Ted Chiang: The Secret Third Thing

I really like Ted Chiang’s writing. [ed. me too!]

I think he's probably the best science fiction short story writer alive, and possibly the best short story writer, period. [ed. well...]

I've read every one of his stories at least twice, and The Merchant and the Alchemist's Gate more like seven times. I’ve noticed many of his readers, including some of his most positive reviewers, miss one key point or another of his works, and thus don't fully appreciate his genius.

This review covers what he does extremely well, especially unique elements that other science fiction writers have not done as well, or at all.

He Writes “True” Science Fiction

Science fiction critics often divide the genre into:

• "hard" science fiction: aka engineering fiction, stories built on scientifically accurate extrapolations of real physics and technology (think Arthur C. Clarke)

• "soft" science fiction: aka science fantasy, which uses scientific trappings as window dressing for character-driven or sociological stories (think Star Wars).

Ted Chiang has written stories plausibly categorized as either, but more excitingly, many of his stories are neither. He often writes what I think of as true science fiction, where the principles of science themselves are meaningfully different from our world, but still internally consistent.

In Omphalos, Young Earth Creationism is empirically true. Astronomers can only see light from stars 6,000 light-years away. Fossilized trees have centers with no rings. The first God-created humans lack belly buttons. The scientists in that story keep discovering multiple independent lines of evidence that converge on creationism: because in that universe, they're simply correct.

In Seventy-Two Letters, technology springs from Jewish Kabbalah. Golems and divine names drive industrial progress in a steampunk world.

Excitingly, he does this not just with natural sciences but social sciences as well. In Story of Your Life, strong Sapir-Whorf (the idea that language significantly constrains thought) isn't a largely discredited linguistic hypothesis, but the key to navigating First Contact with alien minds that experience past and future as equally present.

This comes up in his other stories as well:

• In Division By Zero, mathematics itself is broken from within.

• In Hell Is the Absence of God, divine intervention is empirically observable and follows consistent rules

Many of his readers, even in their otherwise rave reviews, miss this. Multiple reviewers complain about how the science in his stories are “unrealistic” (e.g. strong Sapir-Whorf is “discredited”). They expect hard science fiction; Chiang is doing something different. Chiang creates different universes with internally self-consistent scientific laws, using science fiction and alternative science as a vehicle for exploring philosophical progress and human relationships.

Technology is Often Good

Science fiction writers used to like technology. For some reason, this has become increasingly uncommon, even passé. Doubly so for Western writers, and quadruply so for Western, literary, “humanist” writers.

Now it’s hip and trendy to think of every new technology as the Torment Nexus. Most science fiction today feels like Black Mirror, which ran 7 seasons with exactly one happy ending.

Chiang bucks this trend. Joyce Carol Oates:

It is both a surprise and a relief to encounter fiction that [...] ask[s] anew philosophical questions that have been posed repeatedly through millennia to no avail. Chiang’s materialist universe is a secular place, in which God, if there is one, belongs to the phenomenal realm of scientific investigation and usually has no particular interest in humankind. But it is also a place in which the natural inquisitiveness of our species leads us to ever more astonishing truths, and an alliance with technological advances is likely to enhance us, not diminish us. Human curiosity, for Chiang, is a nearly divine engine of progress.

In the hands of a lesser (or perhaps just more pessimistic) writer, many of the technologies and ideas Chiang explores will have an accursed quality to them, a monkey’s paw that curls into delivering a future much worse than a more innocent, pastoral past. Chiang resists those cliches. In The Truth of Fact, The Truth of Feeling, memory augmentation technology allows the narrator to understand his own self-deceptions, and work towards becoming a better person and reconciling with loved ones and even himself. In Liking What You See: A Documentary, a technology that gives users acquired face-blindness allows the main characters to meditate on the nature of human beauty and the shallowness inherent in privileging the beautiful.

Even in situations where the story is overall tragic, like when the characters are faced with existential crisis (in the individual sense), or existential catastrophe (in the world-ending sense), technology isn't the villain but the vehicle for understanding unbearable truths (whether about the world or about ourselves).

Chiang consistently shows us the potential of technology to help us become more human, and have a deeper appreciation for the world and our place in it.

The Lived Experience of Compatibilism

“Compatibilism is a philosophical stance that reconciles free will with determinism. It argues that free will, understood as the ability to act according to one's desires, is compatible with the idea that all events, including human actions, are causally determined by prior events. Essentially, compatibilists believe that even if our choices are predetermined, we can still be considered free and morally responsible if those choices are a result of our own internal states, like desires and intentions.” 

Does that make sense to you? I’m not sure it does to me. In practice, compatibilism says something like “free will in the normal, pretheoretic sense of the term, doesn’t exist. Your choices still meaningfully matter nonetheless. You can’t meaningfully get out of the bind philosophically. What you can do, however, is make peace with it.” [...]

In Story of Your Life [SPOILERS], the narrator learns an atemporal alien language and begins experiencing past and future as equally real. It takes her some time to make peace with it, but eventually she fully accepts the truth of determinism. She understands that life is full of tragedy, including that her daughter will die young, but life is full of beauty too. With both regret and awe, she sets forth on the path that she was destined to take.

This is compatibilism from the inside. In both stories, the characters discover they cannot change what will happen, but this knowledge transforms how they experience what must happen: with forgiveness, acceptance, and even joy.

As a friend of mine puts it, “he treats philosophical ideas as lived experiences.”The mathematician in Division by Zero doesn't just intellectually understand that mathematics is broken; she experiences it as a personal catastrophe, on par with (and concurrent with) her marriage's collapse. In Lifecycle of Software Objects, the “we are the parents of our mind-children” metaphor for building sentient AI systems becomes quite literal.

by Linch, The Linchpin |  Read more:

Image: uncredited

[ed. Ted Chiang is truly one of the best science fiction writers out there today, and a great essayist too  (I'm also a Neal Stephenson fan). Check out this MetaFilter site: The sublime science fiction of Ted Chiang, which includes most of his stories in full (but please buy his books; you'll look smart and discerning to your friends!). A couple favorites that left a lasting impression on me: Lifecycle of Software Objects; and Understand.]

In Support of Mandatory Nucleic Acid Synthesis Screening and Recordkeeping

As life sciences researchers, builders of AI and biotechnology, and experts with a wide range of views on how to approach AI policy, we call on legislators to make screening of orders for synthetic nucleic acids — and the equipment needed to make them — mandatory.

The ability to order synthetic DNA online has accelerated vaccine development, powered basic research, and made it possible for small teams to access capabilities that used to be confined to major institutions. Since the publication of protocols to reconstruct viruses from strands of DNA more than two decades ago, it has also been recognized as a point in the biotechnology supply chain where a bad actor could cause outsized harm. Recognizing the vulnerability, synthesis companies formed the International Gene Synthesis Consortium in 2009 to develop and implement voluntary safeguards against misuse.

While the issue is not new, the pace of progress in artificial intelligence is. AI systems now outperform PhD-level virologists on questions about highly technical laboratory procedures in their own domains of expertise. The evidence about what this means for present-day biosecurity threats is genuinely mixed, but the trend is hard to dispute. AI systems are improving rapidly, and alongside incredible benefits to science and medicine, there is a real possibility that the knowledge barriers which have historically prevented bad actors from obtaining biological weapons will meaningfully erode.

Support for screening does not depend on any particular view of AI; the biosecurity case has been recognized by scientists and governments for decades. Screening is also one of the best understood and least disruptive biosecurity measures available. It asks providers of synthesized DNA and manufacturers of synthesis machines to check synthesis requests for sequences of concern and to verify customer legitimacy before shipping orders. Providers should also record synthesis orders and sequence data to support legitimate biosecurity investigations, so that any threat that might evade initial screening can be traced back to its source — including when individual sequences would not raise concern in isolation. Awareness of traceability itself deters misuse.

Many of the largest and most responsible providers in the industry already screen and record orders voluntarily because it is well understood that they have an important role to play in maintaining public trust in and mitigating potential misuse of this important technology.

For these reasons, the undersigned support mandatory nucleic acid synthesis screening, including recordkeeping, in the United States.

Given the pace at which the underlying technology is changing, we believe the need is urgent. Congress should act this session, and we applaud the legislative efforts currently underway. To ensure a consistent national standard rather than a patchwork of conflicting laws, states should also consider implementing requirements based on existing federal and industry guidelines.

This is a rare moment of agreement across stakeholders that are often at odds. We hope policymakers will meet it with decisive action.

Sincerely,
Signatories: — *Everybody*

[ed. No brainer, right? You don't just leave potential life-threatening bio-warfare components laying around with no oversight. Right?]

***

Amrith Ramkumar (WSJ): Top artificial-intelligence executives are joining security experts in calling for Congress to protect against biological threats posed by AI, adding to growing pressure on lawmakers to address the technology’s risks.

Three major chief executive officers—OpenAI’s Sam Altman, Anthropic’s Dario Amodei and Demis Hassabis of Google’s DeepMind AI lab—are among the signatories of a letter urging Congress to require safeguards when companies order synthetic DNA and RNA, a key step in developing certain vaccines and biotech breakthroughs.

… It was organized by two tech-focused think tanks that said the topic is a rare source of agreement among libertarians, progressives, researchers and rival executives.

Dean W. Ball: I am honored to have signed on to this letter. This is an urgent priority for near-term action by Congress. Biotech is advancing rapidly on its own, and I—and many others—believe the “Mythos moment” in AI/bio is coming soon. It is time for action.

revisions to existing nucleic acid screening requirements were mandated by an EO POTUS signed a year ago; I worked on them while in govt. I genuinely don’t know what happened to that work after I left but it is nine months behind schedule. Congress acting is better anyway.

Joshua Teperowski Monrad: People are so astounded when I tell them this isn't already law

Alec Stapp: it really is insane [...]

Other signatories include Patrick Collison, Paul Graham, Mustafa Suleyman, Alexandr Wang and a lot more where that came from.

We need such letters, despite this having ~100% support among those who understand any side of this, this is such a slam dunk that we should be doing this even before considerations of AI making malicious action vastly easier.

Why? Because political awareness is basically still near zero:

Will Poff-Webster: When I was a Senate staffer and occasionally got the chance to bring up biosecurity risks from AI, the response was often, “What? AI might be able to do that?”

This letter shows how easy it’d be for Congress to act on this

Ocean Observatory Will Go Dark Under Trump Funding Cuts

A portion of one of the most ambitious ocean monitoring networks ever built will go dark this month when scientists board a research vessel and motor off the Oregon coast to pull a research buoy from deep out of the Pacific.

The buoy 80 meters (260 feet) below the water’s surface will be removed June 16 from the Ocean Observatories Initiative — a network of more than 900 ocean sensors built at a cost of $386 million that has continuously collected real-time data for more than a decade. But last month, the National Science Foundation announced it would dismantle most of the system, pulling instruments from waters off Oregon, Washington, Alaska, North Carolina and Greenland by 2027.

Funded by the foundation, the observatories have tracked everything from ocean circulation and marine ecosystems to climate change and extreme weather. Its data has been freely available and has informed more than 500 scientific publications. The project was slated to run for another 15 to 20 years.

In an emailed statement, the foundation said the decision is not a cancellation, but a “descoping” aligned with a “wider strategy of a nimbler approach to prioritize support for evolving scientific priorities and emerging technologies, as well as smart lifecycle management within its research infrastructure portfolio.” The foundation added that its decision drew in part on a 2025 National Academies report on the future of ocean science. [ed. There has to be some kind of annual award for worst word salad example. This would certainly qualify.]

But for the scientists who built and operated the system — and the researchers, educators and students who rely on its data — the timing feels particularly punishing.

An El Nino event, which disrupts weather patterns and supercharges marine heat waves, is predicted to arrive along the Pacific coast this summer. One marine heat wave is already pushing unusually warm water off California.

Without the Oregon and Washington moorings and the network of underwater gliders the Ocean Observatories Initiative operated in the region, researchers say they’ll lose much of their ability to measure what’s happening below the surface, which is precisely where the most significant oceanographic signals are.

“It’s a crippling loss of information,” Ed Dever, a professor at Oregon State University who helped lead the initiative’s Pacific Northwest operations, told The Associated Press Tuesday. Scientists can get some data from the surface, such as temperature and the distribution of chlorophyll, which drives photosynthesis in plants, but information below cannot be gathered from satellites alone, including low oxygen zones. [...]

The initiative operated on roughly $48 million a year, not including the cost of research vessels, which adds substantially to the overall price. Prior to budget cuts, which began in 2025, around 60 to 70 people worked directly on the project across its partner institutions, Dever said.

“What’s happening with the Ocean Observatories Initiative is not unique,” he said. “This is just one of a number of science facilities that is being dismantled at the present time. It seems to really mark the end of a federal commitment to basic scientific research — a commitment that has served this nation very well for the last 70 years.”

by Annika Hammerschlag, AP |  Read more:
Image: Darlene Trew Crist/Woods Hole Oceanographic Institution via AP

[ed. See also: How the 19th-Century Know Nothing Party Reshaped American Politics (Smithsonian):]

***

Like Fight Club, there were rules about joining the secret society known as the Order of the Star Spangled Banner (OSSB). An initiation rite called “Seeing Sam.” The memorization of passwords and hand signs. A solemn pledge never to betray the order. A pureblooded pedigree of Protestant Anglo-Saxon stock and the rejection of all Catholics. And above all, members of the secret society weren’t allowed to talk about the secret society. If asked anything by outsiders, they would respond with, “I know nothing.”

So went the rules of this secret fraternity that rose to prominence in 1853 and transformed into the powerful political party known as the Know Nothings. At its height in the 1850s, the Know Nothing party, originally called the American Party, included more than 100 elected congressmen, eight governors, a controlling share of half-a-dozen state legislatures from Massachusetts to California, and thousands of local politicians. Party members supported deportation of foreign beggars and criminals; a 21-year naturalization period for immigrants; mandatory Bible reading in schools; and the elimination of all Catholics from public office. They wanted to restore their vision of what America should look like with temperance, Protestantism, self-reliance, with American nationality and work ethic enshrined as the nation's highest values.

The Pleasure of Finding Things Out

This is the edited transcript of an intewiew with Feynman made for the BBC television program Horizon in 1981, shown in the United States as an episode of Nova. Feynman had most of his I$ behind him by this time (3e died in 1988), so he could reflect on his experiences and accomplishments with the perspective not often attainable by a younger person. The result is a candid, relaxed, and very personal discussion on many topics close to Feynman's heart: why knowing merely the name of something is the same as not knowing anything at all about it; how he and his fellow atomic scientists of the Manhattan Project could drink and revel in the success of the terrible weapon they had created while on the other side of the world in Hiroshima thousands of their fellow human beings were dead or dying from it; and why Feynman could just as well have gotten along without a Nobel Prize.

The Beauty of a Flower 

I have a friend who’s an artist and he’s sometimes taken a view which I don’t agree with very well. He’ll hold up a flower and say, “Look how beautiful it is,” and I’ll agree, I think. And he says - “you see, I as an artist can see how beautiful this is, but you as a scientist, oh, take this all apart and it becomes a dull thing.” And I think that he’s kind of nutty. First of all, the beauty that he sees is available to other people and to me, too, I believe, although I might not be quite as refined aesthetically as he is; but I can appreciate the beauty of a flower. At the same time I see much more about the flower than he sees. I can imagine the cells in there, the complicated actions inside which also have a beauty. I mean it’s not just beauty at this dimension of one centimeter, there is also beauty at a smaller dimension, the inner structure. Also the processes, the fact that the colors in the flower evolved in order to attract insects to pollinate it is interesting - it means that insects can see the color. It adds a question: Does this aesthetic sense also exist in the lower forms? Why is it aesthetic? All kinds of interesting questions which shows that a science knowledge only adds to the excitement and mystery and the awe of a flower. It only adds; I don’t understind how it subtracts. 

Avoiding Humanities 

I’ve always been very one-sided about science and when I was younger I concentrated almost all my effort on it. I didn’t have time to learn and I didn’t have much patience with what’s called the humanities, even though in the university there were humanities that you had to take. I tried my best to avoid somehow learning anything and working at it. It was only afterwards, when I got older, that I got more relaxed, that I’ve spread out a little bit. I’ve learned to draw and I read a little bit, but I’m really still a very one-sided person and I don’t know a great deal. I have a limited intelligence and I use it in a particular direction.

Tyrannosaurus in the Window 

We had the Encyclopaedia Britannica at home and even when I was a small boy [my father] used to sit me on his lap and read to me from the Encyclopaedia Britannica, and we would read, say, about dinosaurs and maybe it would be talking about the brontosaurus or something, or the tyrannosaurus rex, and it would say something like, “This thing is twenty five feet high and the head is six feet across,” you see, and so he’d stop all this and say, “Let’s see what that means. That would mean that if he stood in our front yard he would be high enough to put his head through the window but not quite because the head is a little bit too wide and it would break the window as it came by.” 

Everything we’d read would be translated as best we could into some reality and so I learned to do that - everything that I read I try to figure out what it really means, what it’s really saying by translating and so (LAUGHS) I used to read the Encyclopaedia when I was a boy but with translation, you see, so it was very exciting and interesting to think there were animals of such magnitude - I wasn’t frightened that there would be one coming in my window as a consequence of this, I don’t think, but I thought that it was very, very interesting, that they all died out and at that time nobody knew why. 

We used to go to the Catskill Mountains. We lived in New York and the Catskill Mountains was the place where people went in the summer; and the fathers - there was a big group of people there but the fathers would all go back to New York to work during the week and only come back on the weekends. When my father came he would take me for walks in the woods and tell me various interesting things that were going on in the woods - which I’ll explain in a minute - but the other mothers seeing this, of course, thought this was wonderful and that the other fathers should take their sons for walks, and they tried to work on them but they didn’t get anywhere at first and they wanted my father to take all the kids, but he didn’t want to because he had a special relationship with me - we had a personal thing together - so it ended up that the other fathers had to take their children for walks the next weekend, and the next Monday when they were all back to work, all the kids were playing in the field and one kid said to me, “See that bird, what kind of a bird is that?” And I said, “I haven’t the slightest idea what kind of a bird it is.” He says, “It’s a brown throated thrush,” or something, “Your father doesn’t tell you anything.” But it was the opposite: my father had taught me. Looking at a bird he says, “Do you know what that bird is? It’s a brown throated thrush; but in Portuguese it’s a . . . in Italian a . . . ,” he says “in Chinese it’s a . . . , in Japanese a . . . ,” etcetera. “Now,” he says, “you know in all the languages you want to know what the name of that bird is and when you’ve finished with all that,” he says, “you’ll know absolutely nothing whatever about the bird. You only know about humans in different places and what they call the bird. Now,” he says, “let’s look at the bird.”

He had taught me to notice things and one day when I was playing with what we call an express wagon, which is a little wagon which has a railing around it for children to play with that they can pull around. It had a ball in it - I remember this - it had a ball in it, and I pulled the wagon and I noticed something about the way the ball moved, so I went to my father and I said, “Say, Pop, I noticed something: When I pull the wagon the ball rolls to the back of the wagon, and when I’m pulling it along and I suddenly stop, the ball rolls to the front of the wagon,” and I says, “why is that?” And he said, “That nobody knows,” he said. “The general principle is that things that are moving try to keep on moving and things that are standing still tend to stand still unless you push on them hard.” And he says, “This tendency is called inertia but nobody knows why it’s true.” Now that’s a deep understanding - he doesn’t give me a name, he knew the difference between knowing the name of something and knowing something, which I learnt very early. He went on to say, “If you look close you’ll find the ball does not rush to the back of the wagon, but it’s the back of the wagon that you’re pulling against the ball; that the ball stands still or as a matter of fact from the friction starts to move forward really and doesn’t move back.” So I ran back to the little wagon and set the ball up again and pulled the wagon from under it and looking sideways and seeing indeed he was right - the ball never moved backwards in the wagon when I pulled the wagon forward. It moved backward relative to the wagon, but relative to the sidewalk it was moved forward a little bit, it’s just [that] the wagon caught up with it. So that’s the way I was educated by my father, with those kinds of examples and discussions, no pressure, just lovely interesting discussions.

by Richard Feynman, Learning Media MIT.edu |  Read more: (pdf)
Image: uncredited

via:

Dognosis

At a former pomegranate farm on the outskirts of Bengaluru, a team of specially trained dogs is doing something that some of the world's most sophisticated medical machines cannot — detecting multiple types of cancer from a single breath, at early stages, for two dollars a test.

Dognosis, the Indian startup behind this system, published the results last week of its Phase 2 clinical trial in the Journal of Clinical Oncology — the world's most influential cancer journal — making it the largest study of its kind ever conducted and placing canine-based diagnostics firmly into the mainstream of medical science.

What Dognosis Does

The company was co-founded by Akash Kulgod, who built on his Honours thesis at Berkeley, and Itamar Bitan, who brings a decade of Special Ops K9 training experience from Israel. What the two founders realised was that the solution to early cancer detection had been living in our homes the whole time — the dog's nose, a product of fifteen millennia of co-evolution with humans, can detect the faint chemical trace of cancer in breath at a resolution that machines, algorithms, and laboratory tests have never come close to matching.

Therefore, Dognosis is building an ultra-affordable, non-invasive breath-based multi-cancer early detection test that combines trained dogs' exceptional olfactory abilities with brain-computer interfaces and machine learning to create quantitative signatures of disease.

How the Test Works

The test is straightforward: a person breathes normally into a cotton face mask for 10 minutes. The mask is sealed, stored, and later evaluated by trained detection dogs at a central laboratory. Each sample is assessed independently by at least three dogs and their assessments are combined using an advanced Bayesian statistical model that weighs each dog's track record and the participant's background information. No blood is drawn, no scan is needed, and no fasting is required.

 
The Science: What the Dogs Are Smelling

The dogs are detecting changes in volatile organic compounds — substances produced by the body when diseases like cancer are present. These VOCs create a unique odour signature or volatilome that trained dogs can identify, just as they are trained to detect explosives and drugs.

According to Dognosis, over 40 double-blind trials published in peer-reviewed journals have demonstrated that dogs can detect various diseases, including different types of cancer, with high accuracy, and this ability is now well-established in scientific literature spanning journals including Nature and The Lancet.

The Phase 2 Trial: What It Found

According to the paper published in the Journal of Clinical Oncology, the study was conducted across six hospitals in Karnataka — three each in Hubballi and Bengaluru — in an assessor-masked, multi-centre case-control format. A total of 3,275 participants were enrolled, with 1,773 used for training and 1,502 for testing. The test cohort included 283 treatment-naïve, biopsy-confirmed cancer cases spanning seven major cancer groups and 1,219 controls including healthy volunteers.

The Phase 2 data showed 91% accuracy in detecting cancer-associated VOC breath signals across seven cancer groups, with accuracy stable across cancer types as well as in early stages — when detecting cancer early matters the most. The study was conducted in collaboration with Medical Detection Dogs, a UK-based charity and world leader in canine bio-detection research. 

"We've known for over two decades that dogs are capable of detecting multiple types of cancers with high accuracy," said Akash Kulgod, chief executive officer of Dognosis. "The challenge has always been building a system around canine olfaction that is reproducible, scalable, and aimed at a clinical problem worth solving."

"Multi-cancer risk stratification from a single breath sample in countries like India is that problem, and this study shows that it can be done," Kulgod said.

 
Why It Matters

The rise of multi-cancer early detection tests and AI-powered imaging has created an acute need for effective first-tier screening, which breath-based testing is uniquely positioned to fulfil — particularly in low- and middle-income countries where expensive imaging infrastructure remains out of reach for the majority of patients.

At $2 per test, Dognosis's system costs a fraction of existing screening tools, many of which also fail to detect cancer at its earliest and most treatable stages.

by NDTV Profit News |  Read more:

Image: uncredited via

Why Japanese Companies Do So Many Different Things

Consider Toto.

If you spend much time in American public bathrooms, or rather if you’re simply a particularly attentive patron of American public bathrooms, you’ll probably have noticed Toto’s toilets at some point or another: they’re distinguished by a quite memorable serif-font “TOTO” logo. Toto toilets aren’t quite dominant in American bathrooms, since they have healthy competition from our homegrown toilet champions American Standard and Kohler—though Toto is doing better and better as Americans start to fall in love with the bidet-toilet—but globally Toto is the world’s largest manufacturer of toilets and bidets. And in its home country of Japan, Toto is simply everywhere: 80 percent of Japanese homes contain a Toto bidet-toilet.

And if you’re a longtime Toto shareholder—maybe an investor with a particular interest in bathroom fixtures—this has been a wonderfully lucrative year for you. Toto’s stock is up 60 percent year to date; in just the last few weeks, it’s risen by 30 percent. Toto is doing better than ever: its net profit, in the first quarter of 2026, was up 230 percent year over year.

But Toto’s remarkable year doesn’t have much to do with toilets or bidets. Toto might have been founded in the 1910s to “provide a healthy and civilized way of life” through affordable toilets, and in the decades since might have become the global leader in the bathroom game. But Toto also does a lot of other things. Toto manufactures not just bidets and toilets but also bathroom tiles, prefabricated bathroom modules, faucets, modular kitchens, photocatalytic coatings for buildings, and assistive equipment for the elderly. And, most importantly, Toto has a very lucrative sideline in the fabrication of memory chips.

Since 1988, in a once-obscure corner of the company called the “advanced ceramics division,” Toto has been producing a very particular component called the electrostatic chuck, or the “e-chuck.” The e-chuck is a sort of high-precision ceramic plate, about the size of a steering wheel, that uses electrostatic force to hold a silicon wafer perfectly flat and thermally stable while memory chips are etched into it with bombardments of plasma. Making these components is extraordinarily difficult, since the ceramic body needs to have near-zero particle generation and be polished to submicron flatness: and this means that there are only a few companies in the world that are capable of manufacturing e-chucks reliably. Almost all of them—Shinko Electric, NGK, Toto, Kyocera, Sumitomo Osaka Cement, Niterra—are based in Japan.

For most of its history, the advanced ceramics division was a rounding error on Toto’s balance sheet: the money maker, as it had been since the 1910s, was the toilet and bidet business. But we’re in a new era. Demand for AI is exploding, meaning that demand for the high-bandwidth memory that AI data centers require is exploding, meaning that demand for memory chips is exploding, meaning that demand for e-chucks is exploding. And so Toto’s advanced ceramics division is suddenly the company’s largest business, generating the majority of its operating profit. Toto’s leadership, suddenly awash in AI-driven revenue, announced that they would double down by investing hundreds of millions in expanded electrostatic chuck production: the toilet company had become, quite unexpectedly, a supplier to the semiconductor supply chain.

The Toto story is a fun and interesting illustration of corporate diversification and how strange bets can pay off. But that type of diversification—a toilet company that also produces photocatalytic coating and high-precision components for semiconductors—isn’t really unique to Toto. Practically every company in Japan seems to do a thousand very different things.

Consider, for example, Kyocera, another one of the e-chuck makers. Kyocera was founded in 1959 as a producer of ceramic insulators for cathode-ray tubes; today it manufactures not only industrial ceramics but also printers, smartphones, ballpoint pens, kitchen knives, solar PV modules, lens components, industrial cutting tools, automotive camera modules, electronics components, semiconductor packaging, biocompatible tooth and joint replacements, UV-LED curing systems, LCD systems, medical products, and lab-grown gemstones. Or another e-chuck maker. Sumitomo Osaka Cement, as you might have been able to deduce from the name, produces cement and ready-mixed concrete; but it also produces optical components, measuring instruments, industrial ceramics, artificial marine reefs, cosmetics and nanoparticle materials.

And this degree of diversification extends to many of Japan’s most famous companies. Yamaha, for example, manufactures pianos, motorcycles, guitars, drums, boats, snowmobiles, ATVs, audio equipment, golf clubs, tennis rackets, home appliances, specialty metals, molding and bonding equipment for semiconductors, and industrial robots. Hitachi makes nuclear reactors, power grids, railway systems, elevators, semiconductor manufacturing equipment, medical imaging devices, data storage, IT consulting, and industrial machinery. Even a company as simple as Oji, Japan’s largest paper company, has been drawn into the production of disposable diapers, functional films, adhesives, cellulose nanofibers, and wood-based EUV photoresists; and it also operates a hotel, an airport catering business, a concert hall, and an insurance agency.

All of which is to say: Japanese companies do a lot of things.

There are, of course, other countries with companies that “do lots of things”: much of Indian economic life, for example, is defined by the sprawling activities of a few large business clans—the Adanis, the Ambanis, the Tatas, the Birlas. But India is a relatively poor country with a low level of economic specialization, and the sprawling conglomerates that dominate its economy focus on relatively simple things like cement, steel, ports, and telecommunications. Japan, by contrast, is a wealthy, developed society—by one measure, the most economically complex country in the world. What’s striking about Japanese companies is not that they do lots of different things but rather that they do them very well. There are all sorts of high-precision inputs—the e-chuck being just one example—that are produced virtually only by Japanese firms.

This is very different from how most wealthy countries operate. American firms, for example, tend to prioritize focus above all else: it would be bizarre for an American paper mill to also operate a concert hall and an airport catering business, or for American Standard or Kohler to somehow have something to do with semiconductors. Even a country like Germany, which matches Japan in its depth of high-precision firms, has nothing like Japan’s corporate diversification. Only a few large conglomerates, like Siemens, have anything approaching the lateral breadth of the Japanese firm. South Korea—whose economic system was not coincidentally modeled off the Japanese one—does have a few chaebol conglomerates, like Samsung and SK, that truly do as many things as Japanese companies. But these are economy-dominating, state-entangled megafirms, cultivated as national champions by Korean industrial policy. They look nothing like, say, Sumitomo Osaka Cement, which is hugely diversified despite being relatively small. (“Look what they need to mimic a fraction of our power!”)

So why are Japanese companies like this? Why do they do so many different things? And how do they manage to do so all those different things so well?

Here is the answer I want to suggest: Japanese companies excel in lots of very different domains because it’s inherent in how they’re structured. The form of the corporation that we know and love in the United States—specialized, market-oriented, governed by shareholders—is just one form that the corporation can take; but it’s not the only way to coordinate capital and labor in a successful and profitable way. The protean corporations of Japan are best understood as a different species of thing altogether: better at some things, worse at others, but still highly adapted to their particular environment. And the things that they’re very good at turn out to be extraordinarily helpful for all sorts of things in which American companies tend to struggle.

by David Oks, Website |  Read more:

Image: uncredited

Price's Law

Spotify has about 11 million artists, but 50% of all streams are generated by only 3,300 artists. That’s insane.

Oh and this isn’t just a Spotify problem or even a music industry problem.

This is a pattern that shows up everywhere once you know what to look for

What Is Price’s Law?

In 1963, a physicist named Derek J. de Solla Price was studying scientific publications, trying to understand why some researchers dominated their fields while others published and got zero attention.

He noticed something strange: the distribution of productivity wasn’t a bell curve as you’d expect… it wasn’t even close.

It followed a completely different mathematical pattern.

Price’s Law states that the square root of the number of people in a domain does 50% of the work.

Here’s what that looks like in practice:

• In a company with 100 employees, 10 people produce half the output

• In a field with 10,000 scientists, 100 produce half the meaningful research

• On a team of 25, 5 people carry the entire operation

Price discovered this while analyzing scientific citations. In any given field, a small fraction of researchers generated half of all cited papers. The rest still published, but their work barely got noticed.

The formula is simple: √n = your high performers, where n is the total population.

Oh, and it wasn’t exclusive to research papers—this pattern showed up everywhere he looked.

Once you see it, you can’t unsee it.

In corporate America, Price’s Law shows up with eerie precision. Of the 30 million businesses in the United States, about 5,500 (the square root) generate half the total economic output.

Amazon, Apple, Microsoft, and a few thousand other companies produce as much as the other 29,994,500 combined.

In astrophysics, the square root of stars in a galaxy produce half the light. The Milky Way has roughly 100 billion stars, but 316,000 of them (0.0003%) generate half the luminosity. Most stars are dim, unremarkable red dwarfs.

A handful of blue giants blaze so bright they illuminate entire stellar neighborhoods. (Scientifically known as a Power Law distribution)

In creative fields like YouTube, very few channels account for the vast majority of both views and ad revenue.

The list goes on and on. River systems, sales teams, Wikipedia editors, wealth distribution, anywhere you look, the square root does half the work.

And this is not a coincidence or rigged systems or unfair advantages (though those exist too).

This is just how complex systems work when skill, consistency, opportunity, and luck all compound over time.

And if you’re building a personal brand or a one-person business, understanding this law might literally save you.

by Kaguura Gichuru, The Write Path |  Read more:

Image: via

Ben Sasse's Warning

When Ben Sasse walked onto the Senate floor in November 2015 to deliver his first speech as a member of the upper chamber, he did something unusual: He had waited a full year to speak. It’s part of a Senate tradition known as the “maiden speech.” A historian by training and a management consulting associate by early vocation, he had spent his first year in the chamber interviewing colleagues, studying how the institution functioned, and developing a diagnosis before offering it publicly. When he finally spoke, the speech landed with enough force that Sen. Mitch McConnell (R-KY) distributed the text to every Republican senator, a gesture the Senate GOP leader at the time rarely made.

“No one in this body thinks the Senate is laser-focused on the most pressing issues facing the nation,” Sasse told his colleagues. “No one.”

The indictment was bipartisan, surgical, and delivered with the calm of a man who had considered it carefully before speaking. The Senate, he argued, had surrendered its institutional identity to the rhythms of the 24-hour news cycle, to the demand for sound bites, and to the incentive to grandstand for a narrow base and raise money rather than legislate for a country. “The people despise us all,” he said. “And why is this? Because we’re not doing our job.”

It served as a warning that went unheeded, and 11 years later, we’re watching more dysfunction in government than ever before. Sasse, now dying of Stage 4 pancreatic cancer at 54, is still saying the same thing. The diagnosis has not changed the message. It has sharpened it.

Whether Sasse was a “good” or “effective” senator is debatable. Whether Washington currently has enough senators like him is not a close question.

The criticism that followed him throughout his eight-year tenure is almost entirely subjective. His critics on the Left saw a man willing to deplore Trumpism in public while voting with President Donald Trump‘s agenda in practice. His critics on the Right, particularly as the party realigned, saw a posturing institutionalist more interested in making points and serving as a pundit than in getting on board fully with the president’s policies. The most durable version of this critique runs something like: He gave great speeches and passed no significant legislation.

Yuval Levin, founding editor of National Affairs and director of Social, Cultural, and Constitutional Studies at the American Enterprise Institute, largely rejects both sets of criticisms. On the Trump question specifically, Levin is direct: “The notion that there was much more he could have done to hold Trump to account is misdirected and mistaken. He took on Trump when he disagreed with him, and when he thought Trump had exceeded his authority or violated his oath. And unlike most Senate Republican critics of Trump, he ran for reelection and won after doing that.”

The objection to the lack of signature legislation mistakes the Senate’s function for a body it was never designed to be. In the framework Sasse spent years articulating, the Senate is not primarily a factory for producing legislation. It is a deliberative institution meant to apply friction to democratic impulses in the House of Representatives, to slow things down when people want to move too fast, and to force the executive and judiciary to operate within appropriate constitutional limits. By that standard, which is closer to the Founders’ intent than the one applied by Sasse’s critics, he understood and performed his role better than most of his colleagues.

The “pundit” critique oversimplifies his actual record. Sasse served on the Senate Intelligence Committee throughout his tenure, and his work on China there was substantive and largely ahead of the political mainstream. When it was still unfashionable for a Republican to identify Beijing as a generational geopolitical threat rather than an irritating trade partner, Sasse was making that case in the committee rooms that mattered. He had genuine expertise in China’s intelligence operations and, accordingly, used his position, spending considerable time in secure facilities at times when most of his colleagues were busier developing a social media strategy.

Sen. Mark Warner (D-VA), who worked alongside him on the intelligence committee, offered perhaps the most precise characterization of what made Sasse different, telling Scott Pelley on 60 Minutes in April that Sasse “never really thought about things as conservative, liberal. He thought much more about issues, such as the future and the past.” Senate Majority Leader John Thune (R-SD) said Sasse had a “concern not just for today, but for tomorrow and the future” and that he “wasn’t distracted by all the noise that goes around us on a daily basis.” [...]

Levin, who watched Sasse’s tenure closely, offers a candid accounting of his legislative limitations. “It’s true that Ben was not an active legislator, advancing proposals, sponsoring and co-sponsoring legislation, and building coalitions,” he said. “He was active in some key committees, especially the Intelligence Committee, where it seemed to him that active engagement could make a difference. But I think he concluded this was not the case in some of his other committees and that he might be more useful as a critic and observer of the institution. No individual senator gets a lot done right now, and of course, that’s part of the frustration he had.”

But the moments that defined Sasse as a senator were the ones that did not produce legislation, and those are the moments worth examining without the usual condescension.

On the first day of Justice Brett Kavanaugh‘s Supreme Court confirmation hearings in September 2018, the chamber descended almost immediately into the theater that had by then become customary. Protesters disrupted proceedings from the gallery. Democratic senators jockeyed for camera time. The atmosphere was more performance than inquiry. Into this circus, Sasse delivered a 12-minute statement that went viral because it said plainly what almost no one in that room was willing to say: The hysteria around confirmation hearings is a symptom, not the disease. Congress had spent decades delegating its legislative authority to executive agencies and now blamed the courts for filling the vacuum.

“It is predictable now that every confirmation hearing is going to be an overblown, politicized circus,” he said. “And it’s because we’ve accepted a bad new theory about how our three branches of government should work.” The corrective he offered was simple: Congress should pass laws and stand before voters. The executive should enforce those laws. Judges should apply them, not write them. Naturally, no one disagreed out loud.

He delivered a version of the same argument at Justice Amy Coney Barrett‘s hearing in 2020. Neither speech moved the institution. Both captured something true and important about why the institution was failing, and both were widely shared by people who had largely stopped expecting a sitting senator to say anything worth sharing. The Kavanaugh statement was described in this publication at the time as the civics lesson Washington desperately needed. That it needed to be given by a freshman senator to the full Senate Judiciary Committee was Sasse’s real point.

He also understood, more clearly than most of his colleagues, that the Senate’s dysfunction was not incidental but structural. The cameras, he argued, were a bad incentive. The constant travel and time spent fundraising corroded the relationships that make effective governing possible. Most tellingly, he believed that senators had come to treat their office as the purpose of their lives rather than a temporary form of service to something larger. When Pelley noted on 60 Minutes that many senators he knew “would not be able to breathe without that job,” Sasse replied that he feared that was true and that it represented “a much, much deeper problem.” The best title a person could hold, he said, was dad, mom, neighbor, friend. Senator was “a great way to serve. It should be your 11th calling or maybe sixth, but never top.”

When he resigned from the Senate in January 2023 with four years remaining in his term to become president of the University of Florida, many observers treated it as confirmation of the pundit critique: He could not stay the course. The more honest reading is that he had concluded the institution was, as he told Pelley, “very, very unproductive” and that there were better things for him to do. “We didn’t do real things,” he said. “And it felt like the opportunity cost was really high.” He moved to Florida, then stepped down from that post roughly a year and a half later when his wife, Melissa, was diagnosed with epilepsy and required full-time care. The man who had argued that being a senator should rank no higher than sixth on a person’s list of priorities was living accordingly.

Then, on Dec. 23, 2025, he posted the news to X. “Last week I was diagnosed with metastasized, stage-four pancreatic cancer, and am gonna die.” He was 53. Doctors at MD Anderson Cancer Center had cataloged the full spread: lymphoma, vascular cancer, lung cancer, liver cancer, and pancreatic cancer, the point of origin. He had been given three to four months to live. He called it what it was: “Advanced pancreatic is nasty stuff; it’s a death sentence.”

What followed was unexpected, at least to anyone who had expected Sasse to retreat from public life. He launched a podcast called Not Dead Yet. He sat down for a conversation with New York Times columnist Ross Douthat on the latter’s Interesting Times podcast in April, which was released just days after the interview aired and subsequently circulated widely. He appeared on 60 Minutes with Pelley on April 26, his face visibly marked by his medication, a drug called daraxonrasib from Revolution Medicines that had shrunk his tumors by 76% and extended his life by months that were not supposed to exist. He credited the extra time to “providence, prayer, and a miracle drug.”

The Douthat interview was the more intimate of the two conversations and the more remarkable. Douthat asked Sasse at the close whether he felt ready to die. Sasse said he did not feel ready but that he had hope, grounded in his Reformed Christian faith, that he would be with God. The response moved Douthat visibly to tears, something Sasse responded to with his characteristic dry humor. Earlier in the conversation, Sasse reflected on what the disease had given him alongside what it had taken. “I hate pancreatic cancer,” he told Douthat. “I would never wish it on anyone, but I would never want to go back to a time in my life where I didn’t know the prayer of pancreatic cancer. I can’t keep the planets in orbit. I can’t even grow skin on my face.”

The “prayer of pancreatic cancer,” as Sasse uses the phrase, is something like the acknowledgment of dependence that most people spend their healthiest years avoiding. He is not unusual among the terminally ill in arriving at that acknowledgment. He is unusual in the way he has extended it outward, into public argument, into the same institutional critique he was making in November 2015. On 60 Minutes, he was asked what Congress was missing, and he named the artificial intelligence revolution, the future of work, and the complete absence of 2030 or 2050 thinking in either party. Then, without prompting, he returned to the frame he had always used. “The Senate needs to be less like Instagram. The Senate needs to be more deliberative, and that means less smack-down nonsense,” he told Pelley, adding, “The Senate should be plodding, and steady, and boring, and trustworthy.”

by Jay Caruso, Washington Examiner |  Read more:

Image: uncredited via

[ed. I knew very little about Ben Sasse before reading an article about daraxonrasib, the new breakthrough drug given to him in his treatment for aggressive pancreatic cancer. It goes without saying that Congress would be an entirely different place if there were more people like him. See also: Pancreatic cancer just met its match (Works in Progress):]

***

"For most of the last half-century, a diagnosis of metastatic pancreatic cancer was a death sentence. In December 2025, former Nebraska Senator Ben Sasse announced he had been diagnosed with stage four pancreatic cancer that had spread to his lungs, liver and other organs, and was given three to four months to live from the time of diagnosis. With little to lose, he enrolled in a clinical trial for an experimental drug. Four months later, he reported a 76 percent reduction in tumor volume, describing the drug, daraxonrasib, as a ‘miracle’. His face, ravaged by a severe skin rash from the treatment, told a more complicated story. Yet he was alive and grateful to be able to talk to his family.

A few days after Sasse’s interview, in April 2026, Revolution Medicines announced Phase 3 trial results for daraxonrasib showing the drug had roughly doubled survival in patients with metastatic pancreatic cancer compared to standard chemotherapy. For a disease where median survival has long been measured in months and where little had changed for decades, that result represents a genuine turning point.

But the significance extends beyond pancreatic cancer. Daraxonrasib is among the first drugs in an emerging generation designed to target RAS, a protein implicated in roughly a quarter of all human cancers and long considered beyond reach, in all its mutant forms. And it belongs to a broader class of medicines, molecular glues, that are beginning to show what becomes possible when drugs no longer depend on finding a ready-made pocket in their target. Several compounds in this class are now in clinical development, each probing a different protein that previous generations of drugs could not touch."

Why the Future of College Could Look Like OnlyFans

Last week, I asked whether, as a forty-six-year-old father of two, I should keep contributing to my children’s college funds, or if perhaps some combination of anti-establishment fervor, A.I., and a shifting economy could save me some money. I don’t have a particularly good answer yet, at least not one good enough to inspire the purchase of a midlife-crisis car, my son’s and daughter’s futures be damned. But, after wrestling with that query in Part 1 of what will be a series of articles, I think there may be a better one to ask. The question is not, I think, “How will A.I. change higher education?” but rather “What irreversible changes have already taken place, and how will colleges and universities respond to them?”

I wanted to talk with someone who stood outside the polite consensus which holds that college as we know it will survive, if only because, as I wrote last week, humans will always want to differentiate their children from other people’s children. Hollis Robbins, a professor of English and a special adviser in the humanities at the University of Utah, and the former dean of arts and humanities at Sonoma State University, has been writing about A.I. and higher education for years on her Substack, “Anecdotal Value.” Through her writing on the subject, her own experiments with A.I., and her experience at both élite private and regional public universities, she has hashed out a theory of sorts. In Robbins’s opinion, an excessively bureaucratic, increasingly generic, and poorly taught version of higher education has taken hold around the country, and that has made the modern university seriously vulnerable to an A.I. takeover.

What can academics do about this? College, Robbins believes, should be more bespoke; schools should cultivate their own character based on the charisma of professors, the novelty of their inquiries, and the quality of their instruction. Today, thanks in part to the Common Application and to the always increasing pressure for students to go simply to the most prestigious college they can, even élite schools are becoming interchangeable. Brown and the University of Chicago have roughly the same pool of students as, say, Vanderbilt, or Georgia Tech. And, once the unique essence of a school has been lost, and the curricula have been standardized for maximum friendliness to students, who are treated as customer kings, A.I. may come to seem like a plausible alternative. In this view, rampant A.I.-assisted cheating, rapidly declining faith in the value of a college education, and general agita on the part of the nation’s faculty are all symptoms of a larger sickness: an academy that has been stripped of everything that once made it special. [...]

In a widely discussed Substack post from last year, titled “It’s Later Than You Think,” Robbins argued that artificial general intelligence would require a culling of sixty to seventy per cent of the country’s professors, and that every professor who wanted to keep their job should write a memo answering the question “What specific knowledge do I possess that AGI does not?” Faculty members who could not produce a compelling memo “with concrete defensible answers,” she wrote, “have no place in the institution.” The university in the age of A.I. will be leaner, odder, and more differentiated from its peers, she maintains, because “students cannot be expected to continue paying for information transfer that AGI provides freely.” Instead, they will “pay to learn from faculty whose expertise surpasses AI, offering mentorship, inspiration, and meaningful access to AGI-era careers and networks.” Any institution that does not adapt will die. “This isn’t a mere transformation but a brutal winnowing,” Robbins writes. “Most institutions will fail, and those that remain will be unrecognizable by today’s standards.”

I recently asked Robbins about how she came to this conclusion, and what, exactly, those surviving institutions might look like. This interview has been edited for length and clarity.

You’ve written a lot about how the modern university has primed itself for an A.I. takeover. How did that happen?

... The first two years of a college education are now more or less the same, regardless of where you go to school. Courses now need to be equivalent to one another, so that a student at one school will be learning something similar to a student at a different school. What that has done over time is created a system where it doesn’t really matter who is teaching the classes. We tell the student, “You’re special,” and we tell the faculty, “You’re not special.” This is the tension and the problem that is plaguing higher education and what’s made it so vulnerable to A.I. Everything else—whether Trump, the enrollment cliff, or whatever—is secondary to this tension. [...]

I’m not a car person, but I have friends who have fancy BMWs, and they have to go to their fancy BMW place to fix their car, because BMW parts are often very specific to BMWs. So what does it mean for higher ed when all the parts are interchangeable? Almost forty per cent of students transfer at least once from institution to institution, and that places additional pressure to make everything the same. What happens is that colleges make it easier for their students to transfer, because parents want to have some backup plan. The high number of transfers leads to more fungibility and commodification.

In a Substack post from last year, you suggested that sixty to seventy per cent of faculty will ultimately lose their jobs once generative A.I. starts to hit the classroom, and that those who survive will need to explain why they’re still needed. How do you think they should be proving their worthiness?

Higher education and professors can differentiate themselves from all this sameness by teaching at the edges of knowledge. My expertise, for example, is in the African American sonnet tradition. There are probably three people on the entire planet who know as much as I do about this tiny little thing, and so I’ve spent a lot of my time experimenting with these large language models to just see what they know about my field, and where the edges are. Specialists are going to be key to selling education as something the A.I. can’t do. When your daughter is going to go to school, in eight years, you are not going to want, for any money, to have her learn standard educational product that A.I. knows—and A.I. will know so much, right?

I’m not sure about that, because I do think that there’s value in her learning things that a computer knows. Human beings still play chess, even though a human being hasn’t beaten the best chess computers in twenty years—and I would think there’s still value in her understanding the basic theories and foundations of, say, chemistry. Even if A.I. knows all of that, she should probably know it, too, if she wants to understand what those edges of knowledge are, no?

So, in my ideal vision of the academy, you’re going to be in class with a mentor who isn’t going to have to teach you Chemistry 101 but will want to quickly move to where the edges are, to do something new. Maybe they would decide together to 3-D-print some new material that has never been printed before, or what have you. Whatever they decide together will not be something every university is going to be able to do. It will be what’s particular at this place. [...]

Does that lead to a kind of obscurity? It would seem to encourage the esoteric sort of inquiry that the public sometimes resists.

Well, I won’t use the word “obscurity.” I would say “specialization.”

Let me make a couple of predictions and distinctions. Social science is going to matter so much less when your daughter goes to college. It is already on its way out. A.I. can do it. And here’s an example of the type of inquiry I’m talking about: I have a weird, funny Twitter group about life on Mars. Someone will ask, for instance, if it’s true that you’re going to need kidney dialysis on the way back from Mars. Another person is theorizing about a 3-D printer that’s going to use Mars soil, which will allow people to build on Mars using its materials instead of shipping everything there. These sorts of inquiries are obscure, specialist, niche, at the edge. [...]

Does that mean kids will be coming to college with a different baseline of knowledge because of A.I.? That a lot of the canon in whatever field they choose will already have been transferred to their brains? I can’t help but remember my own experience as a freshman in college, being completely unprepared for an upper-level religion course, much less any edge-of-knowledge inquiry.

They’re going to be coming in with a different baseline. Once upon a time, you walked into class and a hundred per cent of what was delivered to you was through your professor. Now, you go to a class, maybe you’ll do the reading, but you’ll also ask ChatGPT or Claude. And so your course content is already coming from somewhere else. This is a problem that higher ed has not addressed substantially. What does it mean for me to grade you on something where you got all your information from somewhere else and not from my reading list? That is a complicated question. The only thing that works is for us to get to the edge quickly.

There’s a growing idea I’ve seen in some circles that college could be replaced by conversations between an A.I. tutor and a student. When I think about your model, I wonder why college even needs to exist. If I can just seek out a tutor, somebody that I like, and they just charge me a little bit, and we go through these edge-knowledge cases together, what’s the degree for? Couldn’t you, as Hollis Robbins—not only a specialist in African American sonnet traditions but also an idiosyncratic thinker on the subject of A.I. and the future of the academy—just set up your own shop?

I was in Austin, Texas, a couple of times in March with a bunch of twenty-five-year-old billionaires. This is what they’re looking at. Instead of having the credential from the institution, why not have the credential from the professor? If you have a Hollis Robbins education, what would that signal? What would that credential mean as opposed to a degree from a university? There was some conversation about what that would look like, and one guy at the end of the dinner said, “Instead of OnlyFans, it’s like OnlyProfessors.”

Do you think an OnlyProfessors model would be good? That the dissolution of the vast majority of the higher-education infrastructure, with this replacing it, would be a good outcome?

I worry about where the great middle of America is going to go. I do think students are going to have to withdraw enrollment from schools unless things change. And I don’t think institutions are going to change themselves. They’re caught up in this bureaucratic system, this transfer system, these standardization agreements across state lines, so that anybody can move anywhere. The idea of delivering a standard education product is so embedded within the current structure that it will never change unless students say, “This is not what I want from going to college.” So, yes, OnlyProfessors is an alternative. [...]

And the death of our current universities? What does that look like?

I think there’s contraction. The big flagships are going to stay the same, because they have the football players and all the other things. I’m at the University of Utah—I think it’s going to be fine. We’re going to pick up the lifeboats from the places that crumble. But, ultimately, at the very top, presidents and provosts are going to have to understand that expertise is their mission. Yale, even, went back to making their mission statement about knowledge, not about making a better world. We’re not in the making-a-better-world game anymore. We’re in the knowledge game, and that means getting rid of some of the feel-good stuff. [ed. Like humanities, civics, history, philosophy, logic...] 

by Jay Caspian Kang, New Yorker | Read more:
Image: David Rowland/Getty

[ed. Couldn't disagree more. Started writing all the reasons why but then just figured 'eh... what's the use'. This really is a bizarre interview with... whoever this person is. I will say that if having ready information at your fingertips (or some personal estoteric knowledge) were all it took to be educated, Google would've put universities out of business a long time ago. There's a reason (with all the instructional videos on YouTube) that people still go to teachers.]

Sunstones

For over a thousand years, historians thought the Viking "sunstone" was nothing more than a myth, until the ocean gave up its secret. The Norse sagas repeatedly referenced a mysterious object called a "sólarsteinn" or sunstone, a navigational tool so powerful that Viking sailors could locate the exact position of the sun even on the most overcast and cloudy days. For centuries, scholars debated whether this was real technology or simply folklore embellished over generations of retelling. Most assumed it was legend. They were wrong. 

In 2013, marine archaeologists excavating a British warship that sank near the Channel Islands in 1592 made a stunning discovery buried among the wreckage. Alongside navigational instruments including a pair of dividers and a slate, they found a rectangular chunk of translucent crystal. Testing confirmed it was Iceland spar, a remarkably pure form of calcite with extraordinary optical properties. The fact that it was found stored alongside other precision navigation tools was not a coincidence. 

Iceland spar possesses a property called birefringence, meaning it splits a single beam of light entering the crystal into two separate beams. When you hold the crystal up toward the sky and slowly rotate it, the two beams will vary in brightness independently until, at one specific angle of rotation, they become perfectly equal in intensity. That precise angle points directly toward the sun, regardless of whether the sun is visible to the naked eye. Cloud cover, fog, and even twilight conditions cannot defeat it. 

Researchers from the University of Rennes in France conducted extensive testing and published their findings in the Proceedings of the Royal Society A. Their experiments demonstrated that Iceland spar could locate the sun's position with an accuracy of within one degree, even under completely overcast skies. For Viking navigators crossing the North Atlantic toward Iceland, Greenland, and eventually North America, this accuracy would have meant the difference between a successful voyage and sailing hopelessly off course into open ocean. The Viking Age spanned roughly 793 to 1066 AD, and during this period Norse sailors were completing oceanic crossings that would not be replicated by other European cultures for another 400 years. Historians had long puzzled over how they achieved such consistent navigational precision without magnetic compasses, which did not reach Europe until the 12th century. The sunstone appears to be a significant part of that answer. 

What makes the Channel Islands find especially compelling is that the 1592 shipwreck is far outside the traditional Viking era, suggesting that knowledge of this navigational technique survived and was still being used by European sailors centuries after the Viking Age officially ended. The crystal was not a relic or a curiosity on that ship. It was working equipment. 

via: SubRosa/X

Why Consciousness Researchers Have Failed (So Far)

Oh god, I barely made it through.

Experienced sensations while reading: frustration, dread, restless legs, and overwhelming waves of weariness. At one point I felt physically nauseous.

I’ve been trying to figure out why, since (a) Michael Pollan is a great writer who has proven his chops over countless other topics, and (b) this is objectively quite a good book about the science of consciousness. Indeed, I should be happy! Consciousness is clearly having “a moment” right now—a science book about consciousness has been on The New York Times bestseller list for nine weeks, and meanwhile, the online world is abuzz with debates about AI consciousness.

And yet… I hated Pollan’s book.

I felt that every next chapter or section could have been predicted by some statistical machine for producing books about consciousness (“Okay, here’s the part about David Chalmers coming up”). And yes, I have the advantage of being a researcher in the same subject and have even worked with some of the figures Pollan writes about, which is why in my own The World Behind the World (we all seem to gravitate to the same titles, huh) I broadly told much the same story. But you can even go back to science journalist John Horgan’s The Undiscovered Mind, published in 1999, to get similar progress beats and quite familiar names. It’s been 27 years, during which the discussion has (as many fields of science do) centered around major figures like neuroscientists Christof Koch or Giulio Tononi or Antonio Damasio or philosophers like David Chalmers. There’s always the part where Alison Gopnik makes an appearance. Karl Friston pops his head in. And all these people are intellectual titans. Truly. But honestly, this stage of consciousness research feels played out.

Like you have Christof Koch, one of the highest-profile figures, who broke open the field in the 1990s with Francis Crick (co-discoverer of DNA’s structure) and gave one of the first proposals for a neural correlate of consciousness: gamma oscillations in the ~40Hz range in the cortex.

Koch, who is soon to turn seventy, was for a while after the death of Francis Crick a staunch supporter of Integrated Information Theory (I was part of the team that worked on developing that theory after Giulio Tononi proposed it, and even once did a conference submission with Koch himself). But now Koch has apparently moved on to other approaches to consciousness, mentioning his attendance of an ayahuasca ceremony and his accessing of a “universal mind.”

Here’s Pollan talking to Koch at the end of the book:

When I confessed to Koch my fear—that after my five-year journey into the nature and workings of consciousness, I somehow knew less than I did when I started—he simply smiled.

“But that’s good,” he said. “That’s progress.”

No, it isn’t!

Consciousness is not here for our personal therapy. It’s not tied to our life journeys. And I’m guilty of all that artsy and personal stuff too! But it’s no longer about how the grand mystery makes us feel, or the friends we made along the way.

It’s all changed.

HOW WE FAILED

Right now, there’s some college student falling in love with a chatbot instead of the young woman who sits next to him in class, all because science literally cannot tell him that the chatbot is lying about experiencing love. On the other hand, if somehow AIs are conscious, either right now (to some degree), or near-future ones will become so, then they deserve rights and protections, and the entire legal and social apparatus of our civilization must expand rapidly to include radically different types of minds (or we must choose to restrict what kinds of minds we create). There are immediate practical matters here. Long term, we also need to protect against extremely bad futures where only non-conscious intelligences remain—the worst of all possible worlds is that our civilization acts like a reverse metamorphosis, where something weaker but more beautiful, organic consciousness, gets shed in the birth of some horrible star-devouring insect made of matrix multiplication. And then it turns out there is nothing it is like to be two matrices multiplying.

While it’s my opinion that modern LLMs operate more like tools right now, or at best like a lesser statistical approximation of what a good human output would be (with their main advantage being search, not insight), this is all just the beginning of the technology. The door is open and will never be closed again.

Of course, consciousness matters far beyond just AI. Table stakes for actual scientific progress on consciousness include shifting neuroscience and psychiatry from pre-paradigmatic to post-paradigmatic sciences (and all the pile-on effects from that). This was always true. But my point here is that LLMs act like a forcing function. Before everything changed, consciousness research was an unhurried subfield of neuroscience that was always a little weird and niche; therefore academics are guilty of treating consciousness like an academic exercise. [...]

Due to the rise of behaviorism and logical positivism, “consciousness” became a dirty word in science for half a century or more—precisely when the rest of the sciences rocketed ahead! The consciousness winter only really ended in the 1990s because of the collective weight of several Nobel Prize winners (like Francis Crick and Gerald Edelman) determined to make it acceptable again.

The two major scientific conferences (which are how scientists organize) devoted to consciousness also only started in the mid-90s. That’s just 30 years ago! Modern science is incredibly powerful, maybe the most powerful force in existence, but in the grand scheme of things, 30 years is not long at all. That’s just one generation of scientists and thinkers. Kudos to them. Pretty much all of the big names (including definitely Koch) deserve their laurels, and contra Pollan, I do think consciousness actually has made progress over the last 30 years, in that our conceptions are a lot cleaner, the definitional problem is pretty much solved, a lot of the space of initial possible theories is mapped, the problems and difficulties are much better known and clearly outlined, and there is organizational and behind-the-scenes structure that exists in the form of established conferences and labs and minor amounts of funding, etc.

And that’s another thing: no one has tried throwing money at the consciousness problem, at all—and for many problems, from AI to cancer cures, a necessary component often ends up being finance and scale and concentrating talent.

Humanity spends something like a billion dollars a year on CERN. To compare, let’s look at the biggest scientific funder in the United States, the NIH. Out of 103,280 grants awarded to scientists during the 2007-2017 decade, want to guess how many were about directly studying the contents of consciousness?

Five.

That’s probably, at most, a couple million dollars in funding over a decade. Total. So if you’re a consciousness researcher, what can you do, cheaply? What can you do, for free? You can pontificate. You can propose your own theory of consciousness! That requires no funding whatsoever. And so for 30 years the meta in consciousness research has been to create your own theory of consciousness. We’ve let a thousand flowers bloom. The problem is that, if any flower is at all true or promising, you can’t identify it, as its sweet subjectivity-solving scent is completely masked by the bunches of corpse flowers around it. We have too many flowers, and one more just isn’t meaningful anymore. As is sometimes said at the end of fairy tales: “Snip, snap, snout. This tale’s told out.”

What we need are efforts at field-clearing, and methods that can actually make progress on consciousness in ways not tied to just promoting or trying to find evidence for some pre-chosen pet theory—which means finding ways to select over theories, to test theories en masse, so you don’t reinvent the wheel each time, and, perhaps most importantly, you have to do all this while scaling institutions with funding to specifically get a bunch of smart people in a room working together on this.

ME GETTING OFF MY ASS

If the 2020s were all about intelligence, then necessarily the 2030s will be all about consciousness. Intelligence is about function, while consciousness is about being, and forays and progress into understanding (and shaping) function will in turn force our attention toward a better understanding of being. And if the answer to “Why has consciousness not been solved?” is secretly “Material and historical conditions made it hard for anyone to actually try!” then the answer is to actually try.

I refuse to live in a civilization where we consciousness researchers have so obviously failed. I refuse to live in a civilization where we cannot tell consciousness from non-consciousness. Where we can offer no guidance for the future. Where we cannot explain the difference between actually experiencing things vs just processing them. In the short term, this is destabilizing and harmful. In the long term, it may be literally existentially dangerous.

by Erik Hoel, Intrinsic Perspective |  Read more:

Image: Michael Pollan/Penguin Random House

[ed. I thought consciousness research was going great guns since it's central to determining AGI (artificial general intelligence). Huh. See also: His ‘Machine’ Could Uncover the Origin of Human Consciousness—And if It Truly Connects to the Whole Universe (Popular Mechanics)]

AI Systems Are About to Start Building Themselves.

What does that mean?

I’m writing this post because when I look at all the publicly available information I reluctantly come to the view that there’s a likely chance (60%+) that no-human-involved AI R&D - an AI system powerful enough that it could plausibly autonomously build its own successor - happens by the end of 2028.

This is a big deal.

I don’t know how to wrap my head around it.

It’s a reluctant view because the implications are so large that I feel dwarfed by them, and I’m not sure society is ready for the kinds of changes implied by achieving automated AI R&D.

I now believe we are living in the time that AI research will be end-to-end automated. If that happens, we will cross a Rubicon into a nearly-impossible-to-forecast future. More on this later.

The purpose of this essay is to enumerate why I think the takeoff towards fully automated AI R&D is happening. I’ll discuss some of the consequences of this, but mostly I expect to spend the majority of this essay discussing the evidence for this belief, and will spend most of 2026 working through the implications.

In terms of timing, I don’t expect this to happen in 2026. But I think we could see an example of a “model end-to-end trains it successor” within a year or two - certainly a proof-of-concept at the non-frontier model stage, though frontier models may be harder (they’re a lot more expensive and are the product of a lot of humans working extremely hard).

My reasoning for this stems primarily from public information: papers on arXiv, bioRxiv, and NBER, as well as observing the products being deployed into the world by the frontier companies. From this data I arrive at the conclusion that all the pieces are in place for automating the production of today’s AI systems - the engineering components of AI development. And if scaling trends continue, we should prepare for models to get creative enough that they may be able to substitute for human researchers at having creative ideas for novel research paths, thus pushing forward the frontier themselves, as well as refining what is already known.

Upfront caveat

For much of this piece I’m going to try to assemble a mosaic view of AI progress out of things that have happened with many individual benchmarks. As anyone who studies benchmarks knows, all benchmarks have some idiosyncratic flaws. The important thing to me is the aggregate trend which emerges through looking at all of these datapoints together, and you should assume that I am aware of the drawbacks of each individual datapoint.

Now, let’s go through some of the evidence together.

by Jack Clark, Import AI |  Read more:

[ed. From what I can tell, most people in the AI field find this timeline entirely plausible (give or take a couple of years). Others expect, the next five years to be a time of great change and turbulence. See also:]

The seven deadly curses of superhuman AI: