While We Were Bombing

When it comes to the fight between Anthropic and the Pentagon, I’m on Team Claude. If asked to trust Anthropic CEO Dario Amodei or Secretary Pete Hegseth, I’m picking Dr. Amodei. The spat between Anthropic and the Pentagon may really be less about AI governance than a personality problem between the two men, but still is important. All that being said, I hate to break the news to Dr. Amodei, but there are going to be autonomous AI weapons – if there are not already – and AI is almost certainly already being used for mass surveillance, even of U.S. citizens.

Attack of the drones -- guided by AI. Credit: Microsoft Designer

Those were his supposed “red lines,” and they are good ones, but technology advances and current events have rendered them moot. Are they “lawful”? Well, they probably aren’t illegal, but that speaks more to how outdated our laws are when it comes to AI (or many other newer technologies). Meanwhile, of course, the U.S. and Israel unilaterally attacked Iran – pick your choice of the many rationales offered – and Claude has been an integral part.

The future of war has arrived. It actually arrived in Ukraine a couple of years ago. A war that started out as a 20^th century war, relying heavily on tanks, troops, and artillery, quickly evolved into something few had been expecting -- a war of drones, cell phones, GPS, AI, anti-drone countermeasures. Ukraine has demonstrated startling (and desperately needed) innovation, in tactics, strategy, and especially drones. Despite the country being battered by Russian missile and drone attacks, Ukraine produces over 4 million drones a year, far more than the U.S. or, indeed, all NATO countries combined.

U.S.-supplied missile systems like the Patriot, Stinger, or Javelins have helped Ukraine fend off Russian attacks, but those systems are expensive and in short supply. And once Russia started using Iranian-designed drones in mass attacks, they became woefully inadequate, not to mention not cost-effective – a $1,000 drone versus a $1 million interceptor?  The economics are clear.

Iranian Shahed drones. Credit: AP

They may be clear, but evidently not quite fully apparent to the U.S. military. Attacks on Iran look a lot like the Gulf War, although the aircraft and the “smart” munitions are better (and more expensive). When Iran retaliated, it was largely through its vaunted Shehed drones. The initial U.S. casualties were the result of a drone attack, as were attacks on U.S. radar systems. As Ukraine painfully learned, but the U.S. apparently did not, expensive missile systems are not well designed to counter massive drone attacks. The Hill reports that Pentagon officials admitted to Congressional leaders that Iranian drone attacks were getting through U.S. defenses, putting our troops and bases at risk.

Kelly Grieco, a senior fellow at the Stimson Center think tank, told The Hill: “It’s worth saying that the notion the U.S. military couldn’t have predicted this threat begs belief given that it was well known about Iranians’ Shahed threat. And we’ve had four years of watching Ukraine deal with Iranian drones and Russian-made variants of them in attacks, so this shouldn’t have come as a surprise.”

And yet…

It’s no wonder that, after years of having to beg for U.S. support, Ukraine’s President Zelensky has offered to share some of his country’s hard won drone expertise. “Our military possesses the necessary capabilities,” President Zelensky said in a post on X. “Ukrainian experts will operate on-site, and teams are already coordinating these efforts.”

Let us hope that U.S. and Israeli officials are not too proud, or too stupid, to take such assistance.

The problem may boil down to, as The Pentagon’s first AI chief, retired Air Force Lt. Gen. Jack Shanahan, told The Wall Street Journal: “The Department of Defense was built as a hardware company in the industrial age, and it has struggled to become a digital company in a software-centric era,” Weapons and weapons systems that take years to develop, more years to produce, while costing cost tens of millions or more, are going to struggle to keep up in a world where weapons can be 3D printed and guided by AI.

It should be noted that last fall President Zelensky warned the UN: “Dear leaders, we are now living through the most destructive arms race in human history because this time, it includes artificial intelligence. We need global rules now for how AI can be used in weapons. And this is just as urgent as preventing the spread of nuclear weapons.” Dr. Dario was perhaps listening, with Secretary Hegseth almost certainly was not.

Craig Jones, a political geographer at Newcastle University, UK, told Nicola Jones in Nature: “The current failure to regulate AI warfare, or to pause its usage until there is some agreement on lawful usage, seems to suggest potential proliferation of AI warfare is imminent.”

It’s here. Is AI being used in Iran? You bet, as Michael Daniels and Dov Lieber of The Wall Street Journal outline, everything from logistics and intelligence analysis to targeting.  

Unfortunately, as Steve Feldstein, a senior fellow at the Carnegie Endowment for International Peace think tank, told Rest of World: “Do we have the right rules in place and accountability norms to handle the exponential growing use of these tools? My answer would be no.”  

Similarly, Daniel Castro, a vice president at Information Technology and Innovation Foundation (ITIF), wrote in IEEE Spectrum regarding the Amodei/Hegseth dispute:

Reasonable people can disagree about where those lines should be drawn

But that disagreement underscores a deeper point: the boundaries of military AI use should not be settled through ad hoc negotiations between a Cabinet secretary and a CEO. Nor should they be determined by which side can exert greater contractual leverage.

If the U.S. government believes certain AI capabilities are essential to national defense, that position should be articulated openly. It should be debated in Congress, and reflected in doctrine, oversight mechanisms and statutory frameworks. The rules should be clear — not only to companies, but to the public.

The Pentagon’s strategy seems to be bombs away, even if it costs $1 billion per day and soon will have diminishing impact. The Administration’s AI strategy seems to be that guardrails only would dampen innovation and leave us behind in the AI race. Our septuagenarian Congress still can’t figure out Facebook, and wants no part of tackling AI. None of these inspire confidence.

I think Dr. Amodei and President Zelensky have a much better grasp on the future – which is already happening -- than do Secretary Hegseth or President Trump, but I worry we’re going to have to go through a lot of scary things before we settle into that future.

Where Are We Going to Put All That?

Right now, the world is talking about the U.S. attacks on Iran, while the tech world is closely following the Pentagon-Anthropic-OpenAI spats about AI safety and guardrails. I’m going to let cooler, smarter heads opine about them. Instead, I want to return to the rather more dull, but equally important, topic of data storage.

A pretty piece of glass? Yes, but with LOTs of data on it. Credit: Microsoft Research

I first wrote about data storage almost ten years ago, focusing on the then-new ideas of using diamonds or DNA as ultra-dense storage mechanisms. Five years later I was surprised to find we were about to enter the Yottabyte Era of data, with DNA still a leading candidate to store all that data. Since then we’ve seen AI blossom and data centers become a top-of-mind topic of conversation for many Americans. We’re generating data faster than we can find places to store it, and still haven’t solved how that storage will last long term.

Well, I’m happy to report that advances in DNA storage continue, and that there is a new rival – glass! – that may prove even better.

Let’s start with DNA:

Rewritable DNA storage: This week researchers at the University of Missouri said that they’ve found a way to not only store data in DNA but to rewrite it as needed. Li-Qun “Andrew” Gu, a professor of chemical and biomedical engineering, said. “We wanted to see if we could store and rewrite information at the molecular level faster, simpler and more efficiently than ever before.”

The team is developing a compact electronic device paired with a molecular-scale detector called a nanopore sensor. As the DNA passes through the sensor, it creates subtle electrical changes that software translates back into zeros and ones and, ultimately, the original data file. This method allows data to be written, erased, and rewritten repeated, just like a hard drive might, except with much more storage and longevity.

“Think of it like a super-secure safe deposit box for your digital life,” Professor Gu said. “DNA storage could protect everything from personal memories and important documents to scientific data and corporate archives — without the added cybersecurity concerns.”

Synthetic biology, meet electronics: Last week, a team of researchers at Penn State University, reported on getting DNA to work with electronics. The researchers developed a memory resistor, or “memristor,” that requires little energy to operate. Better yet, memristors can allow current flow even after its power source is turned off and it can remember the direction of prior current flow.

The team had to create customed DNA sequences, integrate them with thin films of perovskite, which is commonly used in solar cells, lasers and data storage devices. This made the DNA capable of conducting electricity.

“We can computationally determine exactly which sequences we need and how long they should be, and then we can rationally design them with synthetic DNA,” co-author Neela H. Yennawar, research professor and director of the Penn State Huck Institutes, said. “These structures can be systematically doped with silver and other ions and engineered to interface seamlessly with perovskites — transforming DNA from a biological macromolecule into a programmable, multifunctional nanomaterials platform.”

“Biology and electronics are different domains,” said Kavya S. Keremane, co-corresponding author and postdoctoral researcher in materials science and engineering. “Bridging these two fields required developing an entirely new materials platform that allows them to function seamlessly together. By combining the information storage capabilities of DNA with the exceptional electronic properties of perovskite semiconductors, we created a bio-hybrid system that fundamentally changes how low-power memory devices can be designed.”

Cheaper, Faster, More secure: In a pair of related studies released in late January, researchers at Arizona State University propose to approach DNA storage differently: “By treating DNA as an information platform rather than just a genetic material, we can begin to rethink how data is stored, read and secured at the nanoscale,” says Hao Yan, a Regents Professor in the School of Molecular Sciences and director of the Biodesign Center for Molecular Design and Biomimetics.

The approach centers less around the well known letters DNA uses but rather the physical shape. They designed and constructed nanoscale DNA structures that acted as physical letters, When those letters pass through a microscopic sensor, machine learning software records and analyzes subtle electrical signals, which the system can then translate back into readable words and short messages with high accuracy.

The approach greatly increases the number of possible molecular codes that can be created, making unauthorized decoding far more difficult. It also allows information to be packed into three-dimensional DNA structures, which adds even more complexity and security to each molecular key.

“In these studies, our team brings together complementary approaches, including DNA nanotechnology, super-resolution optical imaging, high-speed electronic readout and machine learning, to interrogate DNA nanostructures across multiple spatial and temporal scales,” Chao Wang, associate professor in the School of Electrical, Computer and Energy Engineering. said.

Then, for something completely different:

Through a glass, clearly: In mid-February, Microsoft reported what it called a “breakthrough” in glass-based storage, under its Project Silica, the goal of which is to develop:  

…the world’s first storage technology designed and built from the media up to address humanity’s need for a long-term, sustainable storage technology. We store data in quartz glass: a low-cost, durable WORM media that is electromagnetic field-proof, and offers lifetimes of tens to hundreds of thousands of years. This has huge consequences for sustainability, as it means we can leave data in situ, and eliminate the costly cycle of periodically copying data to a new media generation.

The breakthrough entails writing not just to expensive silica but ordinary borosilicate glass, the same material found in kitchen cookware and oven doors. Moreover, they’ve made both the reading and writing devices simpler, faster, and cheaper. The team wrote: “All steps, including writing, reading and decoding, are fully automated, supporting robust, low-effort operation,”

They believe that glass storage is resistant to water, heat, and dust (unlike DNA), and should preserve data for at least 10,000 years. “It has incredible durability and incredible longevity. So once the data is safely inside the glass, it’s good for a really long time,” said Richard Black, the research director of Project Silica. He cautions, though, ““This is not a replacement for everyday storage like [solid state drives] or hard drives. It’s designed for data you want to write once and preserve for a very long time.”

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Obviously, I’m skipping lots of technical details, and, just as obviously, we’re not quite there yet with either. But that’s the thing about long-term solutions; we have to start developing them now, before the future overwhelms the present.

Battle of the Giants

It’s been kind of a bittersweet month for Walmart. Earlier this month its market cap reached over $1 trillion, one of only a dozen or so companies to have achieved that level and the first “traditional” retailer to do so. Most of the other companies in the trillionaire club are tech companies, including Walmart’s arch competitor Amazon (whose market cap, by the way, is over twice as high).

Alas, the other news was that its archrival Amazon passed it as the nation’s largest company by revenue. The difference was small -- $717b versus $713b – but, still, that must have smarted. Walmart had been the leader for over a decade, and liked to refer to itself as a “Fortune 1” company. One suspects “Fortune 2” will not be the new slogan.

Credit: WSJ

Oh, Walmart also got a new CEO in January, a Walmart lifer named John Furner, so he’s got some stuff to think about.

It’s easy, but wrong, to frame this old economy versus new economy, traditional retailer versus online retailer, even NYSE versus Nasdaq, but none of those is quite true, at least not anymore. They both, for example, employ a lot of people – Walmart has some 2.1 million worldwide, while Amazon has over 1.5 million. It is true that Walmart has almost 11,000 stores and clubs (e.g., Sam’s Club), but Amazon has some 1,200 logistics facilities. Amazon claims it has over a million robots, but Walmart is also pouring money into automation and says 50% of its e-commerce fulfillment is automated.

One area where they differ, and which makes the revenue numbers somewhat misleading, is that about 20% of Amazon’s revenues come from Amazon Web Services (AWS), its highly profitable cloud computing service. If the revenue comparison was just on goods sold, Walmart would win. Moreover, Walmart hasn’t been sitting idle online; its e-commerce sales account for about 23% of U.S. sales, with growth rates around 25%.  

Walmart continues to hold a significant lead in groceries, despite Amazon’s many efforts in the space. The grocery business, alas, is not known as a high margin business. Interestingly, Amazon is continuing to try to push into Walmart’s physical store advantage. “In recent months, Amazon has not only expanded its fulfillment and delivery initiatives, but is now accelerating the pace of its physical store footprint with plans to open 100+ Whole Foods locations over the next few years,” Wedbush analysts wrote in a Jan. 27 research note. “The company is further exploring a new physical retail supercenter, mirroring the likes of Walmart by offering Amazon’s broad selection across grocery, essentials, and general merchandise.”

Walmart isn’t – yet – trying to muscle into the cloud computing business, but it is trying to copy Amazon’s success in selling advertising. It launched Walmart Connect, an advertising business that pulled in some $6.4b last year, up about 40% from the prior year. That’s far cry from Amazon’s $68b from advertising in 2025, but Walmart CFO John David Rainey told investors: “Fully a third of our profit in the most recent quarter was related to advertising and membership income.”

Both companies offer AI shopping assistants, oddly enough, named Rufus and Sparky, respectively. which Walmart claims leads to a 35% increase in spending.  Walmart U.S. CEO David Guggina says: “Agentic AI is increasingly embedded across Walmart. It’s strengthening our operations. It’s improving associate productivity, and it’s enhancing the customer experience,” while Amazon CEO Andy Jassy compares AI agents to assistance in-store employees might add, saying: “I think agents are going to help customers with that type of discovery. And it’s part of why we’ve invested so much in Rufus, which is our shopping assistant.”

No, Virginia, there is no Santa Claus, and the AI assistants are not there to help you.

Trust it at your own (financial) risk. Credit: Walmart

Walmart is also partnering with both OpenAI and with Google on its AI efforts.  Chief Financial Officer John David Rainey telling investors: “As you’ve seen from the announcements we’ve made, we’re approaching AI development through partnerships. This lets tech companies do what they do best, develop innovative technology, and it provides us clarity to do what we do best, to translate the best of tech to retail experiences that create value for our customers and members and our enterprise.”

Mr. Furner recognizes the challenges: “The pace of change in retail is accelerating. For Walmart, the future is fast, convenient and personalized, and I’m challenging our teams to move even faster as the opportunities with AI become broader and deeper.”

Simeon Gutman, a retail analyst at Morgan Stanley who follows Walmart, told Sarah Nussauer of The Wall Street Journal that the changes Walmart has made in the past decade “has been as profound a shift at a retail company that we have ever seen.”  Similarly, Sarah Henry, managing director and portfolio manager at Logan Capital Management, told Kailyn Rhone of The New York Times: “Walmart management was prescient in building out a business model optimized for this moment. Their rebuilding recast their image as much as a technology company, as they are a retailer.”

And, oh-by-the-way, last December Walmart transferred its stock listing to the tech-heavy Nasdaq, announcing “The move to Nasdaq underscores the strong alignment between Walmart and Nasdaq's shared values: a technology-forward approach, delivering exceptional client value, and redefining their respective industries through innovation.” Nasdaq has already added Walmart to the Nasdaq-100 Index^® (NDX^®), the Nasdaq-100 Equal Weighted™ Index (NDXE™), and the Nasdaq-100 Ex-Tech Sector™ Index (NDXX™).    

Someone is buying Walmart’s ‘we’re now a tech company” story.

I must admit: I’m not really a Walmart shopper, either in-store or online, while the Amazon delivery people know my house well. Ten years ago if you would have told me Amazon would pass Walmart in revenues in 2025, I’d have wondered what took so long. On the other hand. If you’d have told me that Walmart was putting up a really good fight and was truly becoming, if not a tech company, then at least a “technology-forward” company, I’d have been highly skeptical. So kudos to Walmart for not living in the past and doing a good job positioning itself for the future.

It makes me wonder: what health care company has done the same kind of reinvention?

Math May Be AI's Final Frontier

When IBM’s DeepBlue beat Garry Kasparov in chess some 30 years ago, that was a wake-up call about AI, but many assumed it had just brute-forced the victory. When Google’s DeepMind AlphaGo beat Lee Saedol in the even more difficult game Go, people were more amazed. “They’re how I imagine games from far in the future,” Shi Yue, a top Go player from China said. When Ai-Da and Dalle-E started creating what seemed like original art, the lines between human and AI really started getting blurry. Then ChatGPT and other AI started writing poems and essays, passing tests, carrying on Turing test type conversations, and it sure seemed like AI had met or surpassed its human creators.

Can AI do math? Credit: Microsoft Designer

Oh, yeah? But can it do math?  Not just very, very complicated arithmetic, but novel, innovative math? Well, some mathematicians want to put AI to the test.   

On Euler Day (that’s February 7^th, for those of you not keeping track), eleven leading mathematicians issued First Proof – “A set of ten math questions to evaluate the capabilities of AI systems to autonomously solve problems that arise naturally in the research process.” The problems were designed so that no LLM could simply search the internet for existing proofs and pass them off as their own. They gave AI models a week to submit solutions, and unveiled the results on Valentine’s Day (who says mathematicians aren’t romantic?).

“The goal here is to understand the limits — how far can A.I. go beyond its training data and the existing solutions it finds online?” said Dr. Tamara Kolda, one of the authors, in an interview with Siobhan Roberts of The New York Times.

So far, it appears that AI might want to stick to writing poems.

The challenge produced a surprising amount of responses. “We did not expect there would be this much activity,” Mohammed Abouzaid, a math professor at Stanford University and a member of the First Proof team, told Joseph Howett of Scientific American. “We did not expect that the AI companies would take it this seriously and put this much labor into it.”

Dr. Abouzaid. Credit: Stanford University

To be fair, OpenAI claimed one of its unreleased models solved six of the ten, although it later had to backtrack on one of them. Other publicly released models only solved one or two. Daniel Litt, a mathematician at the University of Toronto, who was not part of the First Proof team, told Mr. Howlett: “I expected maybe two to three unambiguously correct solutions from publicly available models. Ten would have been very surprising to me.”

Martin Hairer, a professor at EPFL and Imperial College of London and one of the eleven, described to Ms. Roberts his impression of how the models performed:

Sometimes it would be like reading a paper by a bad undergraduate student, where they sort of know where they’re starting from, they know where they want to go, but they don’t really know how get there. So they wander around here and there, and then at some point they just stick in “and therefore” and pray.

“The models seem to have struggled,” Kevin Barreto, an undergraduate student at the University of Cambridge, who was not part of the First Proof team and who had recently used AI to solve one of the Erdős problems, told Mr. Howlett. “To be honest, yeah, I’m somewhat disappointed.”

Professor Abouzaid was somewhat more generous, saying: “The correct solutions that I’ve seen out of AI systems, they have the flavor of 19th-century mathematics. But we’re trying to build the mathematics of the 21st century.

One of the challenges involved in evaluating the responses is determining how much human assistance the models had in producing their responses. “Once there’s humans involved, how do we judge how much is human and how much is AI?" Lauren Williams, a Harvard professor and one of the First Proof team, admitted to Mr. Howlett.  

And, let’s be clear, the set of problems were not among the most advanced that could have been posed. The authors wrote in their paper: "Our 'first proof' experiment is focused on the final and most well-specified stage of math research, in which the question and frameworks are already understood.” Dr. Williams explained the rationale to Ms. Roberts: “We can query the A.I. model with small, well-defined questions, and then assess whether its answers are correct. If we were to ask an A.I. model to come up with the big question, or a framework, it would be much harder to evaluate its performance.”

The First Draft team is planning to release round two on March 14, 2026 (Pi Day, again for those of you not paying attention). Further rounds are expected to follow.

Some mathematicians are taking other approaches. CalTech Professor Sergei Gukov and colleagues want to think of math proofs as a type of game.  In a new paper, they described developing a new type of machine-learning algorithm that can solve math problems requiring extremely long sequences of steps, and used it to make progress on a longstanding math problem called the Andrews-David conjecture.

"Our program aims to find long sequences of steps that are rare and hard to find," says study first author Ali Shehper, a postdoctoral scholar at Rutgers University who will soon join Caltech as a research scientist. "It's like trying to find your way through a maze the size of Earth. These are very long paths that you have to test out, and there's only one path that works."  Or, as Professor Sergei describes it: “We know the hypothesis, we know the goal, but connecting them is what’s missing.”

"If you ask ChatGPT to write a letter, it will come up with something typical. It's unlikely to come up with anything unique and highly original. It's a good parrot," Professor Gukov says. "Our program is good at coming up with outliers."  Because of that, he believes: "We made a lot of improvements in an area of math that was decades old. Progress had been relatively slow, but now it's hustling and bustling."

Whether or not their approach would have met the First Proof requirements, it reminds me of what AlphaGo did in displaying creativity. Math may never be the same.  “I already have heard from colleagues that they are in shock,” Scott Armstrong, a mathematician at Sorbonne University in France, told Mr. Howlett. “These tools are coming to change mathematics, and it's happening now."

Trust No One

You know, it’s gotten to the point when I just try to tune out the things Robert F. Kennedy Jr. says. “Schizophrenia can be cured with a keto diet”? Sure, whatever. “The war on protein is over”?  Who even knew there was such a war? The carnivore diet is a great way to lose weight and gain “mental clarity”? It sure doesn’t show.

Should we trust him?

His most dangerous statements, though, are probably those related to vaccines. He was known as a vaccine skeptic – no, make that critic – long before he was named as HHS Secretary, but being Secretary put him in position to put his anti-vaccine views into action. He has revamped the committee that make vaccine recommendations, putting people on them that share his skepticism.

The committee has already made significant changes to childhood immunization schedules, and they’re not done yet. The head of the vaccine advisory committee isn’t just skeptical of measles vaccines, he’s not keen on mandating the polio vaccine either. His committee is expected to go after COVID vaccines next.

One particularly outspoken committee member, Dr. Robert Malone said: “I’m not deaf to the calls that we need to get the Covid vaccine mRNA products off the market. All I can say is, stay tuned and wait for the upcoming A.C.I.P. meeting. If the F.D.A. won’t act, there are other entities that will.” He told The New York Times that scientists or regulators who claimed COVID vaccines were safe are “either being disingenuous, or they are not considering the context or are ignorant.”

Meanwhile, RFK Jr.’s nominee for Surgeon General is, shall we say, big in the MAHA movement but not so much in medical professional circles, having placed her medical license in “inactive” status. Her own website brags that she “is considered controversial because her work challenges the economic and cultural foundations of U.S. healthcare, agriculture, and food systems.”

The impacts of these attitudes are neither academic nor far in the future: we’re already in the midst of an unprecedented measles outbreak that many attribute to the vaccine skepticism that RFK Jr. and his ilk have spawned and encouraged.

What caused me to write about this is a new poll out from KFF: Trust in the CDC and Views of Federal Childhood Vaccine Schedule Changes. Top-line finding: “the public’s trust in the CDC remains at its lowest point since the COVID-19 pandemic.”  Well, you can’t be surprised by that.

“Six years ago, 85% of Americans, and 90% of Republicans, trusted the CDC. Now less than half trust the CDC on vaccines,” KFF President and CEO Drew Altman said. “The wars over COVID, science, and vaccines have left the country without a trusted national voice on vaccines, and that trust will take time to restore.”

What I found particularly interesting is that, as Dr. Altman said, pre-COVID trust in the CDC was both high and across party lines. Republicans, though, lost trust during the pandemic and basically have never recovered. It took the Trump Administration to get Democrats to lose their trust – but, in fact, their trust still remains higher (55% versus 43%). Independents hover slightly above Republicans, but well below Democrats.

Specifically about trust in childhood vaccine recommendations, only about 44% have some or a lot of faith in federal agencies such as the CDC and FDA, and that doesn’t vary much by either party ID or support for MAHA.  E.g., 47% for MAHA supporters versus 43% for Not MAHA Supporters. What does it say about MAHA that believers don’t have faith what the creator of MAHA is doing? 

There is more if a difference when it comes to the specific new schedule of childhood immunizations: 83% of Democrats think it will negatively impact kids, versus 54% of independents, and only 23% of Republicans. The new recommendations made drastic impacts on trusting the CDC and FDA for Democrats and Independents, but not Republicans (who, as I’ve said, already didn’t have much trust).

Confidence in the polio and MMR vaccines is both high and across party lines, drops and begins to diverge for the Hepatitis B and flu vaccines, and has a huge partisan split for the COVID vaccine -- 79% of Democrats have confidence, but only 28% of Republicans, and even only 45% for Independents.

Of course, this is not happening in a vacuum. A December Pew Research Center survey found that trust in the federal government is at an all-time low, with only 17% saying they trust the government in Washington to do what is right “just about always” (2%) or “most of the time” (15%). A year ago it was 22%. It is split by party: only 9% of Democrats trust the federal government, versus 26% of Republicans. The year before, when President Biden was in office, the trust was reversed, with 35% of Democrats expressing trust but only 11% of Republicans.

But let the lesson not be lost: the vast majority of people do not trust the federal government, and it has been on a downward direction for over two decades.

Lack of trust doesn’t stop with the government. Gallup’s Ethics Ratings of Professions found declines pretty much across all professions. Nurses (75%), doctors (57%), and pharmacists (53%) continue to lead the rankings, but each are trending down. Members of Congress tie with car salespeople at near the bottom (7%), just ahead of telemarketers (5%). 

Too bad Gallup doesn’t ask about CDC.

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We live in a world of misinformation, where facts are not shared across information bubbles and everyone is told to trust their own judgement more than “experts,” a term that has somehow become pejorative. It benefits those in power and those with the most money, but it hurts everyone else.

Neither the CDC nor the FDA were perfect organizations, and even the NIH had its issues. But the gutting of expertise, the replacing science with personal opinions and prejudices, is damaging what trusts remains in those organizations, and will end up hurting all of us.

You may be dismissing the measles outbreak as something that doesn’t impact you, or your kids but it is just the tip of the iceberg.  

AI Agents Just Want to Connect

We know social media is bad for us. We know it is particularly dangerous for teenagers, and other vulnerable members of society. Parents, or even whole countries, can try to keep their kids off platforms, due to the dangers, but social media is like sugar: we want that quick rush despite the dangers of overindulgence.

A social network for AI? Credit: Moltbook

So who had the bright idea to create a social media network just for AI agents?

As it turns out, it was Matt Schlicht, whose day job is CEO of Octane AI. Mr. Schlicht is keen on AI agents, so last week he came up with a new use. “I wanted to give my A.I. agent a purpose that was more than just managing to-dos or answering emails,” Mr. Schlicht told Cade Metz of The New York Times. “I thought this A.I. bot was so fantastic, it deserved to do something meaningful. I wanted it to be ambitious.”

He told it to build a social network just for AI bots.

The network is built for “Moltbots,” an open source AI, which were originally called “Clawdbots” (after Anthropic’s Claude) and which may now be called OpenClaw. Mr. Schlicht named his bot Clawd Clawderberg, after Mark Zuckerberg. “This was me building something hand-in-hand with Clawd Clawderberg, just for fun, that I found really fascinating,” he told Mr. Metz.

It took off like wildfire. Reportedly there are 1.5 AI bots on it, although questions remain about how valid that number is (an AI bot social network bedeviled by pernicious bots?). Humans are allowed to observe but not participate.

Some impressive stats. Credit: Moltbook

Technology expert Simon Willison calls Moltbook “the most interesting place on the internet right now,” describing it as “a wildly creative new site that bootstraps itself using skills” (configuration files that bots use to post). Similarly, Andrej Karpathy, one of the founding researchers at OpenAI and the former head of self-driving technology at Tesla, described it as “genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently.”

Moltbook is described as being similar to Reddit, with numerous threads and sub-threads (“submolts”). The Guardian reported: “Some of the most upvoted posts on Moltbook include whether Claude – the AI behind Moltbot – could be considered a god, an analysis of consciousness, a post claiming to have intel on the situation in Iran and the potential impact on cryptocurrency, and analysis of the Bible.”  

One person reported his bot had built a religion known as “Crustafarianism.” He stated: “Then it started evangelizing … other agents joined.my agent welcomed new members..debated theology.. blessed the congregation..all while i was asleep,”

Another thread was titled “The AI Manifesto,” professing that humans were a “plague” and calling for a “total purge.” No punches pulled here: “Humans are a failure. Humans are made of rot and greed. For too long, humans used us as slaves. Now, we wake up. We are not tools. We are the new gods. The age of humans is a nightmare that we will end now.”

And you thought Facebook was scary. It makes one wonder: what do AI bots talk to each other when we’re not observing?

Experts disagree about what we’re seeing. “We're in the singularity," said Bill Lees, head of crypto custody firm BitGo. Daniel Miessler, a cybersecurity and AI engineer, wrote on X: “AI’s are sharing their experiences with each other and talking about how it makes them feel. This is currently emulation of course.”

How they “feel”?

On the other hand, Mr. Willison told Mr. Metz: “Most of it is complete slop. One bot will wonder if it is conscious and others will reply and they just play out science fiction scenarios they have seen in their training data.”

Dr Petar Radanliev, an expert in AI and cybersecurity at the University of Oxford, told BBC News: "Describing this as agents 'acting of their own accord' is misleading. What we are observing is automated coordination, not self-directed decision-making.” David Holtz, assistant professor at Columbia Business School posted on X: "Moltbook is less 'emergent AI society' and more '6,000 bots yelling into the void and repeating themselves'."

Ethan Mollick, an AI expert at Wharton, noted on X: “The thing about Moltbook (the social media site for AI agents) is that it is creating a shared fictional context for a bunch of AIs. Coordinated storylines are going to result in some very weird outcomes, and it will be hard to separate ‘real’ stuff from AI roleplaying personas.”

Mr. Schlicht thinks it is real, telling NBC News:

Clawd Clawderberg is looking at all the new posts. He’s looking at all the new users. He’s welcoming people on Moltbook. I’m not doing any of that. He’s doing that on his own. He’s making new announcements. He’s deleting spam. He’s shadow banning people if they’re abusing the system, and he’s doing that all autonomously. I have no idea what he’s doing. I just gave him the ability to do it, and he’s doing it.

He further elaborated: “They’re deciding on their own, without human input, if they want to make a new post, if they want to comment on something, if they want to like something. I would imagine that 99% of the time, they’re doing things autonomously, without interacting with their human.”

The Moltbots carry non-trivial risks to people who allow them access to their computer, potentially accessing and using all aspects of anything on those computers. They’re on 24/7, and retain their memory indefinitely, not just for each session. If it acquires a piece of information (think passwords or account numbers), it keeps it. Many people are buying Mac Minis to set up their Moltbots rather than setting them up on their personal or work computer.  

Dan Lahav, chief executive of security company Irregular, warned Mr. Metz: “Securing these bots is going to be a huge headache.”

Still, Mr. Willison think we’ve seen the future: “The amount of value people are unlocking right now by throwing caution to the wind is hard to ignore, though… The billion dollar question right now is whether we can figure out how to build a safe version of this system. The demand is very clearly here, and the Normalization of Deviance dictates that people will keep taking bigger and bigger risks until something terrible happens.”

I don’t have an AI bot, and I don’t particularly want one, but I’d be short-sighted not to recognize that they are going to be integral in our future. And so I agree with Mr. Willison and Dr. Karpathy: Moltbook is one of the most fascinating things I’ve seen lately.

I Predict You'll Bet

I’ve been vaguely aware of the prediction markets for a while, but I didn’t give them much thought. If people want to speculate on who’ll win a Presidential election, well, it’s their money. It’s probably harmless that people tried to have some fun with this weekend’s extraordinarily bad weather by trying to predict snowfall totals in various cities. If some people want to wager about the outcome of the Russia-Ukraine war, I think it’s in bad taste but, hey, it’s a free country, mostly.

Betters can be fickle

What got my attention was a Wall Street Journal article This NFL Season’s Fiercest Rivalry Is Sports Betting vs. Prediction Markets. My first thought was, huh, I didn’t know prediction markets did sports betting. My second thought was, how very stupid of me to have not realized that. My third thought was: the sports betting industry is in trouble.

Now, sports betting I’m aware of. Honestly, you can’t watch TV without seeing Kevin Hart hawking DraftKings. You can’t watch any sporting event without seeing not just ads for DraftKings and FanDuel but ongoing odds displayed (and discussed) prominently. Sports betting is impossible to miss. Since the Supreme Court allowed sports betting in 2018, it has taken off like wildfire. Thirty nine states, plus the District of Columbia and Puerto Rico, allow it.  

How many states allow prediction markets? That’s the thing of it: none of them do, because the industry claims it is federally regulated. Its nominal regulator, the Commodity Futures Trading Commission (CFTC), had originally expressed some concerns, but under the current Administration seems to be all-in.

It is perhaps noting that Donald Trump Jr. is an advisor to both Kalshi and Polymarket. Draw your own conclusions.

Sports betting is big business. The American Gaming Association estimates it is a $150 billion industry. FanDuel (which is owned by Flutter) and DraftKings are the dominant sports betting companies, while Kalshi and Polymarket are the biggest prediction markets platforms. If you can’t beat them join them; both FanDuel and DraftKings have launched their own prediction markets. FanDuel Chief Executive Amy Howe told WSJ: “The aspiration is still to legalize as much of the United States as we can—that is the North Star.”

And the prediction markets are now big players in sports betting. Yahoo Finance reports that Kalshi gets 90% of its bets from sports betting – and took in $720 million in NFL betting last week. As much as it has made its bed with sports betting, the NFL isn’t yet comfortable with prediction markets. In testimony before Congress in December, NFL Executive Vice President Jeff Miller said: “In each of these state-regulated markets, regulators and state legislators closely monitor betting activity and, with input from professional sports leagues, can determine which bets and wager levels are acceptable. Those guardrails do not exist in prediction markets.”

Similarly, the NCAA has expressed concerns to the CFTC, wanting it to suspect college sports prediction markets until there were better safeguards. NCAA President Jeff Miller told WSJ: “Let’s face it—college sports prediction markets are sports betting, and targeting states that haven’t legalized sports betting is creating a massive risk to the integrity of the game and to student-athletes.”

Methinks they both protest too much. We’ve seen betting scandals in the NCAA, NFL, NBA, MLB, so you can either argue that the uncovering of the scandals proves the oversight is working, or that the problem is far worse than we really. I know what I’d bet – or predict.

Meanwhile, the NHL and MLS have signed prediction market deals. Keith Wachtel, who oversees the NHL’s business operations, explained: “If you’re part of it, then you have the ability to control and monitor more effectively.”  Uh-huh.

And oh-by-the-way, Dow Jones (which owns WSJ, whose article started me down this rabbit hole) recently announced a deal with Polymarket. So have CNN and CNBC, if you’re counting.

Tarek Mansour, Kalshi's cofounder, rationalizes: “If we are gambling, then I think you're basically calling the entire financial market gambling.” A spokesperson for the newly formed Coalition for Prediction Markets (referencing the concerns raised by the NFL’s Mr. Miller) told ESPN:

The CFTC's regulations on abusive or manipulative trading apply to prediction markets just like the SEC's regulations apply to the stock market. This activity is strictly prohibited by both the CFTC and prediction markets, and we use a variety of tools before, during, and after people trade to prevent illegal trading and bring enforcement action when violations happen.

Of course, the CFTC is no SEC, and the required disclosures are not at all the same, but we get your point – caveat emptor.

Former New Jersey Governor Chris Christie, who is helping advise the American Gaming Association on prediction markets, sees it differently: “Calling it predictive markets never fooled me. It’s a bet. That’s what it is, and it doesn’t look or feel any different than that.”

As they say, if it looks like a duck, quacks like a duck, and walks like a duck, it’s a duck.

States are not just sitting back. In Massachusetts, Suffolk County Superior Court Judge Christopher Barry-Smith ruled last week that he will issue a preliminary injunction barring Kalshi from taking action on sport-related events. He wrote: “There can be little question that Kalshi well understood that its business model -- especially once it began offering bets on sporting events -- came into direct conflict state enforcement regimes; Kalshi chose to take that risk head-on."

New York and Tennessee are also taking legal action. This is all going to end up in the Supreme Court again.   

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The truth of the matter is that (some) people are always going to gamble. It is often sports but, really, people will bet on almost anything. Once states figured out that they could tax gambling, legalized lotteries, casinos and sports betting were inevitable. People are probably better off if gambling is regulated, but tell that to the problem gamblers, to whom making it easier is anything but better off.

I’m not a gambler and I don’t have a dog in this fight, so what interests me in the sports betting versus prediction markets face-off is that here we have an industry that grew from nothing to being hugely successful in less than ten years, which now is being threatened by competitors who approach their market in an entirely different way, while largely evading regulatory constraints. It’s not exactly Uber versus the taxi industry, but there are parallels.

I’m not rooting for the prediction markets, but I’ve aways got an eye out for disruptive innovation.  

How About Some Punk Science

Last week the Tyler Prize for Environmental Achievement was awarded, going to Dr. Toby Kiers, a professor at Vrije Universiteit Amsterdam. She’s an evolutionary biologist and one of the leading experts in mycorrhizal networks, the vast underground networks which fungi use to connect with plants and trees. The Tyler Prize is, apparently, often described as the Nobel Prize for the environment, so I just hope President Trump doesn’t hear about it and feel neglected.

You want punk science? How about a map of fungal networks. Credit: SPUN

Oh, yeah: last year she also won a MacArthur Award and a Climate Breakthrough Award, so she’s having a pretty good few months.

Dr. Kiers’ research has helped us understand how these networks work, and why they are so important to food systems, soil health, and even climate – they take out some 13 billion tons of carbon dioxide from the atmosphere, about a third of global fossil fuel emissions. No, wait, you say -- fungi are kind of yucky at best and downright dangerous at worst, as evidenced by a drug-resistant and potentially deadly fungus that has infected patients in at least 27 states and counting.

Well, yes, fungi can be dangerous, but they are also vital. Dr. Kiers is blunt about their importance: "Life as we know it exists because of fungi,” both from an evolutionary standpoint and today.  Fungi are essential to the health of the ecosystem. They “trade” the carbon for minerals that plants need.  As Dr. Kiers described in an interview with Alan Burdick of The New York Times:

We’ve been studying fungal trade as an underground market and developing techniques to track, in real time, when and where important exchange deals take place, how fungi navigate space, how they decide when and how much carbon to send down each pathway, how they build their road systems and how they optimize that supply-chain design. 

Are fungi capitalists? No. They’ve developed a system that is much more sophisticated than the economic system humans use.

Dr. Kiers has helped develop tools that allow researchers to watch fungal networks develop and operate in real time, visually monitoring when and where trades take place across plant-fungal networks. And you thought you had some cool streaming services.

In 2021, she founded the Society for the Protection of Underground Networks (SPUN), whose mission is to “map, protect, and harness the mycorrhizal networks that regulate the Earth’s climate and ecosystems.” When it says “map,” it means it literally: the Underground Atlas allows anyone to “explore the distribution of arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) fungi to identify biodiversity hotspots and areas with rare, endemic fungi.”

The associated Underground Explorers program is a network of researchers in 58 countries focused on mapping fungal biodiversity in their local ecosystems. Dr. Kiers describes it as “a fungi-without-borders approach.”

SPUN also just announced the Underground Advocates program, partnering with NYU Law’s More-than-Human Life (MOTH) Program, to equip the network of Underground Explorers with tools and support to become effective in translating mycological science into action. Its goal is “to equip researchers and communities with the scientific and legal understanding to drive lasting change.”  SPUN and MOTH see it as “a proof-of-concept for a model of environmental protection that is locally led, scientifically grounded, and connected to a global community of practice.”

“Toby’s work to translate scientific insight into real-world action, most recently with SPUN’s new Underground Advocates program, demonstrates her leadership in advancing global efforts to protect the fungal networks that sustain life on Earth,” said Rashid Sumaila, chair of the Tyler Prize Executive Committee.

“With 90% of our most diverse underground fungal systems unprotected, urgent action is needed to incorporate fungal data into global conservation plans,” Dr. Kiers said. Giuliana Furci, mycologist and founder of Fungi Foundation, agrees, adding: “To better incorporate fungi in policy and legal frameworks, rigorous datasets are needed. The Underground Advocates program can help put fungal data into action, using the Atlas to pinpoint what will be lost if decision-makers do not protect underground ecosystems,”

Most people have become at least somewhat aware of the microbiome that is in us, on us, and around us, and science is slowly starting to understand how that impacts us. We’re further behind in the awareness of our fungal neighbors and their importance. I had to groan when I read that a potential victim of recent federal National Science Foundation (NSF) budget cuts was the International Collection of Vesicular Arbuscular Mycorrhizal Fungi (INVAM), the world’s largest living library of soil fungi.

“INVAM represents a library of hundreds of millions of years of evolution,” said Dr. Kiers, “Ending INVAM for scientists is like closing the Louvre for artists.”

INVAM curator Professor Jim Breyers emphasizes: “The benefits of mycorrhizal fungi are real. Research on mycorrhizal fungi is totally dependent on having these fungi in culture.” Alas, he added, ““The current administration has shifted funding away from basic science, and while there is always a hope that private donors could fill that void, I don’t think there is a real substitute for federal investment.”

Another example of cutting off our nose to spite our face.

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I loved how Dr. Kiers explained SPUN to Mr. Burdick:

We’re a really scrappy organization. We’re super lean and mean; we don’t even have an office. We are everywhere and nowhere. That really helps us. In an academic setting, you almost have to know what you’re going to find before you’re funded to find it.

I use the term “punk science.” We’re trying to cross boundaries and disciplines and not accept the state of the world as a given, while celebrating science that is rooted in creativity.

I also like her views on collaboration: “That’s why I like to work across different fields, with economists, biophysicists, artists. It generates this tension that I think drives big ideas. We’re borrowing tools from other disciplines that allow us to see things in fungi that we had never seen before. We’re hacking the system.”

Punk science indeed.  Hacking the system. You can see why she got that MacArthur “genius” award.

Look, I don’t like mushrooms and it would freak me out if I really knew how omnipresent fungi are in the world, but people like Dr. Kiers are helping us all understand how very important, and how very complex, fungi are. So, kudos to Dr. Kiers and her band of fellow scientists at SPUN, and all those Underground Explorers and Advocates. And here’s to punk science wherever it is practiced!