Accused hacker and Chinese national Xu Zewei was arrested in Italy at the request of U.S. prosecutors.
Read more Michigan may be best known as the birthplace of the American auto industry, but its innovation legacy runs far deeper, and its future is poised to be even broader. From creating the world’s largest airport factory during World War II at Willow Run to establishing the first successful polio vaccine trials in Ann Arbor to the invention of the snowboard in Muskegon, Michigan has a long history of turning innovation into lasting impact.
Now, with the creation of a new role, chief innovation ecosystem officer, at the Michigan Economic Development Corporation (MEDC), the state is doubling down on its ambition to become a modern engine of innovation, one that is both rooted in its industrial past and designed for the evolving demands of the 21st century economy.
“How do you knit together risk capital founders, businesses, universities, and state government, all of the key stakeholders that need to be at the table together to build a more effective innovation ecosystem?” asks Ben Marchionna, the first to hold this groundbreaking new position.
Leaning on his background in hard tech startups and national security, Marchionna aims to bring a “builder’s thinking” to the state government. “I’m sort of wired for that—rapid prototyping, iterating, scaling, and driving that muscle into the state government ecosystem,” he explains.
But these efforts aren’t about creating a copycat Silicon Valley. Michigan’s approach is uniquely its own. “We want to develop the thing that makes the most sense for the ingredients that Michigan can bring to bear to this challenge,” says Marchionna.
This includes cultivating both mom-and-pop businesses and tech unicorns, while tapping into the state’s talent, research, and manufacturing DNA.
In an era where economic development often feels siloed, partisan, and reactive, Michigan is experimenting with a model centered on long-term value and community-oriented innovation. “You can lead by example in a lot of these ways, and that flywheel really can get going in a beautiful way when you step out of the prescriptive innovation culture mindset,” says Marchionna.
This episode of Business Lab is produced in partnership with the Michigan Economic Development Corporation.
Full Transcript
Megan Tatum: From MIT Technology Review. I’m Megan Tatum, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.
Today’s episode is brought to you in partnership with the Michigan Economic Development Corporation.
Our topic today is building a statewide innovation economy. Now, the U.S. state of Michigan has long been recognized as a leader in vehicle and mobility innovation. Detroit put it on the map, but did you know it’s also the birthplace of the snowboard or that the University of Michigan filed more than 600 invention disclosures in 2024, second only to the Massachusetts Institute of Technology, or that in the past five years, 40% of the largest global IPOs have been Michigan built companies?
Two words for you: innovation ecosystem.
My guest is Ben Marchionna, chief innovation ecosystem officer at the Michigan Economic Development Corporation, the MEDC.
Ben, thank you ever so much for joining us.
Ben Marchionna: Thanks, Megan. Really pleased to be here.
Megan: Fantastic. And just to set some context to get us started, I wondered if we could take a kind of high-level look at the economic development landscape. I mean, you joined the MEDC team last year as Michigan’s first chief innovation ecosystem officer. In fact, you were the first to hold such a role in the country, I believe. I wondered if you could talk a bit about your unique mission and how this economic development approach differs from efforts in other states.
Ben: Yeah, sure would love to. Probably worth pointing out that while I’ve been in this role for about a year now, it was indeed a first-of-its-kind role in the state of Michigan and first of its kind in the country. The slight difference in the terminology, chief innovation ecosystem officer, it differs a little bit from what folks might think of as a chief innovation officer. I’m not all that focused on driving innovation within government, which is what some other chief innovation officers would be focused on around the country. Instead, you can think of my role as Michigan’s chief architect for innovation, if you will. So, how do you knit together risk capital founders, businesses, universities, and state government, all of the key stakeholders that need to be at the table together to build a more effective innovation ecosystem? I talk a lot about building connective tissues that can achieve one plus one equals three outcomes.
Michigan’s got all kinds of really interesting ingredients and has the foundation to take advantage of the moment in a really interesting way over the next decades as we look to supercharge some of the growth of our innovation ecosystem development.
My charter is relatively simple. It’s to help make sure that Michigan wins in a now hyper-competitive global economy. And to do that, I end up being super focused on orienting us towards a growth and innovation-driven economy. That can mean a lot of different things, but I ultimately came to the MEDC and the role within the state with a builder’s mindset. My background is not in traditional economic development, it’s in not government at all. I spent the last 10 years building hard tech startups, one in Ann Arbor, Michigan, and another one in the Northern Virginia area. Before that, I spent a number of years at, think of it like, an innovation factory at Lockheed Martin Skunk Works in the Mojave Desert, working on national security projects.
I’m sort of wired for that, builder’s thinking, rapid prototyping, iterating, scaling, and driving that muscle into the state government ecosystem. I think it’s important that the government also figure out how to pull out all the stops and be able to move at the speed that founders expect. A bias towards action, if you will. And so this is ultimately what my mission is. There are a lot of real interesting things that the state of Michigan can bring to bear to building our innovation ecosystem. And I think, tackling it with this sort of a mindset, I am absolutely optimistic for the future that we’ve got ahead of us.
Megan: Fantastic. It almost sounds like your role is sort of building a statewide startup incubator of sorts. As we mentioned in the opening, Michigan actually has a really interesting innovation history even in addition to the advances in the automotive industry. I wondered if you could talk a bit more about that history and why Michigan, in particular, is poised to support that sort of statewide startup ecosystem.
Ben: Yeah, absolutely. And I would even broaden it. Building the startup ecosystem is one of the essential layers, but to be able to successfully do that, we have to bring in the research universities, we have to bring in the corporate innovation ecosystem, we have to bring in the risk capital, et cetera. So yes, absolutely, startups are important. And equally as important are all of these other elements that are necessary for a startup ecosystem to thrive, but are also the levers that are just sitting there waiting for us to pull them.
And we can get into some of the details over the course of our chat today on the auto industry and how this fits into it, but Michigan does a lot more than just automotive stuff. And you noted, I think, the surfboard as an example in the intro. Absolutely correct. We have a reputation as Motor City, but Michigan’s innovation record is a lot weirder in a fun way and richer than just cars.
Early 20th century, mostly industrial moonshot innovation. So first paved mile of concrete was in Detroit in 1909. A few years later, this is when the auto sector started to really come about with Henry Ford’s moving assembly line. Everyone tends to know about those details. But during World War II, Willow Run Airport sort of smack between Detroit and Ann Arbor, Michigan they had the biggest airplane factory in the world. They were cranking out B-24 bombers once every 63 minutes, and I’ve actually been to the office that Henry Ford and Charles Lindbergh shared. It’s still at the airport. And it was pretty cool because Henry Ford had a window built into the office that looked sort of around the corner so that he could tick off as airplanes rolled out of the hanger and make sure that they were following the same high rate production mentality that the auto sector was able to develop over the decades prior.
And so they came in to help make sure that you could leverage that industrial sector to drive very rapid production, the at-scale mentality, which is also a really important part of the notion of re-industrialization that is taking hold across the country now. Happy to get into that a bit, but yeah, Willow Run, I don’t think most folks realize that that was the biggest airplane factory in the world sitting right here in Michigan.
And all of this provided the mass production DNA that was able to help build the statewide supplier base. And today, yes, we use that for automotive, EVs, space hardware, batteries, you name it. But this is the foundation, I think, that we’ve got to be able to build on in the future. In the few decades since you saw innovations in sports, space, advanced materials, it’s like the sixties to the eighties. You said the snowboard. That was invented in Muskegon on the west side of the state in 1965.
Dow Chemical’s here in a really big way. They’ve pioneered silicone and advanced plastics in Michigan. University of Michigan’s Dr. Thomas Francis is the world’s first successful polio vaccine trials that were pioneered out of Ann Arbor, and that Big 10 research horsepower that we’ve got in the state, between the University of Michigan, Michigan State University. We also have Wayne State University in Detroit, which is a powerhouse. And then Michigan Tech University in the Upper Peninsula just recently became an R1 research institution, which essentially means those top-tier research powerhouses and that culture of tinkering matter a lot today.
I think in more recent history, you saw design and digital innovations emerge. I don’t think a lot of people appreciate that Herman Miller and Steelcase reinvented office ergonomics on the west side of the state, or that Stryker is based in Kalamazoo. They became a global medical device powerhouse over the last couple of decades, too. Michigan’s first unicorn, Duo Security, the two-factor authentication among many other things that they do there, was sold to Cisco in 2018 for 2.35 billion.
Like I said, the first unicorn in the few years since we’ve had another 10 unicorns. And I think probably what would be surprising to a lot of people is it’s in sectors well beyond mobility, it’s marketplace like StockX, FinTech, logistics, cybersecurity, of course. It’s a little bit of everything, and I think that goes to show that some of the fabric that exists within Michigan is a lot richer than what people think of, Motor City. We can scale software, we can scale life sciences innovation. It’s not just metal bending, and I talked about re-industrialization earlier. So I think about where we are today, there’s a hard tech renaissance and a broad portfolio of other high-growth sectors that Michigan’s poised to do really well in, leveraging all of that industrial base that has been around for the last century. I’m just super excited about the future and where we can take things from here.
Megan: I mean, genuinely, a really rich and diverse history of innovation that you’ve described there.
Ben: That’s right.
Megan: And last year, when Michigan’s Governor Whitmer announced this new initiative and your position, she noted the need to foster this sort of culture of innovation. And we hear that a lot that terminal in the context of company cultures. It’s interesting to hear in the context of a U.S. state’s economy. I wonder what your strategy is for building out this ecosystem, and how do you foster a state’s innovation culture?
Ben: Yeah, it’s an awesome point, and I think I mentioned earlier that I came into the role with this builder’s mentality. For me, this is how I am wired to think. This is how a lot of the companies and other founders that I spent a lot of time with, this is how they think. And so bringing this to the state government, I think of Blue Origin, Jeff Bezos’ space company, their motto, the English translation at least of it, is “Step by Step, Ferociously.” And I think about that as a lot as a proxy for how I do that within the state government. There’s a lot of iterative work that needs to happen, a lot of coaching and storytelling that happens to help folks understand how to think with that builder’s mindset. The wonderful news is that when you start having that conversation, this is one of those in these complicated political times, this is a pretty bipartisan thing, right?
The notion of how to build small businesses that create thriving main street communities while also supporting high-growth, high-tech startups that can drive prosperity for all, and population growth, while also being able to cover corporate innovation and technology transfer out of universities. All of these things touch every corner of the state.
And Michigan’s a surprisingly large and very geographically diverse state. Most of the things that we tend to be known for outside the state are in a pretty small corner of Southeast Michigan. That’s the Motor City part, but we do a lot and we have a lot of really interesting hubs for innovation and hubs for entrepreneurship, like I said, from the small mom-and-pop manufacturing shop or interest in clothing business all the way through to these insane life sciences innovations being spun out of the university. Being able to drive this culture of innovation ends up being applicable really across the board, and it just gets people really fired up when you start talking about this, fired up in a good way, which is, I think, what’s really fantastic.
There’s this notion of accelerating the talent flywheel and making sure that the state can invest in the cultivation of really rich communities and connections, and this founder culture. That stuff happens organically, generally, and when you talk about building startup ecosystems, it’s not like the state shows up and says, “Now you’re going to be more innovative and that works.” That is not the case.
And so to be able to develop those things, it’s much more about this notion of ecosystem building and getting the ingredients and puzzle pieces in the right place, applying a little bit of funding here and there, or loosening a restriction here or there, and then letting the founders do what they do best, which is build. And so this is what I think I end up being super passionate about within the state. You can lead by example in a lot of these ways, and that flywheel that I mentioned really can get going in a beautiful way when you step out of the prescriptive innovation culture mindset.
Megan: And given that role, I wonder what milestones the campaign has experienced in your first year? Could you share some highlights and some developing projects that you’re really excited about?
Ben: We had a recent one, I think that was pretty tremendous. Just a couple of months ago, Governor Whitmer signed into law a bipartisan legislation called the Michigan Innovation Fund. This was a multi-year effort that resulted in the state’s biggest investment in the innovation ecosystem development in over two decades. A lot of this funding is going to early stage venture capital firms that will be able to support the broad seeding of new companies and ideas, keep talent within the state from some of those top tier research institutions, bring in really high quality companies that early stage, growth stage companies from out of state, and then develop or supercharge some of that innovation ecosystem fabric that ties those things together. So that connective tissue that I talked about, and that was an incredible win to launch the year with.
This was just back in January, and now we’re working to get some of those funds out over the course of the next month or two so we can put them to use. What was really interesting about that was, it wasn’t just a top-down thing. This was supported from the top all the way up to and including Governor Whitmer. I mentioned bipartisan support within Michigan’s legislature and then bottom-up from all of the ecosystem partners, the founders, the investors advocating as a whole block, which I think is really powerful. Rather than trying to go for one-off things, this huge coalition of the willing got together organically and advocated for, hey, this is why this is such a great moment. This is the time to invest. And Governor Whitmer and the legislators, they heard that call, and we got something done, and so that happened relatively quickly. Like I said, biggest investment in the last two decades, and I think we’re poised to have some really great successes in the coming year as well.
Another really interesting one that I haven’t seen other states do yet, Governor Whitmer, around a year ago, signed an executive order called the Infrastructure for Innovation. Essentially, what that does is it opens up state department and agency assets to startups in the name of moving the ball forward on innovation projects. And so if you’re a startup and you need access to some very hard-to-find, very expensive, maybe like a test facility, you can use something that the state has, and all of the processes to get that done are streamlined so that you’re not beating your head against a wall. Similarly, the universities and even federal labs and corporate resources, while an executive order can’t compel those folks to do that, we’ve been finding tremendous buy-in from those stakeholders who want to volunteer access to their resources.
That does a lot of really good things, certainly for the founders, that provides them the launchpad that they need. But for those corporations and universities, and whatnot, a lot of them have these very expensive assets sitting around wildly underutilized, and they would be happy to have people come in and use them. That also gives them exposure to some of the bleeding-edge technology that a lot of these startups today are developing. I thought that was a really cool example of state government leadership using some of the tools that are available to a governor to get things moving. We’ve had a lot of early wins with startups here that have been able to leverage what that executive order was able to do for them.
Here we are talking about the MIT Technology Review to tie in an MIT piece here, we also started a Team Michigan for MIT’s REAP program. It’s the Regional Entrepreneurship Acceleration Program, and this is one of the global thought leaders on best practices for innovation ecosystem development. And so we’ve got a cohort of about a dozen key leaders from across all of those different stakeholders who need to have a seat at the table for this ecosystem development.
We go out to Cambridge twice a year for a multi-day workshop, and we get to talk about what we’ve learned as best practices, and then also learn from other cohorts from around the world on what they’ve done that is great. And then also get to hear some of the academic best practices that the MIT faculty have discovered as part of this area of expertise. And so that’s been a very interesting way for us to be able to connect outside of the state government boundaries, if you will. You sort of get out there and see where the leading edge is and then come back and be able to talk about the things that we learned from all of these other global cohorts. So always important to be focused on best practices when you’re trying to do new things, especially in government.
Megan: Sounds like there are some really fantastic initiatives going on. It sounds like a very busy first year.
Ben: It’s been a very busy first year couldn’t be more thrilled about it.
Megan: Fantastic. And in early 2023, I know that Newlab partnered with Michigan Central to establish a startup incubator too, which brought in more than a hundred startups just in its first 14 months. I wonder if you could talk a bit about how the incubator fits in with the statewide startup ecosystem and the importance of partnerships, too, for innovation.
Ben: Yeah, a key element, and I think the partnerships piece is essential here. Newlab is one of the larger components of the Southeast Michigan and especially the Detroit innovation ecosystem development. They will hit their two-year launch anniversary in just a couple of weeks, here I think. This will be mid-May, it will be two years and in that time, they’ve now got 140 plus startups all working out of their space, and Newlab they’re actually headquartered in Brooklyn, New York, but they run this big startup accelerator incubator out of Detroit as well and so this is sort of their second flagship location. They’ve been a phenomenal partner, and so speaking of the partnerships, what do those do?
They de-risk the technologies to help enable broader adoptions. Corporations can provide early revenues, the state can provide non-dilutive grant matching. Universities can bring IP and this renewable source of talent generation, and being able to stitch together all of those pieces can create some really interesting unlocks for startups to grow. But again, also this broader entrepreneurship and innovation ecosystem to really be able to thrive.
Newlab has been thrilled with their partnership in Southeast Michigan, and I think it’s a model that can be tailored across the state so that, depending on what assets are available in your backyard, you can make sure that you can best harness those for future growth.
Megan: Fantastic. What’s the long-term vision for the state’s innovation landscape when you think about it in five, 10 years from now? What do you envisage?
Ben: Amazing question. This is probably what I get most excited about. I think earlier we talked about the Willow Run B-24 bomber plant. That is what made Michigan known as the arsenal of democracy back in the day. I want Michigan to be the arsenal of innovation. We’re not trying to recreate a Silicon Valley. Silicon Valley does certain things, not trying to recreate what El Segundo wants to do in hard tech or New York City in FinTech, and all of these other things. We want to develop the thing that makes the most sense for the ingredients that Michigan can bring to bear to this challenge.
I think that becoming the Midwest arsenal of innovation, that’s something that Michigan is very well poised to use as a springboard for the decades to come. I want us to be the default launch pad for building a hard tech company, a life sciences company, an agricultural tech company. You name it. If you’ve got a design prototype and want to mass produce something, don’t want to hop coast, you want to be somewhere that has a tremendous quality of life, an affordable place, somewhere that government is at the table and willing to move fast, this is a place to do that.
That can be difficult to do in some of the more established ecosystems, especially post-covid, as a lot of them are going through really big transition periods. Michigan’s already a top 10 state for business in the next 10 years. I want us to be a top 10 state for employment, top 10 state for household median income for post-secondary education attainment, and net talent migration. Those are my four top tens that I want to see in the next 10 years. And we covered a lot of topics today, but I think those are the reasons that I am super optimistic about being able to accomplish those.
Megan: Fantastic. Well, I’m tempted to move to Michigan, so I’m sure plenty of other people will be now, too. Thank you so much, Ben. That was really fascinating.
Ben: Thanks, Megan. Really delighted to be here.
Megan: That was Ben Marchionna, chief innovation ecosystem officer at the Michigan Economic Development Corporation, whom I spoke with from Brighton, England.
That’s it for this episode of Business Lab. I’m your host, Megan Tatum. I’m a contributing editor and host for Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print on the web and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.
This show is available wherever you get your podcasts, and if you enjoy this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Giro Studios. Thanks ever so much for listening.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.
This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
From a cluster of call centers in Canada, a criminal network defrauded elderly victims in the US out of $21 million in total between 2021 and 2024. The fraudsters used voice over internet protocol technology to dupe victims into believing the calls came from their grandchildren in the US, customizing conversations using banks of personal data, including ages, addresses, and the estimated incomes of their victims.
The proliferation of large language models (LLMs) has also made it possible to clone a voice with nothing more than an hour of YouTube footage and an $11 subscription. And fraudsters are using such tools to create increasingly more sophisticated attacks to deceive victims with alarming success. But phone scams are just one way that bad actors are weaponizing technology to refine and scale attacks.
Synthetic identity fraud now costs banks $6 billion a year, making it the fastest-growing financial crime in the US Criminals are able to exploit personal data breaches to fabricate “Frankenstein IDs.” Cheap credential-stuffing software can be used to test thousands of stolen credentials across multiple platforms in a matter of minutes. And text-to-speech tools powered by AI can bypass voice authentication systems with ease.
“Technology is both catalyzing and transformative,” says John Pitts, head of industry relations and digital trust at Plaid. “Catalyzing in that it has accelerated and made more intense longstanding types of fraud. And transformative in that it has created windows for new, scaled-up types of fraud.”
Fraudsters can use AI tools to multiply many times over the number of attack vectors—the entry points or pathways that attackers can use to infiltrate a network or system. In advance-fee scams, for instance, where fraudsters pose as benefactors gifting large sums in exchange for an upfront fee, scammers can use AI to identify victims at a far greater rate and at a much lower cost than ever before. They can then use AI tools to carry out tens of thousands, if not millions, of simultaneous digital conversations.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.
This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Inside the most dangerous asteroid hunt ever
If you were told that the odds of something were 3.1%, it might not seem like much. But for the people charged with protecting our planet, it was huge.
On February 18, astronomers determined that a 130- to 300-foot-long asteroid had a 3.1% chance of crashing into Earth in 2032. Never had an asteroid of such dangerous dimensions stood such a high chance of striking the planet. Then, just days later on February 24, experts declared that the danger had passed. Earth would be spared.
How did they do it? What was it like to track the rising danger of this asteroid, and to ultimately determine that it’d miss us?
This is the inside story of how a sprawling network of astronomers found, followed, mapped, planned for, and finally dismissed the most dangerous asteroid ever found—all under the tightest of timelines and, for just a moment, with the highest of stakes. Read the full story.
—Robin George Andrews
This article is part of the Big Story series: MIT Technology Review’s most important, ambitious reporting. The stories in the series take a deep look at the technologies that are coming next and what they will mean for us and the world we live in. Check out the rest of them here.
How scientists are trying to use AI to unlock the human mind
Today’s AI landscape is defined by the ways in which neural networks are unlike human brains. A toddler learns how to communicate effectively with only a thousand calories a day and regular conversation; meanwhile, tech companies are reopening nuclear power plants, polluting marginalized communities, and pirating terabytes of books in order to train and run their LLMs.
Despite that, it’s a common view among neuroscientists that building brainlike neural networks is one of the most promising paths for the field, and that attitude has started to spread to psychology.
Last week, the prestigious journal Nature published a pair of studies showcasing the use of neural networks for predicting how humans and other animals behave in psychological experiments. However, predicting a behavior and explaining how it came about are two very different things. Read the full story.
—Grace Huckins
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get it in your inbox first every Monday, sign up here.
Why the US and Europe could lose the race for fusion energy
—Daniel F. Brunner, Edlyn V. Levine, Fiona E. Murray, & Rory Burke
Fusion energy holds the potential to shift a geopolitical landscape that is currently configured around fossil fuels. Harnessing fusion will deliver the energy resilience, security, and abundance needed for all modern industrial and service sectors.
But these benefits will be controlled by the nation that leads in both developing the complex supply chains required and building fusion power plants at scales large enough to drive down economic costs.
Investing in supply chains and scaling up complex production processes has increasingly been a strength of China’s and a weakness of the West, resulting in the migration of many critical industries from the West to China. With fusion, we run the risk that history will repeat itself. But it does not have to go that way. Read the full story.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Donald Trump has announced a range of new tariffs
Southeast Asia has been hit particularly hard. (Reuters)
+ Some tariffs on other countries have been delayed until next month. (Vox)
+ Investors are hoping to weather the storm. (Insider $)
+ Sweeping tariffs could threaten the US manufacturing rebound. (MIT Technology Review)
2 Ukraine’s fiber-optic drones are giving it the edge over Russia
The drones are impervious to electronic attacks. (WSJ $)
+ Trump is resuming sending arms to Ukraine. (CNN)
+ Meet the radio-obsessed civilian shaping Ukraine’s drone defense. (MIT Technology Review)
3 OpenAI is seriously scared about spies
It’s upped its security dramatically amid fears of corporate espionage. (FT $)
+ Inside the story that enraged OpenAI. (MIT Technology Review)
4 Amazon is asking its corporate staff to volunteer in its warehouses
It’s in desperate need of extra hands to help during its Prime Day event. (The Guardian)
5 Google’s AI-created drugs are almost ready for human trials
Isomorphic Labs has been working on drugs to tackle cancer. (Fortune $)
+ An AI-driven “factory of drugs” claims to have hit a big milestone. (MIT Technology Review)
6 Apple’s AI ambitions have suffered yet another setback
Their executive in charge of AI models has been wooed by Meta. (Bloomberg $)
+ Ruoming Pang’s pay package is likely to be in the tens of millions. (WSJ $)
7 Waymo’s robotaxis are heading to NYC
But its “road trip” announcement is no guarantee it’ll launch there. (TechCrunch)
8 Brands don’t need influencers any more
They’re doing just fine producing their own in-house social media videos. (NYT $)
9 We may age in rapid bursts, rather than a steady decline
New research could shed light on how to slow the process down. (New Scientist $)
+ Aging hits us in our 40s and 60s. But well-being doesn’t have to fall off a cliff. (MIT Technology Review)
10 This open-source software fights back against AI bots
Anubis protects sites from scrapers. (404 Media)
+ Cloudflare will now, by default, block AI bots from crawling its clients’ websites. (MIT Technology Review)
Quote of the day
“I think we’ve all had enough of Elon’s political errors and political opinions.”
—Ross Gerber, an investor who was formerly an enthusiastic backer of Elon Musk, tells the Washington Post he wishes the billionaire would simply focus on Tesla.
One more thing
How Silicon Valley is disrupting democracy
The internet loves a good neologism, especially if it can capture a purported vibe shift or explain a new trend. In 2013, the columnist Adrian Wooldridge coined a word that eventually did both. Writing for the Economist, he warned of the coming “techlash,” a revolt against Silicon Valley’s rich and powerful, fueled by the public’s growing realization that these “sovereigns of cyberspace” weren’t the benevolent bright-future bringers they claimed to be.
While Wooldridge didn’t say precisely when this techlash would arrive, it’s clear today that a dramatic shift in public opinion toward Big Tech and its leaders did in fact happen—and is arguably still happening. It’s worth investigating why, and what we can do to start taking some of that power back. Read the full story.
—Bryan Gardiner
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)
+ Struggling to solve a problem? It’s time to take a nap.
+ If any TV show has better midcentury decor than Mad Men, I’ve yet to see it.
+ Sir Antony Gormley’s arresting iron men sculptures have been a fixture on Crosby Beach in the UK for 20 years.
+ Check out this definitive Planet of the Apes timeline.
Fusion energy holds the potential to shift a geopolitical landscape that is currently configured around fossil fuels. Harnessing fusion will deliver the energy resilience, security, and abundance needed for all modern industrial and service sectors. But these benefits will be controlled by the nation that leads in both developing the complex supply chains required and building fusion power plants at scales large enough to drive down economic costs.
The US and other Western countries will have to build strong supply chains across a range of technologies in addition to creating the fundamental technology behind practical fusion power plants. Investing in supply chains and scaling up complex production processes has increasingly been a strength of China’s and a weakness of the West, resulting in the migration of many critical industries from the West to China. With fusion, we run the risk that history will repeat itself. But it does not have to go that way.
The US and Europe were the dominant public funders of fusion energy research and are home to many of the world’s pioneering private fusion efforts. The West has consequently developed many of the basic technologies that will make fusion power work. But in the past five years China’s support of fusion energy has surged, threatening to allow the country to dominate the industry.
The industrial base available to support China’s nascent fusion energy industry could enable it to climb the learning curve much faster and more effectively than the West. Commercialization requires know-how, capabilities, and complementary assets, including supply chains and workforces in adjacent industries. And especially in comparison with China, the US and Europe have significantly under-supported the industrial assets needed for a fusion industry, such as thin-film processing and power electronics.
To compete, the US, allies, and partners must invest more heavily not only in fusion itself—which is already happening—but also in those adjacent technologies that are critical to the fusion industrial base.
China’s trajectory to dominating fusion and the West’s potential route to competing can be understood by looking at today’s most promising scientific and engineering pathway to achieve grid-relevant fusion energy. That pathway relies on the tokamak, a technology that uses a magnetic field to confine ionized gas—called plasma—and ultimately fuse nuclei. This process releases energy that is converted from heat to electricity. Tokamaks consist of several critical systems, including plasma confinement and heating, fuel production and processing, blankets and heat flux management, and power conversion.
A close look at the adjacent industries needed to build these critical systems clearly shows China’s advantage while also providing a glimpse into the challenges of building a fusion industrial base in the US or Europe. China has leadership in three of these six key industries, and the West is at risk of losing leadership in two more. China’s industrial might in thin-film processing, large metal-alloy structures, and power electronics provides a strong foundation to establish the upstream supply chain for fusion.
The importance of thin-film processing is evident in the plasma confinement system. Tokamaks use strong electromagnets to keep the fusion plasma in place, and the magnetic coils must be made from superconducting materials. Rare-earth barium copper oxide (REBCO) superconductors are the highest-performing materials available in sufficient quantity to be viable for use in fusion.
The REBCO industry, which relies on thin-film processing technologies, currently has low production volumes spanning globally distributed manufacturers. However, as the fusion industry grows, the manufacturing base for REBCO will likely consolidate among the industry players who are able to rapidly take advantage of economies of scale. China is today’s world leader in thin-film, high-volume manufacturing for solar panels and flat-panel displays, with the associated expert workforce, tooling sector, infrastructure, and upstream materials supply chain. Without significant attention and investment on the part of the West, China is well positioned to dominate REBCO thin-film processing for fusion magnets.
The electromagnets in a full-scale tokamak are as tall as a three-story building. Structures made using strong metal alloys are needed to hold these electromagnets around the large vacuum vessel that physically contains the magnetically confined plasma. Similar large-scale, complex metal structures are required for shipbuilding, aerospace, oil and gas infrastructure, and turbines. But fusion plants will require new versions of the alloys that are radiation-tolerant, able to withstand cryogenic temperatures, and corrosion-resistant. China’s manufacturing capacity and its metallurgical research efforts position it well to outcompete other global suppliers in making the necessary specialty metal alloys and machining them into the complex structures needed for fusion.
A tokamak also requires large-scale power electronics. Here again China dominates. Similar systems are found in the high-speed rail (HSR) industry, renewable microgrids, and arc furnaces. As of 2024, China had deployed over 48,000 kilometers of HSR. That is three times the length of Europe’s HSR network and 55 times as long as the Acela network in the US, which is slower than HSR. While other nations have a presence, China’s expertise is more recent and is being applied on a larger scale.
But this is not the end of the story. The West still has an opportunity to lead the other three adjacent industries important to the fusion supply chain: cryo-plants, fuel processing, and blankets.
The electromagnets in an operational tokamak need to be kept at cryogenic temperatures of around 20 Kelvin to remain superconducting. This requires large-scale, multi-megawatt cryogenic cooling plants. Here, the country best set up to lead the industry is less clear. The two major global suppliers of cryo-plants are Europe-based Linde Engineering and Air Liquide Engineering; the US has Air Products and Chemicals and Chart Industries. But they are not alone: China’s domestic champions in the cryogenic sector include Hangyang Group, SASPG, Kaifeng Air Separation, and SOPC. Each of these regions already has an industrial base that could scale up to meet the demands of fusion.
Fuel production for fusion is a nascent part of the industrial base requiring processing technologies for light-isotope gases—hydrogen, deuterium, and tritium. Some processing of light-isotope gases is already done at small scale in medicine, hydrogen weapons production, and scientific research in the US, Europe, and China. But the scale needed for the fusion industry does not exist in today’s industrial base, presenting a major opportunity to develop the needed capabilities.
Similarly, blankets and heat flux management are an opportunity for the West. The blanket is the medium used to absorb energy from the fusion reaction and to breed tritium. Commercial-scale blankets will require entirely novel technology. To date, no adjacent industries have relevant commercial expertise in liquid lithium, lead-lithium eutectic, or fusion-specific molten salts that are required for blanket technology. Some overlapping blanket technologies are in early-stage development by the nuclear fission industry. As the largest producer of beryllium in the world, the US has an opportunity to capture leadership because that element is a key material in leading fusion blanket concepts. But the use of beryllium must be coupled with technology development programs for the other specialty blanket components.
These six industries will prove critical to scaling fusion energy. In some, such as thin-film processing and large metal-alloy structures, China already has a sizable advantage. Crucially, China recognizes the importance of these adjacent industries and is actively harnessing them in its fusion efforts. For example, China launched a fusion consortium that consists of industrial giants spanning the steel, machine tooling, electric grid, power generation, and aerospace sectors. It will be extremely difficult for the West to catch up in these areas, but policymakers and business leaders must pay attention and try to create robust alternative supply chains.
As the industrial area of greatest strength, cryo-plants could continue to be an opportunity for leadership in the West. Bolstering Western cryo-plant production by creating demand for natural-gas liquefaction will be a major boon to the future cryo-plant supply chain that will support fusion energy.
The US and European countries also have an opportunity to lead in the emerging industrial areas of fuel processing and blanket technologies. Doing so will require policymakers to work with companies to ensure that public and private funding is allocated to these critical emerging supply chains. Governments may well need to serve as early customers and provide debt financing for significant capital investment. Governments can also do better to incentivize private capital and equity financing—for example, through favorable capital-gains taxation. In lagging areas of thin-film and alloy production, the US and Europe will likely need partners, such as South Korea and Japan, that have the industrial bases to compete globally with China.
The need to connect and capitalize multiple industries and supply chains will require long-term thinking and clear leadership. A focus on the demand side of these complementary industries is essential. Fusion is a decade away from maturation, so its supplier base must be derisked and made profitable in the near term by focusing on other primary demand markets that contribute to our economic vitality. To name a few, policymakers can support modernization of the grid to bolster domestic demand for power electronics and domestic semiconductor manufacturing to support thin-film processing.
The West must also focus on the demand for energy production itself. As the world’s largest energy consumer, China will leverage demand from its massive domestic market to climb the learning curve and bolster national champions. This is a strategy that China has wielded with tremendous success to dominate global manufacturing, most recently in the electric-vehicle industry. Taken together, supply- and demand-side investment have been a winning strategy for China.
The competition to lead the future of fusion energy is here. Now is the moment for the US and its Western allies to start investing in the foundational innovation ecosystem needed for a vibrant and resilient industrial base to support it.
Daniel F. Brunner is a co-founder of Commonwealth Fusion Systems and a Partner at Future Tech Partners.
Edlyn V. Levine is the co-founder of a stealth-mode technology start up and an affiliate of the MIT Sloan School of Management.
Fiona E. Murray is a professor of entrepreneurship at the MIT School of Management and Vice Chair of the NATO Innovation Fund.
Rory Burke is a graduate of MIT Sloan and a former summer scholar with ARPA-E.
Today’s AI landscape is defined by the ways in which neural networks are unlike human brains. A toddler learns how to communicate effectively with only a thousand calories a day and regular conversation; meanwhile, tech companies are reopening nuclear power plants, polluting marginalized communities, and pirating terabytes of books in order to train and run their LLMs.
But neural networks are, after all, neural—they’re inspired by brains. Despite their vastly different appetites for energy and data, large language models and human brains do share a good deal in common. They’re both made up of millions of subcomponents: biological neurons in the case of the brain, simulated “neurons” in the case of networks. They’re the only two things on Earth that can fluently and flexibly produce language. And scientists barely understand how either of them works.
I can testify to those similarities: I came to journalism, and to AI, by way of six years of neuroscience graduate school. It’s a common view among neuroscientists that building brainlike neural networks is one of the most promising paths for the field, and that attitude has started to spread to psychology. Last week, the prestigious journal Nature published a pair of studies showcasing the use of neural networks for predicting how humans and other animals behave in psychological experiments. Both studies propose that these trained networks could help scientists advance their understanding of the human mind. But predicting a behavior and explaining how it came about are two very different things.
In one of the studies, researchers transformed a large language model into what they refer to as a “foundation model of human cognition.” Out of the box, large language models aren’t great at mimicking human behavior—they behave logically in settings where humans abandon reason, such as casinos. So the researchers fine-tuned Llama 3.1, one of Meta’s open-source LLMs, on data from a range of 160 psychology experiments, which involved tasks like choosing from a set of “slot machines” to get the maximum payout or remembering sequences of letters. They called the resulting model Centaur.
Compared with conventional psychological models, which use simple math equations, Centaur did a far better job of predicting behavior. Accurate predictions of how humans respond in psychology experiments are valuable in and of themselves: For example, scientists could use Centaur to pilot their experiments on a computer before recruiting, and paying, human participants. In their paper, however, the researchers propose that Centaur could be more than just a prediction machine. By interrogating the mechanisms that allow Centaur to effectively replicate human behavior, they argue, scientists could develop new theories about the inner workings of the mind.
But some psychologists doubt whether Centaur can tell us much about the mind at all. Sure, it’s better than conventional psychological models at predicting how humans behave—but it also has a billion times more parameters. And just because a model behaves like a human on the outside doesn’t mean that it functions like one on the inside. Olivia Guest, an assistant professor of computational cognitive science at Radboud University in the Netherlands, compares Centaur to a calculator, which can effectively predict the response a math whiz will give when asked to add two numbers. “I don’t know what you would learn about human addition by studying a calculator,” she says.
Even if Centaur does capture something important about human psychology, scientists may struggle to extract any insight from the model’s millions of neurons. Though AI researchers are working hard to figure out how large language models work, they’ve barely managed to crack open the black box. Understanding an enormous neural-network model of the human mind may not prove much easier than understanding the thing itself.
One alternative approach is to go small. The second of the two Nature studies focuses on minuscule neural networks—some containing only a single neuron—that nevertheless can predict behavior in mice, rats, monkeys, and even humans. Because the networks are so small, it’s possible to track the activity of each individual neuron and use that data to figure out how the network is producing its behavioral predictions. And while there’s no guarantee that these models function like the brains they were trained to mimic, they can, at the very least, generate testable hypotheses about human and animal cognition.
There’s a cost to comprehensibility. Unlike Centaur, which was trained to mimic human behavior in dozens of different tasks, each tiny network can only predict behavior in one specific task. One network, for example, is specialized for making predictions about how people choose among different slot machines. “If the behavior is really complex, you need a large network,” says Marcelo Mattar, an assistant professor of psychology and neural science at New York University who led the tiny-network study and also contributed to Centaur. “The compromise, of course, is that now understanding it is very, very difficult.”
This trade-off between prediction and understanding is a key feature of neural-network-driven science. (I also happen to be writing a book about it.) Studies like Mattar’s are making some progress toward closing that gap—as tiny as his networks are, they can predict behavior more accurately than traditional psychological models. So is the research into LLM interpretability happening at places like Anthropic. For now, however, our understanding of complex systems—from humans to climate systems to proteins—is lagging farther and farther behind our ability to make predictions about them.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
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