Expect the Unexpected

Most people probably know about Alexander Fleming “discovering” penicillin by accident, thus inventing the field of antibiotics. Others may know that Viagra was originally developed to combat hypertension and angina pectoris. You may think of Botox for its cosmetic purposes, but it was originally intended to treat strabismus (cross eyes), and has a host of other medical purposes as well. All of those, and countless other examples, speak to the importance of serendipity in science.

Science often surprises. Credit: Microsoft Designer

A new study, by Aslan et. al., attempts to quantify how common such serendipity is. Bottom line: it is way more common than you think.

The team analyzed over 1.2 million publications, which had resulted from 90,000 NIH grants between 2008 and 2016. They used the NIH's Research, Condition, and Disease Categorization (RCDC) to categorize what the researchers said they were looking for in their grant application versus what their findings were when published.

The results:

We found that 70 % of the publications have at least one RCDC category not in its grant, which we termed ‘unexpected’ categories. On average, 40 % of categories assigned to a publication were unexpected. After adjusting for similarity across some of the RCDC categories by empirically clustering the categories, we found 58 % of the publications had at least one unexpected category and, on average, 33 % of publication categories were unexpected.

Larger grants tend to result in more unexpected results, as do results published longer after the grant was issued.

Fig. 1. Proportion of publications with (A) one or more unexpected categories or (B) one or more unexpected categories (clustered); distribution of (C) unexpected category proportions and (D) unexpected category proportions (clustered).

“The bottom line is that ‘unexpectedness’ is not rare — this came through loud and clear,” said Ohid Yaqub, a biochemist and social scientist at the University of Sussex in Brighton, UK, who led the work. According to Nature, this research is “part of a wider project to understand the role in research of serendipity, of which unexpectedness is just one aspect.”

The researchers do caution: “what we are calling “unexpected” on the basis of text in the grants and publications may not in fact be unexpected for the investigators, or others in the field. Future research could make progress on these issues by using interviews and surveys to validate text-based measures of unexpected spillovers.” Professor Yaqub admits: “What we’ve looked at is only just scratching the surface.”

Telmo Pievani, a philosopher of biological sciences at the University of Padua in Italy, told Nature that the results go “beyond the anecdotal view of serendipity in science” and “for the first time verifies it on a quantitative and statistical level.” It is, indeed, part and parcel of how science works.

Somewhat surprisingly, the researchers also found:

Our results suggest that disease-orientation and clinical research were less likely to be associated with spillovers. Grants resulting from targeted requests for applications were more likely to result in publications with unexpected categories, though the magnitude of the differences was relatively small.

E.g., one would think those targeted requested would result in more targeted results, but that was not the case.

Samatha Copeland, a philosopher at Delft University of Technology in the Netherlands, told Nature that she worries that funding pressures may inhibit such serendipitous findings: “What’s happening right now is, scientists have actually been working around funding processes in order to make room for unexpected discoveries,” with Ph.D. students in particular likely to feel “oppressed by the scientific method and model of producing exactly the results you said you would produce.” Getting unexpected results may not be good for tenure or for Ph.D. thesis approval.

The key is being open to the unexpected results. Professor Pievani believes: “It is okay to fund both basic research and applied research, as long as both are open to unexpected results and do not eliminate anomalies too hastily.” Indeed, in his recent book Serendipity: The Unexpected in Science, he writes: “The common thread is chance and observational sagacity: a mixture of skill, clairvoyance, an incisive and fortunate mind, and the ability to discover connections.”

As the saying goes (oft attributed to Louis Pasteur), chance favors the prepared mind.

Still, Professor Pievani worries: “In the dictatorship of an instantaneous, emotional, and overwhelming present, you can always look for something specific with a quick google and find it for sure. Serendipity instead blossoms in the bends and meanders, the dull moments and wanderings.” Scientists struggling to stay within their funding or to attract new funding may be more reluctant to follow those bends and meanders, wherever they might lead.

Innovation expert John Nosta, founder of Nostalab, believes that AI can serve as “serendipity engines” by using AI’s so-called hallucinations. “What if these hallucinations could be harnessed to create a serendipity engine?” he writes. “An AI that doesn’t merely predict the next word but facilitates unexpected connections, delightful surprises, and groundbreaking insights?”

If you doubt that, note that a 2024 Wharton study found that AI was more creative than Wharton students (which may say more about Wharton students than AI): “There was a significantly higher preference for the ideas created by AI than by the Wharton students…Of the 400 ideas generated, only five human-created ideas were among the 40 most desirable products in this experiment.” The researchers say: “ChatGPT-4 can generate ideas much faster and cheaper than students, the ideas are on average of higher quality (as measured by purchase-intent surveys) and exhibit higher variance in quality. More important, the vast majority of the best ideas in the pooled sample are generated by ChatGPT and not by the students.”

The authors of that study, Christian Terwiesch and Karl Ulrich, wrote in The Wall Street Journal:  “First, generative AI has brought a new source of ideas to the world. Not using this source would be a sin…Second, the bottleneck for the early phases of the innovation process in organizations now shifts from generating ideas to evaluating ideas.”

The question is whether organizations are open to unexpected results when evaluating those new ideas.

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In an era of Big Science, with expensive projects staffed by dozens or hundreds of researchers, is there flexibility to pursue unexpected results? In an era of corporate innovation centers, can those workers really follow the “bends and meanders,” or are they constrained by budget and corporate goals? I.e., is there room for serendipity?

Science and innovation do not show linear progress. They take unexpected turns, they run into dead ends, and they take leaps no one could have predicted. If we’re not open to serendipity, if we’re not encouraging it and on the lookout for it, we’re going to miss those leaps.     

Take Note of RedNote

Admit it: until a week or so ago, you’d never heard of the Chinese app RedNote.

RedNote logo. Yes, it's in Mandarin. Credit:  Xingin Information Technology

Its actual name is Xiaohongshu, which I’m told means “little red book” in Mandarin. That may or may not be an allusion to Chairman Mao’s little Red Book; it may simply be a play on “red” as a term for “popular” in Chinese. It has over 300 million users, but until recently almost all of them were in China, especially among young women.

Now is has been one of the leading downloads in the U.S. Why the surge? It’s all about TikTok, of course.

Not that long ago, TikTok was seen as a threat to U.S. national security. Since it was owned by a Chinese company (ByteDance), there were fears that the Chinese government had access to the data on the 170 million Americans on it, and could use TikTok’s algorithms to push out all kinds of propaganda to impressionable youth. Despite ByteDance’s protestations of its independence, and its ultimate agreeing to store data in the U.S., Congress banned it last April, giving it until January 19, 2025 to be sold to a U.S. company. The Supreme Court affirmed the ban last Friday.

So TikTok went dark yesterday…for part of the day.

TikTok on January 19. This didn't last long.

Many TikTok users weren’t going to stick around for the drama, and somehow landed on RedNote. There have been hundreds of millions of posts with the phrase “TikTok refugee” in the past week. Although such refugees are just a fraction of TikTok users, the growth rate has been incredible.

Never mind that RedNote is also owned by a Chinese company (Xingin Information Technology). Never mind that its servers, and thus all its data, are all in China. Never mind that its terms and conditions are in Mandarin, just in case you are the kind of person to want to read such things. And never mind that it is openly subject to Chinese government censorship and oversight.

Talk about jumping from the frying pan into the fire.

TikTok creator Manimatana Lee posted on TikTok: “How funny would it be if they ban TikTok and we all just move over to this Chinese app.” She told The New York Times: “I don’t really care if I’m using a Chinese app at all. It’s like a place for me to escape reality. And if it’s making me feel good, I’m here for it.”

Oh, and I’d be remiss if I didn’t note that another leading App store download this past week is Lemon8, which is not only another Chinese app but is also owned by ByteDance.

Ivy Yang, a China tech analyst and founder of consulting firm Wavelet Strategy, commented to CNN about the migration: “Users are finding creative ways to transcend language barriers, navigate cultural differences, and co-exist in fascinating ways. This community building happening in real time could have lasting impact, and I’m cautiously optimistic.”

RedNote preview in the Apple App Store. Credit: Apple

The Chinese government is barely disguising its glee. In a briefing last week, Chinese Foreign Ministry spokesperson Guo Jiakun said: “As a matter of principle, China has always supported and encouraged strengthening people-to-people exchanges and the promotion of people-to-people bonds with all countries.” Similarly, a commentary in People’s Daily opined: “Moving to RedNote can be seen as an act of defiance against the U.S. government’s narrative that Chinese apps are security threats. By embracing RedNote, users challenge the assumption that Chinese platforms are inherently dangerous.”

Users may not want to get too complacent. The law that banned TikTok wasn’t TikTok-specific. "This appears to be the kind of app that the statute would apply to and could face the same restrictions as TikTok if it's not divested," a U.S. official told CBS News. Daria Impiombato, China analyst at the Australian Strategic Policy Institute, told The Washington Post: “We’ve probably spent too much energy worrying about the single app. Once you have the capacity to build those algorithms and those apps, it doesn’t take very long to create a TikTok or something different.” 

TikTok isn’t quite dead yet, of course. Last spring then former President Trump did a 180 degree shift in his opinion about TikTok, from demanding a ban in his first Administration to his 2024 campaign heavily using TikTok to reach young voters. Once he jumped onboard, all the other critics seemed to melt away; even President Biden said he wouldn’t enforce the ban. TikTok went dark for part of January 19, until President Trump indicated that he would give the platform additional time to comply with the law.

He may want ByteDance to sell TikTok to Elon Musk. Seriously.

It’s important to note that, although TikTok is a huge international success, there is a separate ByteDance app (Douyin) for Chinese citizens. Most of Chinese internet companies do almost all their business within China (which, granted, has a huge population). Li Yuan writes in The New York Times:

As the Chinese Communist Party tightens its grip on the country’s private sector, it’s increasingly difficult for the world to entrust their citizens’ personal data to Chinese companies, which ultimately answer to Beijing.

There are good reasons that the outside world, including the U.S. government, doesn’t trust these companies. In a country where the government owns much of everything and wields power randomly and often ruthlessly, the private sector has been on its toes. The internet companies are heavily censored and must self censor to survive. All the big ones, with no exception, have had their apps removed from app stores or been fined or disciplined by regulators in recent years.

RedNote and Lemon8 are noteworthy because the Chinese version is available outside of China as well. All that access to personal data, all that censorship, all that government control – apparently many Americans just don’t care. "Did the U.S. government forget our founding principles? We are a nation built on spite," user @thesleepydm posted on TikTok. "We're giving our information directly to the Chinese government now. The communists just have our information directly because of … what you did."

As Amanda Hess writes in The New York Times: “As if American-owned social media companies like Meta have never sought to mine and exploit sensitive data. As if American-owned platforms like X would never juice their algorithms to reward certain political ideas.”

I don’t think RedNote is going to supplant TikTok, but, then again, I don’t think TikTok is going away. A face-saving deal will be made, as long as President Trump finds TikTok useful. But, hey, since X and Meta are basically abandoning content moderation, I can see the appeal of a RedNote.

Maybe AI Doesn't Read Blueprints

Gosh, who knew that today would be an AI day, with at least three major announcements about “blueprints” for its development going forward? Of course, these days every day is an AI day; trying to take in all AI-related news can be overwhelming. But before some other AI news drowns them out, I wanted to at least outline today’s announcements.

The Biden Administration thinks it has an AI blueprint. Credit: AI.gov

The three I’m referring to are the Biden Administration’s Interim Final Rule on Artificial Intelligence Diffusion, OpenAI’s Economic Blueprint, and the UK’s AI-driven Plan for Change.  

The Biden Administration’s rules aim to preserve America’s lead in AI, stating: “it is essential that we do not offshore this critical technology and that the world’s AI runs on American rails.” It establishes who advanced chips can be sold to and how they can be used in other countries, with no restrictions on 18 key allies and partners.

It also sets limits on model weights for AI models, seeking to constrain non-preferred entities’ ability to train advanced AI models.

“The U.S. leads the world in AI now, both AI development and AI chip design, and it’s critical that we keep it that way,” Commerce Secretary Gina Raimondo said in a briefing with reporters ahead of Monday’s announcement

Not everyone is happy. The Information Technology & Innovation Foundation blasted the rule, claiming it would hamper America’s competitiveness.  Vice President Daniel Castro warned: “By pressuring other nations to choose between the United States and China, the administration risks alienating key partners and inadvertently strengthening China’s position in the global AI ecosystem.”

Similarly, Nvidia, which makes most of those advanced AI chips, expressed its opposition in a statement from Ned Finkle, vice president of government affairs, claiming the rule “threatens to derail innovation and economic growth worldwide.”  He explicitly contrasts how the first Trump Administration (and, one assumes, the next Trump Administration) sought to foster “an environment where U.S. industry could compete and win on merit without compromising national security.”  

Not to be outdone, Ken Glueck, Executive Vice President, Oracle, says the rule “will go down as one of the most destructive to ever hit the U.S. technology industry,” and “we are likely handing most of the global AI and GPU market to our Chinese competitors.”

It will be interesting to see what the Trump Administration does with the Rule.

Meanwhile, OpenAI’s economic blueprint believes “America needs to act now to maximize the technology’s possibilities while minimizing its harms…to ensure that AI’s benefits are shared responsibly and equitably.” Its goals are to:

• Continue the country’s global leadership in innovation while protecting national security
• Make sure we get it right in AI access and benefits from the start
• Maximize the economic opportunity of AI for communities across the country.

It sees “infrastructure as destiny,” with investment in AI infrastructure “an unmissable opportunity to catalyze a reindustrialization of the US.” It wants to ensure that “an estimated $175 billion sitting in global funds awaiting investment in AI projects” get invested here rather than in China.

OpenAI does want “common-sense rules” that promote “free and fair competition” while allowing “developers and users to work with and direct our tools as they see fit” under those rules. And, of course, all this while “Preventing government use of AI tools to amass power and control their citizens, or to threaten or coerce other states.” It particularly wants to avoid a “patchwork of state-by-state regulations”

The company is planning an event in Washington D.C. on January 30 with CEO Sam Altman “to preview the state of AI advancement and how it can drive economic growth.”  I’ll bet Mr. Altman is hoping he gets plenty of Trump Administration officials, although probably not Elon Musk.

Credit: OpenAI

Last but not least, UK Prime Minister Keir Starmer has endorsed an ambitious set of AI recommendations, wanting to turbocharge the economy by turning the UK into an AI superpower. Mr. Starmer vowed:

But the AI industry needs a government that is on their side, one that won’t sit back and let opportunities slip through its fingers. And in a world of fierce competition, we cannot stand by. We must move fast and take action to win the global race.

Our plan will make Britain the world leader. It will give the industry the foundation it needs and will turbocharge the Plan for Change. That means more jobs and investment in the UK, more money in people’s pockets, and transformed public services.

There are three key elements:

First, “laying the foundations for AI to flourish in the UK,” including AI Economic Growth Zones and  a new supercomputer.

Second, “boosting adoption across public and private sectors,” such as through a new digital government center that “will revolutionise how AI is used in the public sector to improve citizens lives and make government more efficient.”

Third, “keeping us ahead of the pack,” with a new team that “will use the heft of the state to make the UK the best place for business.”

It will do so while also charting its own course on regulation. "I know there are different approaches (to AI regulation) around the world but we are now in control of our regulatory regime so we will go our own way on this," the PM said. "We will test and understand AI before we regulate it to make sure that when we do it, it's proportionate and grounded."

Credit: Gov.UK

Chris Lehane, Chief Global Affairs Officer at OpenAI, praised the plan: “The government’s AI action plan - led by the Prime Minister and Secretary Peter Kyle - recognises where AI development is headed and sets the UK on the right path to benefit from its growth:”

All nice words, but lots left unsaid. As Gaia Marcus of the Ada Lovelace Institute pointed out: "Just as the government is investing heavily in realising the opportunities presented by AI, it must also invest in responding to AI’s negative impacts now and in the future."

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These things are true: AI is going to play a major role in the world economy, and to be a superpower, a country will have to be an AI superpower. To be an AI superpower, a country has to have the best AI infrastructure, including chips and data centers. AI is equally capable of positive impacts as well as negative impacts, and some regulation is needed to mitigate the latter. Lastly, regulation is going to lag innovation -- and AI will drive innovation at rates we haven’t seen before.

I envy the people working on AI innovation, but I don’t envy those trying to figure out how to best regulate it.

Program Me Some Cells, Please

Tempted though I might be to write about Nvidia’s new platform for “physical AI” – aka, robots – I figured plenty of others will do that. What’s another trillion in market cap for Nvidia, anyway?  On the other hand, I don’t see enough excitement about some recent research at Rice University on “smart cells.”

If you want to program cells, Xiaoyu Yang is your man. Credit: Jeff Fitlow/Rice University

The research, published in Science with the matter-of-fact title Engineering synthetic phosphorylation signaling networks in human cells (by contrast, Nvidia’s marketers named their foundation models for humanoid robots “GRooT Blueprint” -- now, that’s catchy), was about how to program human cells to detect and respond to signals in the body. Between synthetic biology and robots. I’ll pick synthetic biology everyday (unless the robots are nanobots, of course).  

“Imagine tiny processors inside cells made of proteins that can ‘decide’ how to respond to specific signals like inflammation, tumor growth markers or blood sugar levels,” said Xiaoyu Yang, a graduate student in the Systems, Synthetic and Physical Biology Ph.D. program at Rice who is the lead author on the study. “This work brings us a whole lot closer to being able to build ‘smart cells’ that can detect signs of disease and immediately release customizable treatments in response.”   

Imagine, indeed.

It turns out that there is a natural process called phosphorylation, which cells use to respond to their environment. As the Rice press release explains: “Phosphorylation is involved in a wide range of cellular functions, including the conversion of extracellular signals into intracellular responses — e.g., moving, secreting a substance, reacting to a pathogen or expressing a gene.”

It goes on to elaborate:

Phosphorylation is a sequential process that unfolds as a series of interconnected cycles leading from cellular input (i.e. something the cell encounters or senses in its environment) to output (what the cell does in response). What the research team realized — and set out to prove — was that each cycle in a cascade can be treated as an elementary unit, and these units can be linked together in new ways to construct entirely novel pathways that link cellular inputs and outputs.

“This opens up the signaling circuit design space dramatically,” said Caleb Bashor, an assistant professor of bioengineering and biosciences and corresponding author on the study. “It turns out, phosphorylation cycles are not just interconnected but interconnectable — this is something that we were not sure could be done with this level of sophistication before. Our design strategy enabled us to engineer synthetic phosphorylation circuits that are not only highly tunable but that can also function in parallel with cells’ own processes without impacting their viability or growth rate.”

The “sense-and-respond” cellular circuit design occurs rapidly – seconds or minutes – which allows it to be used for processes that occur on similar timescales, unlike other previous efforts. For example, the researchers tested it to detect and respond to inflammatory factors, which they believe could be used to control autoimmune flare-ups and reduce immunotherapy-associated toxicity.

Soon-to-be Dr. Yang added: “We didn’t necessarily expect that our synthetic signaling circuits, which are composed entirely of engineered protein parts, would perform with a similar speed and efficiency as natural signaling pathways found in human cells. Needless to say, we were pleasantly surprised to find that to be the case. It took a lot of effort and collaboration to pull it off.”

Professor Bashor concluded: “Our research proves that it is possible to build programmable circuits in human cells that respond to signals quickly and accurately, and it is the first report of a construction kit for engineering synthetic phosphorylation circuits.”

A “construction kit” for “programmable circuits” in human cells.  Tell me that’s not exciting stuff.

Caroline Ajo-Franklin, director of the Rice Synthetic Biology Institute, added: “If in the last 20 years synthetic biologists have learned how to manipulate the way bacteria gradually respond to environmental cues, the Bashor lab’s work vaults us forward to a new frontier — controlling mammalian cells’ immediate response to change.” 

“This is like embedding tiny processors in cells, made entirely of proteins, that can ‘decide’ how to respond to specific signals such as inflammation, tumor growth, or high blood sugar,” Dr. Yang explained to SynBioBeta. “Our work moves us significantly closer to constructing ‘smart cells’ that can detect disease indicators and instantly produce tailor-made treatments.”

You had me at “smart cells.”

I would be remiss if I didn’t mention a couple of other developments that offer to make this kind of advance even more powerful. Last month researchers at University of California San Diego announced a new software package they call SMART: Spatial Modeling Algorithms for Reactions and Transport. “SMART provides a significant advancement in modeling cellular processes,” said Emmet Francis, PhD, lead author of the study and a postdoctoral fellow at UC San Diego

They believe it can realistically simulate cell-signaling networks; it “takes in high-level user specifications about cell signaling networks and then assembles and solves the associated mathematical systems.” This “could help accelerate research in fields across the life sciences, such as systems biology, pharmacology and biomedical engineering.”

If you are not a fan of geometry, much less computational geometries, SMART is not for you, but if you are a biologist it opens up lots of possibilities. Someone such as Blaise Manga Enuh, a Postdoctoral Research Associate in Microbial Genomics and Systems Biology at University of Wisconsin-Madison. He writes in The Conversation about genome-scale metabolic models, or GEMs, which can be used to virtually carry out experiments that would have taken painstaking, time-consuming experiments in the lab.

“With GEMs,” Dr. Enuh says, “researchers cannot only explore the complex network of metabolic pathways that allow living organisms to function, but also tweak, test and predict how microbes would behave in different environments, including on other planets.”

Moreover:

Synthetic biologists can use GEMs to design entirely new organisms or metabolic pathways from scratch. This field could advance biomanufacturing by enabling the creation of organisms that efficiently produce new materials, drugs or even food.

I have a feeling Dr. Yang, Dr. Francis, and Dr. Enuh would have a lot to talk about.

So with GEMs or SMART, you could model out what you want to happen at a cellular level, then use the Rice technique to program cells to accomplish that. That’s 22^nd century medicine – and we’re lucky enough to be catching glimpses of it in 2025.

Mayday, Mayday

They’re crucial to the U.S. and the world economy, yet most people rarely think about them. The U.S. used to lead in their manufacturing, but now has fallen far behind, losing tens of thousands of well-paying blue collar jobs as a result. China has become a leader, while the U.S. has become heavily dependent on southeast Asia, particularly South Korea. Developing a more proactive federal industrial policy for rebuilding the U.S. capacity has bipartisan support, yet it is not clear if this can happen quickly enough – or at all.

Yeah, that's probably not in the U.S. Credit: Bing Image Creator

You’d be forgiven if you assumed I was referring to chips, but that’s one letter off. I am worried about U.S. chip production, but for today I want to talk about ships.  

Daniel Michaels writes in The Wall Street Journal: “No nation has ever successfully ranked as a world naval power without also being a global maritime power.” We used to be such a power, with the biggest navy, protecting the biggest merchant fleet. Those days are long gone. Mr. Michaels laments:

U.S. commercial ships today account for less than 1% of the world fleet. U.S. ports are racked by strikes and battles over the type of automation that has supercharged expansion of container terminals across the globe. The Navy struggles to find commercial vessels to support its far-flung operations.

In Noahpinion, Brian Potter of Construction Physics shares similar concerns:

Commercial shipbuilding in the U.S. is virtually nonexistent: in 2022, the U.S. built just five oceangoing commercial ships, compared to China’s 1,794 and South Korea’s 734. The U.S. Navy estimates that China’s shipbuilding capacity is 232 times our own. It costs roughly twice as much to build a ship in the U.S. as it does elsewhere.

Credit: Voronoi/Visual Capitalist

James Watson, a retired U.S. Coast Guard rear admiral, told Mr. Michaels: “Not thinking of the maritime industry as an important part of your economy, that’s kind of crazy.”

Yes, it is.

We spend massive amounts on our military budget – more than the next nine countries (Chinaincluded) combined spend – yet China’s navy already has more ships and is planning to double that number by the end of the decade. U.S. Navy leaders believe our ships are more capable, but, at some point, quantity outweighs quality.

“It’s a major problem for us, especially if we wound up in a conflict or we wind up in a situation where China decides for whatever reason that they want to, you know, stop our economy and put brakes on it in a big way,” Senator Mark Kelly said in an interview. “They have the ability to do that.” 

And, of course, if and when the U.S. needs to boost its number of navy (or other) ships, we’ll be dependent on our South Korean friends to produce and maintain them. President-elect Trump is already talking to South Korean leaders about our reliance on their capabilities.

Last June, The Center for Strategic and International Studies (CSIS) warned:  

China’s massive shipbuilding industry would provide a strategic advantage in a war that stretches beyond a few weeks, allowing it to repair damaged vessels or construct replacements much faster than the United States, which continues to face a significant maintenance backlog and would probably be unable to quickly construct many new ships or to repair damaged fighting ships in a great power conflict.

“Part of it is we don't have the backbone of a healthy commercial shipbuilding base to rest our naval shipbuilding on top of,” National Security Advisor Jake Sullivan said earlier this month at the Aspen Security Forum in Washington. “And that's part of the fragility of what we're contending with and why this is going to be such a generational project to fix.”

Anyone believe we have a generation before China flexes its naval or maritime prowess, such as in the South China Sea (or the Panama Canal)?

Credit: Infomaritime.EU

When it came to chip manufacturing, Congress finally acted, passing the Chips and Science Act in 2022. It is starting to have an impact, although slower than originally hoped, and it is not clear that it will ever put us back in world leadership. We’re starting to take ship manufacturing more seriously as well. Earlier this month Senators Kelly (D-AZ) and Todd Young (R-IN) and Representative John Garamendi (D-CA) introduced The Ships for America Act.  

Senator Kelly explained:

We’ve always been a maritime nation, but the truth is we’ve lost ground to China, who now dominates international shipping and can build merchant and military ships much more quickly than we can.

The SHIPS for America Act is the answer to this challenge. By supporting shipbuilding, shipping, and workforce development, it will strengthen supply chains, reduce our reliance on foreign vessels, put Americans to work in good-paying jobs, and support the Navy and Coast Guard’s shipbuilding needs.

Sal Mercogliano, associate professor of history at Campbell University, told USNI News: “This is the first major piece of maritime reform since the Merchant Marine Act of 1970. So you’re talking about 55 years since we’ve had anything like this.”

Of course, whether this bill gets a high priority in the next Congress, which will be obsessed with tax and immigration legislation, remains to be seen. But, as CSIS noted, “the clock is ticking.”

As with chips, rebuilding shipbuilding capabilities won’t be easy. Robert Kunkel, president of Alternative Marine Technologies, writes in MarineLink: “The problem is not the cost of labor. It is our inability to build infrastructure that supports ship manufacturing. And with that, the path forward needs to be a fresh start with greenfield locations and new technology in commercial shipyards surrounded by a manufacturing base that supports the effort.”

Mr. Kunkel hopes for some uniquely American approaches:

We are seeing interest from American technology and investment capital as we address questions from investors asking if we can move ship manufacturing to a “Space X” model.  Is it possible to 3D print a vessel or provide new technology to redefine “ship manufacturing”? Can we move toward a full production line similar to the auto industry?  Can this manufacturing process be operated by robotics to ease the reported labor shortages and train a new shipbuilding work force.

Mr. Michaels quotes Navy Secretary Carlos Del Toro, who likes to cite early 20^th century naval strategist Alfred Thayer Mahan: “naval power begets maritime commercial power, and control of maritime commerce begets greater naval power.” We’ve forgotten part of that equation, and that is putting both sides at risk.

As Mr. Potter concludes his piece, when it comes to regaining our shipbuilding capabilities: “The picture is not pretty, and it should concern us all.”

Consider me concerned.

It's Quantum Time

In Fast Company, Adam Bluestein writes: “It’s an unscientific fact that nine out of every 10 conversations about tech in the past year have been about AI. But the 10th has been about quantum computing.”

This is one of those conversations.

You're going to be surprised by quantum computers. Credit: Bing Image Creator

Mr. Bluestein continues:

In a period of just over a year, the perennial technology of the future has become suddenly real—with major breakthroughs in computing hardware and software, significant public and private investments, and rising stock prices for companies in the burgeoning quantum ecosystem.

For example, you may have noticed that earlier this month Google announced Willow, its breakthrough quantum chip. Hartmut Neven, Founder and Lead of Google Quantum AI, claimed two major accomplishments for Willow. One was that it “performed a standard benchmark computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion (that is, 10²⁵) years — a number that vastly exceeds the age of the Universe.” 

The second was that it cracked a key problem with quantum computing, reducing errors “exponentially” as it scaled up using more qubits (the quantum version of bits). The error reduction was also important because Dr. Neven states: “it’s also one of the first compelling examples of real-time error correction on a superconducting quantum system.” Googles believes it has reached an “error correction threshold” that is critical to making quantum computing reliable.

Credit: Google Quantum AI

“When quantum computing was originally envisioned, many people — including many leaders in the field — felt that it would never be a practical thing,” Mikhail Lukin, a professor of physics at Harvard, told The New York Times. “What has happened over the last year shows that it is no longer science fiction.” Even Elon Musk responded to Google’s announcement with “Wow” on X.

Meanwhile, Steven Rosenbush wrote a Wall Street Journal article “The Age of Quantum Software Has Already Started.” For example, IBM already has some 250 paying customers for its quantum systems and services. “It’s actually not a matter of waiting for that to be built. In fact, it’s already happening,” Jerry M. Chow, an IBM fellow and director of quantum infrastructure, told him.

Mr. Rosenbush mentions several other quantum computing companies, such as Terra Quantum, which touts itself as “The leading global independent full stack quantum technology company, IonQ, whose mission is “To build the world’s best quantum computers to solve the world’s most complex problems,” and PsiQuantum, which claims it is “building the world’s first useful quantum computer.”

I would be remiss if I didn’t note that Terra Quantum specifically mentions life sciences and healthcare as a target industry, pointing out: “Quantum technologies help us truly understand, simulate and optimize the quantum properties of nature. This, in turn, unlocks enormous potential in the areas of biochemistry, pharmacogenomics, medical imaging, and others.” You can bet other quantum companies are or will be doing the same.

PsiQuantum is interesting for at least three other reasons. As Elizabeth Gibney outlines in Nature, first, it is basing its structure on photons instead of atoms to make qubits – a “photonics approach.” Second, it has already raised $1b and values itself at $3b. “They have received one of the biggest venture-capital investments in the quantum community,” Doug Finke, of the business-analysis firm Global Quantum Intelligence, told her.

Third, and more to the point, by the end of 2027 it “aims to be operating a photonic quantum computer that can run commercially useful problems and is ‘fault-tolerant’.” It plans to have this operational at its Brisbane site in 2027 and at Chicago’s new Illinois Quantum and Microelectronics Park in 2028.

Illinois, it should be noted, is investing some $500 million in IQMP, and will give PsiQuantum $200 million more in incentives. It wants the park to be the Silicon Valley of quantum computing. “Our vision of Illinois as a global quantum capital comes further into focus at Illinois Quantum and Microelectronics Park, providing limitless opportunities for economic investment and innovation right here on the South Side,” said Governor JB Pritzker.   

Rendering of IQMP. Credit: State of Illinois

PsiQuantum Chief Business Officer Stratton Sclavos told Mr. Rosenbush: “We’re not building a science project.” He further explained: “I’m not trying to speed up your simulation that, you know, works perfectly, well. What I’m trying to do is give you a simulation of a thing you can’t simulate today.”

Still, PsiQuantum has not published much research, so validating its hopes is difficult. “My impression is there’s a lot of skepticism about how much progress PsiQuantum has made,” Shimon Kolkowitz, a quantum physicist at the University of California, Berkeley, told Ms. Gibney.  He warned her that a bet on them would be “extremely high risk.”

Still, money is flowing into the field. Fast Company reports:

The number of quantum computing deals soared more than 700% from 2015 through 2023, according to PitchBook data, and total deal value grew tenfold to $1 billion. Governments around the world have made quantum computing a strategic national defense priority. As of February 2024, the U.S government had invested $3 billion in quantum computing projects, plus an additional $1.2 billion from the National Quantum Computing Initiative. China, meanwhile, has reportedly invested some $15 billion in quantum computing efforts.

One reason interest is s high – and this may be the main thing you knew about quantum computing – is that once it happens, our traditional encryption methods become useless; a quantum computer could crack them in nanoseconds.

Cryptocurrencies, for example, would be very vulnerable. “What you’ve got here is a time bomb waiting to explode, if and when someone gets that ability to develop quantum-computer hacking and decides to use that to target cryptocurrencies,” said Arthur Herman, senior fellow at the Hudson Institute.

People are already working on how to make encryption safe from quantum computers, such as quantum token, using quantum key distribution (QKD). IEEE Spectrum reports:

QKD is, in theory at least, an unbreakable method for sharing a cryptographic key between two parties that can then be used to encrypt and decrypt private messages. The technology is currently being tested by financial institutions, government entities, major technology firms and militaries.

“There is definitely a quantum apocalypse on the horizon at some point in the future, but that point is a sufficiently long time away that there is no need for panic,” Emin Gün Sirer, founder of the Avalanche cryptocurrency, told WSJ.

Umm, you might want to start panicking – or at least start planning.

As Dr. Lukin told NYT: “People no longer doubt it will be done. The question now is: When?” As AI has recently proven, I’m betting “when” will be much sooner than we’ll be ready for.

Mirror, Mirror...Everywhere

One biology fact that, until last week, that I never had to worry about is why life on earth not just is all DNA-based but also all share the same chirality. E.g., all life we know about has DNA with a right-handed double helix, uses right-handed sugar molecules, but builds proteins with left-handed amino acids. That’s just how life is, right?

DNA's mirror image could be scary. Credit: Bing Image Creator

But it turns out that life’s chirality is not a law of nature, and that scientists believe that “mirror life” is not only theoretically feasible but plausible within the next ten years. And, many of them believe, that is something we should be very worried about.

Last week, a group of scientists released a lengthy Technical Report on Mirror Bacteria: Feasibility and Risks, along with an accompanying commentary in Science: Confronting risks of mirror life. Long story short, this is a mirror into which we should look very cautiously – if at all.

The report explains the fundamentals:

In a mirror bacterium, all of the chiral molecules of existing bacteria—proteins, nucleic acids, and metabolites—are replaced by their mirror images. Mirror bacteria could not evolve from existing life, but their creation will become increasingly feasible as science advances.

Credit: Adamala, et. alia

That’s the kind of progress science makes, for better and, sometimes, for worse. The problem, as the report also points out, is:

Interactions between organisms often depend on chirality, and so interactions between natural organisms and mirror bacteria would be profoundly different from those between natural organisms. Most importantly, immune defenses and predation typically rely on interactions between chiral molecules that could often fail to detect or kill mirror bacteria due to their reversed chirality. It therefore appears plausible, even likely, that sufficiently robust mirror bacteria could spread through the environment unchecked by natural biological controls and act as dangerous opportunistic pathogens in an unprecedentedly wide range of other multicellular organisms, including humans.

“The threat we’re talking about is unprecedented,” co-author Prof Vaughn Cooper, an evolutionary biologist at the University of Pittsburgh, told The Guardian. “The consequences could be globally disastrous,” another co-author, Jack W. Szostak, chemist at the University of Chicago, agreed in The New York Times. 

OK, that does sound bad.

Michael Kay, MD, PhD, professor of biochemistry at the University of Utah and one of the contributors to the report & commentary, warns:

If these bacteria are able to grow at all—and there is evidence that they probably would be able to grow, at least to some extent, in our natural world—maybe, over time, they could evolve the ability to eat our food and convert it to mirror food. If that happened, that would release a brake on their growth, and then all these other controlling mechanisms, as far as we can tell, would not be effective against these mirror bacteria.

I was especially chilled by this statement from Professor Kay: “There is a real possibility that mirror bacteria would struggle to find enough food to eat in order to grow, but we are humble in the face of evolution.”

As we should be. Evolution tells us that life finds a way (or did you not see Jurassic Park?).

Credit: Adamala, et. alia

The authors believe this is a time for caution. They urge:

However, in the absence of compelling evidence for reassurance, our view is that mirror bacteria and other mirror organisms should not be created…In light of our initial findings, we believe that it is important to begin a conversation on how the risks can be mitigated, and we call for collaboration among scientists, governments, funders, and other stakeholders to consider an appropriate path forward.

The people involved in the report and commentary are not alarmists. They are scientists who have been working in the field. “It’s inherently incredibly cool,” co-author Kate Adamala, a synthetic biologist at the University of Minnesota, told The New York Times. “If we made a mirror cell, we would have made a second tree of life.”

Cool indeed. But when they started talking about risks, they grew more concerned. “We’ve all done our best to shoot it down,” Professor Cooper admitted to The New York Times. “And we failed.”

Not everyone is so worried. Andrew Ellington, a molecular biologist at the University of Texas at Austin, told Scientific American:  “I’d argue a mirror-image bacteria would be at a gross competitive disadvantage and isn’t going to survive well.” He is dismissive of efforts to curb research: “This is like banning the transistor because you're worried about cybercrime 30 years down the road. I’m not particularly worried about a mostly unknown threat 30 years from now versus the good that can be done now.”

For example, one of the uses researchers were investigating mirror life for was for prescription drugs. Professor Kay explains: “they have the potential to last for a much longer period of time and to open up a whole new class of therapeutics that would allow us to treat a variety of diseases that are currently challenging.” A moratorium on research could hamper progress in drug development, such as for H.I.V. or Alzheimer’s.

The authors conclude their commentary with a very reasoned plan: “To facilitate greater understanding of the risks associated with mirror life and further progress on governance, we plan to convene discussions on these topics in 2025. We are hopeful that scientists and society at large will take a responsible approach to managing a technology that might pose unprecedented risks.”

Yeah, well, that’s not going to happen. As with AI, nuclear weapons, or any other transformative technologies, we’re more likely to plunge ahead regardless of risks, afraid that other scientists/companies/countries will get a jump on us if we slow up.

I wish we were more thoughtful; I wish we were better at anticipating risks versus benefits. I’m proud of these scientists for their innovative work, and for being brave enough to advocate caution about it, but I’m not optimistic that their plea will be heeded. Someone is going to make mirror cells, and probably sooner than we expect.

Then, Professor Kay predicts: “Once a mirror cell is made, it's going to be incredibly difficult to try to put that genie back in the bottle.”