z cloud

Funding the commons and closing the innovation chasm

How are we going to fund the steps we need to take to promote #DigitalEquity and build the circular economy around Community Owned Internet Networks? The Broadband Institute Foundation believes that the best way to advance #DigitalEquity is to take steps towards remaking the Internet as a public commons. In another post we talked about open access fiber. Companies such as Net Equity see fiber as a secure, long-term investment.

Following the electrical grid to deploy fiber, financing fiber like a utility and distributing bandwidth through an open access network can modernize the electrical grid and bridge the digital divide with one investment….

Treat fiber like a public utility

  1. Key principle: Separate infrastructure from services through contractual obligations.
  2. Financing construct: Utilize a well-established project finance construct (e.g. build, operate, transfer) under ~20 your contract term.
  3. Source of equity: Obtain capital commitments from infrastructure funds seeking a repeatable, predictable and cash yielding business model.


Net Equity

A Bit of Internet History

Before the privatization of the Internet during the 1990s, as discussed by Ben Tarnoff, there was NSFnet, which existed as a public commons. The following quote is by David Bollier, author of The Wealth of the Commons, a World Beyond Market & State.

The end-to-end principles of the Internet and its shared protocols constitute a vital infrastructure for creating countless online commons.  This lecture gives a brief overview of this history, with readings by Lawrence Lessig, Richard Stallman, Eben Moglen, David Bollier, Elinor Ostrom and Charlotte Hess.

Listen to this podcast by David Bollier

Decentralized investment structures for public goods and Commons

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Transcript

The transcript has been copied below to enable website search ability.

0:02really excited to see all of the funds

0:03that are coming together

0:04to talk about what they’re doing to talk

0:06about how to build structures for

0:09better funding mechanisms and not just

0:10funding but

0:11optimization mechanisms so this is a

0:14crucial difference that i think is

0:16tremendously overlooked in our macro

0:18system worldwide nation-state

0:21based

0:22grant funding oriented structures which

0:24is primarily a funding system with no

0:27good feedback mechanism and no good

0:29feedback loop and therefore it cannot

0:31optimize well so what i hope to do in

0:33this talk is to talk about

0:36why we need optimization to be much

0:37better what do the feedback loops

0:39represent i’ll use venture capital as an

0:41example to kind of

0:43learn lessons from and then i’m going to

0:45talk about a bunch of the work that

0:46we’re doing to build these things that

0:47we’re calling network funds or blue

0:49funds um

0:51the blue and green dichotomy you’ll

0:52you’ll get a sense that whole like

0:54gradient that you see at the top that i

0:56use in a bunch of talks has a meaning

0:58we’re going from the science-oriented

1:00part the early

1:01long-term

1:03development of knowledge to translate

1:05all of that science into technology that

1:06we can put in products and we can use

1:08and so on so green funds work really

1:10well venture capital funds work really

1:12well

1:12we need better structures for blue funds

1:14or like these teal in-between funds

1:18so the structure of talk is this uh

1:19where we’ll go through

1:21capital allocation as a is a distributed

1:23optimization problem and and why um

1:26capitalism works really well and why

1:27venture capital specifically works well

1:29um we’ll dive into the detail of uh what

1:33makes venture capital work well and then

1:34we’ll try to back into

1:36what must network capital look like how

1:39must it operate what are the components

1:40that we need to

1:42build into these systems to make them

1:43work

1:45so

1:46what’s going on in the in the

1:48broader landscape is that there is a

1:52infinitely dimensional um but maybe

1:54sparsely populated

1:56space of variables to optimize at any

1:58given moment in time and maybe what

1:59humans care about is a much smaller

2:01space than that but still extremely

2:03dynamic extremely large extremely

2:06difficult to measure um and extremely

2:08difficult to make predictions about uh

2:10and so what’s going on in our broader

2:12coordination problems and broader

2:13coordination systems

2:15and this affects us every

2:16from the

2:18local scale of like how you’re operating

2:20right now as a human to how the entirety

2:22of our species is operating at a grand

2:24scale um it’s all about optimization

2:26systems

2:27all right

2:28disconnecting great specific flickering

2:31thank you

2:32um

2:33yeah seem like i think the new macbooks

2:35have not yet optimized their

2:37uh their new hdmi ports so the dongles

2:40probably are still good um

2:42so the the optimization process that we

2:44um

2:45that we have to like get to is how to

2:47allocate and organize our resources to

2:50move through this these these surfaces

2:52that are extremely large extremely

2:54dynamic um and how to do so as

2:56effectively as possible

2:57um in reality like no group gets to look

3:00at the whole surface you’re usually only

3:02looking at a patch you’re looking at a

3:03small area and you can maybe

3:05reason about locally about what’s going

3:07on and you can maybe summarize that

3:09information and propagate it to other

3:10people and i’m sure that all of you have

3:12had trouble convincing somebody else of

3:14something you know to be true based on

3:15all the observations you have seen so

3:18you know how hard it is to then have

3:19chains of reasoning and chains of

3:21of descriptions so imagine how hard it

3:23is to get our systems to

3:25coordinate on some local information and

3:27aggregate that to then make decisions

3:28somewhere else about about reality

3:31this is actually not quite true in

3:32reality like you’re looking at that most

3:34of the time and um the reason that

3:36capitalism has worked so well over the

3:38last 100 few hundred couple hundred

3:40years is that it is a structure that

3:43works well at the at various different

3:45scales in this optimization surface um

3:47it’s similar to to biological evolution

3:50where it enables a run time where new

3:53organisms can emerge

3:54they need resources so they are forced

3:57to optimize if they don’t optimize they

3:59will die

4:01and if they find a good sweet spot they

4:04can grow

4:05potentially reproduce potentially

4:07continue operating and so on and if at

4:09any point they lose track of reality

4:12they’ll weather and die and that’s

4:13extremely crucial to this optimization

4:15process working

4:16the other thing that’s crucial it is

4:18that is that it’s open and

4:19permissionless that at any point a new

4:21entity can can start anywhere in the

4:23optimization surface and try to optimize

4:24from there um using local information

4:27ideally

4:28so

4:29putting this together like imagine how

4:31difficult it is to do central planning

4:32about around a surface of this magnitude

4:35when all the parts are only looking at a

4:36local patch and then trying to convince

4:38each other to create one set of policies

4:41and apply them everywhere even with

4:42supercomputers now even um you know

4:45massive scale ai systems will have

4:47distributed algorithms that to reason

4:49about

4:50all of the complexity in a local way and

4:51apply local policies

4:54so

4:55part of what varies in in the capital

4:57structure is that what looks like this

4:58to some some group might look very

4:59different in another area of the market

5:01or another area of the world or another

5:03industry and so you have all of these

5:04different entities looking at some small

5:06patches and tons of competition in that

5:08area

5:09as the surface is changing all the time

5:11as this surface is encountering new

5:13technologies that totally change the

5:15structure

5:16now

5:17what makes all of this work is that

5:19there is a system of message passing and

5:22value flows between all of these parties

5:24to help organize and

5:26help optimize this large large structure

5:29uh cool so um

5:32one of the things that i’m extremely

5:34interested in helping optimize is this

5:36innovation chasm it’s it’s about um what

5:38happens between coming up with good

5:40ideas and trans translating those good

5:42ideas into technology that we can put

5:44into products and broadly diffuse

5:46because i think that our super the

5:47superpowers that technology grants us um

5:51are uh or and the superpowers that

5:53science maybe illuminates as potential

5:55uh only get realized when you do an

5:57enormous amount of r d um development uh

6:00to get it get it out there

6:02and there’s a lot of like lacking

6:03optimization in that area there’s no

6:06good structure for optimization in that

6:07in that part

6:09um

6:10the

6:11incentive structure on the right is kind

6:12of like the capitalist infrastructure

6:13and that tends to work well for whatever

6:15the optimization service is doing but

6:17it’s very brittle when it comes to what

6:19capital values so if the capital

6:21structure’s value is something that

6:23humanity doesn’t really value then you

6:25get bad results and you can probably

6:26look at

6:27the state of the world today as a good

6:28example of like what happens when you

6:30have capital systems misaligned with

6:32human values

6:33so maybe you know rewriting the

6:34structure there and orienting capital to

6:37maximize for what humanity does value

6:39might yield to much better outcomes

6:41on the flip side on the academic side

6:44we have all kinds of

6:45incentive structure problems as well

6:47where it there’s

6:49academic credit um and that works as a

6:51robust incentive structure

6:53but it tends to be to create an

6:54environment that is very difficult to

6:57experiment in where

6:59you

7:00are punished for trying things that may

7:02not work out you’re um punished for um

7:05uh publishing things that or or not just

7:07publishing but but trying things that

7:09will um that are potentially promising

7:11bad directions and you’re certainly not

7:12rewarded for translating

7:14any of your ideas and thoughts and and

7:16um and good uh publications into

7:19technology that that creates some broad

7:21right utility

7:23uh so let’s look at venture capital for

7:24a moment

7:25uh these like so-called green funds

7:29i like um

7:30should i unplug and replug

7:32or is that too dangerous

7:37yeah i’ll try it

7:42it might be

7:44it’s worked fine in other times i think

7:46it might be cable um

7:48can you live with that is that okay all

7:50right

7:51um so let’s talk about venture capital

7:52um the

7:54basic structure of how venture the

7:56venture capital industry works is this

7:58where there’s you know instead of there

8:00isn’t it’s really a kind of service

8:01providing industry that is helping solve

8:03an optimization problem within within

8:05the broader structure there’s um a lot

8:08of um money in the world um in large in

8:11managing large massive massive scale

8:13funds that don’t have the visibility and

8:16ability to look at some local area in

8:18the optimization surface and then on the

8:19other side there’s entrepreneurs and

8:21companies and builders who need capital

8:23to be able to flesh out their ideas and

8:25get things out there

8:26venture capitalists

8:28venture capital structures are different

8:30funds

8:31that find a spot in the in the

8:33optimization surface

8:34raise capital from other investors and

8:36deploy it into startups and so they

8:38serve as like this really useful signal

8:40processing node in between to use local

8:42information to try and deploy deploy

8:44capital and in reality it’s not just one

8:46entity there there’s a whole set of

8:47networks in there

8:49um

8:50in terms of i won’t kind of like recap

8:52recapitulate the success of venture

8:53capital but you know just look at some

8:55graphs of you know most of the

8:56technologies that we use today

8:58um have been you know in some way shape

9:00or form influenced by venture capital um

9:02and so on

9:04the

9:05the structure has this kind of what i

9:07like to call a ladder

9:09or staircase structure where you have

9:11companies being able to raise different

9:12amounts of funding at different stages

9:15so that you can try out things at

9:17smaller scale and if they’re working if

9:19you get a good signal then you can start

9:21scaling and so this entire structure

9:23this ability of of the the market to

9:25optimize for these pieces

9:27is part of what enables a venture

9:28capital

9:29success story that you can have many

9:31different funds operating at these

9:33different stages with different

9:34perspectives and thesis about how to do

9:36it right um and and in reality you have

9:39thousands to tens of thousands of

9:40entities doing this um to to make this

9:42work really well

9:44so again it’s a signal processing

9:46problem it’s about how do you aggregate

9:48information in that massive scale

9:49optimization surface bring it together

9:51into a resource allocation

9:53distributed system

9:55uh there’s enormous amount of money

9:57flowing through it it’s been very

9:58successful in producing a lot of

9:59corporations and a lot of technology

10:01and there’s an enormous amount of of

10:03capital in in the system

10:05and there’s tons of funds um there

10:07really are um it’s a

10:09super vibrant ecosystem that enables new

10:11fund managers to emerge to it to build

10:13new structures deploy capital and if

10:14they’re successful

10:16and this is the key part if they’re

10:17successful

10:18they tend to be able to raise larger

10:19funds and larger funds and larger funds

10:21and the moment they stop being

10:22successful they raise smaller and

10:23smaller and smaller funds or die and

10:26that’s a critical part of making this

10:28whole optimization process work

10:30um

10:31so i kind of like how this model for for

10:32how the picture works which is you have

10:34a startup or a company of some sort and

10:36selling some products into a market and

10:38creating cash flow now it could try and

10:40sell its stock in the broader public

10:42stock market um but the broader public

10:44stock market doesn’t have enough

10:45information gathering about that

10:47particular company to be able to make

10:49really good decisions um about how to

10:51run it how to help it and so on

10:54uh so you end up in a structure where

10:55instead um that company will

10:58sell part of its cash flow or potential

11:00future cash flow um to investors that

11:02can help it in that stage of its life

11:05and so that means think of like

11:06fractionalizing the potential future

11:08outcome it’s not the outcome today it’s

11:09not the cash flow now it’s a potential

11:11future cash flow as sold to another

11:13market of investors the public markets

11:16um

11:17and they sell that potential prospective

11:20measure

11:22at that moment in time and so this is

11:24really a predict what this is doing is

11:26creating a prediction market on the

11:28um future cash flows of these

11:30corporations

11:32and you know there’s of course many ways

11:33to like realize that cash flow through

11:35dividends liquidations acquisitions and

11:37so on but usually it ends up being

11:39selling the stock in a public market at

11:41some point

11:42which by the way is kind of a bug in for

11:44other reasons but i won’t go into that

11:46now let’s look at a vc fund itself so

11:47this vc fund works by

11:50funneling cash flow

11:51funneling money into companies taking

11:53some pieces from them and they

11:55themselves have

11:57a set of investors and vcs raised from

12:00other investors using the same exact

12:01composable structure so they can

12:04float

12:05this trend this

12:06the transactions of a vc fund are

12:09composable in a super neat way they um

12:12you have a transaction of cash flow

12:13going out in one direction and kind of

12:15getting stock back and you have these

12:16same exact transactions on the other

12:18side to raise capital uh the vc fund

12:20gives stock and uh gets cash on the

12:22other side so you have this structure

12:23where you can feed forward cache and

12:25back propagate

12:26stock and you have this signal

12:28processing unit

12:30and the ease compose super nicely and

12:31super neatly so you you have many uh fun

12:34defund structures

12:36or vcs with with uh angel scout funds

12:38and these you know stock and stagger and

12:40so on there probably aren’t that many

12:41layers but but what i want to sort of

12:44convey to you is that there’s something

12:45else that we’re building a lot of that

12:47looks a lot like this

12:48um that i’ll get to in a moment

12:51but anyway part of what’s doing this is

12:53that the fun the funds upstream are much

12:56larger in size and in capital

12:58range and

12:59these these structures enable um

13:02more fine-grained allocation of

13:04resources and capital across across the

13:05board

13:06and so this is what helps build this

13:08massive staircase with tons of you know

13:10thousands of thousands of of vc funds

13:12that are allocating value this way

13:15so there’s a lot another thing that

13:16looks a lot like this

13:17and these are neural networks um they’re

13:20i don’t think this is an accident i

13:21think this is uh something fundamental

13:23about these composable units that can

13:25over time develop and and help bring

13:27optimization they’re not doing proper

13:28you know feed forward and back properly

13:30in the way that neural networks do but

13:31these are kind of

13:32bayesian reasoning type

13:34entities with

13:35an evolutionary structure encoded into

13:37it which is precisely what you need to

13:39optimize the surface

13:41now let’s talk about uh network capital

13:43i’m running out of time so um the the

13:45key thing that i wanted to to kind of

13:47impart upon is that decomposition of the

13:49venture capital system as an integrated

13:51system with that composability of the

13:53structure so we’ll look at um blue funds

13:55and network capital

13:56and the pieces of those and to see how

13:58how to compose something like that in um

14:01to create funding structures for public

14:03goods

14:04so going back to this problem we we what

14:07we want to do is create incentive

14:08structures and funding things that can

14:09be successful in that area of the of the

14:12market now there isn’t good cash flow

14:14optimization there or this would have

14:15been a solve problem through vc so we

14:17need something else that can that we can

14:18use as a way to

14:20derive value here

14:22the good news is that there’s enormous

14:23amount of funding that is deployed

14:25through to science and

14:27in charity and so on but the bad news is

14:29there aren’t that many funds

14:31it’s it’s highly centralized

14:33the further up you go the fewer entities

14:35there are so it is not a good

14:37optimization structure and and worst of

14:39all is that it’s not composable you

14:41don’t have a good way to stagger funds

14:43and to propagate funding across

14:45different different

14:47to build a network of funding structures

14:49so going back to this we want something

14:50like this we want to have a version of

14:53this that works to do

14:55this kind of public good funding not

14:57just funding

14:58the creation of a private cash flow as

15:02the stock market values but a funding

15:04structure that can enable the broad

15:06production of public goods

15:08and ideally with a feedback mechanism

15:10that that enables a prediction market to

15:12form in to optimize that surface

15:16so let’s look in detail at public good

15:17organizations then they tend to kind of

15:20create a public good and they sort of

15:21give it to to the broad public

15:23and usually what comes back in the other

15:25direction is kind of like some sense of

15:27mission accomplished some goal

15:29has been done that is often one of the

15:31primary reasons why people do this kind

15:32of stuff the other parts is thanks or

15:35broadly um

15:36broadly recognized credit uh for doing

15:38this kind of a good impact

15:40some other kind of measures and so on

15:41but it’s probably you know these kinds

15:43of these kinds of structures and there

15:44is some amount of fundraising that

15:46happens where those organizations can

15:48turn to a set of uh donors or you know

15:50investors in the in the outcome of

15:52public goods

15:53and propagate the credit and the utility

15:55or the sense that the mission has been

15:56accomplished and so these other you know

15:58kind of things are getting propagated

15:59back but it’s not very fungible and

16:01there’s no good way of scaling it

16:04so what we ideally want is we want the

16:06structure kind of like this where you

16:08can you can develop a large scale

16:10optimization surface where anybody can

16:12go and create a new fund and you and you

16:14enable these signal processing units

16:16that can operate at very different

16:17scales you need

16:19fund the funds to to exist here and

16:21crucially you need performance signals

16:23to impact the funding scales many grant

16:26programs out there including some of the

16:28largest scale grant programs in the

16:29world do not really uh have a a

16:33strong feedback loop between the capital

16:35deployed and the capital invested in a

16:37process how well that turned out

16:40and feed that back into their ability to

16:41allocate more and more capital to a

16:43field you also get a cases where you

16:45have very large funds trying to allocate

16:47capital in areas where in many different

16:50fields without a lot of knowledge and a

16:51lot of signal processing and you get

16:52into like these very really bad feedback

16:54loops where massive amounts of money

16:55just gets deployed in poor ways so what

16:58we need is some some composable

16:59structure the ability to create a fund

17:02structure similar to a vc fund that has

17:04composability so you can a fund itself

17:06can raise capital from other funds like

17:09it

17:10that it can deploy capital and can get

17:12feedback directly in that transaction we

17:14need to make that transaction itself

17:16composable and this is what part of the

17:18problem here we don’t have a good unit

17:20to sort of propagate back

17:22um however we might be able to create a

17:24unit like this um so through things like

17:27you know the public funding mechanism uh

17:28exploration that’s happening in the in

17:30the grip space and the dial space um we

17:32might be able to get to

17:34a structure here let me switch

17:38so so one idea and it’s not clear

17:40whether this will work but this kind of

17:41what i think might work

17:44is that we can what we can do is we can

17:46fractionalize the

17:48the value flow of one of these sort of

17:50public public good funding structures

17:53through the use of impact certificates

17:55so if we can use impact certificates to

17:56quantify the value of a particular fund

17:59as it deploys capital in an ecosystem

18:02and use that as a version of a stock

18:04certificate um in a corporation so if we

18:07can use input certificates to create a

18:08much more um

18:11aggregateable and and evaluatable and

18:15legible and so on structure for the and

18:17tradable structure to deal with um uh

18:20impact this kind of a broad-based public

18:22goods impact then we have a component

18:24and a tool that we can then use in this

18:26transaction to trade back and forth

18:28through these through these entities so

18:29that’s kind of what we need in these

18:32structures over here

18:34so if we if we can turn this

18:36so what what in the vc world is is a

18:38stock certificate in the public goods

18:40world we can use an impact certificate

18:42and

18:43part of what’s required here is a broad

18:45market like the stock market that is

18:46going to value these impact certificates

18:48that is going to value the utility of

18:50those components and is going to pay

18:52large amounts of money we’re talking

18:53billions of dollars worth of capital

18:55deployed against these impact

18:56certificates if we can get that to work

18:58then we can build an optimization

18:59surface like this an optimization system

19:02with a bunch of little composable

19:04units

19:05that can build uh you know this broad

19:07larger scale network of blue funds uh

19:10blue here is like the this kind of

19:12public uh good oriented oriented thing

19:14one of the key things here is you can do

19:16carry structures with impact

19:17certificates you can you can have the

19:19traditional vc style

19:21performance indicator of carry and not

19:24have and really couple the the

19:26performance of the fund associated with

19:27the impact that you care about doing and

19:29what’s really cool about impact

19:30certificates is that you can do um

19:32impact certificates associated with

19:33specific fields you can value those

19:35impact certificates with a group of

19:37people that understand that field and

19:39can know after the fact five years later

19:4110 years later and so on what that

19:43impact uh was really worth

19:45so my sense is that we can do this kind

19:47of thing for open source and we can use

19:48impact certificates in these kinds of

19:50kind of structures there’s a great talk

19:53from puja in the last event that goes

19:55into into a bunch of structures i think

19:56that impact certificates can be weaved

19:58through most of these

19:59we can do this in the science and r d

20:01funding we can create

20:03as we have the traditional fund grant

20:05systems we can start flowing back impact

20:06certificates and start accumulating them

20:08we can just start doing it and start

20:09issuing them and just accumulate all

20:11these impact certificates once we have a

20:12bunch of them

20:14then we can start

20:15putting prices for them something would

20:16be really useful that i’ve talked to

20:18people about doing is committing to buy

20:20a number of impact certificates at a

20:21particular moment in time so if a large

20:23funder says we will buy five million

20:26dollars of impact certificates on this

20:27field every year

20:29then there’s a very strong

20:31encouragement for participants all over

20:32the world to do a lot of work to create

20:35those impact certificates and then

20:36compete for that for that funding at the

20:38end

20:40we can do this for decarbonization and

20:42so on and one of the good news is that

20:43carbon credits and

20:45renewable energy certificates and a lot

20:47of other financializing instruments are

20:49exactly the kind of impact certificates

20:52that we’re talking about those are just

20:53a special case uh

20:55example in a specific field but what

20:57we’re talking about is something much

20:58more general something much more

20:59composable and something much more

21:01legible by the capital structures that

21:02exist today like we basically want to

21:04come up with something that we can just

21:05hook into the capital structures and

21:07make them all work

21:09uh cool so with that um last plug for

21:12um sorry this bitcoin it auto corrected

21:14that’s so annoying uh just like

21:18how rude

21:22it’s the most the most detent thing ever

21:25instead of turning into the most regen

21:27thing ever

21:30yes exactly if it only were that easy

21:32right um cool so with that uh thank you

21:35very much uh sorry for going a bit over

21:37over time and i apologize for having a

21:38new macbook and uh filling us all with

21:41problems thank you

21:43[Applause]

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