There’s a subtle distinction between freedom to suggest ideas and freedom to pursue ideas

# §Bell Labs Model

### Questions
- [[Why was Bell Labs Different?]]
- [[Why hasn’t Bell Labs been replicated?]]
- [[Was Bell Labs an anomaly?]]

### Conclusions
- [[Bell Labs and AT&T had timescale alignment]]
- [[Bell Labs is one of the few examples of an innovation org that was aligned with its money factory]]
- [[Bell labs had a budget of 2.8 billion 2020 dollars]]
- [[Bell Labs was only profitable in conjunction with AT+T]]
- [[AT+T benefitted significantly from creating better technology]]
- [[Regulation drove many of Bell Labs’ actions]]
- [[All the work at Bell Labs needed to tie back to the system]]
- [[Bell Labs empowered young people]]
- [[Bell Labs hired people before they had a role or expertise]]
- [[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]]
- [[The famed bell labs research was a fraction of their activity]]
	- [[Bell labs was primarily not researchers]]
- [[Bell labs brought many disciplines together under the same roof and broke down barriers between them]]
- [[Bell Labs did not give researchers complete freedom]]
- [[Bell labs asked people to do useful things but left them room to say huh that’s funny]]
-  [[Bell Labs management was extremely light]]
- [[Bell Labs didn’t have a unique model]]
- [[Bell Labs selected for people with only academic pedigrees and with a sense of adventure]]
- [[Bell Labs was not a business]]::NW::
- [[Bell labs existed before continuous improvement was expected]] ::NW - stub::
- [[Bell Labs was a dance of individuals and institution, prototyping and manufacturing, invention and discovery]]::NW::
- - [[Bell Labs enabled free radicals]]



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Bell Labs

gertnerIdeaFactoryBell2012

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

§Bell Labs Model

Labs Document Outline

# Bell Labs and AT&T had timescale alignment
# Bell Labs and AT-T had timescale alignment
Both Bell Labs and AT&T had a [[Buxton Index]] of a few decades - they both thought about problems on the timescale of decades. 

 On AT&T’s side, their government-approved monopoly and the mandate that allowed them to maintain it both gave them the [[Slack - concept]] to plan on the scale of decades *and* the incentive to do so.  

I’ll make a hand wavy argument for Bell Labs’ Buxton index by using the transistor as an exemplar. It officially took eight years - from 1946 to 1954 to create the silicon transistor. However, work on the transistor began in the 30s before WWII (and was paused during the war) and the first electronic switching centers came on line in 1964.  All together, the transistor timescale was maybe 20 years.[^1]  It seems reasonable to use this 20 year mark as a rough approximation for Bell Labs’ Buxton Index. 

It’s hard to imagine the rough equivalence between AT&T’s Buxton Index and Bell Labs’ was a coincidence.

This alignment changed after AT&T’s breakup. Bell Labs’ Buxton index didn’t change, but thanks to competition AT&T no longer had the luxury of a multi-decade Buxton index. 

![](../BearImages/7922CB30-5949-4360-82B8-20283BFE41AA-88049-000786B4DA543094/IMG_0115.jpg)

### Related
- [[Bell Labs didn’t have a unique model]]
- [[Innovation orgs need to be aligned with their money factory]]
- [[Bell Labs was not a business]]
- [[Rewards in a big company operate on one timescale and R&D happens on another timescale]]
- [[Mismatched Buxton Indexes lead to shear forces]]

[^1]:I have very little evidence, but my hunch is that 20 years is roughly the timescale to go from the hunch that a phenomenon can be exploited to  exploiting it at scale. [[Phenomena-based cycles]]. This timescale is probably compressed for electronics and software because of Moore’s law and development speed (though perhaps not as compressed as many people intuit.) 20 years is *shorter* than the 50 year Buxton index that [[EW Dijkstra]] suggests (is/should be) the norm in Academia. [[The Strengths of the Academic Enterprise]]. 



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Innovation orgs need to be aligned with their money factory

Alignment requires existential threats

Bell Labs was only profitable in conjunction with AT+T

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

Why was Bell Labs Different?

# 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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What are the different roles in an innovation org?

Bell labs had a budget of 2.8 billion 2020 dollars

Bell Labs and AT&T had timescale alignment

Why try to emulate DARPA and not Bell Labs

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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PARPA needs a constitution with checks and balances

Research is especially susceptible to Goodhart’s Law

Rewards in a big company operate on one timescale and R&D happens on another timescale

Charlie Songhurst conversation 31 Aug 2021

There are many parts of the US government that are heavily influenced by term-level time scales

dijekstraStrengthsAcademicEnterprise1994

The timescales of invention and discovery are high variance

Inverting the normal relationship between an R+D organization and is money factory may enable new classes of activities

Glossary

Long-term projects are inherently highly levered up

Peter van Hardenberg Conversation 20 Nov 2020

# Buxton Index
[[Mismatched Buxton Indexes lead to shear forces]]

From [[The Strengths of the Academic Enterprise]]
`The Buxton Index of an entity, i.e. person or organization, is defined as the length of the period, measured in years, over which the entity makes its plans.`

More detail:
` For the little grocery shop around the corner it is about 1/2,for the true Christian it is infinity, and for most other entities it is in between: about 4 for the average politician who aims at his re-election, slightly more for most industries, but much less for the managers who have to write quarterly reports. The Buxton Index is an important concept because close co-operation between entities with very different Buxton Indices invariably fails and leads to moral complaints about the partner. The party with the smaller Buxton Index is accused of being superficial and short-sighted, while the party with the larger Buxton Index is accused of neglect of duty, of backing out of its responsibility, of freewheeling, etc.. In addition, each party accuses the other one of being stupid. The great advantage of the Buxton Index is that, as a simple numerical notion, it is morally neutral and lifts the difference above the plane of moral concerns. The Buxton Index is important to bear in mind when considering academic/industrial co-operation.`

`To begin with, there is the great difference in Buxton Index. For industry, the Buxton Index is less than 10, probably closer to 4 or 5, whereas for the academic scientist the Buxton Index is closer to, say, 50, for what you offer your students should last a lifetime, their lives, to be precise.`

Invented by [[John Buxton]] not [[Bill Buxton]]

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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

How does money work in PARPA?

narayanamurtiGenesisTechnoscientificRevolutions2021

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

“The System” of AT&T

Philanthropies are forced to show consistent short term progress

Healthy corporate R+D requires a trifecta of conditions

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

Regulation drove many of Bell Labs’ actions

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

Tensions are the core theme of the PARPA writeup

Organizations can get incomes via Contracts, budgets, or products

There are many tight feedback loops built into the ARPA model

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

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

Breakthrough fundamental science

DARPA’s primary purpose is to develop military technology

ICT Distillation

An Institute for Creative Technology - Riffing on ARPA

Does the money factory need to necessarily be one organization?

ICT Outline

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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strevensKnowledgeMachineHow2020

Research has many orthogonal and non orthogonal classification axes

Materials and manufacturing underpin civilization

The ability to say ‘huh that’s funny’ is important for discovering new phenomena

Quadrant Model of Scientific Research

Someone needs to buy manufactured technology eventually in a monetized economy

Both Bundling and Unbundling parts of a process is important

Phenomena-based cycles are stuck

Scientific inquiry is an abstracting process while engineering design is a narrowing process

Theory can suggest where to dig for new phenomena

It takes roughly 20 years to exploit a phenomenon at scale

Efficiency biases systems towards false negatives

You need to break rules to create new paradigms

TRLs are not monotonic

drexlerRadicalAbundanceHow2013

J Storrs Hall theorizes regulation has cut off the pathway from technology to science

Multidisciplinary teams need to leverage different paradigmatic lenses

Contemporary research has multiple failure modes

New phenomena can be exploited without understanding or understood without exploiting

Space exploration can surface new phenomena — we need to go out there and poke stuff

A history of matter

A theory that is not fully correct can still be effective

Both science and technology can be either a product or a byproduct

Science and knowledge of the universe as raw resources

The term ‘Double edged sword’ is bothersome

# Phenomena-based cycles 
# Phenomena-based cycles 
If you think of basic building blocks as 
1. Theorizing around  [[phenomena]] (why it happens) 
2. Observing phenomena (seeing it happens)
3. Exploiting phenomena (using it to do something useful) 
([[Phenomena are things that happen without a human consciously making them happen]]) 

There are actually several ways that things happen. 

**A couple of notes**
- The end of one “chain” is almost *always* the beginning of another, so a big picture would show a loop back to the original block. 
- For a given phenomena, there are often multiple chains running in parallel: throughout history people have observed already-theorized phenomena without any knowledge of the theory. The discovery of the cosmic microwave background is a perfect example of this. 
- “Exploiting” is itself a multistep process with its own loops. The [[Technology readiness level - TRL]] system gets at this fact and still ignores the dispersion aspect of technology that might be necessary before it can be used sufficiently to lead to an observation or theory. However, an observation or theory can *also* come from an incomplete exploitation. 

1. **Theory -> Observation -> Exploitation**
This is the [[Karl Popper]]Ian cycle that is also encoded in the idea of basic-applied research. It is the broad outline of how the [[Manhattan project]] worked - theory predicted that a critical mass of fissile material should explode, informing experiments where that was observed, leading to the exploitation of that phenomenon by building the bomb. The explosive, era-defining example of this mode embedded it in many minds. 
2. **Observation -> Exploitation -> Theory**
This is arguably how innovation has happened throughout most of history. “Hey, when I mix this special rock with this other special rock and water it turns into concrete!” Yes, that’s because those rocks have just the right mix of calcium, silicon, aluminum, iron, and other ingredients. “Huh, when I stir wheat-water with this special stick, it turns into beer!” Yes, that’s because that stick is maintaining a colony of yeast - tiny microorganisms that turn the sugars from the wheat into alcohol.
3. **Exploitation -> Observation -> Theory**
This is the “technology-based tool building” mode of phenomena discovery. Scanning electron microscopes or X-ray crystallography are great examples of this. Both take advantage of new phenomena to observe previously unobservable phenomena that can then be theorized around. Note how many Nobel prizes have been awarded for creating new observation tools. 
4. **Theory -> Observation -> Theory**
This is the [[Thomas Kuhn]]sian cycle from [[narayanamurtiCyclesInventionDiscovery2016]]: someone observes something that doesn’t fit with a previous theory which then forces an update to the theory. Galileo is the classic example here. Note that arguably Galileo is *also* an example of a type #3 chain because he was able to make the observation because of the new ability to exploit the lensing phenomena of polished and shaped glass. It’s rare that someone goes into an observation completely theory-free.  
5. **Exploitation -> Observation -> Exploitation**
This is basically just [[Learning by doing]]. Like #2 this is probably one of the most common modes and often operates a bunch of little loops parallel to #2 until theory comes along. It’s super common even in the 20th/21st century - the early days of rocketry were mostly trial and error. 
6. **Exploitation -> Exploitation**
Often, a new way to exploit a phenomenon becomes unlocked just by crossing some ability threshold. For example the ability to do deep learning was unlocked mostly by data and compute reaching a threshold - all of which are arguably exploiting the semiconductor phenomena. *However* because phenomena and thus paradigms are fractal ([[Phenomena are things that happen without a human consciously making them happen]]) this mode can look like a capability advance within a paradigm enabling another capability advance within that paradigm or a capability advance in one paradigm enabling a capability advance in another paradigm.
7. **Theory -> Theory**
Theory can also be built off of the back of other theories. This chain is a two-sided sword. On the one hand, it can enable great logical leaps to escape local equilibria. On the other hand, it can lead to entire fields becoming unmoored from reality. I will not name them here. [[Decoupling from market discipline is like cave diving]]. 

I didn’t realize until after writing this that theory doesn’t ever seem to lead directly to exploitation. The closest might actually be in computer science - especially cryptography where there is a very small gap between theory and reality. 

These cycles are how different axes of research affect each other. [[Research has many orthogonal and non orthogonal classification axes]]

Through this lens, I worry that thanks to specialization-driving forces in the 21st century ([[Competition and lack of slack  creates specialization]]) we are putting more and more effort into chain #6 and #7, without actually completing any loops. Uncompleted loops could absolutely lead to [[Stagnation]].  If this narrative is the case, we need to start asking ‘how can these phenomena we’re exploiting lead to better observations or theories about *different* phenomena?’ [[Phenomena-based cycles are stuck]]

### Related
- [[The ability to say ‘huh that’s funny’ is important for discovering new phenomena]]
- [[X-punk imagines a world dominated by X]]
- [[Technological and scientific paradigms are each based around exploiting a specific phenomenon]]
- [[Heuretic domains share an underlying phenomenon]]

### References
- [[narayanamurtiCyclesInventionDiscovery2016]]



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§Corporate R+D Constraints

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

# Rewards in a big company operate on one timescale and R&D happens on another timescale
# Rewards in a big company operate on one timescale and R-D happens on another timescale
 At the end of the day, the incentives in the org act on[[Human timescales]] - promotions, career progression.

Politics happens on a shorter timescale than results, and the real impact of a piece of research may be on an even longer timescale than a single career. 

These wildly mismatched [[Buxton Index]]es throw a wrench into R&D. 

### Related



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alexanderStudiesSlack2020

Institutions are the second level of a group selection evolutionary system

Most institutions have become cancerous

Systems must take performance hits to get out of local optima

The value of planning is inversely proportional to the cost of experimenting

Heat cycles for democratization and cutting edge experiments innovation and discovery

The word ‘novel’ is used as an idea bludgeon in academia

Peer review has failed as an institution

Ideally corporate R+D enables work on a general purpose technology before it’s specialized

Competition and lack of slack  creates specialization

Systemic decay theory of stagnation

Efficiency

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

Ideally corporate R+D enables targeted dicking around

Bell labs asked people to do useful things but left them room to say huh that’s funny

Classical Liberalism defaults towards gridlock

Culturally we expect modern organizations to become a monopoly

Some 80’s deregulation may have been a bad thing

Astro Teller conversation 1 Feb 2022

Getting to new optima is hard

Margins and innovation have a complicated relationship

Technology doesn’t solve everything but it does generate growth which arguably does solve everything

A consolidated competitive ecosystem creates a number of effects

Some ideas take a large chunk of resources to assess

How do you deal with the tradeoff that technology commoditizes things but high margins are necessary to invest in technology?

If there is a possibility for a monopoly, an institution is either nonexistent or worthless

Notes on resources around market failure

‘Have your cake and eat it too’ life-games have led to a toxic society

Notes on the changing structure of American Innovation

# Slack - concept 
# Slack - concept 
The canonical article: [[alexanderStudiesSlack2020]]
Coined by [[Zvi Moskovitz]]



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Buxton Index

# The Strengths of the Academic Enterprise
66 Institutions have operated continuously since 1530:
- Roman Catholic Church
- Lutheran church
- Parliament of Iceland
- Parliament of the Isle of Man
- Universities

Terms that subtlety change meaning
- Scientist
- Engineer
- Theoretical
- Experimental
- Applied
![](BearImages/27803535-7FCA-430C-B2C3-DE40665BF605-98199-000BD37383818622/B3575AD4-A52E-45FE-B2FB-CFDB3998C3E7.png)
![](BearImages/B6A36F1C-7113-4EF5-B0B3-31EC8CA937C3-98199-000BD380793C254B/1A2E0CF8-86E7-4069-9A02-1A9F54123A71.png)

![](BearImages/FE6D56FC-A07D-4886-8D61-B5BC8D4A9850-98199-000BD378FD30AED1/74D3A943-967D-4BDD-B4D7-93DAF67FDAE0.png)
![](BearImages/97F9B1FD-3919-4801-8FBE-C2BE204EFFCD-98199-000BD385AD0F00DA/EFE0B975-7886-4462-BFB3-30F1AB1843F0.png)
- Introduces the [[Buxton Index]]
- ::Has anybody ever done buxton analyses of institutions?::
- 
![](BearImages/03FD1C6A-AF2D-4406-ACE1-0A9442D7A233-98199-000BD3E366741515/FF1E0D48-0E57-4C61-A561-6AD90EDFC410.png)
![](BearImages/AE3FAED3-4B17-41C7-BDE1-FEC9ADFDADC1-98199-000BD3E9CDFDC925/D0C63DD8-893E-4B33-9F1A-CDF70CFFEF63.png)
::this seems like a false dichotomy - there’s tons of tacit knowledge in universities:: 
![](BearImages/F9120BF1-97AD-4A04-B841-19D961F97C90-98199-000BD411B96889CA/AC0EB00D-7BFB-4A59-AB49-87EC35160DF6.png)
- [[The boundaries between industry government and academia are fuzzy]]
-  [[Institutions need to differentiate between individuals inside and outside the institution]]
![](BearImages/E283E18C-BE97-4A60-8417-369BFA2D4C43-98199-000BD42B2FAE7B55/9289B9A0-8F2D-4DC5-BF5D-AC3C681E1C90.png)
![](BearImages/2DB6327E-C76E-4A49-9523-73F4EDCEDDC5-98199-000BD457946413EA/71EB2C93-A4E1-4AEB-B548-9A6EF739F738.png)
- ::Tension around individuality in academia::
- 
![](BearImages/4AC35689-A04B-4A8F-9522-844D81AABC6C-98199-000BD45FAD1A25F0/1D6AAC6A-C0E2-4B13-B5F5-B81CB17E9723.png)
![](BearImages/3E2EE8CD-D010-44F3-8DFE-9F5B90429A81-98199-000BD463E28FB63E/7879CD8C-F39E-4451-9EBA-765A4EC792E9.png)
- ::Against collaborations!::
![](BearImages/E6F8AEB5-658F-4328-9524-AD6622CEF342-98199-000BD47873568D78/14A46378-6FE8-486B-97BF-E67243191D24.png)
- ::This is a *very* complementary view of academic scientists::
- 
![](BearImages/0596ED5B-4BD0-4206-84BB-AFAA0F14F946-98199-000BD483EDDCF168/0FF25678-E617-42DC-9EE7-12780F755820.png)
	
![](BearImages/A0B7ACA2-4C5A-44B2-8EE4-FEEC5449FDCB-98199-000BD4C573068459/426362D2-9D98-4080-9AE9-8F9ED8CFE153.png)

### Published
## Questions
## Thoughts
## Related
- [[Professors do three or more jobs]] 

## Authors
[[EW Dikjstra]]
## Link
https://www.dropbox.com/s/pnck24xqtp9ikdv/ewdijkstra%20archive%20the%20strengths%20of%20the%20academic%20enterprise%20%28ewd%201175%29_2020-09-19%2016.13.52.pdf.pdf?dl=0



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Benʼs working notes

Bell Labs and AT&T had timescale alignment

Bell Labs and AT-T had timescale alignment

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