Life in the billionaire bunkers after the apocalypse

Billionaires Are Prepping for Doomsday | Glenn Loury, Nikita Petrov & Mark Sussman | The Glenn Show

Timestamps:

0:00 Intro
1:28 Biden’s abysmal debate performance
5:01 Billionaire survivalists
12:53 So you made it to your luxury bunker. Now what?
16:22 The postapocalyptic war of all against all
21:29 Is the very existence of billionaires the real doomsday scenario?
26:20 The doomsday tax
32:24 Will the bunker dwellers have a reason to live?
40:39 The problem of government after nuclear holocaust
46:08 The literal bunker mentality
52:08 Was Mark responsible for Sam Bankman-Fried’s downfall? Who can say for sure?

Colt Clark and the Quarantine Kids + COUSINS play Surfin' U.S.A.

Watch the little guy at the lower left.

A Chinese challenge to Amazon

Spencer Soper, Bloomberg Tech Daily Newsletter, July 5, 2024.

Temu has taught Amazon.com Inc. an important lesson: US shoppers can be patient if it saves them money.

News broke last week that Amazon is planning a low-priced store for apparel and home goods shipped directly to US shoppers from China, signaling that the ecommerce giant is taking seriously the threat posed by discounters like Temu and Shein.

Amazon helped change the way people shop by building a vast network of warehouses designed to stockpile products and quickly send them to customers. That model requires products manufactured in China to be shipped by sea in bulk to the US and trucked to warehouses around the country.

The upside is that products are close to shoppers, enabling delivery in just a day or two. Amazon has been investing in sharpening that delivery advantage over rivals with warehouses closer to consumers to increase the number of products they’ll receive quickly.

That’s not what Chinese rivals like Temu have been doing, in part because they can’t afford to compete with such a cost-intensive strategy.

Bulk shipments of products from China are typically subject to tariffs, which were increased to about 25% in 2018. And Amazon pays for its warehouses through fees charged to online merchants and customers via the $139 annual cost of an Amazon Prime subscription.

Temu and Shein are operating what’s often described as the factory-to-consumer model. Products are shipped in smaller batches from Chinese factories to warehouses close to Chinese airports. When US shoppers place orders, the products are put on US-bound cargo planes and sent directly to customers. But it takes a week or two for shoppers to get what they purchased. The lower delivery costs let Temu and Shein offer prices that Amazon has been unable to match with its costly logistics operation.

The consumer packages shipped from China slip into the US without tariffs thanks to a century-old loophole called “de minimis,” which essentially means any shipment with less than $800 in products enters the US tax-free.

There's more at the link.

Friday Fotos: Along the Hudson River

Bloom the aesthete: Does Bloom abandon the humanistic tradition in his take on the canon?

Dr. Scott Masson: Harold Bloom's strange defence of the Western Canon

This lecture briefly discusses the idea of a literary canon, as opposed to the Biblical canon. The former unlike the latter can admit of additions. Harold Bloom defends the idea of the Western canon on exclusively aesthetic grounds, which is an extraordinary departure from the rationale given for studying it traditionally.

However, while the 'canon wars' of the 1980s that pushed for the inclusion of authors usually on grounds of what we now call 'identity' was objectionable, it is nothing like as problematic as the idea that the previous canon needs to be utterly replaced. The cultural studies approach to literature is an expression of the latent cultural Marxism of the earlier critics being more fully articulated.

I have transcribed some passages from the lecture. I'm simply reproducing the automatically generated transcription without capitalization and punctuation, etc. Starting at about 19:37:

the problem that he brings up at the beginning here is that overpopulation malthusian repletion [p. 19 in The Western Canon] is the authentic context for canonical anxieties this is his rather interesting way of presenting this there are too many books to be read now and and um this is the the problem now when you read Bloom by the way I think you always have to realize that he is um being um humorous I don't think he's altogether serious in his uh it's sort of a playful engagement with the critics and yet there's something that is serious in it and his where where he is serious is in thinking that the Canon serves aesthetic purposes alone and nothing but aesthetic purposes that's the purpose of the the Canon of literature and the Western Canon he sees it as a uh collection of books whose inclusion in the Canon is solely on the basis of aesthetic Merit solely he's very strong on this

Continuing at 21:34:

he strongly opposes uh morality as a consideration here which is an extraordinary position to take now this is the defender of the western Cannon you have to realize when he writes this in the early 90s I think it's 1994 he is defending against the what he calls the uh what does he call them his critics School of resent School of resentment yes so these people who are just motivated by Envy and resentment whing negative emotions um are just not readers at all or they are readers that are moved by politics or social uh motivations and that's not the right way to understand literature well what is the right way well Bloom says to study for the purpose of aesthetic Merit and that alone so this is the defense of the western Canon and interesting you'll you'll be interested interest interested in this as well uh Harold Bloom was uh a Jewish um I say an atheistic Jew um committed to a very Gnostic understanding of life you can see other works written by him and he's also a romantic scholar and I think that's also key to his development [...] but he's opposed to the idea of the Canon including a concept like goodness let alone truth and uh in so doing I think that he abandons the whole humanistic tradition going back from the ancient world all the way up to his contemporaries so he's a very unusual figure

Then at 24:22:

forget the Canon as a list of books for required study will be seen as identical with the literary art of memory not with the religious sense of Canon so it's something that individuals and it's for individuals the Canon then is for individuals it's not it doesn't have a broader humanizing function and it's something that you choose that and here's Mr Bloom's Canon that as an aesthete but it doesn't serve the purpose of humanitas then which the uh tradition of the helenistic critics would most certainly have held that's why we read to be educated Mr Bloom's notion of canonicity is not for the purposes of Education it's for the purposes of titilation or Delight that's it but we saw last semester that um even in Horace he sees the that there are two purpos at least for good literature and one of them is that bloom excludes is to teach to teach and to Delight Augustina adds to move to that to teach to Delight to move and Bloom has reduced it to delighting and I don't see what the difference is in certain respects between uh great works of literature and entertainment at that point it's just one's high brow and the other's low

Not fireworks

On the significance of human language to the problem of intelligence (& superintelligence)

Back in May I did a post entitled, How smart could an A.I. be? Intelligence in a network of human and machine agents. Toward the end I said this:

The question of machine superintelligence would then become:

Will there ever come a time when we have problem-solving networks where there exists at least one node that is assigned to a non-routine task, a creative task, if you will, that only a computer can perform?

That’s an interesting question. I specify non-routine task because we have all kinds of computing systems that are more effective at various tasks than humans are, from simple arithmetic calculations to such things solving the structure of a protein string. I fully expect the more and more systems will evolve that are capable of solving such sophisticated, but ultimately routine, problems. But it’s not at all obvious to me that computational systems will eventually usurp all problem-solving tasks.

Remember, that even as we’re developing ever more capable AI systems, we are also developing more sophisticated modes of human problem solving.

Earlier in the post I observed: “Human intelligence is not fixed in the way that animal intelligence is.” That’s what I want to comment on.

Animal intelligence is fixed by biology. Animals have capacities for sensation and movement that are fixed by biology. Those capacities bind them to a particular environment. That that from that environment and they will perish.

Humans are not quite like that. We developed the capacity to communicate through language. And that capacity allowed us to develop new modes of thought. Just how that happened needs to be thought through in some detail, but I’m just going move through it quickly for now. We notice patterns in the world, capture them in language by talking them through with our fellows. We become curious about those patterns, we ask why? and make up stories in explanation. In this process we work ourselves free of the limits of our biological capacities for sensing and acting. We abstract over and act in the world in the way that no other animals can. From speech, we develop writing, then calculation, and moved onto computation over the last hundred years or so, a progression David Hays and sketched out in The Evolution of Cognition, which we published in 1990. With the emergence of recent developments in artificial intelligence, we’re pushing that process one step farther, leading me to write about the Fourth Arena (beyond Matter, Life, and Culture).

Is there anything beyond this? That’s the question I’m trying to formulate. Is there a “superintelligence” beyond this? We are “free” of our biological embedding in a specific sensory-motor world, free in the sense that we can move beyond that. Tens of thousands of years ago we became the only (higher) primate that moved out of the tropics to inhabit every land-based environment. We’ve sent people to the moon and back, have others living in orbit around the earth for months at a time, and can at least imagine establishing permanent colonies on the moon and Mars and other bodies. This last round of achievements are inextricably interwoven with various kinds of computing technology. Further advance will require more computation, of various kinds.

The difference between, say, the intelligence of a fish and the intelligence of a rat is of a certain kind. The difference between the intelligence of a rat and that of monkey is of the same kind. But the difference between the intelligence of an ape and that of a human is of a different kind. The difference comes about through language and collective culture. As far as I can tell, typical (Silicon Valley) speculation about superintelligence seems to think that is a kind of intelligence that is beyond human intelligence in the same way that human intelligence is beyond animal intelligence. The question I’m asking goes something like this:

In view of the fact that human intelligence is free of biological ‘binding’ to a specific environment, and in view of the fact that this freedom has allowed us to move through a succession of foundational architectures (speech, writing, calculation, computation, {whatever is happening now}), is there a fundamental capacity beyond THAT?

I have two responses: 1) It’s not obvious to me that there is. 2) I don’t know.

Computers are faster that brains, and can be built to have more capacity. What else is there? In a series of posts on AI, chess, and language, I’ve been looking at fundamental architectures, in effect, a family that is chess-like and a different family that is language-like. What else is there?

This brings me back to that earlier post that I referenced at the beginning of this one, and to the question I posed there:

Will there ever come a time when we have problem-solving networks where there exists at least one node that is assigned to a non-routine task, a creative task, if you will, that only a computer can perform?

I’m inching toward a way of suggesting that, if the answer to that question is “yes,” then that computer-based node must have some fundamental capacity that is beyond human capacity in the way that human capacity is beyond animal capacity. What could that (possibly) be? If such a thing were possible, is such a think existed, then we could never know it, could we?

Note: In thinking about that question, you might want to review the remarks I made about epistemological independence of autonomous agents in Intelligence, A.I. and analogy: Jaws & Girard, kumquats & MiGs, double-entry bookkeeping & supply and demand.

Stevens at night

Beverly Hills Cop: Axel F {schlock to schlock} [Media Notes 136]

I loved the original Beverly Hills Cop and was OK with the two sequels, the third less than the second. So I had to watch Beverly Hills Cop: Axel F.

Eh. But the "Axel F" theme still does it for me.

Writing in Variety (7.2.24), Owen Gleiberman admits that he never really like “action comedies.” With that in mind, I offer you some paragraphs from his thoughtful and informative review:

What the movie is really out to tap into is that old 1980s “high-powered” life-is-a-blockbuster feeling. The ’80s, at least in popular culture, were the definition of a carefree decade (in terms of movies, it could have been called: How we learned to stop worrying and love the popcorn schlock on steroids). And “Beverly Hills Cop: Axel F.” is engineered to make us feel, for a couple of hours, as carefree now as we did then. That’s why the whole cash-grab tackiness of the movie isn’t necessarily a liability. It’s actually part of the package.

I’ve always thought the story of how the original “Beverly Hills Cop” came to be was significant — that it was conceived as a straight-up police thriller starring Sylvester Stallone, and then, once Eddie Murphy came aboard, it was turned into a comedy. The motormouth effrontery of Murphy’s early-’80s screen personality, back when he still radiated joy in what he was doing, held the movie together, but “Beverly Hills Cop” was always a patchy, catch-as-catch-can hybrid. And now, with “Axel F.,” a parade of watchable clichés (not just retro-cop-thriller clichés but Eddie Murphy clichés) staged by director Mark Molloy in a slovenly utilitarian style, the series comes full circle: the product/schlock of the ’80s meets the product/schlock of Netflix. Welcome to nostalgia minus the soul!

There’s more at the link, worth reading.

Artificial stars?

Community in House, M.D. [Media Notes 135 B]

When I wrote yesterday’s post about House, M.D. I figured I might have more to say about it, but I didn’t have any explicit plans to do so. When I woke up this morning, I had an idea or two. These ideas center around community.

In this case we’re dealing with community on two levels. On the one level there’s the local community centered on our protagonist, Dr. Gregory House. This community includes his boss, Dr, Lisa Cuddy, his team of associates, Dr. Eric Foreman, Dr. Robert Chase, Dr. Allison Cameron, and his best friend, Dr. James Wilson. This local group then “shades out” through the hospital more generally. On another level there’s the community at large. This is where the patients come from. The hospital serves that community.

Illness and injury threaten that larger community. When a person is ill, they cannot participate fully in the community. When a person dies, the community is diminished. The hospital community exists to serve that larger community. The House-centered community operates within the hospital to serve that larger community.

The irony of the show is that at the center of this web of communal interactions we have an unpleasant misanthrope. House isn’t interested in the community. He’s interested in disease. What is the role of disease in the House community, if you will?

It structures their interactions, gives them purpose. In particular, differential diagnosis seems to be the central organizing activity in that local community. They meet, discuss and argue, and then go about their various tasks, usually assigned by House, who then may hang out in the office, while continuing to think, listen to music, watch TV, whatever. Those tasks will mostly take place elsewhere in hospital, though House’s associates will regularly venture outside the hospital to investigate patients’ homes and/or places of work.

The activity of differential diagnosis itself takes place through talk and writing on a white board. The talk is highly technical. I assume that it’s more or less technically correct, but I don’t know enough about medicine to judge that and I assume that’s true for most of the audience. What’s important is that we see the activity. We see investigation taking place. We experience diagnosis as a communal activity. How does this little community maintain itself in face of disease and under the pressure of the often at odds personalities of these doctors? That’s what we’re seeing. That’s what the show is about.

And then there’s serendipity. The process of differential diagnosis is driven by evidence, a patient’s symptoms and history, and by medical knowledge. And then there’s serendipity. Something accidental happens, someone notices something that might be totally unrelated to the case, but it sparks a train of thought the becomes relevant. Serendipity takes as to the edge of community, if not beyond it.

The upshot is that we see the social construction of truth, a construction that is tested in the process of treatment. The detective show does the same thing, but with a different set of procedures. We know that House was inspired in part by Conan Doyle’s Sherlock Holms and we know that the character of Holms was based, in part, on that of a surgeon, Joseph Bell. So we’ve got a century’s worth of narrative history trailing behind House, M.D., with each title having its particular mix of ingredients. It’s my impression that most of the titles don’t focus on the process of reasoning as closely as House, M.D. does. But this is not the place to even begin to sketch out the coordinates of that space.

* * * * *

Addendum 7.3.24: I should have at least mentioned that, more often than not, the differential diagnosis is a race against death. Generally House and his team win the race, but not always. So, that’s what’s at stake in the various discussions about House’s disregard for procedures and dogged pursuit of the diagnosis. This is a show that forces us to confront and think about death.

Diagramming sentences in the 19th century

I loved diagramming sentences in grade school. I'm sure I did it in 6th grade, but possibly 5th grade as well. Over a Language Log Victor Mair has a post on the subject, Diagramming: history of the visualization of grammar in the 19th century, which links to a review article by Hunter Dukes that contains photographic copies of seven archival texts: American Grammar: Diagraming Sentences in the 19th Century. Mair's article has a number of interesting quotations from Dukes' text.

The Presidential debate as entertainment

I've been watching Zeth's videos for over a year, maybe even two. When I first started watching them it was just Zeth and his daughter, Saylor. Then his with and son joined in, making them family videos. I'm putting this one up because they talk about the Presidential debate starting at 13:30. They don't see it as a serious political event. They see it as entertainment and mostly talk about Biden's poor condition.

Timestamps:

0:00 Visiting California
9:22 Zeth's Hair Problems
13:30 Presidential Debate
18:50 The New Pod
20:56 The Olympics
23:37 France
25:10 Florida Beaches
28:30 Atlas Joins

Flowers

What’s up with House, M.D.? [Media Notes 135]

House, M.D. has been on my to-do list for a couple of years. As you may know, it’s a medical drama than ran on Fox for eight seasons between 2004 and 2012. I watched it back then, and I watched in online since then. I’m now in the second season of rewatching it again.

I’ve got a simple question: What’s it about? Oh, I know, it’s about Dr. Gregory House who’s a world-class diagnostician at the fictional Princeton-Plainsboro Teaching Hospital in New Jersey. What makes it interesting is that House, while a very good diagnostician, is an unpleasant person. He’s rude, self-centered, difficult to get along with, and insists on doing things his way, which often puts him at odds both with accepted medical practice and with Princeton-Plainsboro. Nor is he particularly endearing with his patients. He’s also in chronic pain and, consequently, addicted to pain medication. Each episode is built around a single case, though there may be one or three simpler cases on the side.

Given such a thoroughly unpleasant central character, why was the series popular enough to run for eight seasons a get a bunch of awards? To be clear, I’m not questioning the merits of the show, after all, I’m now on my third time through. No, what I’m curious about is how it is that such a popular show could be built around such a thoroughly unlikable character?

Obviously, there wouldn’t be any show if House were incompetent. He had to have some redeeming quality, medical brilliance in this case. We’ve had medical dramas on TV since the fifties, and I’ve watched a bunch of them. I don’t recall any others where the protagonist was so unlikable and also of such a high level of competence. Those two things go together. Why?

Imagine another drama about a physician with House’s skills but who was more likeable, perhaps married as well, with a beautiful wife and cute children. That would be a very different show, and wouldn’t work. (Or would it?) We also need to emphasize that House is a fairly technical show in it features a lot of complex medical terms, some technology as well, and interior views of the body via special effects. There’s also the activity of differential diagnosis, which is on display 3, 4, 5, or more times during the show. That’s critical to the “texture” of the show. Off hand, the only precedent I can think of is CSI: Crime Scene Investigation, a forensics crime show that ran from 2000 to 2015, was a huge hit, and spawned a spin-off and several imitators. It also featured technical terms, apparatus, procedures, reasoning, and special effects.

I’m thinking that, as American culture is fairly anti-intellectual, ambiguous at best, making the protagonist unpleasant and in pain is a way of taking the edge off his brilliance – Yeah, he’s super-smart, but he’s also an unhappy asshole! I’m not sure I believe that, though it’s been on my mind for a while. It probably needs a better formulation, but I don’t know how to do it, and I fear that it would likely require a bit of apparatus-building.

One final remark, while the unpleasant and tortured genius doctor is at the center of the show, there are other important figures as well: his (female) boss, the Dean of Medicine, his best (and only) buddy (an oncologist), and his three associates, who changed as the show went on. None of these people are unpleasant in the way House is. Getting a good mix of associated characters is certainly part of the formula, but that’s true for all TV shows, movies, dramas, or narratives. What are the specific requirements of “compensating” for a character like Dr. Gregory House?

* * * * *

Given the prominence of AI these days, I assume someone’s working on a show built around an AI doctor. I note that Star Trek: Voyager has already done it, with its holographic doctor. But when that show aired, 1995-2001, AI was purely conjectural. That’s no longer the case. And that changes everything, no?

Bang that drum! [What fun]

Scalable LLMs without Matrix Multiplication

Rui-Jie Zhu, Yu Zhang, Ethan Sifferman, et al., Scalable MatMul-free Language Modeling, arXiv:2406.02528v5 [cs.CL]

Abstract: Matrix multiplication (MatMul) typically dominates the overall computational cost of large language models (LLMs). This cost only grows as LLMs scale to larger embedding dimensions and context lengths. In this work, we show that MatMul operations can be completely eliminated from LLMs while maintaining strong performance at billion-parameter scales. Our experiments show that our proposed MatMul-free models achieve performance on-par with state-of-the-art Transformers that require far more memory during inference at a scale up to at least 2.7B parameters. We investigate the scaling laws and find that the performance gap between our MatMul-free models and full precision Transformers narrows as the model size increases. We also provide a GPU-efficient implementation of this model which reduces memory usage by up to 61% over an unoptimized baseline during training. By utilizing an optimized kernel during inference, our model's memory consumption can be reduced by more than 10x compared to unoptimized models. To properly quantify the efficiency of our architecture, we build a custom hardware solution on an FPGA which exploits lightweight operations beyond what GPUs are capable of. We processed billion-parameter scale models at 13W beyond human readable throughput, moving LLMs closer to brain-like efficiency. This work not only shows how far LLMs can be stripped back while still performing effectively, but also points at the types of operations future accelerators should be optimized for in processing the next generation of lightweight LLMs. Our code implementation is available at this https URL.