How does money work in PARPA?

Bell Labs is one of the few examples of an innovation org that was aligned with its money factory

“The System” of AT&T

AI research is an exception to the decline of corporate R+D

National labs and other government research centers are a research alternative to universities

Problems that require system-level solutions often require massive teams

It is easier to have a multipoint mutation in technology than in evolution

The boundaries between industry government and academia are fuzzy

Why try to emulate DARPA and not Bell Labs

An institution riffing on the ARPA Model could enable paradigm shifts that are not happening

An Institute for Creative Technology - Riffing on ARPA

R+D labs require companies that can win based on Technology

# §Corporate R+D Constraints
 Follow innovation through bell labs
	* Run into problem with “the system” - can’t fit enough calls into a single cable. More cables are expensive. Want people to make more, better, calls. Problems constantly coming down from the top and 
	* 
* Follow Innovation through GoFaAmSoft
* Politics 
	- [[Internal incentive structures within a large organization work against high quality R&D labs]]
	* [[R&D orgs are always on the side of an org chart - The lab is always separated from the mothership]]
	* [[Rewards in a big company operate on one timescale and R&D happens on another timescale]]
* The most valuable research for a company tends to be systems-level improvements. But [[Problems that require system-level solutions often require massive teams]] while [[Research tends to work best when it can be done by small teams]].
* Risk aversion
	* [[Asymmetric career risk]] 
	* [[Asymmetric career risk impacts corporate R+D]] 
* Incentives
	* [[The incentives inherent to corporate R&D mean that researchers motivated by money leave and those who are motivated by glory are not the best in the world]]
	* [[At the organizational level corporate R&D labs either cause brain drain or don’t have the best people]] 
* [[Corporate R+D orgs are expensive]]
* [[R+D orgs are answerable to shareholders both in scope and timescale]]
* [[Companies want R+D to be off of their balance sheets]]
* [[The siloization that tends to happen in large corporations hamstrings applicability and serendipity]]
* [[Big companies cannot start small things]] 
* [[Expensive research needs to address an existential threat eventually at an organizational level to maintain support]]
* [[There are several macro-economic analyses of both why and whether there has been a decline in corporate R+D]]
* [[Corporate R+D orgs experience a tension between Research and Development]]
* [[Corporate R+D orgs have a lot of momentum]]
* [[Healthy corporate R+D requires a trifecta of conditions]]
* Trends
[[Corporate Innovation has four main options: partner, R+D, corporate venture capital, and venture building]]
<draw 2x2 box>
	* Externalize R&D through startups and universities 
	* Internal startups via Red Box at Swisscomm or Area120 at Google
	* “Innovation Arms”
	* Grants
## Related
- [[§Startup Constraints]]

                            

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gertnerIdeaFactoryBell2012

Bell Labs was only profitable in conjunction with AT+T

What are the different roles in an innovation org?

Optimizing individual components of a system is often at odds with the system itself

Bell Labs was not a business

Ideally corporate R+D enables targeted dicking around

AT+T benefitted significantly from creating better technology

One way for an R+D org to address existential threats is to tie into a core product

All the work at Bell Labs needed to tie back to the system

Why was Bell Labs Different?

# “The System” of AT&T
# “The System” of AT-T
AT&T thought of its interconnected communication network as “The System” - all pieces of the company could point back at “The System” and say how they were helping the system’s goals - which were around communication. 
Contrast this to  say Alphabet, where most of the products don’t actually point back to the same core.

## Related
- [[Innovation orgs need to be aligned with their money factory]]
- [[Innovation orgs need a money machine]]
- [[§Corporate R+D Constraints]]



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Systemic decay theory of stagnation

Why hasn’t Bell Labs been replicated?

We need new institutional structures to fill the role that corporate labs once occupied

Corporate labs no longer fill the niche they did in the early-mid twentieth century

Notes on the changing structure of American Innovation

ICT Distillation

26 Oct 2020

ICT Outline

Startups have taken over a chunk of corporate R+Ds niche

# AI research is an exception to the decline of corporate R+D
AI research bucks the trend of the decline of corporate labs as a place where globally important, cutting edge work is done. ([[The decline of science in corporate R&D]]) If you squint, Organizations like [[Facebook AI Research - FAIR]], [[Google Brain]], [[DeepMind]], and possibly [[OpenAI]] [^1] bear strong resemblance to [[Bell Labs]], [[Xerox PARC]], and other legendary Corporate R&D orgs (I’ll just refer to these as Legendary CR&D)  in their heydays.

The parallels manifest in several ways. It’s worth speculating on why they exist in these labs but not elsewhere to understand why the dynamics may or may not be replicable in more areas.

AI research (can) require massive resources - in this case it’s just thousands of dollars of compute for training models and the datasets to train on. These resource requirements mean that there is exploratory research that people just can’t do with the resources available to most labs at universities. You saw a similar effect pulling professors away from universities and into corporate labs in the first half of the 20th century. 

At the same time, corporations running AI labs reasonably expect the research to create value commiserate to the costs of this research. Machine learning can directly improve the core product lines of all the companies listed above, in the same way that Bell Labs’ work directly improved [[“The System” of AT&T]]. [[Innovation orgs need to be aligned with their money factory]]. Additionally, AI promises massive value over long but not infinite timescales. OpenAI’s business model is implicitly based on the assumption that they will create literally infinite value in the not unforeseeable future. 

This alignment between the research and the money factory allow modern AI labs to do highly regarded work and collaborate closely with academia, *without* seeming like a waste of money. Bell Labs was the home for the work that led to nine Nobel prizes. Today, AI conferences are dominated by work from corporate AI labs, not just in quantity but quality as well. 

Like the electronics work at Bell Labs, AI research benefits from having multiple disciplines in the same place and the people who will eventually produce it. When you’re creating “AI for X”, it’s generally helpful to have someone who is an expert in X around. Similarly [[Business and finance people are utilities]]. Training and implementing ML algorithms at scale requires a different skillset than creating and prototyping the algorithms. Corporate AI labs have the budget to hire research engineers and also make it easy for researchers to talk to some of the best infrastructure and production engineers in the world. This dynamic roughly parallels the close ties between Bell Labs and Western Electric.  [[Prototyping needs manufacturing in the room]]. 

The perhaps uncomfortable parallel is between AT&T’s status as a high-margin, cash-printing monopoly and Google/Facebook’s similar situation. AI labs suggest that successful corporate labs can only exist in domains where there are large corporations with monopoly-like power. The decline of corporate labs in chemistry and physics-related domains may have been caused by commoditization of those products. GE, Dupont, Kodak, and others’ share prices suggest that they at least are no longer perceived as monopolies. However, monopoly profits -> high quality corporate research isn’t the entire story because you don’t see a lot of high-quality non-product research coming out of Boeing and Amazon[^2] ::are there other examples::?  Perhaps the missing difference is whether or not the monopoly perceives that it will benefit from significantly better technology. [[AT+T benefitted significantly from creating better technology]] because they had an effective pact with the government at as long as they kept making the system better they wouldn’t be broken up. I wonder what the counterfactual is - being left as a monopoly without the pact. While Google and Facebook have no (publicly known) agreement with the government, I believe [[Peter Thiel]]? Made the argument that at least Google’s monopoly does depend on them continuing to have the best search engine - people have no loyalty to google beyond the quality of their searches. Similarly one could make an argument that advertisers will abandon Facebook as soon as they have worse ad targeting or the kids move to another platform like TikTok or Snap. 

Microsoft is an interesting beast to examine through this lens. It’s unconfirmed, but arguably [[Microsoft Research]] was started as a public offering in the same way Bell Labs was. However, it both explicitly set out to do more product-focused work than PARC and Microsoft’s cash cow was Windows and the Office Suite, both of which didn’t benefit much from MSR work. MSR was subsequently pretty neglected and used for stunts like China expansion. However, Microsoft’s core business has begun to shift towards cloud services, which *do* benefit from AI research and it’s becoming clear with things like GPT-3 that AI research can augment Office Suite products that are now actually under threat. This shift coincides with a[partnership with OpenAI](https://news.microsoft.com/2019/07/22/openai-forms-exclusive-computing-partnership-with-microsoft-to-build-new-azure-ai-supercomputing-technologies/#:~:text=The%20partnership%20covers%20the%20following,promise%20of%20artificial%20general%20intelligence) that looks a bit like the relationship between AT&T and Bell Labs if you squint. Amazon remains a challenge to this just-so story because it also has a massive cloud business but is not (publicly) doing as much speculative AI research.

If it’s accurate, this narrative suggests an uncomfortable truth. Instead of declining because of  “corporate short-termism,” speculative corporate R&D might depend on companies with monopoly-level margins perceiving their fate being intimately tied to a high-potential technology.  This trifecta (monopoly + clearly high potential technology + that technology being tied to the company’s core business) can’t be created by policy or even a cultural shift.  [[Healthy corporate R+D requires a trifecta of conditions]]. The trifecta is the most straightforward answer to the question [[Why hasn’t Bell Labs been replicated?]] and suggests that attempts to “create a new Bell Labs” are doomed to failure if they try to follow the playbook too closely. At the same time, I strongly suspect there are incredibly valuable technologies that don’t fit the criteria of the trifecta (clearly high potential to solve an existential threat for a monopoly rentee) but do need the environment and resources that were once provided by healthy CR&D labs to realize that value.  This is why[[We need new institutional structures to fill the role that corporate labs once occupied]].

### Related
- [[aroraChangingStructureAmerican2020]]
- [[Bell Labs didn’t have a unique model]]
- [[Corporate R+D orgs experience a tension between Research and Development]]
- [[§Corporate R+D Constraints]]
- [[gertnerIdeaFactoryBell2012]]
- [[aroraChangingNatureCorporate2015]]
- [[Does the nature of the activities to create new technology and science change over time?]]

[^1]: At this point OpenAI resembles the Bell Labs equivalent for Microsoft
[^2]: Maybe it’s a [[Seattle]] thing?



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Bell Labs

Bell Labs did not give researchers complete freedom

§Bell Labs Model

Labs Document Outline

# AT+T benefitted significantly from creating better technology
AT+T benefitted from new technology in three distinct ways. First, its scale and the nature of its products and services meant that even small technological improvements could have massive effects. Second, there was a semi explicit contract with the government that AT+T would not be broken up as long as they continued to improve their services and shed excellent technology. Third, M+A blocking regulation meant that AT+T couldn’t depend on acquisitions to provide technological advances. 

![](../BearImages/5733ABA1-C990-4519-921D-35ADC34D7D5A-88049-000758A621BC58CC/IMG_0250.jpg)
[[“The System” of AT&T]] was so huge that even small efficiency gains translated to saving tons of money. Unlike in software, creating new markets (like calls to Europe, cables that can survive extreme environments, etc) required creating new, physical technology which in turn sometimes required new scientific discoveries. 

AT&T’s agreement with the government was that as long as AT&T continued to improve its offerings, stay focused on communication, and shed technology, the government wouldn’t be break it up its monopoly. As noted earlier, the way that AT&T could continue to improve its offerings was through technology. 

Finally, the government blocked large company M+A at several points in the 20th century and startups were just less of a thing before the latter half of the 20th century. At the same time, the nature of the technology increasingly seemed to be beyond the capabilities of a single inventor. [[Does the nature of the activities to create new technology and science change over time?]]  Consequently, in order to benefit from technology, AT+T needed to build it itself.

### Related
- [[Healthy corporate R+D requires a trifecta of conditions]]
- [[Bell Labs was only profitable in conjunction with AT+T]]
- [[aroraChangingStructureAmerican2020]]



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Bell Labs management was extremely light

Expensive research needs to address an existential threat eventually at an organizational level to maintain support

# All the work at Bell Labs needed to tie back to the system
There’s a common conception that research at Bell Labs was completely unfettered. My hunch is that this was not the case and all the work at Bell Labs did need to tie back to AT&T’s core business in the same way that any corporate lab does, but the nature of [[“The System” of AT&T]] and it’s particular location in time and place enabled many researchers to forget about the box that they were in. 

AT&T’s system was so vast and multifaceted that tons of research *did* tie back to it - chemistry, electronics, information theory and other mathematics, materials. [[Bell labs brought many disciplines together under the same roof and broke down barriers between them]] not because abstractly that’s how you get good ideas but because that is what they needed to do to improve the system.

It also helps that this wide range of relevant work happened to coincide with the most exciting research fields at the time. There’s *heavy* mixing between correlation and causation here (silicon electronics and information theory were basically created at Bell Labs, etc.) However, it is important to note the convergence between hot research topics and things that were actually relevant to AT&T’s core business. Today, this type of convergence is arguably a big reason why [[AI research is an exception to the decline of corporate R+D]]. 

[[Bell Labs management was extremely light]], which presumably helped with the perception that the research was unfettered. Of course, management could only be so light at least in part because the range of relevant research was so large. 

Thanks to the size of the boundaries on useful research and the quality of the management, I suspect that they were also able to hire people who had no desire to leave the box. It’s easy to feel unfettered when given free rein, you would do the things that a manager would want you to do anyway. This is of course the ideal everywhere but the circumstances at Bell Labs made it easier to achieve.[^1]

[[Claude Shannon]]’s experience illustrates what happened when researchers strayed outside of work that wasn’t relevant. [[It’s hard to know exactly where a line is until you cross it]]. These anecdotes look like something that would happen at any corporate R&D lab. While there’s no concrete evidence, I suspect that incidents like this happened not-infrequently, but they happened with less prestigious people so they weren’t remembered or recorded.
![](../BearImages/6A8E8720-577B-4BC1-B60A-71DAF6330D20-88049-000786D8D9EBBAA0/5082BE7F-5871-43BC-B95A-782C111B1E5E.png)
![](../BearImages/741B71CF-F149-4515-BBC7-9BA854B08C89-88049-000786DB1790630D/IMG_0188.jpg)

### Related
- [[Expensive research needs to address an existential threat eventually at an organizational level to maintain support]]
- [[Innovation orgs need to be aligned with their money factory]]
- [[Regulation drove many of Bell Labs’ actions]]
- [[Bell Labs did not give researchers complete freedom]]

[^1]: Sidenote - I suspect this is the case with [[JCR Licklider]]’s program at ARPA. [[Alan Kay]] describes him as giving researchers free rein, but zooming out, this was not universally the case. Instead, it seems like Licklider was clear enough on his vision and what needed to be done that he could find researchers who would happily stay in the box he wanted them to be in.



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Innovation orgs need to be aligned with their money factory

Alignment requires existential threats

The incentives inherent to corporate R&D mean that researchers motivated by money leave and those who are motivated by glory are not the best in the world

# Bell Labs is one of the few examples of an innovation org that was aligned with its money factory
 [[Innovation orgs need to be aligned with their money factory]] and arguably one of the reasons behind [[Bell Labs]]’s outlier success was that it managed to have a broad scope and long time scale that were both *still aligned* with AT&T.

At the end of the day AT&T’s goal was to maintain its monopoly and increase its business. In order to do that, it needed to enable people to make more, better calls. 

[[“The System” of AT&T]]  had such an expansive scope that it actually benefitted from the whole spectrum of activity happening at Bell Labs. Everything from information theory to novel materials directly fed back into AT&Ts core business. More cables are expensive so information theory actually helps people make more calls. The faster you can switch, the more calls you can route so semiconductor switchers *directly* help with the goals. 

Additionally, [[Bell Labs and AT&T had timescale alignment]] thanks at least in part to AT&T’s monopoly. The monopoly enabled Bell Labs to plan on multi-decade timescales because they didn’t have to worry about a competitor coming along tomorrow. 

AT&T maintained their monopoly only with tacit approval from the government. This approval rested heavily on Bell Labs’ output - both continuous improvements to A&+Ts offerings and open licenses from the lab. [[Regulation drove many of Bell Labs’ actions]]. 

Between the cost reductions and monopoly maintenance, Bell Labs was actually addressing existential risks to AT&T. [[Alignment requires existential threats]]. Even R&D labs that are building new product lines within the scope of a company’s actives rarely address existential threats to that extent.

This alignment in both timescale and focus-scope between an innovation org an its money factory. See [[§Startup Constraints]], [[§Corporate R+D Constraints]], [[§Philanthropy and Non-Profit Constraints]], and [[§Academia Constraints]] for all the lovely ways the misalignment can happen.

## Related
- [[gertnerIdeaFactoryBell2012]]



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Bell labs had a budget of 2.8 billion 2020 dollars

Bell Labs and AT&T had timescale alignment

Week of 22 Nov 2020

# Bell Labs was not a business
Bell Labs didn’t actually make most of its money directly off of its technology. Its primary source of revenue was just a % of the money from the local operating companies and AT&T itself. It gave technology to Western Electric to manufacture and they in turn gave it to AT&T and the operating companies who then were paid and gave the money back to Bell Labs. The trick is that at no point in this cycle is anybody putting a value on the technology directly. Because of its monopoly status, AT&T would be getting paid regardless of how good its service was. However, the only reason AT&T could maintain that monopoly was because they had a <semi-implicit> agreement with the government that they would continue to improve their services. [[Alignment requires existential threats]]. 

When each piece of the puzzle was separated and needed to interact via contracts and prices, Bell Labs clearly couldn’t stand on its own as a business. The exact explanation of this is tricky and requires some detailed analysis on data that may not even exist.  

![](../BearImages/E3753743-2D42-4C5F-902F-81CE9479EEBB-88049-0006A6BE36DA27BB/IMG_0250.jpg)
According to Peter Drucker’s analysis of the AT&T breakup, it is possible that Bell Labs *could have* become a business, but that would have required radically reconfiguring from what it had been. 

Bell Labs didn’t actually produce products. Once technology was at a point where it was ready to be manufactured at scale, it was handed off to Western Electric. If both organizations weren’t wholly owned subsidiaries of AT&T,  Western Electric would both want a cut (reducing Bell Labs’ hypothetical profit margins) and would either need to be paid up-front or convinced to manufacture new things that they would then sell to AT&T.

It wasn’t that Bell Labs wasn’t creating value - it’s just that it was doing it in the context of [[“The System” of AT&T]].   
![](../BearImages/6DE120B4-C48E-48D4-9713-D49775DDC3BA-88049-0006CEF5E8D607A5/IMG_0231.jpg)

Perhaps one way to look at it is through the lens of [[Transaction costs]]. Bell Labs could only exist because it was getting continuous payments for extremely lumpy outputs (presumably some years, the direct value it delivered for AT&T was massive and some years it was near zero. Because of how human brains work, few companies would be willing to sign a contract that traded a consistent cash flow now for an uncertain innovation in the future. There are also some things that cannot be written into contracts - the trifecta relationship between Bell Labs, AT&T, and government regulators was incredibly valuable to AT&T but couldn’t be made explicit and wouldn’t have been possible if Bell Labs were a separate entity. 

It’s important to note that Bell Labs was not a business both to build a mental model of the organization and to stare a major problem with trying to build the next Bell Labs straight in the face. [[Healthy corporate R+D requires a trifecta of conditions]] and it’s unlikely that those conditions will arise outside of software any time soon. People have implicitly realized this and most ideas to ‘build the next Bell Labs’ involve creating an independent organization. However, building an external organization will require money and  [[People don’t invest in technology, they invest in businesses]]. The upshot is that any spiritual successor to Bell Labs will need to have a radically different structure than the original. 

This note is perhaps a dual to [[Bell Labs was only profitable in conjunction with AT+T]]. 

### Related 
-
- [[The Nature of the Firm]]
- [[gertnerIdeaFactoryBell2012]]
- [[Research should be treated like infrastructure]]



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You need a certain scale for technology development to be worthwhile

The work at Bell Labs that was most valuable to AT+T and the work that was most valuable to the world was fairly disjoint

Comparing and contrasting Bell labs, DARPA, and Venture Research

PARPAs ideal legal structure comprises both a nonprofit and a for profit

# Bell Labs was only profitable in conjunction with AT+T
[[Bell Labs]] *did* pay for itself by making [[“The System” of AT&T]] more efficient. [[Xerox PARC]] did as well via the Laser Printer. However, most corporate research labs have more tenuous arguments for their profitability. Note that in both cases, the profitable outputs were *not* the most impactful outputs.  [[There is a significant class of innovations that would create drastically less value for the world if their value had been captured by their creators]]. This disjoint between profitable outputs and outputs later hailed as valuable and important happens so often that I can’t believe it’s a coincidence. [[Seen vs Unseen]]. 

![](../BearImages/4E0869F4-2A3C-4466-AC27-925F7D05EC80-88049-000710A05F0F715D/11D837FA-70D5-43C8-B01D-F49EB1CB8A87.png)

It’s worth paying attention to the mechanism by which both Bell Labs and PARC (and extrapolating wildly, other corporate labs) pay for themselves. In both cases profit was through leveraging the scale and existing competence of the parent company. In Bell Labs’ case, it was by simply reducing cost at scale and in PARCs case it was something that could be produced at sold at scale with the same factories and sales channels.  

The above quote is also notable because it illustrates how the efficiency gains were *actually* existential threats to AT+T because of the roundabout logic of “monopoly maintenance requires continuous improvement and expansion which would be impossible without finding a lead replacement.” [[Alignment requires existential threats]]

There’s a strong and a weak proposition here. The strong proposition is that without AT+T’s scale, Bell Labs would not be profitable. The weak proposition is that even given AT+T’s scale, the transaction costs would be too high for Bell Labs to have been profitable if it were a fully independent organization. 

The strong proposition is pretty straightforward - any invention that isn’t wildly expensive like early computers and rocket ships requires scale to create value. To get scale, non-software inventions require either large manufacturing and sales apparatus and/or a large system to deploy on (in the case of efficiency-type inventions[^1].) So, the profitable inventions from Bell Labs leaned on AT+T’s existing scale.  

The weak proposition is more debatable but important to consider. In a world with zero [[Transaction costs]], it wouldn’t matter whether Bell Labs was joined at the hip to AT+T - if there was an invention that would save AT+T billions of dollars, it would pay a large fraction of that gladly and Bell Labs would be able to support itself as a fully separate institution. However, transaction costs are real (see: [[The Nature of the Firm]].) An independent Bell Labs need to convince a string of non-technical executives at AT+T that they would eventually run out of lead, the size of the problem, and the fact that the synthetic material would work as well as tried-and-true lead. On top of that, Bell Labs would need to realize that they *should* develop a lead replacement or what specific affordances need to be which is the sort of insight that is non-obvious if you aren’t constantly talking to the people who manufacture the cables. [[Prototyping needs manufacturing in the room]].  On top of that, you would then need to convince someone to fund development for the lead-sheath replacement (either internally to your org, for whom cable sheathing is not an existential concern, or externally) which gets you into a chicken-and-egg situation with all the previous considerations. 

There’s a fuzzy thought here about value capture depending on where you draw a box around the system. 

### Related
- [[Bell Labs was not a business]]
- [[Bell Labs is one of the few examples of an innovation org that was aligned with its money factory]]
- [[Profit-maximizing organizational structures can hamstring technologies whose impact depends on them]]
- [[It is hard to capture value from research]]
- [[A technology’s value is relative to the amount of value it unlocks]]
- [[AT+T benefitted significantly from creating better technology]]

[^1]:[[Efficiency type heuretics]] are especially dependent on large systems because of [[Transaction costs]]. If an efficiency improvement makes something $1 more efficient per node, even if there are a billion nodes in the world, if each one is in a separate system and you need to sell to each one individually the transaction costs make it not worthwhile to create and sell it. However, if those billion nodes are concentrated in a few systems, its well worth it.



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Bottlenecks Workshop June 2021

In the past, corporate labs filled a particular niche in the innovation ecosystem

One function of a private ARPA is to fill in the gap once filled by corporate R+D

Healthy R+D orgs feel like they have very smooth project rampups with high ceilings

What does it mean for a research ecosystem to be healthy?

Could FROs fill the gap left by corporate R+D?

# Ideally corporate R+D enables targeted dicking around
You have lots of stories of golden age R&D orgs where they’re literally just trying out a lot of stuff. “Hey, we came up with this new chemical, what’s it useful for?” In the startup world, that’s often derided as a “solution looking for a problem.” Arguably though, many important technologies started off this way - they weren’t a hole-in one solution to a problem. We don’t seem to have a place for this targeted dicking around to happen anymore for situations that require specialized knowledge and equipment.  

It’s important to call attention to the “targeted” part of “targeted dicking around.” Contrary to common perception, Bell Labs and PARC *didn’t* give researchers free rein to work on whatever they wanted.  There were relatively few milestones and researchers had enough slack from management to explore adjacencies. However, people were explicitly asked to work on high level goals that would benefit [[“The System” of AT&T]].

It’s almost impossible to confirm, but my hunch is that researchers who portray themselves as having free rein ([[Alan Kay]] comes to mind) are unreliable narrators. My hunch is that they perceive themselves as having free rein because the lab managers were good at hiring people whose interests were sufficiently aligned with the lab’s target that anything they chose to do was within some window. Another alternative is that they gave a *few* people free rein and the personal accounts are from the wunderkinds. [[The famed bell labs research was a fraction of their activity]]

[[Comparing and contrasting Bell labs, DARPA, and Venture Research]]

Disciplines where targeted dicking around can happen seem to be more healthy. You still see it a lot in software. It seems like there is a tradeoff between the democratization of a technology and the ability to dick around with it. Corporate R&D labs may have been able to change that equation. Stories about heyday chemical and other company R&D that created physical products - [[Nylon]], [[3M]] involved a lot of just ‘trying stuff out.’ It’s unclear that happens anymore 

There’s an implicit assumption that targeted dicking around happens in universities. This may be the case with *ideas* but it’s less so with technology applications. You can’t really write a paper about how you spent a year modifying your novel technology to 100 specific applications. 

Making a general purpose technology requires both generality and specificity. Great results have come from both a mode where people grope towards a general goal and also a mode where they grope towards a specific one. The development of the GUI at  [[Xerox PARC]] is a good example of the former mode. The PARC folks created general paradigms for computing like overlapping windows and visual representations of files that continue to dominate today by doing the hard work to build a full system, using it themselves, and seeing what worked. [[Edison’s Lab]] also did a lot of “trying stuff out” but in contrast to the taste-based cycles at PARC, the inventors at Menlo Park had a concrete application like a long-lasting-lightbulb in mind went through a thousand materials to see if they would fit the bill. This ‘iterating towards a concrete target’ mode of experimentation is much more suitable for startups. 

However, the two modes seem like they could be strongly coupled. While you’re trying out a thousand things to do a specific thing, you may realize that the five hundred and twenty first thing is no good for the intended purpose, but might be amazing at another thing. [[The ability to say ‘huh that’s funny’ is important for discovering new phenomena]]. However, that realization can easily be tossed out the door without the room to explore that hunch (because usually it’s a hunch.) Startups, academia, and 21st century R&D are rarely set up incentive-wise to enable to run that hunch to ground. You *do* see this happen with software startups because it is *much* easier to do targeted dicking around with software. Arguably this could be one reason that we’ve seen less stagnation in software. 

In contrast to many modern corporate R&D labs [[Bell labs asked people to do useful things but left them room to say huh that’s funny]]. Google Brain feels like it does the same thing. And perhaps that’s why it feels like a much more ‘healthy’ corporate R&D organization. In fact a lot of the pure AI work feels a little bit like this targeted dicking around. Except that they actually don’t take it the one step farther to be an experimental product.

This “targeted dicking around” could be a different way of describing what hanging out in [[The (idea) valley of death]] looks like! 🤔  [[An organization to generate quantum technology leaps and bridge the idea valley of death]]

Targeted dicking around requires [[Slack - concept]] that you don’t have at startups or in academia, and increasingly don’t have in corporate R&D either. [[R+D orgs are answerable to shareholders both in scope and timescale]].

### Related
- [[Bell Labs enabled free radicals]]



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Stripe press could provide low touch support to a community of frontier openers

Philanthropies can easily become misaligned with their money factories

narayanamurtiGenesisTechnoscientificRevolutions2021

ARPA became DARPA in 1972 because of the increased scrutiny on military spending both in the government and outside of it

Healthy corporate R+D requires a trifecta of conditions

Philanthropies are forced to show consistent short term progress

Regulation drove many of Bell Labs’ actions

Organizations can get incomes via Contracts, budgets, or products

Tensions are the core theme of the PARPA writeup

There are many tight feedback loops built into the ARPA model

Breakthrough fundamental science

DARPA’s primary purpose is to develop military technology

Does the money factory need to necessarily be one organization?

The shift of Pioneer to be a remote accelerator is a case study for the incentives around monetization

Who is paying the bills?

# Innovation orgs need to be aligned with their money factory
Aligned incentives are the only thing that will enable the innovation org to not have crushing oversight and be able to work on long-term projects. [[Playing the same game is the only way people can align for extremely long time scales]] so if the innovation org is going to survive long term, it needs to be playing the same game as the money factory. It can get away with diverging for some time, but it’s always finite.  [[Alignment between people playing different games can happen on finite time scales]]. The alignment also needs to be clear to the people who control the money and be on a timescale that’s acceptable to them. So while fundamental research might be in the long-term interest of the United States Government, the timescale that matters to most politicians is their term in office. 

 [[Bell Labs is one of the few examples of an innovation org that was aligned with its money factory]].

The more fund-strapped the money factory is, the tighter the alignment needs to be. When AT&T, Microsoft, or Google are flush with Monopoly money they’re happy to let people dick around on whatever. When stocks dip, the first programs to be cut are the ones that have the least plausible ties to the core product. [[Expensive research needs to address an existential threat eventually at an organizational level to maintain support]]. Similarly [[ARPA became DARPA in 1972 because of the increased scrutiny on military spending both in the government and outside of it]].

### Related
- [[Principles for Innovation Orgs]]
- [[Philanthropies can easily become misaligned with their money factories]]
- [ ] Need to integrate [[Reaper functions dominate other incentives]] 

## References




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Efficiency is overrated

# Optimizing individual components of a system is often at odds with the system itself
This is one of those (Talebian?) statements that are obvious on their face but explains many things and is often ignored in practice. 

Argument by analogy is usually bullshit but I think it may work here. In the simplest form the principle is evident just from optimizing a single variable function like f(x)=1-x^2 - obviously making x as big as possible does not make f(x) as big as possible. You can extend this to any number of variables. Then you can replace all the variables with functions themselves. Then you can replace those functions with whatever you want - systems, unknown probability distributions, utility functions, etc. 

 [[Goodhart's Law]] could be reframed in this light as the idea that if you try to maximize the variable that you can measure, you’ll end up working against the systemic output you care about. 

### Related
- [[Slack - concept]]
- [[alexanderStudiesSlack2020]]
- [[“The System” of AT&T]]
- [[Institutions are the second level of a group selection evolutionary system]]
- [[Efficiency is overrated]]
- [[You can think about institutions as systems]]
- [[Emergent behavior happens when a system has properties that none of its subsystems have]]
- [[Academia is not a good environment for systems engineering]]

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Benʼs working notes

“The System” of AT&T

“The System” of AT-T

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