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Lessons from history's greatest R&D labs

answer.ai

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Re: Lessons from history's greatest R&D labs

#31

Post by gradschoolfail »

jph00 wrote: post #3

Jeremy from Answer.AI here -- Answer.AI is, to some extent, the subject of this article. Perhaps worth noting here that we didn't pay the author, Eric Gilliam; it's his independent analysis based on years of study of 19th & 20th century R&D labs. I'm hoping that not only will Answer.AI be successful, but that Eric's words in the conclusion will come to pass: > "If their USD10 million experiment works, it has the chan…

@publicdaniel asked below about the relevance of openai’s Ken Stanley of “greatness cannot be planned” fame. @jph00 Can you comment on the similarities and difference of your approach as you understand it, given that Ken is or was a research manager at OpenAI?

Here is Ken talking about the concept

https://www.youtube.com/watch?v=lhYGXYeMq_E

https://www.youtube.com/watch?v=dXQPL9GooyI

“ collaboration can sometimes thwart innovation by tacitly forcing its participants into an objective-driven mindset.”

Re: Lessons from history's greatest R&D labs

#32

Post by jph00 »

gradschoolfail wrote: post #30
publicdaniel wrote: post #14

@Jeremy, have you ever encountered Ken Stanley’s book “Why Greatness Cannot be Planned: The Myth of the Objective”? If you’re not familiar with him, he was the guy that invented the NEAT algorithm, Novelty Search, etc. In his book he talks about stepping stones and following what’s “interesting” to individuals. It seems like Answer.AI is focused on applied engineering, but any thoughts on this type of approach from a…

This is funnily relevant because as far as I understand Ken is or was a research manager at OpenAI, and as outlined in the article, Answer.AI is trying not to be OpenAI.

I should caveat this by saying I've only read summaries of the book, not the book itself. My understanding of it is that they view setting ambitious objectives as potentially limiting progress, and instead promote shorter-term novelty-seeking approaches.

This is certainly how we do things at Answer.AI -- we hire people that are passionate tinkerers, and encourage a playful and spontaneous approach. That doesn't mean there's no coordination or long-term goal, but rather that we view these short-term approaches as being a good way to make progress.

Re: Lessons from history's greatest R&D labs

#33

Post by systems_glitch »

eries wrote: post #2

As some of you probably know, I spent a number of years working with GE, which included plenty of time at the legendary GE Research lab in Niskayuna. So it was a special thrill to see this piece connecting Answer.AI to the long history of R&D labs. Our ideas about R&D are kind of out of fashion in our current age, but I hope this says more about the age than it does about the quality of the ideas. Happy to answer que…

Drove Erie Boulevard and survived to tell the tale.

Re: Lessons from history's greatest R&D labs

#34

Post by egillia3 »

Animats wrote: post #22

The classic on the early electrical manufacturers is "The electrical manufacturers 1875-1900".[1] This is the Harvard Business School take on Edison. The business plan for his first power plant is in there. (He way underestimated the payback period, but it was only a few years, so it worked out.) There's also "Men and Volts"[2], a history of the early days of General Electric. Which, I think, is where this article go…

Hey it’s Eric (the author). I talk quite a bit in the article about how to make the lessons of places like Bell and GE work even if you’re not attached to a large lab.

Repurposing Bell-style systems engineers to isolate white hot problems is one example. Another is the general BBN-style approach which worked for them as a stand-alone R&D firm. I have stand alone pieces where I explore both of those quite a bit.

In general, I don’t think the concept of the playbooks of the great industrial R&D labs not working in firms un-attached to large firms holds much water.

Re: Lessons from history's greatest R&D labs

#35

Post by egillia3 »

publicdaniel wrote: post #14

@Jeremy, have you ever encountered Ken Stanley’s book “Why Greatness Cannot be Planned: The Myth of the Objective”? If you’re not familiar with him, he was the guy that invented the NEAT algorithm, Novelty Search, etc. In his book he talks about stepping stones and following what’s “interesting” to individuals. It seems like Answer.AI is focused on applied engineering, but any thoughts on this type of approach from a…

Hey! It’s Eric (the author). To the author of this comment, I’d say that the use of “long leash within a narrow fence” (which directed Langmuir’s work) or “circumscribed freedom” (which directed much Bell work) is generally compatible with researcher interests.

As I talk about in the article, Langmuir was able to pick from a bunch of problems in his wheelhouse…there were just conditions. And those conditions meant whatever area he picked might come with a high willingness to spend from GE! And if his work yielded results GE would have a way to quickly deploy the knowledge. All of which is great. To put his work in a box with what the Coolidge-types did is probably unfair. He was following curiosity under constraints, that’s all.

That is not to say all basic research roles in the world should look like that. But it makes sense given most basic researchers don’t fully understand which of all the problems they could happily pursue are actually most useful to industry. MIT professors of the early 1900s used to source research problems somewhat similarly.

Hopefully all of that helps a bit!

Re: Lessons from history's greatest R&D labs

#36

Post by RcouF1uZ4gsC »

> Legally, Answer.AI is a company. But in practice, it might hover somewhere between a lab and a normal “profit-maximizing firm” — as was the case with Edison’s lab. The founders seem perfectly content to pursue high-risk projects that might lead to failures or lack of revenue for quite a while. In saying this, I do not mean to imply they are content to light money on fire doing research with no chance of a return. Rather, they hope to fund a body of research projects that ideally have positive ROI in the long term. They are just not overly concerned with short-term revenue creation.

This may be the biggest weakness. One things the greatest R&D labs had was a big cash cow that paid the bills. Bell Labs was funded by AT&T’s massive phone monopoly. PARC was funded by Xerox’ massive business. Lockheed Martin’s Skunkworks were paid by massive DoD contracts.

Re: Lessons from history's greatest R&D labs

#37

Post by Mistletoe »

The name is bad and the name is everything in tech. I thought it was some answers.com AI spinoff. This is far too generic and a google search of it is a nightmare. You don't buy your books on books.com, you buy them on amazon.com, you don't buy your pet supplies on pets.com, you buy them on chewy.com.

Re: Lessons from history's greatest R&D labs

#38

Post by gradschoolfail »

jph00 wrote: post #32
gradschoolfail wrote: post #30

Earlier quoted context omitted.

This is funnily relevant because as far as I understand Ken is or was a research manager at OpenAI, and as outlined in the article, Answer.AI is trying not to be OpenAI.

I should caveat this by saying I've only read summaries of the book, not the book itself. My understanding of it is that they view setting ambitious objectives as potentially limiting progress, and instead promote shorter-term novelty-seeking approaches. This is certainly how we do things at Answer.AI -- we hire people that are passionate tinkerers, and encourage a playful and spontaneous approach. That doesn't mean…

Thanks! That nicely dovetails with my understnding. BTW, the two case studies at the end of the book I found to be helpful in analyzing the main ideas!

Re: Lessons from history's greatest R&D labs

#39

Post by class3shock »

This makes me nostalgic for something that I never had and doesn't seem to exist anymore, labs unburdened by either the red tape of government or academia, or alternately, the pressure for results and profits that many startups seem to slaved to. Is there a 21st century equivalent of Bell Labs out there somewhere? Asking for a friend.

Re: Lessons from history's greatest R&D labs

#40

Post by tikkun »

jph00 wrote: post #26
tikkun wrote: post #6

Earlier quoted context omitted.

Awesome! What sorts of products is your lab working on?

Currently we're working on low-resource fine-tuning research (i.e. train larger models on smaller cheaper GPUs), and looking into applications in the education and legal spaces. We're also starting to look at intersections between long-tail image recognition and language models.

Cool - thanks for answering!
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