Summary:

In this episode, Dr. Jemma Green talks with Tom Trowbridge, co-founder of Fluence Labs and former co-founder of Hedera Hashgraph. Tom shares his journey from traditional finance at Goldman Sachs to building decentralized infrastructure networks. The conversation covers the evolution of decentralized compute, the importance of token economics grounded in real fundamentals, and how DePIN projects can scale by focusing on specific customer segments. Tom also discusses his work building the Deep In ecosystem through events and podcasts.

Guest:

Tom Trowbridge: Co-founder of Fluence Labs (decentralized compute platform), co-founder of Hedera Hashgraph (top 20 Layer 1 blockchain), host of Deep In podcast, organiser of Deep In Day events. Former Goldman Sachs and venture capital investor.

Connect with Tom Trowbridge:

- Twitter: @TomTrowbridge

- Website: fluence.network

- Deep In Space: deepinspace.co

Key Topics Discussed:

- Tom's transition from traditional finance to Web3 and co-founding Hedera Hashgraph in 2017

- How Fluence Labs aggregates enterprise-grade compute from top-tier data centres at up to 70% lower costs

- The difference between decentralized compute, storage, and bandwidth in the DePIN space

- Why institutional investors will demand real fundamentals and transparent metrics in DePIN projects

- Fluence's token staking model that creates direct economic alignment between network growth and token demand

- The strategic focus on third-party node providers as the first customer segment

- How decentralized networks enable price discovery and eliminate vendor lock-in

- The Deep In Space ecosystem: 13 events across nine cities and 70+ podcast episodes

- Tom's DePIN Token Economics paper analyzing 30+ projects

- Why buy-and-burn mechanisms provide verifiable revenue proof superior to traditional audits

- The debate between buy-and-burn versus staking rewards for token holders

- Challenges of privacy and security in decentralized compute using trusted execution environments

- Lessons from cloud computing adoption and why decentralized compute is the next evolution

- How Fluence abstracts crypto complexity for both providers and customers

- The importance of SLAs (service level agreements) for enterprise adoption

- Why 2026 will be a significant year for DePIN revenue across the sector

Notable Quotes:

"DePIN is not a meme."

"If you have a project that's generating revenue and there's zero buy-burn, I can't think of a reason to hold the token."

"We're offering similar, if not the same machines, same kind of reliability in top-tier data centres. You don't have the brand name."

"The idea is you're on it for that feature [price discovery] more than you're on it because it is decentralized."

"Every evolution in technology happens faster than the previous."

"Institutional investors are gonna demand very different things than what retail has demanded."

UnBlock'd podcast with Dr. Jemma Green

For more information on Dr. Jemma Green

Visit: https://www.powerledger.io/

Or connect on LinkedIn: https://www.linkedin.com/in/jemmagreen/

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Produced by: Podcasts Done For You

View this episode on YouTube @PodcastsDoneForYou_clients

Decentralized Compute Revolution.

2

Tom Trobridge on Fluence Labs

and deepen token economics.

3

In this episode, Gemma sits down with

Tom Trobridge, co-founder of Fluence

4

Labs, and former co-founder of Hedera

Hash Graph who shares how Fluence

5

is building a decentralized compute

platform offering enterprise grade

6

services up to 70% cheaper than AWS.

7

And traditional cloud providers, Tom

reveals why deep and token economics

8

must be grounded in real fundamentals to

attract institutional capital, and how

9

focusing on specific customer segments

like node providers is the key to

10

scaling decentralized infrastructure.

11

And the lessons learned from hosting 13

deep in day events across nine cities.

12

I'm your co-host Anthony Pearl,

and whether you're an investor or

13

a startup looking for insights,

it's time to get unblocked.

14

Jemma Green: Tom, it's so great

to have you on unblocked today.

15

Welcome

16

Speaker 3: listeners, great to be here.

17

Nice to see you, Jenna.

18

Jemma Green: Likewise, Tom, for

those that may not know you yet,

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could you start by telling us a

bit about yourself and what you're

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building right now with Fluence Labs?

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Speaker 3: Sure.

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Those are a little bit

different questions, I guess.

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But I will start with, fluence is a

decentralized compute platform, and

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so what that means is you think about

what drives internet, what drives

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applications, and what drives kind of the.

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Whole virtual and internet economy to

which we are all accustomed independent

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and it's computing power, right?

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And people think of computing

power with regard to AI training

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and that's a huge part of it.

30

That's GPUs is in the news all the time,

but even before that became a real story

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in the last kind of 18 months compute.

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Powered everything from your Uber

application, figuring out how to price

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a car and how long it was gonna take

to get you and which car to get, or

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your Amazon search, or your Netflix

search, or any of these things.

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You know, your airline.

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These are all consumer oriented stuff,

but also compute is what you use to

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sequence a genome to do drug discovery.

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Like everything relies on compute

power, and so what Fluence has been

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building is a decentralized platform.

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That uses an open network to assemble

enterprise grade compute, which is in

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top tier data centers around the world,

and is effectively stranded or unused or

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for a variety of reasons, is very cheap

and offers that for customers, businesses

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to use for whatever computing they need.

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And so we are effectively

creating a global network.

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Compute, which is up to 70%

cheaper than the centralized

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clouds, and the network is live.

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It's launched.

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We have customers and we are

scaling it, and before helped.

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Joining Fluence as a co-founder,

I helped found Hedera Hash Graph,

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which is a layer one competitor to.

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Ethereum and Solana that I, that

project, I think I, I joined

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that in 2017, basically helped

founded Launch the Public Ledger.

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That token launched in 2019.

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It's a top 20 now, has been

for a while, and before that.

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I had kind of a variety of roles in

kind of intersection of technology

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and finance with time at some venture

capital firms and at Goldman Sachs, the

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well-known American bank, and basically

used a lot of those relationships and

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a lot of those, kind of the skills I

learned and was able to transfer them

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into the crypto world full-time in 2017.

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Jemma Green: And then in terms of, just to

go back to your kind of opening comments

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about decentralized compute and what

fluency is doing, how big is that space?

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Like how much is happening around

that, and what is it about the way that

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you are doing decentralized compute

that is particularly compelling?

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Speaker 3: I guess first

of all, compute is huge.

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If you think about Amazon or the way I

like to kind of frame it is there are

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a, you take Amazon, Microsoft, Google,

and then a couple of the large Asian

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kind of compute hyperscaler equivalents

like Alibaba, Tencent, et cetera.

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There are about 300 to 350 data centers.

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That have each, on

average, 55 or 60,000 CPUs.

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Alright, so that's a huge amount of

compute, and that's even before talking

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about any of the AI focused data

centers, which have been in the news.

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Over, you know, the past kind of

year or so with, you know, Elon

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and XI building one and, and

OpenAI building another, right?

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So just those are a vast amount of

compute and that even existing CPU

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growth is scaling and obviously

GPU growth and demand seems to

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be growing dramatically as well.

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That market is in the kind of

hundreds of billions in aggregate.

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The decentralized compute

market is also large.

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It's a little hard to nail down

exactly how big it is because some

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groups are not super transparent.

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But I would say that I think in

aggregate, we're talking about a

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couple hundred million of reported.

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Annual revenue in decentralized compute,

and that's heavily skewed towards the GPU

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market now, which is done for AI training.

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And there's a couple big pro, there's

project like Athe that reports 70 or over

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a hundred million, and there's io.net,

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which reports a relatively

significant number as well.

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And so I think those are the large ones.

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I think what has changed, and

people have been trying to attack

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the decentralized compute problem.

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An opportunity for quite a while.

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Historically, projects I think

were a little overly ambitious

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and attempted to aggregate.

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Retail machines and retail CPUs

in order to put them into a common

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network and solve kind of significant

enterprise grade computing problems.

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Mm-hmm.

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And that is a very laudable

goal, but it has both technical

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hurdles and also adoption hurdles.

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And so technically it's obviously

more difficult to create a consistent

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kind of enterprise grade offering.

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And then furthermore, you

have a marketing problem.

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Of trying to convince customers who

are working at top tier kind of data

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centers that they should go to a

network that's running off of home PCs.

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And that's also just a difficult

hurdle for people to get over.

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And so ours influence starts from day

one with the top tier data centers.

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And so we both have a less of a

technical challenge in terms of

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promising and delivering reliable

service and also a much easier.

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Story and pitch to tell when

customers can see and know the level

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and quality of the data centers at

which their compute is taking place.

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And so that is, I guess, a big evolution

and that is part of the differentiator

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that we have versus kind of earlier Gen

one projects that, uh, came before us.

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Jemma Green: Got it.

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And I've actually had on the podcast true

decentralized compute projects, one, which

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I'm sure you're aware of, Filecoin and

other one, which was old mobile phones

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that are being repurposed to provide

decentralized compute called Accurus.

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Have you heard of that project before?

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Speaker 3: Yeah.

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So I know both those very well.

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And Protocol Labs is investor

influence, but they're really

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decentralized storage, not compute.

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And they have a compute, they

talk about compute, but they've

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been founded based on storage.

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Correct.

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And they have kind of a, a sort

of a layer that's kind of compute,

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but it's really designed to enable

customers to use their storage more.

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And so I really put them in squarely

in the storage bucket primarily.

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Got it.

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And accuracy is doing some

interesting, and I've had

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them on, you know, my podcast.

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They've spoken a deepened day events, and

what's interesting about them is they're

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really focused on security and the ability

to use as you're probably very well aware.

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The security that is inherent in the

iPhone, which is superior to what

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you have in kind of retail or other

machines, and so they can promise and

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deliver a higher security compute,

which is a terrific solution.

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It's for a number of very specific

applications, and so I think

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that is certainly interesting.

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It's quite different than in terms

of I think, scale of compute in

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terms of what they can offer, but

the security level is clearly a

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very attractive attribute they have.

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Jemma Green: Got it.

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Thanks for just kind of distinguishing

those segments in a more fine grain way.

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I mean, you mentioned io.net

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and Athea.

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Are they the main other projects that you

would put in the same category as Fluence?

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Speaker 3: Yes.

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Both of those projects are in the

decentralized compute space for sure.

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So in one sense, yes.

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They also are exclusively focused on GPUs.

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So we started off on the CPU side.

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We've since added support for GPUs.

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We know them well.

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They've spoken to deepened days.

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Have had both of them

on the podcast as well.

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So like them both, I think.

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Big picture, yes.

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Those are, I think the

two kind of leading.

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From a revenue perspective, decentralized

GPU compute providers for sure.

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Jemma Green: Mm-hmm.

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Great.

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And apart from Fluence Labs, could you

tell us what else you are working on?

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Obviously you've got a podcast.

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Tell us about that and other things.

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Speaker 3: Well, yeah, we've

consolidated a couple things.

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It's something called Deep in

Space, so deep in space.co.

165

Mm-hmm.

166

And what we've done, and

this was a desire I think.

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Basically what happened was we

launched Fluence at East Denver in

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February of 2024, and as part of that

launch event, which is kind of an

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IRL launch event, which had kind of.

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Stopped during the COVID period.

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By the time we got to 2024, people

were back doing those and we

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invited a number of other projects

and investors to speak as well.

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And so we had an IRL day for the Fluence

launch and we realized that there was

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a lot of interest in deepen, and we had

a lot of relationships in this space.

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Even though our launch is done, we

can keep doing deep in focused events.

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Jemma Green: Mm-hmm.

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Speaker 3: And so we then.

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Created more of them.

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And I think we've done as of now,

13 deep end day events around the

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world, and I'd have to look, but nine

different cities or 10 different cities.

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And then realize also

we've got these events.

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It's great to dig into more detail

with a larger number of projects,

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some of whom may not even be

able to make it to these events.

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So I host a podcast called Deep

Pinned as well, and those are just

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all designed to raise awareness.

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Of the deep end space and of projects,

investors and providers and thought

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leaders in the deep end space.

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And so it basically is something

that fluence subsidizes.

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We certainly, there's only a

question of how much money we

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lose, not if we lose money, if.

191

But it's just a way for us to kind

of bring the ecosystem together.

192

And what I find in deep end is that L

ones, as an example, all know of the

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other competing L ones pretty much, right?

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But if you're in deep end, the

commonality is really the business

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model, having a token component to it.

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But you can have.

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Otherwise businesses that would

have no recognition of each other.

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Right?

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And so you could be accurate.

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For example, you could exist for

20 years and not know of wing

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bits, which is tracking airplanes.

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'cause why would you?

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Right?

204

And so I find that this sector benefits

from a space for whether it's a virtual

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space or a physical space for people

to come together because they're not.

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Coming into contact with other projects

as regularly as you would in other sectors

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where you have kind of more natural,

overlapping kind of relationships, and

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there still is a commonality there.

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Of how do you scale networks?

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How do you buy and reward?

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How do you buy hardware?

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How do you design hardware

for some, and then how do you

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attract and send customers?

214

There's still some key commonalities

that make it worthwhile, but it has

215

been, I think, really interesting

and has really helped us as a

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project to get to know the broader

ecosystem than if we hadn't done it.

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Jemma Green: Yeah.

218

So what I'm hearing and from what you're

saying there is it's um, partly just

219

like, just for generally understanding.

220

'cause you're interested to know what's

going on, but there's also the potential

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for information sharing that's actually

useful for your project and others through

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that process that you recognize as well.

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Speaker 3: I mean that is definitely true.

224

We have gotten some customers as a

result of it, some deepened projects

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that are using fluence compute.

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So that's, that has happened.

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But I think it's also just been

helpful overall to know the challenges

228

that other projects face, the

opportunities that they're facing

229

as well, and some of the successes.

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And I think that is also a real benefit

to hosting these and, and I mean, I should

231

have looked this up beforehand, but.

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I know we've had over, it's probably close

to 150 speakers at these different events,

233

and I think I'm at like number 70 or 72.

234

In terms of recorded deep end podcasts.

235

So it's been a considerable effort.

236

I think this earlier this year, just

recently, we did a deep end day a month

237

for a couple like we were in Buenos Aires.

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It's been a big pace.

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Jemma Green: I'm real

Estate South America.

240

Yeah.

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Speaker 3: Yeah.

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Well, Buenos Aires was around devcon.

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Jemma Green: In terms of like token

models, could you tell us about the

244

token model for fluence and how it works?

245

If you've got one?

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Speaker 3: Well, sure.

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Listen, I think that's a really

important thing and that is I think a

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key thing that is important and deepen.

249

And also I'll just mention that I wrote

a paper on deepen token economics,

250

which you can find a deepen space.co

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where I review.

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Probably 30 different projects in terms

of their token economics and kind of

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try to distill down the key factors

in the different types of deepen

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projects and how to attract and use it.

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But I think the basic point I

have is that deepen is a space

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as we'll generate real revenue.

257

And with that will come real investors.

258

And with real investors

comes real scrutiny.

259

And it's not just meme coins.

260

And my, the comment I love to

say is, deepens not a meme.

261

And so with regard to fluence, what we've.

262

Recognize is that in order for a

token to be successful over the

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long term, that token should bear

relation, direct economic relationship

264

to the scale of the network.

265

And so those have to be linked together.

266

And so with regard to fluence, you

know, with many, many projects,

267

you know, you can have revenue that

revenue can buy and burn a token.

268

And that I think is works for

a number of deepen models.

269

But for us, because we're

a network, we connect.

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Providers and suppliers.

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So Fluence itself doesn't generate

the lion's share of the revenue,

272

but what does happen is we have to

secure the compute on the platform.

273

And so for every CPU that

joins the Fluence network.

274

Fluence tokens must be staked in order for

that CPU to be active and provide service.

275

And then people add CPUs because then they

share in the revenue of those CPUs, right?

276

And so as fluence scales, more

and more fluence tokens need to

277

be staked, and importantly, their

fluence tokens, but the amount staked.

278

Is dollar based.

279

So if the token goes down and you add

a new CPU, that new CPU will require

280

more tokens to be staked than the

previous CPU because the dollar amount's

281

consistent, not the token amount.

282

And now token goes up, right?

283

The next CPU that joins requires

fewer tokens, but obviously

284

it's higher at that point.

285

So it is, I think the dollar

kind of denomination of that

286

I think is very important.

287

And I also think.

288

The relationship of that demand

to the scale of the network.

289

And the thing I like to say is that

if, or I should say when we get to

290

the scale of, back to my comment about

the scale of, of the compute ecosystem

291

globally, one 55,000 CPU data center.

292

Right?

293

I mentioned that hyperscalers

have about 300, 350 of those.

294

One of those.

295

Would require about $300 million

influence stake, which is many,

296

many, many, you know, multiples of

our entire market cap right now.

297

Right.

298

So that gives you a sense as to, as

we scale what the demand possibility

299

is for the Fluence token, we're

also looking at adding some other.

300

Attributes to it as well, which will I

think be related to compute units and

301

helping set a value for compute credits.

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In a way that you effectively create

a real world asset for compute

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on fluence that can be traded.

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So there'll be a token that will then

allow you to buy compute on fluence.

305

That token price will

change based on that demand.

306

So that's something else that we're,

we're looking to implementing.

307

We've, we've written about this.

308

Flu is an RWA real world assets

relationship with regard to compute and.

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We're making steps to actually launch

that in the kind of coming quarter or so.

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Jemma Green: Nice.

311

Thanks for fleshing that out

for everyone's understanding

312

your background's.

313

Like in traditional finance, I think

you worked in investment banking,

314

private equity, and hedge fund roles

before getting into Web3, are there

315

any assumptions from finance that

you now challenge or that give you

316

a unique lens on being in crypto?

317

Speaker 3: The main thing I am aware of

coming from that space is I think regards

318

the token economics piece, which is this

memes, I've always sort of been a bit

319

skeptical of memes and that fundamentals

ultimately do matter, and that's why

320

I'm attracted to deep in overall.

321

Mm-hmm.

322

And that's also why I wrote

this total economics report

323

because I'm convinced that.

324

As the deep end space evolves, real

investors will come and real investors

325

will bring with them the traditional

lens of evaluation, which crypto

326

projects historically have not really

had to deal with or bother with,

327

but with retail, particularly now

being so exhausted and hurt by the

328

incredible volatility in the space.

329

Institutional investors are

kind of the only hope the whole

330

sector has for significant kind

of value creation, appreciation.

331

And those investors are gonna

demand very different things

332

than what retail has demanded.

333

And so I think I bring that outside,

kind of traditional finance.

334

Perspective to this, which was

completely irrelevant and unnecessary

335

for the first, you know, decade of

crypto where people just cared about

336

memes and kind of all kinds of unusual

metrics or non-traditional metrics,

337

I should say, that I think over time

are gonna become much less relevant.

338

As crypto becomes more mainstream and with

it becoming mainstream, huge amount of

339

capital is potentially allocated to it.

340

But that capital is going to be looking

at things in the way that capital looks

341

at things, which is not how the kind

of crypto ecosystem has historically.

342

Jemma Green: Yeah, I mean, I was at

Solana Breakpoint last week in Abu

343

Dhabi, and the opening presentation

was about how crypto has produced

344

techs fastest growing companies to

a hundred million in revenue there.

345

Most of the, in the last 12 months, the

companies in that category have come

346

from the crypto space, and so I do think

you're seeing an inflection point in.

347

What you're saying, Tom, but I would

just say that I don't think it's mutually

348

exclusive like mean coins or this, because

I mean, it's very easy to dismiss them,

349

but they're really about the attention

economy and marketing, and I think

350

that's a really key part of commerce.

351

I heard also, not at Breakpoint, but

previously Lili Lou, the president of

352

Solana, talk about that mean coins are

like the test net for the new operating

353

system for financial markets in Web3.

354

That just kind of makes them

sound more like itinerant rather

355

than anything of substance.

356

But yeah, I don't think they're

as trivial as, and the real

357

stuff's happening over here.

358

I think they're both significant.

359

Speaker 3: Fair enough.

360

But I guess I'll make two comments.

361

So those first, the comment you said

about the fastest to a hundred million

362

revenue, how many of those were exchanges?

363

I would think a lot were, I'd love to

see that list because I gotta think

364

a bunch of those were exchanges.

365

Jemma Green: Yeah, so

fans and Snowflake Ave.

366

Ramp Radium.

367

I mean there are Dexus

in there, obviously.

368

Backpack, sky,

369

Speaker 3: snowflake,

370

Jemma Green: Jupiter.

371

I'll send it to you.

372

Uni Swap.

373

Speaker 3: Unis swap, right?

374

So there a bunch of is pumped off.

375

I mean, those are great, but

a lot of those are companies.

376

Unis, SWP a little bit different,

but because I, I would think that

377

a lot of the crypto success has

been, I mean, look at Tether, right?

378

These are centralized tethers, like

the biggest success in the space.

379

And so I would love to see that, but I

think a lot are gonna be more traditional

380

businesses in the crypto space.

381

So it's a little different.

382

Jemma Green: Yeah, Tina's not on the list.

383

I've just sent it to you on WhatsApp

for what it's worth, so you can have

384

a little glance if you wanted to.

385

Speaker 3: Let's see.

386

And then the other point is that on memes.

387

Memes, let me be super clear,

memes are not going away.

388

And for sure they provide something

in fascinating, interesting.

389

And I don't think they go,

but I also don't think that

390

that's where pension funds.

391

Endowments and foundations.

392

Totally right.

393

That's, they're not going there.

394

Now, they may go into a pump

do fund that enables that.

395

Great.

396

But people will always trade meme coins,

no doubt in their meme stocks, right?

397

So, don't get me wrong, I

don't think that goes away.

398

Mm-hmm.

399

I at all.

400

But that's not where I think the

institutional capital is gonna go.

401

That's all.

402

Jemma Green: I would

agree with you on that.

403

But having said that, you know the

institutional capitals going into

404

the layer one, which is using that.

405

So they are why doing that, but more in a

secondary or inadvertent way, let's say?

406

Speaker 3: Yeah, they're monetizing it.

407

Jemma Green: Mm-hmm.

408

Speaker 3: It's a way to monetize that.

409

It's a use case which is being monetized.

410

It's like going into an exchange that.

411

Trades that where money is created,

where the value is created by the

412

people who are trading these be coin.

413

Same thing, which is, again, I don't

think it goes away at all, but I would

414

also be curious to see meme coin volume

over time because I, I gotta think it's

415

down significantly, but I don't know.

416

Jemma Green: Well.

417

There was a debate actually on stage about

whether, you know, token burns good and

418

in I think the case of pump Pump fund,

the community wasn't happy about the

419

company reinvesting to grow the market.

420

'cause they didn't believe there

was a huge growth opportunity

421

beyond the current status.

422

So they were not, you know, because

the debate was about should you do

423

value distribution to token holders?

424

Should you burn tokens?

425

And how much should the

company retain as well?

426

So it's kind of like.

427

Speaker 3: And that's a fun

philosophical debate because I get it.

428

And if you compare it back, traditional

world of stock buybacks, right?

429

Mm-hmm.

430

Can the company invest capital

more effectively and grow, right?

431

Or does it buy back the stock and

effectively return money to shareholders?

432

And so if you want to be in a company that

has a better use for the capital, right?

433

So that's the concept.

434

However, the crypto concept,

what I would say is that.

435

Lemme phrase it this way, you, you have

another overlay in crypto, which is trust.

436

And a lot of the projects that

I've mentioned who claim a lot of

437

revenue, there's no auditing, there's

no not even case studies, right?

438

They're just, here's what I have.

439

Right?

440

And so you have zero.

441

Accountability.

442

And I frankly think there's just a

question of time before some of these

443

projects that claim a bunch of revenue

are found out to not have them or have

444

it to be, you know, very overstated.

445

And so by burn is even

more verifiable than.

446

An audit.

447

We've all seen audits that have a huge

amount of number of companies in the

448

traditional finance space that the

auditors have been completely fooled.

449

So by burn done correctly,

transparently validates, proves

450

revenue in a way that even auditors

can't, are not as effective at doing.

451

So.

452

That's kind of 0.1.

453

And then 0.2,

454

if the company holds some treasury,

as many do, if you buy burn.

455

You then have treasury.

456

Your treasury is more valuable,

and then you can then spend some

457

of that treasury on whatever you

need to do and sell some of that.

458

Now, you end up in some of a similar

place, but you're at least fully aligned

459

with the token holders at that point.

460

And what I argue is that every divergence

from a hundred percent by burn is now

461

diverging from your token holders.

462

Now, name may not be much, may

just be a little bit, but it is

463

some divergence as a token holder.

464

I would like to be fully aligned

with the management of the

465

project and what they're doing.

466

And so any divergence from

a hundred percent starts to

467

creep that disalignment up.

468

And to the extent where they do zero by

burning, keep all the revenue themselves,

469

well then why do I even hold the token?

470

That doesn't make any sense whatsoever.

471

Right?

472

So you gotta figure out where

you are on that spectrum.

473

But if I have a project that's

generating revenue and there's zero

474

by burn and there's, I can't think

of a reason to hold the token.

475

Jemma Green: Interesting.

476

Yeah, I mean, you can actually listen

to the debate that's on YouTube.

477

You might find it interesting, Tom,

'cause you're, obviously, you've thought

478

about this quite a lot and the analogy

to, you know, traditional financial

479

markets was made as well, and that with

Tradify, they can just basically apply

480

for permission to do a buyback, but

then sit on it and not actually do it.

481

Whereas in crypto, if that was stated

that the company was operating like that

482

and then they didn't, it would be seen

far more negatively than in tradify.

483

And it sounds like you would prefer a

buy and burn than like a staking model

484

with value distribution to token holders.

485

Is that right?

486

Speaker 3: I guess it depends

a little bit on the project.

487

I think it's a buy burn is

just much, much simpler.

488

Staking can be useful, but I guess unless

there's a reason to stake IE trust.

489

Mm-hmm.

490

Then you add a layer of complexity,

but you also add a layer.

491

Of additional token demand, right?

492

And you are then rewarding people who

stake and lock up for a longer period.

493

So I would say that if you have a

hundred million of revenue and you

494

want to reward people that stake with

that revenue, I'm not against that.

495

It's a different mechanism, but it's

what, to be clear, that's a different

496

mechanism of rewarding token holders

that may take a little bit longer and

497

they may not reward all token holders.

498

But it also rewards activity, the

behavior that you wanna reward.

499

So I'm not against staking

rewards at all, presuming they're

500

done openly, transparently.

501

But again, we're back to the same

thing of that rewards token holders.

502

And again, if it's a hundred percent the

capitals return, revenues return to stake.

503

Your rewards.

504

That's a hard to argue with.

505

It's more, to me the question of how

much is retained to run the business.

506

And obviously you would think some needs

to be retained to run the business.

507

That comes back to how big

is treasury, how aligned are

508

you with the treasury or not?

509

And that is, I think, more

the question, whether it's a

510

stake in rewards or a buy burn.

511

Jemma Green: Got it.

512

How do your clients find that maybe aren't

in Web3, find having to buy and state

513

tokens in order to access the service?

514

Speaker 3: Well, they don't because

they don't have to know about it at all.

515

And so the important thing with

Fluence is we've separated.

516

The staking from the

people who provide servers.

517

So for example, these are

all different ecosystems.

518

So if you are a data center and

you want to contribute servers,

519

investors can stake those tokens.

520

So you don't have to do it, you just

promise them a share of revenue.

521

So they don't have to buy because

that just effectively, it just

522

raises the cost for providers and

that's not their business to do that.

523

So we have a model where

individual investors can do that.

524

Institutions can, or their

pools that do that as well.

525

So you as an individual who don't

have enough to stake to particular

526

machine, can contribute money to a pool.

527

That pool then stakes.

528

So the provider isn't forced to do that.

529

And then if you're a compute user.

530

You also can pay in fiat so you

don't have to pay in tokens as well.

531

So the idea is we sort of own an

abstract out as much as possible,

532

the complexity of crypto.

533

Gotcha.

534

Jemma Green: I mean, you

mentioned I think, early that

535

that fluence has lower costs.

536

I think you said earlier, something like

70% compared with traditional services.

537

What are the trade-offs, if there

are any, around like things like

538

performance or stability or latency

or availability for AI or compute

539

teams to take this lower cost route?

540

Speaker 3: I guess the main point

on the pricing is that it's not

541

like there's one price for compute,

and so when I say that price,

542

Jemma Green: mm-hmm.

543

Speaker 3: That is off of a list price

at a data center, but then if you are

544

going to have a longer term commitment

at a certain scale, right, then your

545

pricing starts to go down and so.

546

Our pricing, the discount at which it

is available, or rather the discount

547

in which you can compare really differs

based on the scale and duration of

548

the compute you want to purchase.

549

And so if you're talking about larger

numbers for longer periods of time,

550

then the fluence price is at less

of a discount than the hyperscalers.

551

Now, in terms of trade-offs, the

main point is that we're offering

552

similar, if not the same machines,

same kind of reliability and top tier.

553

Data centers, you don't

have the brand name.

554

Mm-hmm.

555

Right.

556

So that is one thing you don't have.

557

We also are working to implement SLAs

that I hope that comes soon, but the SLA

558

is a key piece that we need to have that

we don't, which is something that is, I

559

think, will unlock a lot of use for us

when we complete it, but we don't yet.

560

But those, it's really.

561

Brand name and kind of comfort in using

it is are really the two main things.

562

But let's also be clear that.

563

We don't offer a full

range of services at all.

564

And compute sounds like it's one thing.

565

Jemma Green: Mm-hmm.

566

Speaker 3: Compute is a very complex,

heterogeneous set of services,

567

and so our first customer base

are third party node providers.

568

And so these are companies

that you know, provide and run.

569

Knows that that support a wide number of

layer one and other blockchains, and they

570

run 'em for individuals and for companies.

571

And so for those businesses, about

half of their cost is compute.

572

Jemma Green: Mm-hmm.

573

Speaker 3: And so we can then save them.

574

Again, these are people that

buy at scale in longer duration.

575

Right.

576

So we're not saving them 70%.

577

We can save them 20 or 30, and that's

off of half of their cost base.

578

And so that is compelling, and I think

that is by itself a billion dollar market.

579

And so that just gives you a

little bit more detail in terms of

580

what we're looking at and doing.

581

And because it's selling a

very basic compute service.

582

Differentiation in terms of what's offered

versus centralized clouds is very, very

583

small because of the basic purpose and

basic use of compute for that use case.

584

Anthony Perl: I'm intrigued about

the decentralized versus the

585

centralized option, and is your target

market the same market as people?

586

Are you trying to convince some of

the people that traditionally have

587

now been using those more centralized

services, AWS, and the like to

588

start considering this as an option?

589

A hundred

590

Speaker 3: percent.

591

And that's, and they are, and I

guess the main reason people do it, I

592

think is not that it's decentralized.

593

That's sort of a nice to have at best.

594

It is more that is the mechanism

that allows pricing to stay cheap.

595

And I'll explain it, is that it's

an open network, which means that if

596

you're running compute on fluence.

597

A provider wants to raise price, you

can easily find the next provider that

598

hasn't raised price or is cheaper.

599

So your switching costs are effectively

zero, which means price is always

600

competed down to like the lowest level.

601

There's no lock-in.

602

Like if you wanna leave

Amazon, it's a headache.

603

And you know, it's a real arduous journey.

604

And so.

605

The idea influence is

that it's an open network.

606

Anyone can contribute, compute, and so

that basically allows price discovery

607

across the world of lowest price.

608

And that works because it's decentralized

and because it's an open network.

609

So you're on it.

610

For that feature more than you're

on it because it is decentralized.

611

Now, it being decentralized

also means you're maybe more

612

resilient in terms of failure.

613

You've got heterogeneous hardware and

you know you're not on one network and

614

you're not in one geography, right?

615

So there's other attributes

that come with decentralization,

616

but that hasn't been the focus.

617

And if you're an L one, it's kind of

crazy for all these L one, you know,

618

decentralized projects to be running.

619

On Amazon or Google, which many are

right, but that's just where the nodes are

620

running 'cause it's cheapest and easiest.

621

So the goal here at Fluence is to help

decentralize this whole ecosystem, but

622

doing it not for the sake of doing it.

623

Doing it because the decentralized

mechanism actually provides a value

624

and a durable value to that ecosystem.

625

Anthony Perl: In terms of security

though, I mean that would be I, I

626

guess a primary concern for people.

627

Is there a security issue?

628

Is there a security

advantage perhaps in between

629

Speaker 3: one and the other?

630

Well, there's two components.

631

There's reliability and there's security,

and so those are quite different.

632

And so with regard to.

633

Reliability.

634

You can argue this is more reliable

because you can shift providers.

635

You're in different geographies, right?

636

So you can be more reliable.

637

Obviously, despite Amazon

going down a bunch of times,

638

it obviously is very reliable.

639

It has gone down.

640

It will go down again.

641

We know that, but it just, so there

are vulnerabilities, but, and that also

642

comes by the way, of having a homogeneous

software stack that has a lot of single

643

points of failure where if CloudFlare

goes down or what goes down, you have

644

these ripple effects across the network.

645

Right.

646

So you've seen that architecture

that's built a specific way.

647

It obviously has vulnerabilities in it.

648

You know, in a decentralized network

you may have other vulnerabilities, but

649

you may not have that vulnerability.

650

So I think it is as secure or that

as resilient, if not more, but it's

651

a conversation we can certainly have.

652

I argue open source in general is

more resilient, but that's a whole.

653

Path.

654

And then in terms of security and

privacy, which is really the key

655

piece here, that is a very complicated

conversation because the privacy in

656

data centers, if you're using Amazon,

is effectively done via contract.

657

And so it is trust.

658

And so if you're doing it decentralized,

you now no longer have that trust.

659

You wanna make it trustless.

660

That gets difficult.

661

And so the only way really execute that

is trust execution, environment kind of

662

chip, that very sort of chip specific.

663

And that is a challenge.

664

And so the privacy component

of it is certainly an issue.

665

And it's something that I don't think

that we have solved at scale, but it's

666

also why the use cases that we're working

on right now are not privacy focused.

667

Anthony Perl: I mean, are there

lessons to be learned as well?

668

From what the move into cloud was a

big thing for a lot of people, right?

669

There was a lot of resistance

for a long period of time.

670

There's probably still people out

there that don't like the idea

671

of things being on the cloud.

672

Are there lessons to learn from how to

market it and how to gain that trust

673

and that market space that you can

take forward for what you are doing?

674

Speaker 3: It's funny you mention that

because I am in the long career that

675

Gemma mentioned earlier in my venture

676

in data centers that were effectively

trying to, you know, we didn't have

677

the term then create the cloud, right?

678

That was in 1998 and we

said this is inevitable.

679

This is happening.

680

You know, I don't think Amazon

681

or something along those lines.

682

Right.

683

And it may be longer.

684

It took a long time to scale.

685

And so, you know, I'm quite familiar

with the adoption challenges in

686

getting companies to move to the cloud.

687

It's obviously been enormously

successful, but it's taken a while.

688

I think every evolution in technology

happens faster than the previous,

689

so this will not, and, and we view

decentralized compute as like the

690

next and maybe final evolution.

691

But it will coexist with the cloud.

692

But the cloud to be clear, has spent

decades and tens of billions of

693

dollars on not only infrastructure,

but products and services.

694

And so that is a very difficult

thing to compete with.

695

And so.

696

What I think our lesson is, is to focus on

one segment at a time and really work to

697

find a product and offering that resonates

with one particular segment, and then grow

698

from that segment to one other segment.

699

Because it is just impossible to try

and compete with the cloud across all

700

the products and services they offer.

701

And I think in the beginning, if I

think back to my data center investment

702

days, you know, there was a wide

number of different types of businesses

703

that these, I can think of two we

invested that were trying to bring

704

into the data centers and we probably.

705

Should have focused on customer segments

more than geography at the time.

706

And that would've, I think,

helped our scalability back then.

707

So that's, that's one way we look at it.

708

And one thing we've taken away.

709

Jemma Green: You just touched on the kind

of challenges with adoption and users.

710

Many of the projects, obviously in

deepened struggle with the flywheel,

711

you know, in terms of scaling users

and nodes and value all simultaneously.

712

What are the design principles

that you think are really critical

713

to overcoming this challenge

and that you are implementing?

714

Speaker 3: Well, I mean, listen, I think

there's a question and answer for fluence.

715

There's a question answer for other

compute and question answer for kind

716

of the sector overall and, and more

what I call physical deep ends, which

717

are not compute or storage or kind

of bandwidth, I suppose related.

718

And I guess with fluence particularly, I

think that is just customer segment focus.

719

Scaling within one customer base

and using that, getting that

720

customer, and having that customer

be a reference for the next one.

721

And they know each other, right?

722

It's an ecosystem and building

trust within that segment is a

723

way to start that flywheel for us.

724

And I think that's also true for other.

725

Projects in the kind of what I call

digital deep end space compute,

726

storage bandwidth, et cetera.

727

Mm-hmm.

728

And I think it's not that different

than the physical side where you know,

729

if you're mapping or you're selling

location services or whatever, is still

730

understanding the different customer

segments and how to target, I think

731

is the only way really to go about it.

732

Jemma Green: So you really gotta

have like a deep understanding of

733

your core customer, understand what

segment you're gonna focus on, and

734

that there's like enough addressable

market there to make it worthwhile and

735

really deeply understand your customer

and the product tailored for that.

736

Speaker 3: A hundred percent.

737

Jemma Green: Got it.

738

I mean, it is akin to traditional

markets and I think also what you've

739

said earlier, you know, you're putting,

blockchain is front and center,

740

but for the customer experience, it

might be more of a background thing

741

to the extent that they're, you

know, more Web3 native or inclined.

742

Speaker 3: Oh, for sure.

743

It's all background.

744

Yeah.

745

Yeah.

746

Without a doubt.

747

Mm-hmm.

748

I mean, and that's how this industry goes.

749

I'm pretty sure ultimately, not

just deepen, but overall where we

750

need to survive and thrive based on

the products and services we offer.

751

How we get to that may be blockchain

related, may be decentralized, but that's

752

not, no one is gonna buy a product or

service because of the infrastructure.

753

They're gonna buy it

because of the attributes.

754

Now, those attributes may be

unique to the infrastructure.

755

It's decentralized, but really

it's about the value that

756

project and service can offer.

757

Right?

758

And, and the blockchain is just, for

some projects, it is the most effective.

759

Infrastructure to deliver the product

and service that they think is valuable.

760

And we're waiting to see, and

we'll see, and by some projects are

761

showing us the case, others are not.

762

But that in some sectors will make sense.

763

Others it won't.

764

Jemma Green: Absolutely.

765

I mean, I'm aware of like blockchain

project that might be merging with

766

like a tradify project and then the

blockchain rails make the margins

767

and EBITDA much more compelling

compared to the industry norms.

768

And you can see with like use cases

like that, that it's, you know,

769

as you say that the attributes.

770

Maybe I'll just turn to like what's

on your mind and how are you thinking

771

about 2026 in terms of the work

that you're doing and your focus.

772

Speaker 3: 2026 should be a, an

exciting year from a revenue side.

773

So we've got a pipeline that keeps

growing and so we just need to kind

774

of just pull these customers in and

get it on and start to scale it.

775

That's the real focus and

the only focus really.

776

Really for Fluence is doing that.

777

And so that is a big thing

that we're all kind of mm-hmm.

778

Pulling together to make happen.

779

And I'm excited to see that, by

the way, across the whole deepened

780

space is revenue coming in across

the deepened space overall.

781

And I thought 25 would

be a big year for that.

782

I would, I think it, we've obviously

seen some terrific strides there, but I

783

think 26 will be much more significant.

784

Jemma Green: Gotcha.

785

What about slightly different topic music?

786

What's your favorite

song at the moment, Tom?

787

Speaker 3: Ah.

788

The favorite song is, and it's

actually my kids are annoyed

789

because I was just playing it this

morning here, was Lose Your Soul.

790

I don't know if you know Lose

Your Soul, six months old or so.

791

It's by Interplanetary Affair.

792

Jemma Green: Oh, okay.

793

I'm gonna look it up.

794

Thank you so much for that.

795

And are your kids are not fond

of the song, I'm guessing?

796

Speaker 3: Well, it's because

it says I'm going to get up, I

797

wake up to the beat of the drums.

798

So in the morning it's kind of a

fun thing to try to get 'em going.

799

You know, it's

800

Jemma Green: kind of like the Dolly

Parton song, uh, working nine to five.

801

Speaker 3: Yes.

802

But the other one I play is

Five Minutes Before School.

803

There is a country song

called, you Got Five Minutes.

804

And so they're very familiar with

the five minutes song as well.

805

Oh,

806

Jemma Green: I'm gonna use

that for my kids as well.

807

Uh, they're quite often telling me

that I'm very cringe and I'm sure

808

this will help in that accolade.

809

Speaker 3: Yes, exactly.

810

Jemma Green: Dom, it's really been

a pleasure to have you on unblock.

811

Thank you so much for joining us for the

conversation and helping us to understand

812

more about Deep in and also decentralized

compute space and what you're working on.

813

And it's not just about, you know, the

work you're doing, you're really trying

814

to support the ecosystem to understand

itself, understand each other, and through

815

that kind of cross pollination for it to

kind of reach and fulfill its potential.

816

So I just wanted to acknowledge

you on that and really

817

appreciate your time today.

818

Speaker 3: Well, appreciate it.

819

It's a bunch of work on our side, but

it's been fulfilling and so we want to

820

keep doing it and we've gotta get you on

in person at one of our deep end days, so

821

hopefully we can do that in 2026 as well.

822

Jemma Green: Thank you for the invite

and I accept I would be delighted.

823

Thank you.

824

Anthony Perl: That's all for

this episode of Unblocked.

825

Please check out the show notes

for information on Power Ledger.

826

And other contact information.

827

We welcome your comments and

feedback and please hit subscribe

828

wherever you are listening.

829

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830

We look forward to your

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