> Alternative views definitely have reach.

Yes, but are we in a 1984 situation where that reach is managed behind the scenes. Reach, but perhaps not too much reach. With respect to the chart, how do we know that Twitter users are not largely partitioned? How representative is the fact you saw something compared to other "communities" on X?

All the while, even if you saw a 'dissenting' chart, the fact the chart exists is direct evidence to the power of a subtle shadow-ban effect. It's not about tears and whining, it's that a single act by 'powerful' accounts can control who gets visibility, and who does not. The point is that it is not you, the community that controls what is popular, but it is the powerful accounts that do. That is the issue.

Yeah, they wouldn't have to rely so much on Madison Avenue if they were just paying the news agencies to report whatever they want.

Incidentally, I'm not sure I'd characterize even PBS' government funding as "vast sums", either absolutely or relatively (to the rest of their funding).

How much influence do you imagine PBS wields and how much money do you suppose is in these vast sums they are paid?

PBS is mostly known for Sesame Street and nature documentaries. Their government funding has been whittled down to almost nothing over years of relentless attack from the Republicans.

Here's some discussion from PBS itself on the topic:

https://www.pbs.org/newshour/show/a-look-at-the-history-of-p...

A pull quote:

"The U.S. is almost literally off the chart for how little we allocate towards our public media. At the federal level, it comes out to a little over $1.50 per person per year. Compare that to the Brits, who spend roughly $100 per person per year for the BBC. Northern European countries spend well over $100 per person per year."

Travel 75 to 150 miles outside of a US city and it will feel like time travel. If so much is still 100 years behind, how will civilization so broadly adopt something that is yet more decades into the future?

I got into starlink debates with people during hurricane helene. Folks were glowing over how people just needed internet. Reality, internet meant fuck all when what you needed was someone with a chainsaw, a generator, heater, blankets, diapers and food.

Which is to say, technology and its importance is a thin veneer on top of organized society. All of which is frail and still has a long way to go to fully penetrate rural communities for even recent technology. At the same time, that spread is less important than it would seem to a technologist. Hence, technology has not uniformly spread everywhere, and ultimately it is not that important. Yet, how will AI, even more futuristic, leap frog this? My money is that rural towns USA will look almost identical in 30 years from now. Many look identical to 100 years ago still.

I see https://en.wikipedia.org/wiki/Beggars_in_Spain and the reason why they vote the way they do. Modern society has left them behind, abandoned them, and not given them any way to keep up with the rest of the US. Now they're getting taken advantage of by the wealthy like Trump, Murdoch, Musk, etc. who use their unhappiness to rage against the machine.

> My money is that rural towns USA will look almost identical in 30 years from now.

You mean poor, uneducated and without any real prospects of anything like a career? Pretty much. Except there will be far more people who are impoverished and with no hope for the future. I don't see any of this as a good thing.

Indeed, more the point though is that many people still live these lives. The propagation of technology is not uniform, slow, ongoing, and not necessarily even a good thing. My point is that technological progress and the feeling of living in a very advanced age is actually a veneer. The second point is how are we going to get massive adoption of technology that is decades away, when we still haven't fully adopted the technologies of the last two centuries?

> You mean poor, uneducated and without any real prospects of anything like a career?

A lot of those rural towns had large farms, which had people far richer than software engineers. I think there is a lot of complexity when characterizing 'rural' america (which is a lot closer to a lot people than I think they otherwise know).

I don't quite share those value judgements. I think it's varied and complicated. My point instead is really more about the propagation of technology. Another example is all of the US compared to say Japanese smart phones. I was told the USA is about 15 years behind in generalized smart phone tech. A podcast I was listening to recently talked about the deep integration of technology in Chinese Uber equivalents, something that is only recent in US offices where you can go into a room and 'cast' something onto a screen. Apparently in China, for a while, being able to play a movie on a screen in the back of an Uber has been a seemless and integrated experience for a long time. Another good example is credit card technology. The oldest is to do a carbon copy of the embossed phone numbers, to the magnetic strip, to the chip, to tap. Europe had chips used in all of their credit cards while some places in the US were still doing carbon copy, and even the "advanced places" were doing magnetic strip only. Canada has been ahead of the US for a while for point-of-payment systems, virtually every restaurant brings a card reader to you instead of (as is in the US) this dance where you give someone a credit card so they can go to the register where there is a wired machine where they swipe the card.

So, I suppose my biggest point is that technology spreads a lot slower than we tend to think. It's not a process of years, but decades and centuries. I'm really pushing back on this technophile sentiment that we're already living in a super advanced age with a strong society that is robust, that instead these are veneers with very uneven and slow moving advancement. This is not going to change overnight (or in the next century) just because someone creates an humanoid AI robot thing that can lift bails of hay and stack them in the right place. Given the lack of adoption of various technologies that we already see, I take that as evidence that nothing will change too quickly, 30 years or even more, just because we get a bit better with robotics.

An analogy I think is like crypto problems that would require 1 billion years to compute. Even if we find a way to get that 100x more efficient, we're still not coming up with a solution anywhere near in our lifetimes.

> Today's LLMs are capable of outperforming your average human in a variety (not all, obviously!) of fields

My impression is many of those are benchmarks that are chosen by companies to look good for VCs. For example, the video showing off Devin was almost completely faked (time gaps were cut out, tasks were actually simpler and more tailor made than they were implied to be).

Something I was trying to convey to a non-technical stake holder is that some tasks are stupid easy for humans, but insanely hard for computers - and vice versa. A big trick was therefore to delegate some things to humans and some things to computers. For example, computers are excellent at recollection and numerical computations - while humans can taste salt easily and tell you when something is too salty or undersalted trivially. In my opinion, AGI is an attempt to have computers do those things that are trivial for humans, but insanely tough for humans. There is a long, long way to go; getting that first 50% is the easy part, the last 50% (particularly the last 30% and the last 5%) IMO is several hundreds (if not thousands) of __magnitudes__ harder.

I believe Active Record is a more specific implementation of something that is ORM-like. We can stop speaking of Active Record since my point holds for the more generic ORM, and therefore holds for Active Record as well.

To clarify my point, there is a fundamental impedance mismatch between object mapping of data vs relational database mapping of data. One implication of this is you cannot use database as a service. Interactions with database must instead be gated behind the ORM and the ORM controls the database interaction.

I'll note that database as a service is very powerful. For example, when there is an API contract exposing a value that is powered by some raw-dog SQL, when the database changes, anything using the API does not need to change. Only the SQL changes. In contrast, when an ORM exposes an object, an attribute might sometimes be loaded, sometimes not. A change to load or not load that attribute ripples through everything that uses that object. That type of change in ORM-land is the stuff of either N+1 problems, or Null-Pointers.

To back up a bit, let me re-iterate a bit about the impedance mismatch. Wikipedia speaks of this [1]: "By contrast, relational databases, such as SQL, group scalars into tuples, which are then enumerated in tables. Tuples and objects have some general similarity... They have many differences, though"

To drive the point home - in other words, you can't do everything in object world that you can do in a database 1:1. A consequence of this is that the ORM requires the application to view the database as a persistence store (AKA: data-store, AKA: object store, AKA: persistence layer). The ORM controls the interaction with database, you can't just use database as a data service.

I believe this point is illustrated most easily from queries.

To illustrate, let's pull some query code [3] from Java's Hibernate, a prototypical ORM.

```

public Movie getMovie(Long movieId) {

    EntityManager em = getEntityManager();

    Movie movie = em.find(Movie.class, new Long(movieId));

    em.detach(movie);

    return movie;

```

So, getting a release year might look like this:

```

int movieId = 123;

Movie m = orm.getMovie(movieId);

return m.getReleaseYear();

```

In contrast, if we put some raw-dogged SQL behind a method, we get this code:

```

int movieId = 123;

return movieDao.getMovieReleaseYearByMovieId(movieId);

```

Now, let's illustrate. To do this, let us look at the example of finding the release year of the highest grossing movie. As a service, that looks like this:

```

return dao.findReleaseYearOfHighestGrossingMovie();

```

In contrast, as an ORM, you might have to load all Movies and then iterate. Maybe the ORM might have some magic sugar to get a 'min/max' value though. We can go on though, let's say we want to get the directors of the top 10 grossing movies. An ORM will almost certainly require you to load all movies and then iterate, or start creating some objects specifically to represent that data. In all cases, an ORM presents the contract is an an object rather than as an API call (AKA, a service).

For the update case, ORMs often do pretty well. ORMs can get into trouble with the impedance mismatch when doing things like trying to update joined entities. For example, "update all actors in movie X". Further, ORM (and objects) creates issues of stale/warm caches, nullity, mutability, performance, and more... What is worse, all of this is intrinsic, relational data and objects are intrinsically different.

[1] https://en.wikipedia.org/wiki/Object%E2%80%93relational_mapp...

[2] https://en.wikipedia.org/wiki/Active_record_pattern

[3] https://www.baeldung.com/hibernate-entitymanager

ORM and entity manager – which, in turn, is a query builder combined with a few other features. Your code is really focused on the latter. While the entity manager approach is not the same as active record, that is true, the bounds between query building and ORM, I think, are even clearer. In fact, your code makes that separation quite explicit. I can at least understand how ORM and query building get confused under active record.

> We can stop speaking of Active Record

While I agree in theory, since we are talking about ORM only, if we go by Wikipedia we cannot as is ends up confusing active record and ORM as being one and the same. That is a mistake. But as my teachers, and presumably yours too, told me in school: Don't trust everything you read on Wikipedia.

But we don't need to go to Wikipedia here anyway. Refreshingly, ORM literally tells what it is right in its name. All you need to do is spell it out: Object-Relation Mapping.

My point is that (bluntly speaking), ORMs are intrinsically fucked because relational mapping and object mapping are just fundamentally different. Because of that difference, some things will always be difficult when doing so in any orm.

Here is an example of something that an ORM does well:

```

Person p = entityManger.findById(123);

p.setAge(23);

entityManager.persist(p);

```

I suppose an active record example is something like:

```

Person p = Person.findById(123);

p.setAge(23);

p.persist();

```

Regardless, of Active Record or ORM, the above is doing this query:

```

update person set age = 23 where id = 123;

```

The above is simple. When trying to update a linked entity is an example where ORMs are going to have complexity. Let's say a person owns books, and books are unique in the system. This type of query:

```

update book set person_id = (select id from person where name = 'Joe') where person_id = (select id from person where name = 'Jill')

```

In code, that looks like this:

```

Person joe = findByName("Joe");

Person jill = findByName("Jill");

jill.getBooks().stream().forEach(book -> { book.setPerson(joe); book.persist()) });

```

The ORM code is so convoluted... We do a full select for two Person entities, possibly eager fetching all their books with more queries (N+1) problem, but all other entities attached to a person as well, and then we do 'N' update statements. These types of problems are AFAIK unavoidable. They will happen for one scenario or another. One can choose the object representation to mitigate one case or another, but it's not long before something that is trivial in SQL becomes a huge burden in OO.

Thus, my thesis, Object-Relation Mapping will create unavoidable cases of convoluted code because RDBMS do not have a perfect mapping to Objects. The mapping is not perfect,the result of this is intrinsic complexity that is easily solved by sticking to SQL, but very difficult in ORMs (which manifest as various issues of inappropriate eager vs inappropriate late fetching, N+1 queries, caching issues, transaction issues, etc..)

Was hoping to find a source to back up my memory on this,FWIW, Google's AI summary states it well:

> On geological timescales (millions to billions of years), rocks, even those that seem brittle, can deform plastically, or flow like wax, due to the immense pressures and temperatures deep within the Earth, allowing for slow, gradual deformation

Which is to say, preservation without awareness of the threat will look like hoarding. A secondary question is to what extent is that threat real? Without seeing what true rampant piracy looks like, I think it would be easy to be ignorant of the threat.

The gist is that Republicans are going to blame the Fed of playing politics when I terest rates are lowered, and blame Biden for when interest rates rose. Rates go up, Bidens fault, rates go down - politics. That is the republican talking point. The article ascribes no direct motive but says the reduction in rates is due to the fed claiming victory on inflation. Which, was wel down and approaching target when the fed started cutting rates.

It is ironic that an article that says (paraphrasing) "here is what the political talking point would be", be used as __evidence__ for that talking point.