Lessons from history's greatest R&D labs
answer.ai
answer.ai
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 chance to spark a rush of emboldened researchers and engineers to found small research firms, leveraging the models of the once-great dragons of American industrial R&D."
I'm happy to answer any questions you have about our experiment, and my co-founder Eric Ries (@eries) is around too. (Note that there are 2 Erics mentioned here -- that can get confusing!) By way of background, Eric Ries is the creator of the "Lean Startup", coined the term "Minimal Viable Product", and created the Long Term Stock Exchange, and I'm the co-founder of fast.ai, Enlitic, Kaggle, FastMail, and Optimal Decisions Group.
I think it would be awesome to be able to use GPUs from second-hand crypto mining rigs for cheaper fine-tuning research.
Good luck! As an enthusiast who loves The Lean Startup and who recently started playing around with LLMs, I'm super stoked about Answer.AI
I'll be rooting for you to succeed in this endeavor. I used to visit IBM ARC when I was a kid, and to my mind the academic environment is not quite the same. But as you know we really have not seen corporate R and D recover from the peaks it attained over fifty years ago.
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.”
How do you plan to research potential problems to solve?
Would it be possible to publish and discuss those to-be-solved problems, so that hobbyists can also try their luck at solving them?
Initially, I thought that Kaggle competitions would be a great way to get the industry's problems into the hands of motivated problem-solvers. But I don't think I've ever seen a large car manufacturer (for example) as Kaggle competition host. So it looks like something is holding companies back.
How are you thinking about the role of patenting at Answer.AI? How about handling tech transfer issues with universities?
In terms of tech transfer, Jeremy has quite a bit of experience with collaborating with the best academic labs, especially in machine learning, so I expect we will do a lot of that kind of partnering.
Appreciate your writing by the way!
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 Research perspective?
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.
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!
The big corporate labs were part of far larger manufacturing companies. It's not clear that a standalone lab can function in the same way.
[1] https://www.degruyter.com/document/doi/10.4159/harvard.97806...
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.
I'm going to have to look at some of your other material.
Experimentation is different than other research or engineering but I think anything that amounts to a "system" can benefit from a systems problem solver who can perform as needed across the whole system.
Any organization is fortunate to have a person who can go without routine or typical workdays and do this.
It does seem like the bigger companies which have the most clearly defined roles can eventually get by on momentum without having anyone at all in a creative problem-solving position.
OTOH a small outfit can deploy unique problem-solving ability using only a handful of people that many corporations have none of. So the "very, very best people" may be what can get the momentum going to begin with given the right opportunity.
You wouldn't want it to function the same way as a modern corporate lab. Those are already making as much progress as they can by now.
Something worthwhile to do in a smaller organization is things that bigger labs need but don't do.
If you do it "right" a single-handed individual can make more promising creative progress than a whole team of corporate researchers can often end up with, but you need some pretty good breadth of innovation.
If you look carefully at the historical illustration, you may notice a pipe organ is the central device in the picture.
In the natural science lab I always liked to have different instruments that attract the attention of different types of visitors at different times.
And some instruments that are only developed or used in the presence of no visitors at all.
We also just launched Unbelievable Labs (unbelievablelabs.com), with the ambition to combine Physics-oriented venture building with applied research. It would be great to form a network of these to emulate some of the scale that Bell Labs had due to monopoly funding.
There's a lot to be said for just exploring the combinatorial space of possibility in even a naive or brute force manner.
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.