Mothers, Do Let Your Babies Grow Up to Be Mathematicians

Last week I was mulling writing about the awarding of this year’s Field Medals, which are often described as math’s equivalent of the Nobel Prize (no doubt to the dismay of both awarding organizations). Nah, I told myself; sure, I’m interested in math, but how many other people are? Most people barely even care about Nobel Prizes, and when they do it’s likely to be more about the Peace or Literature Prizes, not Physics or Chemistry. Math reminds most people of junior high algebra.

Don't let the tuxedo fool you. Jacob Tsimerman winning the Fields medal. Credit: Simmons Foundation

But then I saw the hook: one of the medalists – Jacob Tsimerman, of the University of Toronto – announced he was "pivoting toward AI safety” and would soon be going to work at OpenAI. People can’t get enough about AI, and with AI agents “going rogue” and creating all sorts of mischief, AI safety should be top of mind for everyone interested ion our (AI) future.

Professor Tsimerman won the award for “his contribution in the recasting of o-minimality as a fundamental method of arithmetic and complex algebraic geometry, and his role in the proof of many central conjectures including Griffiths' conjecture on the algebraicity of images of the period maps, and the Andre-Oort conjecture for Siegel modular varieties.” If you have the slightest idea what any of that means, you may be going to work for an AI company soon too. Note, though, nary a mention of AI in all that.

He did, though, co-author a paper last year about various scenarios where AI lead to most or all humans being killed, so o-minimality may have to wait. That paper ominously concluded: An AI-driven omnicide may involve an intent to kill a large number of people, or may be wholly unintentional. And, if an intent to kill exists, that intent may exist within a large group of individuals such as a military or corporation, or just a few people, or in an AI system itself.”

He told Janet Hurley of The Toronto Star: “The reason I wrote that paper with Andrew Critch is that, even though this has been going on for a long time, I felt there wasn’t a visceral story people could engage with in terms of, concretely, what are we afraid of here?”

Consider me afraid.

It turns out that Professor Tsimerman is not alone in leaving mathematical academia for AI. There has been what has been described as a “wave of top mathematicians "exiting" academia for industry.” If you are a graduate student in math, or, better yet, a math professor, you are, as Ben Affleck’s character told Matt Damon’s math genius character in Good Will Hunting, “sitting on a winning lottery ticket.” The AI companies want you, and are putting up big bucks to get you.

Just in the past week Julia Amann of The Wall Street Journal writes of The Million-Dollar Talent Wars for 20-Something Math Geniuses and Lila Shroff of The Atlantic says Something Weird Is Happening in Math, both describing the impact of AI on academic mathematics.

Wall Street firms having been going after math students since the 1980’s to serve as “quants,” designing ever more elaborate trading models, while Silicon Valley firms have been snapping up computer science students for the last three decades. Now the AI companies can’t get enough math geeks either, and they have money to burn.

Matt Stabile, founder of New York-based recruitment firm Stabile Search, told Ms. Amann: “But a million dollars is something people don’t even bat an eye at anymore…The delineation is pre-OpenAI and post-OpenAI, that’s when you saw competition really take off.”  Charlie Witmer, COO of quant firm Optiver, acknowledged to her the effect of AI firm’s interest in math geniuses: “Outstanding people are in more demand than they’ve ever been, and that does create competitive pressure on wages. As competition increases for outstanding people, prices naturally rise.”

Part of the reason mathematicians may be tempted to leave academia is that, well, AI may soon be better than they are at math. A few months ago, I wrote about how mathematics might be one area that AI hadn’t yet conquered. That didn’t age well. “In a few years, AI systems will be robustly superhuman at the act of doing mathematics,” Professor Tsimerman told Ben Cohen of The Wall Street Journal. “The social consequence of that, how we choose to react, what you feel about it—those are much harder questions.”

He admitted to Ms. Shroiff that there are pluses and minuses (pun intended) to AI’s improving math skills:

From one point of view, I think it will be extremely exciting. We might speed up the process of generating interesting mathematics by enormous factors of 10 or 100. If that happens, we might see the connection between pure math and applications (which typically takes many decades) really speed up and become a much tighter pipeline.

But from the perspective of research mathematicians, and especially young people who are pursuing a Ph.D. in mathematics, it’s a bit of a turbulent time. The skills that we’ve acquired and learned to propagate might become less relevant than they are now.

On the other hand, he thinks math expertise may help us understand what AI is up to:

Mathematics is historically the language by which you take intuitions and fuzzy notions of how things work and you make them precise. We’ve done this with information theory; we have done this with complexity theory. Just a little bit of understanding and precise definitions can provide a ton of mileage. Once we have that understanding, the hope is that we could do a better job of anticipating the behavior of new AI systems, adjusting for them, controlling them, and reacting to them. That’s where I think mathematicians fit in.

He told Kenneth Chang of The New York Times about AI: “It’s mostly an empirical and engineering kind of science. If we understood how these things work better, we might be able to steer them better, or understand them better, or control them better.”

We can hope so, anyway.

The AI industry first sucked up university AI researchers, then academic leaders in computer science, and now is going after the math departments. The trouble is, there aren’t enough of them. Even worse, we’re eating our seed corn. Who will train the next generation of mathematicians?  That’s fine if you assume AI is that next generation, but if you still want human creativity and brilliance, it’s daunting.

Work Requirements Target the Wrong People

One of the key “cost savings” in last years’ Big, Beautiful Bill were work requirements imposed on most working aged beneficiaries in SNAP and/or Medicaid, despite the fact that the few times such requirements had been tried showed they were costly to implement and operate and don’t do much to increase work participation, although they are effective at getting beneficiaries to lose benefits. Republicans who pushed these requirements were infuriated at the thought that some able-bodied people – stereotypically young men – were sitting around on their couches playing video games while benefiting from the programs, despite those programs’ complex administrative burdens and meagre benefits.

Who is really abusing our federal tax dollar?

A new GAO report reminds us that the people coasting off SNAP and Medicaid were not so much the beneficiaries but rather employers, especially large employers. And the names of the most likely employers won’t come as a big surprise.

The report -- Federal Social Safety Net Programs: Millions of Workers, Including Many Employed by Large Employers, Continue to Rely on Medicaid and SNAP – was requested by Senator Bernie Sanders, in his role as Ranking Member of the Senate Committee on Health, Education, Labor, and Pensions, and is a follow-up to a similar 2020 report. It focused on 11 states: Arkansas, Georgia, Indiana, Maine, Massachusetts, Nebraska, North Carolina, Oklahoma, Rhode Island, Tennessee, and Washington.

The top-lines are that working aged beneficiaries in both programs were, in fact, not only likely to already be working—mostly full-time -- but also at participation rates higher than working aged people not on the programs, and that companies like Amazon and Walmart were among the largest employers of these beneficiaries.

The key change in employment in these populations has been the explosion of gig workers in the app-based food delivery and ride sharing sectors. Workers at Amazon on these programs also tripled since the prior report. Walmart remains the employer with the largest number of these workers who receive Medicaid, but has slipped to second to ride sharing gig workers receiving SNAP. McDonalds and Dollar General round out the top five employers.  

Now, these are among the largest employers generally, but, gosh, doesn’t it gall you that have so many of their workers who still need SNAP and/or Medicaid?  It’s not like they’re not making money, it’s not that their CEOs and other executives aren’t raking in tens of millions of dollars, but they sure are reluctant to pay federal income taxes. The Wall Street Journal reported earlier this year that, as a result of The Big, Beautiful Bill, Amazon’s federal income taxes dropped from $9b to $1.2b in 2025, while profits soared 44.5% to $90b. Walmart looks like a sucker for paying $6b in 2025, an effective tax rate of about 23%.

An Amazon spokesperson defended its practices in a response to The Washington Post: “Amazon pay is among the best in the industry, regular full-time employees have access to health care from their first day … and 74% of our regular full-time employees are enrolled in an Amazon health insurance plan, well above the 65% private sector take-up rate for full-time workers.”

So, if all those employees have access to coverage from their first day and get among the best pay in the industry, why are any on SNAP or Medicaid?  And couldn’t you at least pay more than 1.3% on federal taxes?

Bernie, of course, was outraged:

American taxpayers should not be forced to subsidize the starvation wages of large corporations like Walmart and Amazon. These corporations are making record-breaking profits, paying their CEOs exorbitant compensation packages and spending billions of dollars on stock buybacks to enrich their wealthy shareholders. It is beyond unacceptable that these corporations, owned by some of the wealthiest people on the planet, are receiving corporate welfare from the federal government.

He pointed out that, in the 11 states, Walmart had 16,000 workers on Medicaid and 15.500 workers on SNAP, while Amazon had 11,000 workers on Medicaid and 12,000 workers on SNAP.  

And, oh-by-the-way, an analysis by the Oregon Capital Chronicle of the most listed employers ion applications for Medicaid found “that dozens of major national and multinational corporations that often pay relatively low hourly or median wages rely on the government’s health insurance program for low-income and disabled people to cover the costs of thousands of their Oregon employees’ healthcare.”  The top five employers were Walmart, Safeway/Albertsons, Amazon (and affiliates), Fred Meyer/Kroger, and McDonald’s. The articles noted that those five employers were also the top five listed employers on SNAP applications in a prior analysis.

New Jersey, for one, has had enough. It recently passed a law requiring employers to pay an annual fee per employee on Medicaid, if there are at least 50 such workers. The fee ranges from $345 to $725, based on how many employees the company has on Medicaid. The fees are expected to raise $145 million annually. The state estimates that Amazon, for example, has 5,600 workers, and 10,000 dependents, on the state’s Medicaid program, while Walmart has more than 10,000 workers and family members.

Credit: Washington Post

Similar bills have been introduced in California, Colorado, and Washington.

“Our feeling about this is that it’s time for corporations working in our communities to step up for our communities,” Alan Dubinsky, a spokesperson for the Service Employees International Union Local 49, said. “Stop gouging the state and provide healthcare for your workers. If Jeff Bezos can afford hundreds of billions of dollars to build data centers, he can afford to provide healthcare for the people that built this wealth for him through their labor.”

I was around when there was active debate about “employer mandates,” requiring employers to offer health insurance for workers. The complaint from employers was always, oh, it will cost jobs, and others speculated employers would just manipulate employees’ hours to avoid them qualifying. Maybe both of those are true, but whatever sympathy I might have had for employers is diminished by their recent tax breaks and soaring executive pay. Corporations have successfully fought to be considered “people,” but they seem to only want the advantages that come with that standing, not the obligations.

I’d rather we ensure that even a few people sitting on their couches have adequate food and health care than I would that corporate executives can afford more yachts and helicopters. So, Republicans, spare me your faux outrage and focus on fairness.

Status Quo Wins, Until It Doesn't

With all that’s going on – e.g., congrats to Spain for its World Cup victory, scary about the cyclosporiasis outbreak and the Canadian wildfire smoke, dismaying but entirely predictable that the Iran-U.S. war is flaring up again – you may have missed the news that Ukrainian President Zelensky fired defense minister Mykhailo Fedorov.

Better times for President Zelensky and (former) Defense Minister Fedorov. Credit: Radio Free Europe

Now, perhaps Mr. Zelensky was worried he was inadvertently creating a future political rival, or maybe there’s some kind of corruption scandal behind the scenes, but the most common take is that the old guard military establishment disliked the acclaim Mr. Fedorov had gotten and the power he was accumulating. After all, even during war – perhaps especially during war – protecting one’s own interests often comes first.

Mr. Fedorov, who is only 35, had been in the role for just six months, having previously served as a digital transformation minister. His push for increased use of drones, and innovations in how they were used, led to his appointment. By all accounts, Ukraine leads the world in drone warfare: offensive and defensive, learning to cope with mass attacks, jamming, fiber-optic controlled drones, and other tactics no military had attempted or had to defend against before.   

He even created an Amazon-like arms procurement system that soldiers on the front lines could use to get the right weapons they needed, bypassing normal procurement channels, which were slower, more centralized, and more expensive. That helped lead to an ecosystem of young Ukrainian entrepreneurs working on military start-ups. “This level of innovation, and the way it’s been integrated into Ukraine’s fight, wouldn’t be possible without these young people,” Per Holst, the deputy defense attaché at the Danish Embassy in Kyiv, told Constant Méheut of The New York Times.

Example of Ukraine's digital procurement system

"One of the faces of the modern and technological war, it's Mykhailo Fedorov. He totally changed the rules. He's not afraid to take some risk or responsibility," said Ihor Fedirko, who leads the Ukrainian Council of Defense Industry.

The final straw that seemingly led to Mr. Fedorov’s ouster was his blocking of the purchase of artillery shells, preferring that the money be spent on his preferred weapons. The commander of Ukraine’s military, Gen. Oleksandr Syrskyi, felt that the “old school” weapons were still needed for the old school battlelines.

Mr. Zelensky was caught in the middle. "I wanted unity very much," Zelensky told reporters. "The sides did not find it. And that is not only their problem, but mine as well. I do not absolve myself of responsibility. And I respect the sides, I know their strengths, I know their weaknesses, and I very much want them to strengthen Ukraine. But it is what it is."

It did not go smoothly. “The season of shooting oneself in the foot has opened,” Kostyantyn Batozsky, a political analyst, wrote on social media.  Mass protests broke out, expressing support for Mr. Fedorov and distain for General Syrskyi.  They demanded Mr. Fedorov be reinstated, and General Syrskyi be removed, by July 24 or they’d hold nightly rallies.

Some raised not-so-subtle charges of what was really at stake: “You can’t even imagine what streams of funding have been cut off,” Serhiy Sternenko, an adviser to the Defense Ministry wrote on social media. He subsequently quit as well.

Mr. Fedorov held his own press conference, saying: “Today, my task is to show what we’ve done, and to talk about the risks that lie ahead for all of us. I don’t want to later look my children in the eyes and realize that I didn’t speak up on what’s really going on.” He criticized General Syrskyi for being too focused on tactics and not enough on strategy.  

Paul Adams of BBC reports that many in the Ukrainian military are “outraged” by Mr. Fedorov’s dismissal. "It is a blatant slap in the face to all service members," said one soldier. Another cynically pointed out: "If you can't come to an agreement with the old fossils, they'll eat you alive," while military analyst and former intelligence officer Ivan Stupak made it clear who the old fossil was: "Fedorov is an iPhone 16, Syrskyi is a telephone from the 1980s.”

One soldier told The New York Times: “Right now, we are facing the enemy. We believed that there were no enemies behind our backs, in our rear. As it turns out, there are.”  Another noted: “Almost all conversations right now are about this.” This is not what you want on the front lines. 

President Zelensky is likely to survive this, as he did a corruption scandal last summer. He’s holding lots of meetings, including with both General Syrskyi and Mr. Federov, who promises: “There will definitely be changes.” “Decisions regarding the army will be worked out,” the president promised in a statement.

Meanwhile, General Syrskyi defends himself:

The strangest accusation I’ve heard is that I supposedly ‘don’t want to fight with drones,’ A person who ‘does not want to fight with drones’ does not create the world’s first separate branch of unmanned systems and does not appoint a commander to it, contrary to all traditions of the military hierarchy.

Fair points. I suspect that Mr. Fedorov did push harder than the military establishment was comfortable with, while that establishment did, in fact, adopt radically new tactics out of the sheer desperation of the situation. But, at some point, push came to shove.

I have to note that, with all the lessons Ukraine has learned/taught about the new era of war, the vaunted, hugely expensive U.S. military has seemed flummoxed by the same Iranian drones Ukraine has battled for four years. Despite all the new, tech-based military start-ups across the world, experts predict that the old guard military contractors will still rake in 80% of military spending by 2033.  

Credit: Boston Consulting Group

Lockheed Martin, for example, has taken lots of criticism for how expensive its Patriot missiles are, and for how long they take to produce, so they’re introducing a new, cheaper version: it only will cost $2 million per missile. I don’t think they’re reading the room, or the battlefield, correctly.

 It’s amazing the Ukraine has held on this long, and is now even taking the fight to Russia. But no one who has attempted innovation in a big corporation or in a big industry can be surprised at this drama. Change is hard. Status quo doesn’t give up easily.

The point isn’t that the future of war is drones, or even AI drones. The point is that the future of war – and, in an AI world, the future of every industry -- is constant, rapid innovation. We are not living in a time when the status quo can hold.

Value Is in the Eye of the Beholder

The most (unintentionally) amusing story I read this week was Tim Higgin’s Wall Street Journal article Alex Karp Is Saying What Every Angry CEO Is Thinking About AI. Dr. Karp (yes, he has a Ph.D.), co-founder and CEO of Palantir Technologies, is upset about how AI companies are using relationships with their business customers to harvest data and business insights from those customers. “Something has gone completely wrong,” he fumed.

AI is collecting our data; why aren't we being paid? Credit: Microsoft Designer

Now, this is Palantir, mind you; it may not have invented surveillance capitalism but it might have perfected it. It has become essential to government and large corporations across the world. Most of us are aware of how tech companies like Meta or Google give us “free” services that exist primarily to collect more data on us, which they then use to target ads to us, but Palantir’s data collection and analysis operate at a level we often don’t recognize.  But make no mistake; it is using our data, and not necessarily in our best interests.

Mr. Higgins quotes former White House AI czar David Sacks in support of Dr. Karp’s concerns:

Anthropic has launched Claude Science, Claude Security, Claude Legal, and of course Claude Code—each expanding into categories previously served by companies building on top of their models. The pattern is consistent: Watch where value is being created, then move in directly. Dominate the model layer, then use that position to capture the most lucrative verticals.

So it is delicious irony that Dr. Karp and others are finding themselves at the wrong end of the power inequality with their data.

I find myself thinking about healthcare when I think above this new wave of data collectors/ synthesizers. It seems pretty clear that the AI companies aren’t going anywhere, and are expected to reshape most industries, including healthcare. Lots has been written about AI’s use in healthcare, including by me. It is both inevitable and, in many cases, desirable. Now this issue of AI’s insatiable appetite for data makes me wonder if we’re looking at things wrong.

I’ve worked in healthcare for longer than I care to admit, and at no point did people not complain that healthcare in general, and health insurance in particular, was too expensive. And yet, costs have kept rising. We’re closing in on $6 trillion in U.S. healthcare expenditures. No matter what kind of health insurance you have – large employer, small employer, ACA Marketplace, Medicare Advantage, even Medicare Supplements for traditional Medicare – your premiums (and/or out-of-pocket costs) are likely going up at rates we haven’t seen in years.

Two well known facts about rising costs are, one, that it is not so much we’re using too many services as it is that Americans pay way higher prices for healthcare than in most countries, and, two, that a relatively small percentage of people account for the vast majority of healthcare spending. The latter has an insidious effect on health insurance premiums, as people with fewer expenses are less likely to have or keep health insurance, making premiums for the remaining people higher. Nobody wants to pay for the people who use a lot of health care, but they want other people to help pay if they end up being one of those people. It’s a conundrum.

Now, optimists hope that AI can do a better job of identifying all the wasted, unnecessary, or inappropriate care we use – estimated as much as one-third – and help make administration more efficient; current levels are estimated as 15-30% of spending. Good goals, both of them, and it is entirely plausible that AI can help with both. But it would still remain that sick people are the “problem” with our health care spending and health insurance premiums, and I want to propose a different way of looking at them.

Healthcare generates massive amounts of data, increasing all the time. Some estimates put it well in the exabyte level, which, trust me, is way more than any of us can comprehend. We generate data when we go to the doctor, when we get lab work, when we fill a prescription, when we go to the hospital, even when we use a wearable like a smartwatch. All those health insurance claims and all those healthcare bills generate data. And, yet, most of that data isn’t effectively used, which I sure hope AI does something about.

So we have a system in which the people who use more health services generate more data, and an AI industry that craves data. This seems like it should be a match made in heaven.

Why couldn’t we have a healthcare system in which AI companies pay people generating healthcare data for that data? I.e., instead of heavy users of healthcare being drivers of spending, they become a valuable resource? And, oh-by-the-way, why aren’t we being paid for our data?

Our data, healthcare data included, is being shared, bought and sold now. Sometimes it is deidentified (supposedly), sometimes not. Either way, we’re not the ones getting paid for it. That should change.

Now, realists will point that that “value” of our healthcare data is nowhere near the costs of our health care, so paying for the latter with the former is impractical. I’ll grant that is currently true, but I’ll also ask: why is that?

I’d argue that our health data is grossly undervalued, because the companies using it are used to getting it so cheaply, and that our health services are wildly overpriced. Reorienting the system so that the former funds the latter should bring them closer into equilibrium.

If data is, as has been said, the new oil, then I’ll point out that oil was also once very cheap, until enterprising people figured out that they could control the supply and thus raise the price virtually at will. We should be those people when it comes to our data, especially our healthcare data.

So I’ll be amused at Dr. Karp being faux outraged at other data companies profiting off of his company’s data, and I’ll hope that we have a fundamental rethinking about who generates value in our data world and how that value is realized. There can’t be a better place to do this than in healthcare.

Life Not As We Know It

Well, let’s see. Laat week much of the U.S. and parts of Europe were under a crippling heat dome. The U.S. celebrated its 250^th birthday. And there’s something called the World Cup going on, for those of you who care about such things. But, I mean, really, the news of the week? SpudCell.

It may not look like much, but SpudCell is close to synthetic life. Credit: Orion Venero, Adamala Lab

OK, maybe you missed that one. If you are not a fan of science, or of synthetic biology in particular, news about it might not have shown up in your feeds, or perhaps you thought it was another ploy by the Potato Association of America to get you to buy even more potatoes. SpudCell is something truly new: “the world’s first synthetic cell with a complete life cycle, built entirely from non-living chemical components.”

Take a minute to take that description in.

“SpudCell performs the behaviors often used to tell the living from the inert — it feeds, grows, replicates its genome, divides and undergoes selection — yet it is far simpler than any natural cell and was assembled, part by part, by hand,” the project researchers wrote in a statement.

It was designed and built by researchers at the University of Minnesota, announced last week along with a preprint of their paper. The team was led by Professor Kate Adamala, and the name is either due to its supposed resemblance to a potato or it’s a play on “Sputnik.”

“This is likely the most exciting project I've ever worked on,” said Professor Adamala. “We’ve replicated in chemistry what only used to be possible in biology: the complete set of behaviors of a cell. It proves that the most fundamental functions of life, like growth and replication, do not need a mysterious magical spark.”

Scientists have been working for decades on stripping away genetic material from living cells to try to find the minimum necessary for life, but Professor Adamala and her team went the other way, gradually building up genetic material until it started behaving in ways we’d expect cells to.

The impressive thing is that the team engineered everything SpudCell does. As The Economist put it: “Everything the resulting cells do, they do because of molecules that Dr Adamala’s team put there. That leaves no room for mysteries.” That’s not true when researchers start with living cells.

Drew Endy, a synthetic biologist at Stanford University, told Carl Zimmer of The New York Times, “It’s a cell that was built, not born. It’s constructed, but it does what cells do.”

SpudCell is very basic. The human genome has about 3 million kilobase pairs (kbp); SpudCell has 90. And, instead of a single chromosome, SpudCell’s genome is split across seven separate DNA plasmids, while allows researchers to program various cell functions independently.

Whether SpudCell qualifies it as “life” is murky. Professor Adamala cautioned: “Life is not binary. That’s why I’m hesitant to call this ‘alive.’ There’s no clear line, as much as we would love it to be.”

For example, SpudCell doesn’t make its own ribosomes, using ones from e coli bacteria instead, which means it can only replicate for 5-10 generations before things degrade. It also needs some help feeding, with nutrient-carrying liposomes having to be added regularly. But, still; not bad for 90 kbp.

Other scientists are pretty impressed. “Kate Adamala’s team designed and built a nonliving synthetic cell that is much closer to being ‘alive’ than anything else produced by the bottom-up synthetic cell field,” said John Glass, who leads synthetic cell research at the J. Craig Venter Institute. ”It is dazzling that she has put these things all together.”  

“This is a stunning scientific achievement,” says Roseanna Zia, a computational cell biologist at the University of Missouri.

Prof Tom Ellis, at Imperial College London, told The Guardian the work was probably the field’s “biggest breakthrough in recent times,” further explaining: “Making a synthetic cell helps us understand the exact minimum requirements for life and how life might have emerged from chemistry. It’s also useful as it provides a fully understood system for testing biological circuits and computer models of cellular life.”

Professor Adamala admits that in some ways SpudCell is “as dumb as it gets,” and likens it to the Wright brothers’ first airplane, noting that researchers who start with real cells are “like an engineer that’s given a full Dreamliner without all the plans.” Dr. Endy also used the Wright brothers analogy, telling Mr. Zimmer: “The Wright flyer flying for 12 seconds doesn’t get you a 737. This is just the beginning.”

Professor Adamala, along with Professor Endy and two other researchers, have founded Biotic, a public-benefit nonprofit research organization to further the research. They hope to create a shared technical infrastructure for synthetic cell engineering, with a mission “to responsibly enable and steward foundational advances in bioengineering.”

To help other scientists use SpudCells in their research, the Biotic site includes detailed protocols for building SpudCells. It notes: “While our motivation for this research is to make biology a general purpose technology, usable freely by all, we are currently operating in the sandbox environment.” 

Early days.

Professor Adamala says:

This work is just the beginning. We are showing it’s possible to engineer the basic functions of the cell. To fully realize the promise of this technology – to make it robust and practical – we need combined international effort. The role of Biotic is to focus engineering efforts and make them compatible with a shared chassis. SpudCell is that chassis, and with Biotic setting the protocols for collaboration, we are eager to start applying this technology to serious challenges.

“This work demands our attention, not for what has been produced but for where it leads,” Dr. David A. Relman, a microbiologist at Stanford University, told K.R. Callaway of NYT, adding: “It is creative, disruptive and provocative in revealing what might be possible in the not-so-distant future.”

“Creative, disruptive, and provocative” -- music to my ears.

The University of Minnesota announcement makes clear the hope for synthetic biology in general, and SpudCell in particular:

Cells built from scratch could perform molecular transformations industrial chemistry cannot. That could first transform molecular medicine, building precise therapeutic molecules including drugs incorporating amino acids evolution never used. We could see materials that are grown, rather than synthesized, and manufacturing approaches that operate at biological temperatures, not industrial ones. Underneath it is a truly engineerable platform, which SpudCell provides for the first time.

OK, maybe the researchers didn’t “create life,” but the Wright brothers crashed many times before they succeeded. I love this idea of building from the bottom, and I’m rooting for SpurCell to grow up.

Thorin, We Hardly Knew Ye

Humans – that is to say, homo sapiens – have been fascinated by the Neanderthals since they were first identified in 1856. For many years, they were thought to be the original cave dwellers, leading a brutish, animal-like existence sometime in the distant past. Over the years, and especially with the advent of DNA as a tool, we’ve learned that were quite possibly were as intelligent as modern humans, they used tools, they buried their dead, and they even practiced dentistry,  Not only that, they not only overlapped with modern humans but also interbred with us; we have an estimated 1-4% of their DNA even today.

 

You're not likely to run into a Neanderthal, but wouldn't it be cool? Credit: Microsoft Designer

And yet the mysteries continue.

A new paper in Nature sheds some new light on the genetic data from Neanderthals, using the DNA from 27 individuals across ten sites and dating back some 50,000 years. Although the species apparently died out within 10,000 years from then – a blink of the eye in the evolutionary timescale -- these individuals seemed to be healthy and well-connected to other Neanderthal populations.

It had long been speculated that humans essentially drove Neanderthals to extinction, outcompeting them and forcing their populations to small enough sizes that they became inbred and unsustainable. This research does not support that thesis.

“Until now, we only had four high-quality Neanderthal genomes and a limited number of lower-quality ones, so most questions about the regional diversity of Neanderthals have been difficult to address,” said lead author Alba Bossoms Mesa, a doctoral researcher at the Max Planck Institute for Evolutionary Anthropology. “By generating genetic data from multiple individuals from the region of present-day Belgium and France, we can now examine late Neanderthal populations in much greater detail.”

Neandertal skeletal elements from the Spy 1 and 2 skeletons (Lohest Collection, 1886) from Spy Cave in Belgium. © P. Semal, Royal Belgian Institute of Natural Sciences, CC-BY 4.0

UCLA computational geneticist Benjamin Peter, who is one of the paper’s corresponding authors. added: “In other, earlier Neanderthal populations, close relatives were interbreeding, leading to unhealthy levels of genetic diversity similar to what we see today in some endangered species. But this population in Belgium and France does not seem to be dying out, even though we know that they will die out in the end.”

That’s not even the most surprising finding. Professor Peter says: “I think the most interesting finding we made is that these Neanderthals are genetically relatively healthy, with no strong signs that there was inbreeding depression. It’s also interesting that we didn’t find evidence that they have ancestry from anatomically modern humans, even though we know that at least they must have overlapped in time.”  

It gets even more interesting. Dr. Blossoms Mesa notes: “Our results add to a striking asymmetry. We repeatedly find Neandertal ancestry in early modern humans, but so far, we have not found clear evidence of recent modern human ancestry in late Neandertals."

Perhaps modern human men didn’t find Neanderthal women attractive (or vice-versa), perhaps Neanderthals were too formidable for humans to approach, or perhaps homo sapiens-Neanderthal babies didn’t survive. I like to think that homo sapiens women found the Neanderthal tough guy image irresistible, while Neanderthal women found our men to be, well, kind of wimpy. Or perhaps homo sapiens women were more likely to wander alone, where they might meet a Neanderthal man. We’ll never know.

Or perhaps we may yet gain more insight. Co-author Marie Soressi, Professor of Hominin Diversity Archaeology at Leiden University, says: “We are only beginning to uncover the diversity and complexity of Neanderthal populations. As more genomes become available from sites across Europe and beyond, we can move from studying isolated individuals to reconstructing entire communities, their relationships, and the social networks that connected them.”

"This study highlights the power of ancient DNA to reveal variation within Neandertals on a much finer scale than was previously possible," says co-author Janet Kelso, a group leader at the Max Planck Institute for Evolutionary Anthropology. "Rather than viewing late Neandertals as a single declining population, we are beginning to recognise a more complex picture of regional diversity, connectivity, and population history."

Illustrating that complex picture, I can’t help thinking about a finding from a couple years ago, the so-called Thorin (no, not the dwarf from “the Hobbit”). He was a Neanderthal who was part of a unique lineage that existed in Europe for some 50,000 years. 

“Until now, the story has been that at the time of the extinction there was just one Neanderthal population that was genetically homogeneous, but now we know that there were at least two populations present at that time,” said first author and population geneticist Tharsika Vimala of the University of Copenhagen.

That’s not the most surprising thing. The real surprise, as co-first author and discoverer of Thorin Ludovic Slimak of the Center for Anthropobiology and Genomics of Toulouse, France, told LiveScience: "The population of Thorin had spent 50 millennia without exchanging a single gene with the classical Neanderthal populations."

He further noted: “50,000 years of divergences is what separates the tiny dog of your grandma from a wolf.” It’s a long time to be genetically isolated. 

Speaking to IFLScience, senior author of the study Martin Sikora of the University of Copenhagen alternatively puts it like this: “The divergence between Thorin and the other Late Neanderthals is comparable to all modern humans out-of-Africa. As we all know the wide phenotypic diversity of modern humans, I would expect similar diversity among Neanderthal populations.” 

This was not like the Aboriginals in Australia being separated for other humans for tens of thousands of years due to geographical isolation. There were plenty of other Neanderthals around Thorin’s people. They apparently just chose not to mingle, or weren’t curious enough to find other humans.

Professor Slimak expressed his surprise: “We thus have 50 millennia during which two Neanderthal populations, living about ten days' walk from each other, coexisted while completely ignoring each other. This would be unimaginable for a Sapiens and reveals that Neanderthals must have biologically conceived our world very differently from us Sapiens.”

Keep in mind, that around this time, not only were there homo sapiens and Neanderthals, but also Denisovans, homo luzonensis, and homo floresiensis, although not all of them lived in exactly the same places or at exactly the same times. Still, think of the swap meets, not to mention the dating options.

Humans didn’t drive all of the great apes (e.g., orangutans, gorillas, chimpanzees, and bonobos) to extinction, nor all “intelligent” species (e.g., dolphins or octopuses), so it is an evolutionary mystery why it happened with other types of humans. Maybe they got a sense of what we were going to do to the world and wanted no part of it.

Low Resource Computing to the Fore

Now, this is the kind of thing we should hope for from DARPA: last week it issued an RFI focused on low resource computing (LRC), seeing as the “Department of War (DoW) typically operates in environments with limited power, communication, or physical space, where mission completion depends on the ability to sustain critical computation and adapt at the edge.” DARPA is firm about looking for breakthrough technologies only: “DARPA is interested in disruptive concepts at the material, component, runtime, and authoring levels that represent significant advances beyond current practice for fielding robust, ultra-efficient systems,” further emphasizing: “Approaches resulting in incremental improvement and description of existing capabilities or prior work without a clear vision for advancing the field are not of interest.”

You can see why DARPA is interested in low resource computing. Credit: Microsoft Designer

I love it. I mean, I don’t know what kind of responses DARPA is likely to get, but I love breaking the paradigms that govern most of our computing lives. We worship at the altar of Moore’s law and brag about the computing power of our laptops and smartphones, but AI is driving us back into the era of “bigger is better,” with lots of computing power needed to train and operate them. Your devices may be powerful, but without the cloud to help them, they’re more like expensive paperweights.

Most of us, of course, don’t operate under the kinds of constraints DARPA is worried about, but all of us stand to benefit from any advances its LRC initiative brings. We’ve been operating under basically the same conceptual computer model since the 1940’s, just with better chips, so it is time for a fundamental rethinking.

As DARPA says:

Decades later, the apex of the commercial computing industry follows this same resource-heavy trajectory. Modern data centers, built around advanced graphics processing unit (GPU) clusters to drive artificial intelligence, demand staggering, gigawatt-scale power requirements that necessitate massive, dedicated infrastructure.

While commercial enterprise focuses heavily on scaling upward to exascale capabilities, this trend leaves significant, overlooked potential at the lower end of the computing spectrum. There remains substantial room for improvement and innovation by revisiting architectures through a lens of strict resource scarcity. By optimizing systems for extreme efficiency rather than scale, it is possible to develop highly resilient computing platforms that do not rely on massive infrastructure.

DARPA is looking for responses that address at least one of the physical resources constraints: low power, low memory, low reliability, or low technological level, and may also address one or more logical resource constraints in addition: low trust, low privilege, self-hosting, or low complexity of user experience.

As Colton Jones described the RFI in Defense Blog:

The Pentagon’s most ambitious research arm wants to build computers that can think in the dark, operate on almost no power, and keep working even when their own hardware is failing, and it is now asking the technology world to help figure out how.

Sure, why not?

I can’t help thinking of the work Leidy Klotz and colleagues have done, as described in his book Subtract. Basically, they argue that our design bias is always to add, never to subtract, and that bias causes us to overlook many opportunities. The proponents of frugal innovation would understand. The RFI suggests that it’s time to strip computing down to its essentials, and see if we can rebuild differently.

My first thought, right or wrong, in seeing the RFI was fungal computing, which I wrote about a couple years ago. People like Andrew Adamatzy, Professor of Unconventional Computing at the University of the West of England, or Robert Shepherd, leader of the Organics Robotics Lab at Cornell have been on this track for years.

Professor Adamatzy is also the Editor-in-Chief of The Journal of Unconventional Computing, which publishes research on varied topics like chemical computing, biomolecular computing cellular automata, or logics of unconventional computing. Professor Shepherd is more focused “on using organic chemistry of soft material composites for new capabilities in robots,” but has used fungal computing to guide them. Neither may be the kind of person who will start the next Apple or the next Microsoft, but both seem like the kind of people who see the future differently.

Exactly the kind of people DARPA is hoping to hear from (although, of course, Professor Adamatzy is English, and neither may be interested in helping DARPA or the Defense Department).

If you think that fungi would be an odd choice to power computing, well, you must not have been paying enough attention to them lately. Their networks are everywhere and transmit startling amounts of data, as a recent paper illustrated. As the paper’s lead author, Dr. Toby Kiers, told Alan Burdick of The New York Times: “Are fungi capitalists? No. They’ve developed a system that is much more sophisticated than the economic system humans use.”

Silicon, you’ve been a good friend and ally for many decades, but perhaps it is time we revisited some old friends.

I’ll give another example of out-there technology the DARPA RFI made me think of: 3D printing of batteries, as Christopher Mims recently profiled in The Wall Street Journal. Batteries have long been a pain point for all of our devices, from watches to smartphones to laptops to electric cars, but some innovators don’t think they have to be. Mr. Mims writes:

There’s a revolution in battery technology hiding in plain sight: The 3-D printing of batteries has the potential to put energy storage inside any device. This will enable lightweight and long-lasting consumer gadgets, long-range military drones and even nanoscale robots.

 He goes on to posit:

The promise of battery-tech 3-D printing (aka additive manufacturing) is simple: What if batteries could fill any available space, even structural elements of our gadgets, rather than always taking a rigid shape like a pouch or cylinder?

What if, indeed. What we think batteries are and have to be, may not be. How many other components of our existing computing platforms is that true of?

Responses to the DARPA RFI are due July 17 (which doesn’t seem like very long), and DARPA will hold an in-person, invitation-only workshop in August. I don’t know what kind of responses DARPA will get or who will be attending the workshop, but if I were a venture capitalist looking for the Next Big Thing, I’d sure be paying attention.