Ben Reinhardt Profile picture
Sep 23, 2022 16 tweets 3 min read Read on X
I went to the International Manufacturing Technology Show (IMTS) last week.

It's a ginormous trade show devoted to CNC mills, grinders, robot arms, metrology, CAD, 3D printing etc.

Felt like a new world (especially compared to Twitter) so I thought to share what struck me

1/
The scale was absolutely huge -- not just the conference space (which we logged miles walking around) but the tools themselves: robot arms that could easily lift cars and combination 3D printing and subtractive manufacturing gantries the size of a warehouse.

2/ Image
It was delightfully object level. Nobody talking about transforming human interaction or web3 enabled AI for industry 4.0* — they’re like “this tool cuts metal really well — look at it cutting metal. Here is a piece it just made”

*Ok, almost nobody: there were some startups

3/
There's such a disconnect between how impressive/important a tool is and its market value.

Companies that are doing crazy things like building-size gantries that can both deposit material and mill it out with five-axis heads are only doing yearly revenues of $50M

4/
More on disconnect between impressive/imporant and market value:

Some of the top machine tools companies -- these are the folks that enable basically the entire modern manufacturing stack -- have market caps of ~$400M.

5/
The volumes in this world were strikingly low compared to either consumer goods or software: really good numbers look like moving several hundred machines per year.

5/
There are all these incredible capabilities that seem underused — from additive manufacturing to seamlessly bonded layers of dissimilar metals to ceramic-surfaced metals.

Yet, most people at the show still make things by removing metal from a big piece of metal

6/
My (naïve) hunch is that a big part of why these capabilities aren't used widely to do crazy new things is that it's hard for people to internalize the affordances of these techniques and imagine what they could do with them.

This is why I'm so bullish on easy-to-use models

7/
Manufacturing is perceived as a slow, crusty industry, but it feels like big companies in this world actually innovate on their core products far more than the Googles and even Apples of the world.

Likely because their business model is: you give me money, I give you thing

8/
The demographics were, as you might suspect, very different from either academia or tech: the sales reps skewed towards the grey and (there's no way to put it delicately) most people I saw would look very out of place in coastal metropolitan areas.

9/
CNC user interfaces seem horrible. I'm sure for people who have used them for years they're great, but I suspect there are better ways to do this.

A+ for lots of physical buttons though.

10/ Image
A few more after going through my notes ...

The structure of the industry is fascinating: machining primarily revolves around small shops.

There are ~70,000 of them in the US, which feels small when you think about the market for any specific machine being a fraction of that.
There are dominant companies that people at the show talk about the way folks in tech talk about Google or Microsoft that I'd never heard of:

Hexagon
Fanuc

etc.

12/
The idea of a "digital twin" was everywhere -- the idea of a software representation of a part or system that is updated throughout the manufacturing process.

I would just call this "simulation and modeling coupled with measurement" but 🤷‍♂️

13/
I have yet to verify this, but someone at a company that was doing multimaterial 3D printing claimed that good multimaterial CAD software doesn't exist.

Seems like a big hole if true.

14/
In addition to the companies not being located in places we associated with technology, a lot of the university research being done in the area was happening outside of your traditional coastal unis:

University of Arkansas
RPI
University of Tennessee

etc.

15/

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More from @Ben_Reinhardt

Feb 15, 2023
1/ For the past year, we’ve been building a new research organization:

Speculative Technologies (@spec__tech) exists to create an abundant, wonder-filled future by unlocking powerful materials and manufacturing technologies that don’t have a home in other institutions.
2/ @Spec__Tech runs research programs across multiple organizations to perform surgical interventions to unlock technologies.

We currently have two active programs, with others in the works. (More below!)

Read our launch essay here:
spec.tech/library/introd…
3/ The future is full of possibilities!

Regardless of whether we’ve picked innovation’s “low-hanging fruit” or even whether invention and discovery has slowed down at all, we can do dramatically better.
Read 17 tweets
Oct 7, 2022
It's been out for a while but I recently read through the 2018 Faculty Workload Survey -- it's kind of wild.

The survey digs into how much time federal grant recipients spend getting and administering those grants.

To start, just look at these numbers: Image
Image
The (potentially made up but) funny/sad story I read into the response rate dropping while the time spent keeps going up is that PIs are like "why would I fill out the survey this time when you clearly didn't do anything useful in response to the last one?" Image
Read 11 tweets
Jul 24, 2022
1/ Recently finished "The Genesis of Technoscientific Revolutions" by Narayanmurti and Tsao.

The book lives up to its grand name! It feels like a (fuzzy) image of the elephant that is "how research works" where everybody else is feeling a snake or a tree.

BOOK REPORT THREAD🧵
2/ The authors (who I'll refer to as N+T) call out the post-WWII paradigm from the beginning. I'm not sure that the whole thing can be laid at Bush's feet -- I strong agree that the basic/applied <> science/technology distinction is holding us back.
This image, while it looks like something from @DefenseCharts, actually does summarize the book -- the first half outlines the nature of research and the second half is about how to nurture research.

It plays to my biases: describing *how* research works -> better research
Read 59 tweets
Jun 4, 2022
Thinking about how the authoritativeness of a medium affects how people engage with it.

The hunch is that people will give more real feedback and riff on a sketch or google doc than a beautiful illustrator-crafted graphic or PDF.
Heard a story about a big-deal professor who spent *more* time on a sketch for a presentation than he would have on a nice-looking graphic to try to create discussion.
I've also run into the opposite, where I had an almost-finished thing but because people were looking at it in google docs, they went straight to suggesting sweeping structural changes.
Read 4 tweets
May 12, 2022
It’s common wisdom that startups are a powerful structure for researchy ideas to become reality.

SpaceX, Genentech, etc

But startup constraints can also be the kiss of death for those ideas.

When should an idea that smells like research be a startup?

parpa.substack.com/p/when-should-…
The nature of research and uncertainty make it impossible to create hard and fast rules, but there are questions that hint at the level of uncertainty in an idea.

More answers that lean towards “No” suggest that a startup might ultimately hamstring the ideas ultimate success:
1/8 Can the desired output be sold?
Read 10 tweets
Mar 29, 2022
Realized that institutions use one of (roughly) two ways to acquire new ideas:

Hunting and Farming

A quick thread to unpack the framework and argue that the world has swung a bit too much towards hunting ideas instead of farming them.

1/
Organizations that hunt ideas go out in the world assuming that someone external to the organization has come up with the idea. “Funding talent", grants, investing, and portfolios are all hunting strategies.

2/
Organizations that farm ideas try to create ideas internally. Program design and research labs are examples of farming strategies.

3/
Read 16 tweets

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