Aug 2, 2022
William Bonvillian does a deep dive about his decades of research on how DARPA works and his more recent work on advanced manufacturing.
William is a Lecturer at MIT and the Senior Director of Special Projects,at MIT’s Office of Digital Learning. Before joining MIT he spent almost two decades as a senior policy advisor for the US senate. He’s also published many papers and a detailed book exploring the DARPA model.
In this podcast, William Bonvillian, and I do a deep dive about his decades of research about how DARPA works and his more recent work on advanced manufacturing. Well humans, a lecturer at MIT and a senior director of special projects at MIT is office of digital learning. Before joining MIT. He spent almost two decades as a senior policy advisor for the us Senate.
He's published many papers and a detailed book exploring the DARPA model. I've wanted [00:01:35] to compare notes with him for years. And it was a pleasure. And an honor to finally catch up with him. Here's my conversation with William
[00:01:42] Ben: The place that I I'd love to start off is how did you get interested in, in DARPA and the DARPA model in the first place you've been writing about it for more than a decade now. And, and you're probably one of the, the foremost people who who've explored it.
So how'd you get there in the first.
[00:01:58] William: You know, I, I I worked for the us Senate as a advisor in the Senate for for about 15 years before coming to MIT then. And I I worked for a us Senator who is on the on the armed services committee. And so I began doing a substantial amount of that staffing, given my interest in science technology, R and D and you know, got early contact with DARPA with some of DARPA's both program managers and the DARPA directors, and kind of got to know the agency that way spent some time with them over in their [00:02:35] offices.
You know, really kind of got to know the program and began to realize what a, what a dynamic force it was. And, you know, we're talking 20, 20 plus years ago when frankly DARPA was a lot less known than it is now. So yeah, just like you know, kind of suddenly finding this, this Jewelbox varied in the.
It was it was a real discovery for me and I became very, very interested in the, kind of the model they had, which was so different than the other federal R and D agencies.
[00:03:05] Ben: Yeah. And, and actually um, It sort of in your mind, what is the for, for people who I, I think tend to see different federal agencies that give money to researchers as, as all being in the same bucket.
What, what do you, what would you describe the difference between DARPA and the NSF as being
[00:03:24] William: well? I mean, there's a big difference. So the NSF model is to support basic research. And they have, you know, the equivalent of project [00:03:35] managers there and they, they don't do the selecting of the research projects.
Instead they queue up applicants for funds and then they supervise a peer review process. Of experts, you know, largely from academia who evaluate, you know, a host of proposals in a, in a given R and D area mm-hmm and and make valuations as to which ones would qualify. What are the kind of best most competitive applicants for NSFs basic research.
So DARPA's got a different project going on, so it doesn't work from the bottom up. It, it has strong program managers who are in effect kind of empowered to go out and create new things. So they're not just, you know, responding to. Grant applications for basic research, they come into DARPA and develop a [00:04:35] vision of a new breakthrough technology area.
They wanna stand up. And so it's, and there's no peer review here. It's really, you hire talented program managers. And you unleash them, you turn them loose, you empower them to go out and find the best work that's going on in the country. And that's, that can be from, from universities and often ends in this breakthrough technology area they've identified.
But it also could be from comp companies, often smaller companies and typically they'll construct kind of a hybrid model where they've got academics. Companies working on a project, the companies are already always oriented to getting the technology out the door. Right. Cause they have to survive, but the researchers are often in touch with some of the more breakthrough capabilities behind the research.
So bringing those two together is something that the program manager at DARPA does. So while at [00:05:35] NSF, the program manager equivalent, you know, their big job is getting grant out the door and supervising a complex selection process by committee mm-hmm . The role of the, of the ARPA of the, of the DARPA program manager is selecting the award winners is just the beginning of the job.
Then in effect you move into their home, right? You work with them on an ongoing basis. DARPA program managers are spending at least one third of their time on the road, linking up with their, you know, with their grantees, the folks they've contracted with sort of helping them along in the process. And then, you know, the typically fund a group of research awards in an area they'll also work on putting together kind of a thinking community amongst those award winners.
Contract winners so that they begin to share their best ideas. And that's not a, that's not easy, right? Yeah. Yeah. If you're an academic [00:06:35] or you, a company, you stuff, you trading ideas is a complicated process, but that's one of the tasks. That the DARPA program manager has, is to really build these thinking communities around problems.
And that's what they that's what they're driven to do. So it's a very, very different situation. This is, this is the different world here that Dar is created
[00:07:01] Ben: and, and sort of actually to, to, to click on The, the how DARPA program managers interact with ideas. Do you have a sense of how they incentivize that idea sharing?
Is it just the, the concept that if you share these ideas, they might get funded in a way that they wouldn't or like what, how do they sort of construct that That trust that people for people could actually be sharing those ideas.
[00:07:28] William: Yeah. In, in some ways then it starts out at an all stage. So before, you know, a new [00:07:35] program manager arrives at DARPA and often they'll have, I mean, this could be ape.
It could be I RPA, which worked slightly different ways, but similar kind of approach RPE is our energy DARPA. I, APA is our intelligence Dar. Right. And then soon we'll have a help DARPA, which has now been funded. Yeah. I wanna
[00:07:55] Ben: your opinion on that later.
[00:07:57] William: Okay. Well, we're working away on this model here.
You know, you hire a program manager and you hire somebody. Who's gonna be, you know, talent and dynamic and kind of entrepreneurial and standing up a new program. They get the DARPA and they begin to work on this new technology area. And a requirement of DARPA is that really be a breakthrough. They don't wanna fund incremental work that somebody else may be doing.
They wanna find a new, new territory. That's their job, revolutionary breakthroughs. To get there. They'll often convene workshops, 1, 2, 3 workshops with some of the best thinkers around the country, including people, [00:08:35] people who may be applying for the funding, but they'll, they'll look for the best people bringing together and get, you know, a day long process going um, often in several different locations to kind of think through.
Technology advance opportunity. How, how it might shape up what might contribute, how might you organize it? What research might go into it, what research areas and that kind of begins the kind of thinking process of building a community around a problem. And then they'll make grant awards. And then similarly, they're gonna be frequently convening this group and everybody can sit on their hands and keep their mouth shut.
But you know, that's not often the way technologists work. They'll get into a problem and start wanting to share ideas and brainstorm. And that's, that's typically what then takes place and part of the job of the, of. Partner manager DARPA is to really encourage that kind of dialogue and get a lot of ideas on the table and really promote it.
[00:09:34] Ben: [00:09:35] And, and then also with, with those ideas do, do you have, like, in your, your having looked at this so much, do you have a sense of how much there there's this tension? You know, it's like people generally do the best research when they feel a lot of ownership over their own ideas and they feel like they're, they're really working on.
The, the thing that they want to work on. But then at the same time to sort of for, for, for the, a project to play into a broader program, you often need to sort of adjust ideas towards sort of a, a bigger system or a bigger goal. Do you have, do you have an idea of how much Program managers sort of shape what people are working on versus just sort of enabling people to work on things that they would want to work on.
[00:10:24] William: Yeah. The program manager in communication with DARPA's office directors and director. Right, right. So it's a very flat organization. You know, and [00:10:35] there'll be an office director and a number of program managers working with that office director. For example in the field of, of biological technologies, a fairly new DARPA office set up about a decade ago.
Yeah. You know, there'll be a group of DARPA program managers with expertise in that field and they will often have often a combination of experiences. They'll have some company experience as well as some academic research experience that they're kind of walking on both sides. They'll come into DARPA often with some ideas about things they want to pursue, right.
And then they'll start the whittle down process to get after what they really wanna do. And that's, that's a very, very critical stage. They'll do it often in dialogue with fellow program managers at DARPA who will contribute ideas and often with their office. Who kind of oversees the portfolio and we can feed that DARPA program manager into other areas of expertise around DARPA.
So coming up with a big breakthrough idea, then [00:11:35] you test it out in these workshops, as I mentioned, right. As well as in dialogue with your colleagues at DARPA. And then if it looks like it's gonna work, then you can move it rapidly to the approval process. But DARPA is, you know, I mean, it's what its name says.
It's advanced research projects agency. So it's not just doing research. It very much wants to do projects. And you know, it's an agency and it's a defense agency, so they're gonna be, have to be related to the defense sector. Although there's often spill over into huge areas of civilian economy, like in the it world really pioneer a lot.
But essentially the big idea to pursue that's being developed by the program manager and refined by the program manager. And then they'll put out, you know, often what's called a broad area announcement, a BIA. We wanna get a technology that will do this. Right. Right. Give us your best [00:12:35] ideas. And put this out, this broad area announcement out and get people to start applying.
And if it's, if the area is somewhat iffy, they can, you know, proceed with smaller awards to see how it kind of tests out rather than going into a full, larger, larger award process with kind of seedlings they'll plant. So there's a variety of mechanisms that it uses, but getting that big breakthrough revolution or idea is the key job at a program manager.
And then they'll, they're empowered to go out and do it. And look, Dora's very cooperative. The program managers really work with each other. Yeah. But in addition, it's competitive and everybody knows whose technology is getting ahead, whose technology is moving out and what breakthroughs it might lead to.
So there's a certain amount of competition amongst the program managers too, as to how their revolution is coming along. Nice.
[00:13:28] Ben: And, and then sort of to, to go sort of like one level down the hierarchy, if you will. When [00:13:35] they put out these, these BAAs do you have a sense for, of how often the performers will sort of either shift their focus to, to, towards a APA program or like how much sort of haggling is there between the performer and the, the program manager in terms of Sort of finding this balance between work that supports the, the broader program goals and work that sort of supports a researcher's already existing agenda.
Right. Because, you know, it's like people in their labs, they, they sort of have this, the things that they're pursuing and maybe they're, they're like sort of roughly in the same direction as a program, but need to be, need to be shifted.
[00:14:20] William: Yeah. It's, you know, the role of the program manager is to put out a new technological vision, you know, some kind of new breakthrough territory.
That's gonna really be a very significant [00:14:35] advance that can be implemented. It's gonna be applied. It's not discovery. It's implementation that they're oriented to. They want to create a new thing that can be implemented. So they're gonna put the vision out there and look the evaluation process. Is gonna look hard at whether or not this exact question you're raising.
It's gonna look hard at whether or not the, the applicant researcher is kind of doing their own thing or can actually contribute to the, to the implementation of the vision. And that's gonna be the cutoff. Will it serve the vision or not? And if it's not, it's not gonna get the award. So look, that's an issue with DARPA.
DARPA is going at their particular technology visions. NSF will fund, you know, it's driven by the applicants. They will think of ideas they wanna pursue and see if they can get NSF funding for it at DARPA's the other way around the program manager has vision [00:15:35] and then sees who's willing to pursue that vision with him or her.
Yeah. Right. So it's a, it's more of a, I won't say top down because DARPA's very collaborative, but it's more of a top down approach than as opposed to NSF, which is bottom up. They're going for technology visions, not to see what neat stuff is out there. right.
[00:15:56] Ben: Yeah. And just to, to shift a little bit you, you mentioned I a RPA and ARPA, E as, as other government agencies that, that used the same model you wrote an article in 2011 about ARPA E and, and I I'm interested in.
What like how you think that it has played out over, over the past decade? Like how, like how well do you think that they, they have implemented the model? Do you think that it, it does work there. And like what other places do you think, I guess do, do you have a sense of like how to know whether a DARPA, the DARPA [00:16:35] model is applicable to an area more broadly?
[00:16:39] William: Yeah. I mean, look that's, and that's kind of a, that's kind of a key question, you know, if you wanna do a, if you wanna do a DARPA, like thing, is it gonna work in the territory that you wanna work in? But let's, let's look at this energy issue. You know, I was involved in, you know, some of the early discussions about creating an, a.
For for energy and, you know, the net result of that was that Congressman named bar Gordon led an effort on the house science committee to really create an ARPA energy. And, and that approach had been recommended by a national academies committee. And it you know, it seemed to make a term on a sense.
So what was going on in energy at the time of formulation of this. Like the 2007 rough time period. You know, 2008, what was happening was that there was significant amount of investment that was moving from, in, [00:17:35] in moving in venture capital towards new energy, clean tech technologies. So the venture capital sector in that timetable was ramping.
It's 2006, 2007 time period was ramping up its venture funding and Cleantech. And that's when AR was being proposed and consider. So it looks like it looked to us, looks everybody, like there would be a way of doing the scale up. Right. In other words, it's not enough just to have, you know, Cool things that come out of an agency, you need to implement the technology.
So who's gonna implement it. Right. Who's gonna do that scale up into actual implementation. And that's a very key underlying issue to consider when you're trying to set up a DARPA model. DARPA has the advantage of a huge defense procurement budget. So, right. It can, you know, it can formulate a new technology breakthrough, like [00:18:35] saying stealth, right.
Mm-hmm or in you know, UAVs and drones. And then it can turn to the defense department that will spend procuring money to actually stand up the model on a good day. Cause that doesn't always happen. doesn't always go. Right. But, but it's there, what's the scale up model gonna be for energy?
Well, we thought there was gonna be venture capital money to scale up Cleantech. And then the bottom fell out of the Cleantech venture funding side in the 2008, 2009 time table and venture money really pulled out. So, you know, in 2009 is. Harpa E first received it, significant early funding. Got an appropriation of 400 million had been authorized for the science committee and then it got an appropriation.
Could you say that again? And the there was a big risk there. So look, RPE was then created, had a very dynamic leader named Maju. Who's now at Stanford leading the energy initiatives there. Aroon [00:19:35] saw the challenge and he frankly rose to it. So if they weren't gonna get this, these technologies scaled up through venture capital, like everybody assumed would work.
How are they gonna do scale up? So who did a whole series of very creative things? There was some venture left. So we maintained, you know, good relations with the venture world. But also with the corporate world, because there were a lot of corporations that were interested in kind of moving in some of these directions.
If these new technologies complimented technologies, they were already pursuing, right. So room created this annual. RPE summit where all of its award winners would, you know, present their technologies and, you know, fabulous, you know, presentations and booths all around this conference. It rapidly became the leading energy technology conference in the us wide widely attended by thousands of people.
Venture capital may not be funding much, but they were there. But more importantly, [00:20:35] companies were there. And, you know, looking at what these technologies were to see how they could get to get stood up. So that was a way of exposing what was RPE was doing in a really big way. Right. Right.
Another approach they tried was very successfully was to create what they call the tech to market group. So in addition to your program manager at RPE, You stand up a new project and assigned to that project would be somebody with expertise in the commercialization of technology by whatever route the financing might be obtained.
And they brought in a series of experts who had done this, who knew venture, who knew startups, who also knew federal government contracting in case the feds were gonna buy this stuff, particularly a D O D and this tech to market group became, you know, that was part of the discipline of standing up a project was to really make sure there was gonna be a pathway to commercialization.
In fact, that approach. [00:21:35] Was so successful and DARPA for a number of years later hired away RPE tech tech to tech, to market director to run and set up its own tech to market program. Right. Which was, you know, the, the new child is just taught the parent a lesson here is what the, what the point was.
So there's now a tech to market group at, at DARPA as well. Another approach they did. Was, you know, there's a, there's a substantial amount of other R and D funding, more incrementally oriented at the department of energy. The E E R E program, but other programs in different energy technology areas will support, you know, companies, company research, as well as academic research.
So RP built very good ties. With E E R E the applied research wing for renewable energy and other applied research, arms of department of energy so that they could provide the kind of next stage in funding. So you do the [00:22:35] prototyping through APA E and then some of the scale up could occur through through.
Some of the applied agencies within the department of department of energy. So that was, there were other things they attempted as well. But those were some of the most creative and, you know, they got around this problem. Now there's an underlying issue in energy technology and, and it's true for many.
DARPA like approaches the technologies don't stand up overnight. In other words, you don't do your applied work and end up with an early prototype and expect it to become a major business within two weeks. Right. Right. That process can take 10 years or 15 years, particularly in the hard tech area.
Right. Anything that requires manufacturing? Yeah. Energy technology stand up. That's a, that's a 10 to 15 year process in the United States. So RPS only been around what, you know, 11, 12 years, something like that. They're still, you know, their technology are still emerging. They have made a lot of [00:23:35] technology contributions in a lot of technology areas that have helped expand opportunity spaces.
Yeah. In many interesting areas. So they really helped, I believe. In identifying kind of new territories where there can be advances. But you know, have we transformed the world and solve climate change because of RPE yet? No, no, that's, that's a longer term project. So you have to have that expectation when you look at these different story of software and in some it sectors, DARPAs played a huge role in the evolution of those.
Those could be shorter. Yeah, but anything really in the heart tech area is gonna take a much more extended period. Yeah. So you have to be patient. The politicians can't expect change in two weeks or two years. They're gonna have to be a little more patient.
[00:24:24] Ben: And, and another sort of just issue that I, I, I'm not sure is, is a real thing, but that I've noticed is that a difference between DARPA and RPE is that [00:24:35] with, with DARPA, when you have the, the DOD acquiring technologies, they can sort of gather together all the different projects that were in, in, within a program and sort of integrate them into an entire system where.
When you have a, an ape E program ending there's, there are a number of different projects, but there, there, isn't a great way of sort of integrating all the different pieces of a program. Is that an accurate assessment or am I, am I off base on that?
[00:25:07] William: No, Ben, I think that's, I think that's accurate. I know.
I mean the part of energy doesn't have a procurement budget. Right, right. Like the defense department does, it's not spending 700 billion a year to make things. So it can't play that system scale up kind of role in the kind of way the defense department does. Now. Look, I, I don't wanna overstate this because DARPA has definitely stood up technologies outside of defense, above procurement.
So [00:25:35] most of its it revolution stuff. Where it played a, you know, big role, for example, as you know, in the development of desktop computing and, and a huge role in, in supporting the internet development of the internet. Absolutely. You know, those got stood up, not particularly through DOD, they got stood up in the civilian sector.
So DARPA, you know, works on both sides of the street here. If it appears advantageous to, to stand it up on the civilian side, let it scale up and then the can buy it. Right. Mm-hmm , it'll do that. But on the other hand, there's, you know, there's very critical areas. Defense's gonna have to be a lead on like, you know, GPS, for example and really scale up the system.
And then it can be shifted over to serve a dual use.
[00:26:22] Ben: And, and then, so, so sort of like looking forward to the, the future how do you see all these considerations playing out with with ARPA H the, the health ARPA that is, I think been approved, [00:26:35] but hasn't actually started doing anything yet.
[00:26:39] William: Yeah.
It's got money appropriated. So you, and it's a priority of the. Of the current administration. So, you know, I believe it's gonna happen here. I mean, look, you know, there, there's some things that just need to be in place for a DARPA model to work well, mm-hmm, scale up is one that we've talked about and, you know, there is a pathway to scale up for new breakthroughs in in, you know, biomedicine and and, and medical device.
We've got strong venture capital support in that area for a series of historical reasons. So that follow one pickup in many fields, right, is gonna be is gonna be available in many biomedical kind of fields. Know, there are issues. There, there was a big debate about an issue that I'll call island bridge, right?
What you want, what you wanna do [00:27:35] with your DARPA is you want to put your, your DARPA team on an island. You wanna protect that island and keep the bureaucracy away from it. Right? Let 'em do their thing out there and do great stuff. And don't let the bureaucracy, the suits interfere with them. Yeah. On the other hand, they really need a bridge back to the mainland to get their technologies scaled up.
So DARPA, for example, reports to the, in effect to the secretary defense and can undertake projects that the secretary defense can then, you know, in effect force the military services to pick up or, you know, use, use budgeting authority to encourage the military services to pick up DARPA has it's an island.
It's got a separate building. It's about five miles away from the Pentagon. It's got its team there. It's got its own established culture. But then it's got a bridge back to the mainland, through the secretary of defense, into the defense procurement system. What's gonna be ARPA HS [00:28:35] relationship there.
So there've been a lot of. About where to put ARPA-h do you put it in NIH, which is another, like NSF, another peer review, basic research agencies by far the biggest it's got its own culture and that culture frankly, is not a DARPA culture, right? That's not a strong program manager culture. It's a peer review culture.
Do you really want to put your DARPA like thing within NIH? And within that NIH culture on the other hand, where else are you gonna put it? Right. So at the moment we've gotta compromise the ARPA H is gonna report to the secretary of HHS, but the secretary of HHS. Doesn't have money to scale up new technologies to speak up.
Right. Right. There is an assistant secretary of health who oversees BARDA and some other entities. So, you know, that's, that's a possibility. But NIH has got a lot of ongoing research going on. [00:29:35] There could be a lot of following research that came out of NIH, NIH. So it's, this is a challenge. This is a challenge to set up the right kind of island bridge model for this new ARPA H.
We've kind of got a compromise there at the moment. It will be located somewhere on the NIH campus. Hopefully in a separate, you know, building or location. Yeah. And then report to the secondary of HHS. But how are these, how is this scale up gonna work here? What's the bridge to the mainland gonna be and will it be protected enough from a very different culture at NIH?
With lots of look, lots of jealousies, you know, when RPE was created for energy, the labs saw the, you know, there's 14 major energy labs, right? They saw RPE as a big competitor for funding that was gonna take money away from the labs. It took a long time to build those relationships so that the lab saw RPE, not as a competitor, but as a way in which their stuff could help.
Move ahead. [00:30:35] Yeah. Uh, And that took a while to kind of sort out. So there's a series of these issues that are gonna have to get well thought through for for this new ARPA H that opening culture is absolutely critical. Say more about that and it, yeah. In other words, the culture of strong program managers that are empowered and ready to pursue breakthrough technologies.
That's the heart of the darker culture, that culture locks in, in the opening months. If you get it wrong, it's very hard to fix it later. You really can't go back. Yeah. So hiring the right people, having a DARPA director who understands, for example, an ARPA age director who really understands the DARPA model and how to implement it that's gonna be key in setting that culture upright to the.
[00:31:23] Ben: Yeah. And, and, and you've mentioned a, a couple of times the, sort of the effect of physical location on, on the culture. Have you, have you seen that, that, like where [00:31:35] people are physically located really like have an effect on, on resulting cultures?
[00:31:41] William: Yeah. I mean, look, obviously post pandemic, we're exploring remote work a lot.
Yes. But there's a lot to be said for getting your, your thinking team in one place where they're bouncing off ideas, each other with each other all the time. Yeah. Where they're exposed and, and critiqued and evaluated. And they just can't see each other, remind each other kind of all the time. So creating that island.
With your talent on it so that they can interact and, and inevitably work pretty intensively together. Yeah. That's a, you know, I think that's a, something of a prerequisite to getting these kinds of organizations together. You've gotta build that earliest free to core and that early culture that that's very empowered.
[00:32:30] Ben: And, and so just sort of to, to take, to take a, a right turn [00:32:35] and, and talk a little bit about your, your work on, on advanced manufacturing. This is, this is an area I personally know much less about. But like, I guess one, one sort of basic thing is I think a lot of people Like don't have a good sense of what sort of advanced manufacturing actually means.
Like what, what is, what is, what, what, what does advanced actually entail in this situation?
[00:33:00] William: Yeah, let me, let me tell you know, a little bit of a story here. Yeah, please. The there are a suite of new technologies. Corresponding processes that are kind of emerging, right. And some have, you know, some have emerged.
Some are earlier at an earlier stage but areas like robotics, you know, 3d printing, additive manufacturing obviously digital digital production technologies. Where it is built into kind of every stage. All of your factory floor equipment is all [00:33:35] linked. You're doing continuous analytics on each machine, but then able to connect them to see the processes as a whole that kind of it revolution side.
Then there's a whole series of advances in critical, you know, materials. that will enable us to do kind of designer materials in a way we've never done before, because we can now really operate at the medical level in designing materials. So, you know, we can have, you know, in the, in the clean tech space or automotive space, for example, we can have much lighter, much stronger materials.
And in a related area, composites are now, you know, an emerging opportunity space. For a lot of, kind of new manufacturing. We may be able to do electronics, which is a whole new generation of electronics based on light and with whole kind of range of new speed for electronics as a result of that and new efficiencies.
So there's a lot of technologies that are, that are [00:34:35] available. Some are starting to enter. Some are further back like Flo for example. But they could completely transform the way in which we make things. And that's what advanced manufacturing is. Can we move to these new technologies and, and the processes that go with them in completely transforming the way in which we make.
[00:34:57] Ben: Yeah. And, and like, so, so this is, I'm very interested in this and it, it feels like there isn't like, like sort of answering that question involves real research. Right? Cause you, you sort of need to, to rethink processes, you need to rethink how you do design. But at the same time, there, there aren't a lot of.
Institutions that are, are organized to do that sort of research.
[00:35:23] William: Yeah, that's look that this has been a big gap in our R and D portfolio in the United States. So at the end of world war II, Ben you know, veever Bush designs, the postwar [00:35:35] system for science. Right, right. So. We do this amazing connected system in world war II.
We have industries working with universities, working with government that're closely tied. We do incredible advances that lead to, you know, the, they lead to the electronics industry. They lead to the whole aerospace industry, right at the kind of scale we have now, they lead to, they lead to nuclear power.
Amazing stuff comes out of world war. I. And we had a very connected system. Then we, we dismantled the military at the end of the work. Cause we thought mistakenly there was gonna be world peace and all those 16 million, you know, soldiers, sailors, airmen that are overseas start to come home and VIN Bush steps in and he says, wait a minute, let's hang on to some of this.
We built this amazing R D capability in the course of the war. Let's hold on to some of it. So he says let's support basic research. That's the cheapest stage, right? Applied research costs a lot more. Yep. So we decided let's hang onto that. [00:36:35] And then we began during the war with a lot of federal research funding and universities really for the first time.
So my school MIT got 80 times. Amount of federal research funding in four years of world war II, as it did in all of its previous 80 years of history, wow. That's happening at a whole bunch of schools. We're creating this incredible jewel in the American system. We're creating the federally funded research university.
So it leads to that which is big, positive, but neighbor Bush's basic research model leaves out the applied side. And the assumption he's got, it's kind of a, what he, what others refer to as a pipeline model. But the federal government role is let's dump basic research into one end of the innovation pipeline.
Let's hope that mysterious things occur and great products emerge. Right. And it's the job of industry to do that interim stage. That's kind the model. That is what it, [00:37:35] your fingers hoping something is gonna happen in that pipeline. And whereas in world war II, every stage that pipeline was pretty well organized in a coordinated kind of way.
So we move away from that world war II connected system to a very disconnected system. We in effect institutionalized the valley of death, right. There's gonna be a gap between research side and on one side of the valley. And. You know, the actual technology implementation applied late stage applied side on the other side of the valley with a big gap, big valley gap in between the two and very few bridging mechanisms across.
So we built that into our system. And look, VIN Bush was worried about science. How are we gonna fund basic science? That's his worry. And we built, you know, the us, wasn't the science leader going into world war II. Yeah. Germany, Britain, war. We weren't, we managed [00:38:35] to bring over lots of immigrants to help lead science in the us.
And they, they took up the reigns and we trained a lot of great talent here in the course of the war. And you know, we got ourselves in a position where the us was the science leader by the end of the. We were going into the war, the world manufacturing leader. We weren't the science leader. We were the world manufacturing leader.
We had built a system of mass production that nobody else had ever seen. Right? Yeah. We went into the war with eight times the production capacity of Japan and four times the production capacity in Germany going into the war. You can only imagine what were coming outta the war. Yeah, exactly. So the least thing on Genever Bush's mind was manufacturing that's in great shape.
[00:39:24] Ben: took that as a given
[00:39:25] William: almost right. That's a given we're always gonna have that. Right. But he was wrong. We
weren't always gonna have that. Uh, And Japan taught us, [00:39:35] you That ended up costing the us it's electronic sector leadership in the electronic sector and leadership in the auto sector, two industry sectors that we had completely dominated. So, and then, you know, comes to China and we have further erosion as well.
So the reason why advanced manufacturing is important is you. We, we got two moves to compete with China. China's lower wage, lower cost. We can lower our wages to Chinese wage levels. That's probably not gonna happen. Right. Or alternatively, although we've been working on it, cause we've definitely stagnated wages in us, manufacturing, believe me.
But secondly, we can get much more efficient, much more productive. We can apply our innovation system to manufacturing. Right. So NSF doesn't have an R and D portfolio related to manufac. Star doesn't have an R D portfolio that's terribly related to manufacturing either. Right? NIH certainly [00:40:35] doesn't we don't do manufacturing.
We don't do these manufacturing technologies and processes in our I D system. Let's get that very talented, still very able us innovation system onto manufacturing. So that's the basic idea and that's the way we're gonna have to compete. We sort of got no other move. Right? We can just have continued erosion with all kinds of social disruption.
And a real decline in the American working glass, we can continue to do that and we watch what that's doing to our democracy, or we can get our act together and do advanced manufacturing. Yeah. And,
[00:41:12] Ben: do you look, I guess, like, what are some of the most sort of promising efforts in that area, in, in that you've seen?
[00:41:21] William: Well, there's, there's amazing work going on that we already see in a whole new kind of robotics. You know, the old industrial robots weighed 10 times. They're very dangerous. You have to put cages around them and make sure that the workers don't go near them. [00:41:35] And they do, you know, they lift up something heavy and they'll do like one perfect spot weld, and then they'll move to the next, you know, next piece of, you know, next piece, moving down the assembly line.
Yeah. That's the old kinda robotics. The new kind of robotics are lightweight, collaborative robotics. Just as you know, we're talking on cell phones, it's like the relationship between me and the cell phone. It's a big enabler for me. It helps me I can do voice commands to the robot and it's, you know, and can work in a precision kind of way, but it was also knows me works around me.
Doesn't endanger. It's a helper, not a, you know, a caged beast that has to be behind a fence. So we're moving to that kind of new robotics. That's a whole new C change in manufacturing. We're doing 3d printing, which you know, is instead of. Instead of subtractive manufacturing, where you cut away a huge piece of metal [00:42:35] and end up with a smaller part with real limits to what the shape and dimensions and content of that, that, that part can be additive enables you to build a part from scratch with these, with powders shape it to exactly the role you want often with new materials and we're moving into.
Metal 3d printing. So it's no longer plastics and resins only, it's a whole new kind of it's metal of production. And look, you know, we haven't figured out yet how to get the volumes that are similar to, to mass production for 3d printing, but there are plenty of product lines where you you're making limited numbers that are, have to be extremely precise, right?
Yeah. Like. Jet engines, right. You know, you're not turning out millions of jet engines every day. You're turning out small numbers, but the precision that additive [00:43:35] can bring potentially with new materials, like ceramics to creating those turbine blades is really quite dramatic. So there's a whole series of industrial sectors that'll be suited to, to additive.
And that's already moving in on some of these sectors and we're learning how to. All kinds of, of new materials for additives, you know, particularly in the metal side and new material side. So that's another huge territory of opportunity to transform their actually new ways.
[00:44:03] Ben: And, and something that I'm particularly interested in is, is so.
You could think of, of many of these, these new technologies as sort of components in a broader system. And what it seems like I, I don't personally see a lot of, is kind of like the like process research work to really sort of rethink the entire The the, the entire, like, call it a manufacturing line or the entire system and sort of ask, like what, how would you like redesign the product around how you're making it?
Have you seen any [00:44:35] sort of like institutions that are sort of trying to do that sort of work?
[00:44:40] William: Yeah. I mean this, this whole idea of, you know, for a long time, you know, we gear. The design had to fit the manufacturing, right? So we moved to, you know, design for manufacturing, right. To make it easily manufacturable.
But now. The manufacturing can be much more embedded into the design process because you can come up with a whole new suite of capabilities that will effectuate new design opportunities. Right? So rather than manufacturing, being a limiting factor on, on design, it's a, it's now an enabler of design and additive manufacturing is an example of.
So a whole new relationship between the production process and design process really possible here with these new technologies. And then getting back to your systems point. You know, now we've got the opportunity through digital [00:45:35] technologies to really take a look at a production. Operation, not as this, a series of isolated machines where material has to be carted from one machine suite to the next machine suite.
Right now we've got the ability to integrate them in, in ways that we have never had before with running the kind of level of data analytics on, on performance for each machine, but also running a new level of analytics on the system itself. Right? So we're now in a position to really connect, collect the metrics.
To a very fine scale and level on the production process itself in a way that we've never really had before. So the opportunities for efficiencies here I think are quite dramatic. And I think that's the way we're gonna have to compete. But a lot of people worry, you know, are we gonna eliminate all work?
Right? Are the, are the robots gonna displace the workers? But the reality of advanced manufacturing is actually something [00:46:35] of the opposite. You know, the robot will display some jobs, but much more frequently, the robot will create all kinds of new possibilities within existing jobs. Yeah. And then thirdly, there will be jobs to get created because we need to make robots right.
And operate program. And so they're gonna be a lot of jobs. So the net job loss problem, I just don't think is a real. Right. Yeah. Instead we get these new possibilities of kind of moving ahead and look at the center of these kinds of new factory systems are gonna be people, right? Yeah. People in the are the ones that have ideas you know, software and AI.
And robotics just can't do a whole lot of things that people are, are able to do. They don't have the kind of conceptual frameworks and the ability to kind of Intuit [00:47:35] change that people have got. So I think in a way the new manufacturing system is going be, you know, more people centric than it's been before.
[00:47:47] Ben: of people just acting like robots.
[00:47:49] William: Yeah. Lot people act acting like robots. It's people, you know, doing the organization and designing and management and the systems and the programming and the processed way that we're gonna need. Yeah,
[00:48:07] Ben: This was awesome. I'm so grateful.
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