much for coming on our [00:25:00] show. If listeners are interested in learning
more about what you're doing, where can people find you online?
Uh, they can, you know, check out our website that's, that's, uh, taylor.capital.
They can check out my LinkedIn profile. Uh, or they can just, you know, if
there's something they want to, they want me to know, they want to
communicate with me, just. Send me an email. It's Mt. Tabor Capital. Very
simple, and I always read my emails.
I don't reply to all of them. It's too sign consuming. So sorry in advance, but
you're welcome to read. Perfect. I will mention all of those in the show notes.
Well, michaeli, Hey, thanks again for coming on the show. Thanks a lot, den.
Thank you and thanks to you, my dear prompter for tuning in, and I hope you
enjoyed this conversation as much as I have.
If you enjoy the show, please consider subscribing and leaving a good review.
Take care and always be prompting.