War -- and Healthcare -- On the Cheap

Like many of you, I’m watching the war in Ukraine with great interest and much support. For all the fuss about expensive weapons -- like F-16 fighters, Abrams tanks, Stryker and Bradley armored fighting vehicles, Patriot missile defense systems, Javelin anti-tank missiles, Himars long range missiles, and various types of high tech drones -- what I’m most fascinated with is how Ukraine is using inexpensive, practically homemade drones as a key weapon.

Making your own (combat?) drone Credit: Bing

It's a new way of waging war.  And when I say “waging war,” I can’t help but also think “providing health care.” It’s not so much that I think drones are going to revamp health care, but if very expensive weapons may, in fact, not be the future of warfare, maybe very expensive treatments aren’t necessarily the future of healthcare either.

Just within the last two weeks, for example, The New York Times headlined Budget Drones Prove Their Value in a Billion-Dollar War, AP said Using duct tape and bombs, Ukraine’s drone pilots wage war with low-cost, improvised weapons, ABC News reports: Inside Ukraine’s efforts to bring an ‘army of drones’ to war against Russia, and Defense News describes how Cardboard drone vendor retools software based on Ukraine war hacks.

This is not the U.S. military-industrial complex’s “shock-and-awe” kind of warfare; this is the guy-in-his-garage-building-his-own-weapons kind of warfare.

Ukraine’s minister for digital transformation, Mykhailo Federov, says the government is committed to building a state-of-the-art “army of drones.”  He promises: “A new stage of the war will soon begin.”

NYT detailed:

Drones made of plastic foam or plastic are harder to find on radar, reconnaissance teams said. Ukraine buys them from commercial suppliers who also sell to aerial photographers or hobbyists around the world, along with parts such as radios, cameras, antennas and motors. The drone units mix and match parts until they find combinations that can fly past sophisticated Russian air defenses.

“The doctrine of war is changing,” one Ukrainian commander said.  “Drones that cost hundreds of dollars are destroying machines costing millions of dollars.”  The AP discusses how an elite drone unit – “a ragtag group of engineers, corporate managers and filmmakers” -- “assembled with just $700,000, has destroyed $80 million worth of enemy equipment.”

Dmytro Kovalchuk, CEO of drone manufacturer Warbird, told ABC News: “In Ukraine, not a single state enterprise is producing drones. It's all private enterprises, sometimes partnerships…It [the drone] costs $1,000 and can destroy a tank that costs $500,000.”

And it is not just attacking tanks or just from the air; Just last month, Ukraine used a sea drone to damage an expensive Russian warship. 

One of the many reasons the war in Ukraine is important is because China is watching closely to see what might happen if it were to invade Taiwan, and I’m hoping Taiwan and its allies, including the U.S., are paying close attention to the importance of drones. NYT is skeptical, charging: “A new generation of cheaper and more flexible vessels could be vital in any conflict with China, but the Navy remains lashed to big shipbuilding programs driven by tradition, political influence and jobs.”

“The U.S. Navy is arrogant,” said retired admiral Lorin Selby, who used to head the Office of Naval Research. “We have an arrogance about, we’ve got these aircraft carriers, we’ve got these amazing submarines. We don’t know anything else. And that is just wrong.”  Another former officer agreed: “Right now, they are still building a largely 20th-century Navy.”

“We are trying to improve Navy power, but we need to do more than that: We need to reimagine Navy power,” he also said. “We’re kind of at a pivotal point in history. It is vital that we throw off old conventions.”

It’s not that the Navy is unaware of the potential of drones; as NYT acknowledged, it has been testing integrating “drone boats, unmanned submersible vessels and aerial vehicles capable of monitoring and intercepting threats over hundreds of miles.” It’s more that it isn’t a priority; the budget devoted to it, one officer lamented, is “the dust particle on the pocket lint of the budget.”

The Wall Street Journal was more optimistic, reporting on details of a recent speech from Kathleen Hicks, the deputy secretary of defense. She vowed that DoD “plans to spend hundreds of millions of dollars to produce an array of thousands of air-, land- and sea-based artificial-intelligence systems that are intended to be ‘small, smart, cheap’”

Of course, when fighter planes now can cost $135 million each, aircraft carriers cost $13b apiece, and the overall DoD budget is closing in on $1 trillion annually, spending “hundreds of millions” on alternative weapons does kind of sound like pocket lint.  The Pentagon admits that China is “displaying growing numbers of autonomous and teaming systems,” including “a substantial amount of development displaying efforts to produce swarming capability for operational applications.” They’re taking this seriously.

“The hundreds of millions of dollars range, while a great start, would only provide hundreds of the truly capable ocean drones we need to establish true deterrence to China and other adversaries,” Kevin Decker, chief executive of Ocean Aero, told WSJ.  “They’ve got to start somewhere, and they’ve got to start now.”

“Quite frankly, industry is well ahead of us,” Marine Lt. Gen. Karsten Heckl, deputy commandant for combat admitted. “So we’re trying to catch up but [there is] a lot of promise.”

As the Ukrainian commander said, the doctrine of war is changing.  Weapons systems started in the 1990’s (F-35 fighter) or early 2000’s (the Gerald Ford aircraft carrier) are just going into service and are already outdated.  Admiral Selby has it right: “It is vital that we throw off old conventions.”

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So it is with healthcare.  Capital sinks like hospitals are healthcare’s aircraft carriers – once essential, but now vastly expensive and hugely vulnerable. Prescription drugs that can cost hundreds of thousands, if not millions, of dollars annually are 20^th century pricing in a world of AI drug development, CRISPR, and 3D printing, to name a few innovations.  Adding facility fees to even telehealth visits is (stupid) 20^th century thinking.  Health insurance premiums that are unaffordable even to middle class customers reflect 20^th approaches.

Similarly, I’m not worried that healthcare won’t find many uses for AI; rather, I’m worried that it will co-opt AI into making existing cost structures even higher, rather than using it to make healthcare become “small, smart, and cheap.”

The doctrine of healthcare must change.  Where is its ragtag team of engineers, computer scientists, physicians, and entrepreneurs making it faster, smaller, smarter, cheaper, more personal, and definitely more effective?

DNA Is Better at Math Than You

I was tempted to write about the work being done at Wharton that suggests that AI may already be better at being entrepreneurial than most of us, and of course I’m always interested to see how nanoparticles are starting to change health care (e.g., breast cancer or cancer more generally), but when I saw what researchers at China’s Shanghai Jiao Tong University have done with DNA-based computers, well, I couldn’t pass that up. 

Credit: Bing

If PCs helped change the image of computers from the big mainframes, and mobile phones further redefined what a computer is, then DNA computers may cause us to one day – in the lifetime of some of you -- look back at our chip-based devices as primitive as we now view ENIAC.

It’s been almost 30 years since Leonard Adleman first suggested the idea of DNA computing, and there’s been a lot of excitement in the field since, but, really, not the kind of progress that would make a general purpose DNA computer seem feasible.  That may have changed.

At the risk of introducing way too many acronyms, the Chinese researchers claim they have developed a general purpose DNA integrated circuit (DIC), using “multilayer DNA-based programmable gate arrays (DPGAs).”  The DPGAs are the building blocks of the DIC, and can be mixed and matched to create the desired circuits.  They claim that each DPGA “can be programmed with wiring instructions to implement over 100 billion distinct circuits.”

They keep track of what is going on using fluorescence markers, which probably makes watching a computation fun to watch. 

One experiment, involving 3 DPGAs and 500 DNA strands, made a circuit that could solve quadratic equations, and another could do square roots.  Oh, and, by the way, another DPGA circuit could identify RNA molecules that are related to renal cancer.  They believe their DPGAs offers the potential for “intelligent diagnostics of different kinds of diseases.”

DNA tracking DNA.

"Programmability and scalability constitute two critical factors in achieving general-purpose computing," the researchers write. "Programmability enables specification of the device to perform various algorithms whereas scalability allows the handling of a growing amount of work by the addition of resources to the system."  The authors believe they’ve made significant progress on both fronts. 

Moreover, they say: “The ability to integrate large-scale DPGA networks without apparent signal attenuation marks a key step towards general-purpose DNA computing.”  

I don’t pretend to understand the chemistry, engineering, or computing logic involved in all that, and I’m not saying you’ll soon be carrying around a bunch of DPGAs instead of your phone.  But I’m pretty sure at some point in the foreseeable future we’ll not be carrying around phones as our devices, and I suspect there’s a pretty good chance that DNA is going to be crucial to our computing future.

For one thing, the storage in DNA is unrivaled. As MIT professor Mark Bathe, Ph.D. told NPR: “All the data in the world could fit in your coffee cup that you’re drinking in the morning if it were stored in DNA.” It’s hard to get our heads around how much more efficient – and resilient -- nature is with DNA data storage than anything we’ve come up with.

For another, as long as we’re DNA-based creatures, it’s going to be relevant to us, whereas I already have computer storage disks I don’t have ports for and computers that are so out-of-date as to be useless.  DNA isn’t going to go out of date.

For a third reason, our current approach to computing rely heavily on a wide range of materials, especially the so-called rare earth elements.  It’s not so much that they’re rare as it is that they are incredibly hard to mine and process, and create a significant amount of pollution along the way.  A computing future based on our silicon chip approach is not sustainable and probably won’t survive the 21^st century. DNA is literally everywhere.

Fourth, biology – specifically, brain cells -- brain cells – may be the best path forward to AI, as suggested by a new field called Organoid Intelligence (OI).  “Computing and artificial intelligence have been driving the technology revolution, but they are reaching a ceiling,” said Thomas Hartung, the leader of the initiative that established OI. “Biocomputing is an enormous effort of compacting computational power and increasing its efficiency to push past our current technological limits.”

Professor Hartung pointed out that only last year a supercomputer exceeded the computational capacity of a single human brain — “but using a million times more energy.”

Organoids at work. Credit: Smirnova, et. alia.

Fifth and most specific to health care, we are biological, DNA-based beings, and there’s just something fitting about using biological computing as one of, and perhaps the primary, approaches to how we track and manage our health.  As I wrote several years ago, what could be better than being your own medical record?   

Sixth and finally, we’ve had a great run with our current approach to computing, but it is overdue for the next big thing.  That next big thing may be DNA/biological computing, or it may be quantum computing, or it may be a combination of both, but I would be willing to bet that 22^nd computing doesn’t look much like 2023 computing.  We need to be looking ahead.

So, yeah, I’m excited by DNA/biological computing, and I think you should be too.

Poor Kids. Pitiful Us

Well, congratulations, America.  The child poverty rate more than doubled from 2021 to 2022, jumping from 5.2% to 12.4%, according to new figures from the Census Bureau.  Once again, we prove we sure have a funny way of showing that we love our kids.

Does Uncle Sam want to shame poor children? Credit: Bing

The poverty rate is actually the Supplemental Poverty Measure (SPM), which takes into account government programs aimed at low income families but which are not counted in the official poverty rate. The official poverty rate stayed the same, at 11.5% while the overall SPM increased 4.6% (to 12.4%), the first time the SPM has increased since 2010.  It’s bad enough that over 10% of our population lives in poverty, but that so many children live in poverty, and that their rate doubled from 2021 to 2022 -- well, how does one think about that?

The increased was expected. In fact, the outlier number was the “low” 2021 rate.  Poverty dropped due to COVID relief programs; in particular, the child tax credit (CTC).  It had the remarkable (and intended) impact of lowering child poverty, but was allowed to expire at the end of 2021, which accounts for the large increase. We’re basically back to where we were pre-pandemic.

President Biden was quick to call out Congressional Republicans (although he might have chided Senator Joe Manchin just as well):

Today’s Census report shows the dire consequences of congressional Republicans’ refusal to extend the enhanced Child Tax Credit, even as they advance costly corporate tax cuts…The rise reported today in child poverty is no accident—it is the result of a deliberate policy choice congressional Republicans made to block help for families with children while advancing massive tax cuts for the wealthiest and largest corporations.

Many experts agree: child poverty, and poverty more generally, is a choice, a policy choice. “This data once again highlights that poverty in our country isn’t a personal failing, but rather a policy choice," said Melissa Boteach, vice president of income security at the National Women’s Law Center.

Economist Paul Krugman blasts the failure to continue the expansion of the CTC, calling it both stupid and cruel for two reasons:

First, avoiding much of this human catastrophe would have cost remarkably little money. Second, child poverty is, in the long run, very expensive for the nation as a whole: Americans who live in poverty as children grow up to become less healthy and productive adults than they should be.

Bruce Leslie, President of First Focus on Children, agrees, telling Time that poverty “really does affect every aspect of the lives of kids. It affects kids' education, their health, their nutrition, and then has negative consequences on things like child abuse and homelessness."

But, as Professor Krugman noted: “Unfortunately, children can’t vote and poor adults tend not to vote either. So politicians can get away with policies that harm poor children.”

We’re better than that…aren’t we? “Ensuring that children have their basic needs met is the bare minimum of what we can and should do,” Renee Ryberg, senior research scientist at Child Trends, a research organization, told CNN. “The payoff for the health and wellbeing of our nation’s children and for our society as a whole is immeasurable.”

It’s worth pointing out that, compared to our peer nations, we fare badly, in the bottom quartile, with child poverty rates comparable to Bulgaria and Chile.  So, no, we’re not remotely even doing the bare minimum. 

Speaking of child statistics on which the U.S. falls far short, we have both maternal and infant mortality rates that rival third world nations.  It’s hard to argue that we love mothers and children when we allow them to die at these shockingly high levels.

Source: Commonwealth Fund

A bare minimum we should be doing for moms and kids is to make sure they have health insurance, yet ten states still have not passed Medicaid expansions despite the federal incentives to do so.  I’ll leave it as an exercise for the interested reader to compare the states without Medicaid expansion with the ones with the worst maternal/infant mortality

To add insult to injury, COVID allowed millions more to qualify for Medicaid, but those special provisions are “unwinding” and – you guessed it – children are being disproportionately impacted, with millions losing their coverage (often due to procedural reasons rather than ineligibility).

I’ve written before about the value of programs that give direct assistance to low income individuals (e.g., cash transfers and SNAP), and there’s new evidence that such a program helps mothers and infants in particular.  The Delaware Healthy Mother and Infant Consortium is testing giving a guaranteed income of $1,000/month to low income pregnant women, and is already claiming a 324% return on investment.  Mothers are more likely to get prenatal care and less likely to have birth complications. 

“We've demonstrated not only that there's a great return on investment, but there's actually decreased cost on the healthcare side,” says DHMIC Chair Dr. Pricilla Mpasi. 

Similarly, despite SNAP and various school lunch programs, the Children’s Defense Fund estimates that 1 in 7 kids – some 10.5 million – are still food insecure, living in households where not everyone gets enough to eat.  Massachusetts is trying to put a dent in that for its school-aged children, by making school breakfast and lunch free for all K-12 students.  No more red tape, no more stigma for poor kids getting subsidized meals. 

California, Colorado, Maine, Michigan, Minnesota, New Mexico, and Vermont have similar programs.  For Pete’s sake, why don’t all states?

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It’s embarrassing that our overall poverty rate is so high, among the highest in the world. We’re the richest nation in the world but have among the highest percentage of poor people. It is literally killing us. Somehow we’ve allowed poverty to be a political debate, a policy decision we persist in. 

But child poverty?  Allowing it to double? When asked about it, Joe Manchin shrugged: “We all have to do our part. The federal government can’t run everything.”  I agree, the federal government can’t do everything, but if it is going to do one thing, helping poor kids should be pretty high on the list.

We shouldn’t just be embarrassed, we should be ashamed.

The Times They Are A-Changin'...Fast

If you have been following my Twitter – oops, I mean “X” – feed lately, you may have noticed that I’ve been emphasizing The Coming Wave, the new book from Mustafa Suleyman (with Michael Bhaskar). If you have not yet read it, or at least ordered it, I urge you to do so, because, frankly, our lives are not going to be the same, at all.  And we’re woefully unprepared.

Not ready for the coming wave. Credit: Bing

One thing I especially appreciated is that, although he made his reputation in artificial intelligence, Mr. Suleyman doesn’t only focus on AI. He also discusses synthetic biology, quantum computing, robotics, and new energy technologies as ones that stand to radically change our lives.  What they have in common is that they have hugely asymmetric impacts, they display hyper-evolution, they are often omni-use, and they increasingly demonstrate autonomy. 

In other words, these technologies can do things we didn’t know they could do, have impacts we didn’t expect (and may not want), and may decide what to do on their own.  

To build an AI, for the near future one needs a significant amount of computing power, using specialized chips and a large amount of data, but with synthetic biology, the technology is getting to the point where someone can set up a lab in their garage and experiment away. AI can spread rapidly, but it needs a connected device; engineered organisms can get anywhere there is air or water. 

“A pandemic virus synthesized anywhere will spread everywhere," MIT”s Kevin Esvelt told Axios.

I’ve been fascinated with synthetic biology for some time now, and yet I still think we’re not paying enough attention. “For me, the most exciting thing about synthetic biology is finding or seeing unique ways that living organisms can solve a problem,” David Riglar, Sir Henry Dale research fellow at Imperial College London, told The Scientist. “This offers us opportunities to do things that would otherwise be impossible with non-living alternatives.”

Jim Collins, Termeer professor of medical engineering and science at Massachusetts Institute of Technology (MIT), added: “By approaching biology as an engineering discipline, we are now beginning to create programmable medicines and diagnostic tools with the ability to sense and dynamically respond to information in our bodies.”

Credit: Bing

For example, researchers just reported on a smart pill -- the size of a blueberry! -- that can be used to automatically detect key biological molecules in the gut that suggest problems, and wirelessly transmit the information in real time. 

MIT News reports:

Current techniques for diagnosing diseases inside the gut can be invasive (think of a colonoscopy or other endoscopic procedure), and can’t detect molecular biomarkers of disease in real-time. The latter is a problem because several important biomarkers are very short-lived, so they disappear before current techniques can detect them.

The pills involves engineered bacteria, electronics, and a battery (all very small, of course). When the bacteria detect the molecules it is looking for, it produces light (I kid you not), which the electronics detect and convert into a wireless signal. 

“The inner workings of the human gut are still one of the final frontiers of science. Our new pill could unlock a wealth of information about the body’s function, its relationship with the environment, and the impact of disease and therapeutic interventions,” says senior author Timothy Lu, an MIT associate professor of biological engineering and of electrical engineering and computer science.

Alessio Fassano, a professor at the Harvard T.H. Chan School of Public Health, who was not involved in the research, praised the findings: “This system may represent a game changer in the management of IBDs [inflammatory bowel diseases] in terms of early diagnosis, interception of disease flareups, and optimization of a therapeutic plan.” Co-first author Maria Eugenia Inda explains: “We still don’t fully understand it [the gut] because it’s difficult to access and study. We lack the tools to explore it. Knowing more about the gut chemical environment could help us prevent disease by identifying factors that cause inflammation before the inflammation takes over.”

The authors believe the results suggest application beyond those molecules or even just the gut. Co-first author Miguel Jimenez says: “We played to the strengths of the biology and the electronics — our tiny pill shows what is possible when we can bridge bacterial sensing with wireless communication.”

We’re just getting started. Dr. Collins told The Scientist:

There are two big challenges – the first is that we still don’t have a broad set of design principles for biology – and that means that its complexity can still get in the way of our best design plans. Secondly, we still have a pretty anemic library of biological parts – to the order of a few dozen that have been reused and repurposed in the last two decades. We need to dramatically expand this toolkit through synthesis and biomining efforts.

As an example, his team engineered a bacteria that helps break down antibiotics in the gut. “By applying synthetic biology, we have designed a living therapeutic that has the potential to help counter the potential negative effects of antibiotic use,” he said.

Dr, Collings is a big believer not only how synthetic biology can help improve our health but also elsewhere: “I think the idea of applying engineering principles to living systems that have evolved over billions of years can provide humanity with a real edge to counter some of the existential challenges we’re facing.”

But, of course, these blessings come with a curse. Add the option of engineering our own bodies, and the implications grow. Mr. Suleyman writes: “As people increasingly take power into their hands, I expect inequality’s newest frontier to lie in biology.” Some will try to alter their DNA, others will augment themselves -- and some will try to harm others.

Since many of the synthetic biology techniques have become “democratized,” as some experts fear, creating pathogens becomes too easy – especially if aided by AI.  "Even relatively mild pandemic viruses can kill more people than any nuclear device," writes Dr. Esvelt.

The possibilities of synthetic biology – and AI, quantum computing, and others – are endless.  So are the dangers.

It's not quite that easy. Yet. Credit: Bing

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I’ll leave you with two of Mr. Suleyman’s cautions:

·       “But we are entering a new era where the previously unthinkable is now a distinct possibility.”

·       “When it comes to technology that could radically extend human life span or capabilities, there clearly has to be a big debate from the get-go about its distribution.”

We need to be thinking that unthinkable, and having that debate.

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Smells Like AI Spirit

There are so many exciting developments in artificial intelligence (AI) these days that one almost becomes numb to them. Then along comes something that makes me think, hmm, I didn’t see that coming.

For example, AI can now smell.

Credit: Bing

Strictly speaking, that’s not quite true, at least not in the way humans and other creatures smell.  There’s no olfactory organ, like our nose or a snake’s tongue. What AI has been trained to do is to look at a molecular structure and predict what it would smell like.

If you’re wondering (as I certainly did when I heard AI could smell), AI has also started to crack taste as well, with food and beverage companies already using AI to help develop new flavors, among other things. AI can even reportedly “taste wine” with 95% accuracy.  It seems human senses really aren’t as human-only as we’d thought.

The new research comes from the Monell Chemical Senses Center and Osmo, a Google spin-off. It’s a logical pairing since Monell’s mission is “to improve health and well-being by advancing the scientific understanding of taste, smell, and related senses,” and Osmo seeks to give “computers a sense of smell.” More importantly, Osmo’s goal in doing that is: “Digitizing smell to give everyone a goal at a better life.”

Osmo CEO Alex Wiltschko, PhD says: “Computers have been able to digitize vision and hearing, but not smell – our deepest and oldest sense.”  It’s easy to understand how vision and hearing can be translated into electrical and, ultimately, digital signals; we’ve been doing that for some time.  Smell (and taste) seem somehow different; they seem chemical, not electrical, much less digital. But the Osmo team believes: “In this new era, computers will generate smells like we generate images and sounds today.”

I’m not sure I can yet imagine what that would be like.

The research team used an industry dataset of 5,000 known odorants, and matched molecular structures to perceived scents, creating what Osmo calls the Principle Odor Map (POM). This model was then used to train the AI. Once trained, the AI outperformed humans in identifying new odors. 

The model depends on the correlation between the molecules and the smells perceived by the study’s panelists, who were trained to recognize 55 odors. “Our confidence in this model can only be as good as our confidence in the data we used to test it,” said co-first author Emily Mayhew, PhD. Senior co-author Joel Mainland, PhD. admitted: “The tricky thing about talking about how the model is doing is we have no objective truth.” 

The study resulted in a different way to think about smell. The Montell Center says:

The team surmises that the model map may be organized based on metabolism, which would be a fundamental shift in how scientists think about odors. In other words, odors that are close to each other on the map, or perceptually similar, are also more likely to be metabolically related. Sensory scientists currently organize molecules the way a chemist would, for example, asking does it have an ester or an aromatic ring?

“Our brains don’t organize odors in this way,” said Dr. Mainland. “Instead, this map suggests that our brains may organize odors according to the nutrients from which they derive.”

“This paper is a milestone in predicting scent from chemical structure of odorants,” Michael Schmuker, a professor of neural computation at the University of Hertfordshire who was not involved in the study, told IEEE Spectrum.  It might, he says, lead to possibilities like sharing smells over the Internet. 

Think about that. 

“We hope this map will be useful to researchers in chemistry, olfactory neuroscience, and psychophysics as a new tool for investigating the nature of olfactory sensation,” said Dr. Mainland. He further noted: “The most surprising result, however, is that the model succeeded at olfactory tasks it was not trained to do. The eye-opener was that we never trained it to learn odor strength, but it could nonetheless make accurate predictions.”

Next up on the team’s agenda is to see if the AI can learn to recognize mixtures of odors, which exponentially increases the number of resulting smells. Osmo also wants to see if AI can predict smells from chemical sensor readings, rather than from molecular structures that have already been digitized.  And, “can we digitize a scent in one place and time, and then faithfully replicate it in another?”

That’s a very ambitious agenda.

Dr. Wiltschko claims: “Our model performs over 3x better than the standard scent ingredient discovery process used by major fragrance houses, and is fully automated.” One can imagine how this would be useful to those houses. Osmo wants to work with the fragrance industry to create safer products: “If we can make the fragrances we use every day safer and more potent (so we use less of them), we’ll help the health of everyone, and also the environment.”

When I first read about the study, I immediately thought of how dogs can detect cancers by smell, and how exciting it might be if AI could improve on that. Frankly, I’m not much interesting in designing better fragrances; if we’re going to spend money on training AI to recognize molecules, I’d rather it be spent on designing new drugs than new fragrances.

Fortunately, Osmo has much the same idea. Dr. Wiltschko writes:

If we can build on our insights to develop systems capable of replicating what our nose, or what a dog’s nose can do (smell diseases!), we can spot disease early, prevent food waste, capture powerful memories, and more. If computers could do these kinds of things, people would live longer lives – full stop. Digitizing scent could catalyze the transformation of scent from something people see as ephemeral to enduring.   

Now, that’s the kind of innovation that I’m hoping for.

Credit: Bing

Skeptics will say, well, AI isn’t really smelling anything, it’s just acting as though it does. E.g., there’s no perception, just prediction. One would make the same argument about AI taste, or vision, or hearing, not to mention thinking itself. But at some point, as the saying goes, if it looks like a duck, swims like a duck, and quacks like a duck, it’s probably a duck.  At some point in the not-so-distant future, AI is going to have senses similar to and perhaps much better than our own.

As Dr. Wilkschko hopes: “If computers could do these kinds of things, people would live longer lives – full stop.”