I attribute the excitement of the VC and CEO cast to the same underlying motive, but I think there are at least several other ways all this could play out:
- the Cul-de-Sac: AI progress flattens as scaling data and compute, RL and algorithmic improvements hit diminishing returns.
- democratization: LLMs decentralize, mirroring the shift from mainframes to personal computers.
- AI creates new jobs and thus new dependencies for the capitalist class
According to the article (and the discussed research) this was only a minor factor:
"The researchers also explored the possibility that index changes are more predictable today than in the past, leading sophisticated market participants to trade ahead of the events. They concluded that this played only a minor role in their findings, however."
The two main factors being:
"...an increase in migrations over time from the S&P MidCap 400 index, and an overall increase in the market's ability to provide liquidity to those investors seeking to buy and sell around the time of index changes.
The additional liquidity has 'made it easier for everyone to trade, and as a result, the prices move less.' says Dr. Greenwood.
And with more stocks migrating to the S&P 500 from the S&P MidCap 400, midcap funds are selling as S&P 500 funds are buying, leading to 'a wash' in demand, he says.
This factor is actually lessening over time. The BlackRocks and Vanguards of the world have dozens, even hundreds, of index funds - all with different benchmarks and goals. When a stock is "rebalanced" out of one fund, it ends up being added to some other fund that the same company manages. So the transfer occurs as a notation on the internal books; no actual arbitrage-able trade actually happens. This is even happening in the ESG space - we are starting to see fund "pairs" - one fund tracks the companies that meet the specific rules of that fund, and the other tracks the companies that do not.
Note that this isn't perfect - index fund A has more assets under management than index fund B, etc. But as index investing grows, the actual investor inflows and outflows are what dominate, not rebalancing moves.
> This is even happening in the ESG space - we are starting to see fund "pairs" - one fund tracks the companies that meet the specific rules of that fund, and the other tracks the companies that do not.
This is very interesting. Do you have any examples of these funds?
There is an easy to understand white paper about this concept at CRSP’s website. Their particular ESG indexes aren’t investable, but it seems to be only a matter of time given that all their others are.
> I read all his novels (and some of his short stories), he's one of my favorite authors
That makes at least two of us. :) But, I suspect there are quite a few more HN readers who like Kafka's works and literature in general (the first is arguably very correlated to the other), judging from how often literature related articles appear on the HN front page. Often, when that is the case I also can't help but wonder the same about the correlation between being a fiction and HN reader.
To me, Kafka’s work is particularly axiomatic. It has an internal logic and tends toward involution. I could see how this would appeal to technically minded people, whereas Dickens, or Austen, authors whose work tends to be discursive, might seem boring or without basis.
They are axiomatic in that Kafka's worlds are frequently built upon a set of conditions, and the development is contingent upon how these conditions interact, whereas other writers often depart from pre-established rules because they become cumbersome, or they introduce new ones as a matter of convenience. Kafka, in a story like The Burrow, seems to be in search of a complete system that becomes fully expressed by virtue of an exhaustive exploration of its potential, in accordance with its own stipulations. It develops like a drop of ink in a glass of water. Due also to a desire not to retread ground, as he criticizes Dickens of doing, this may be why much of his work went unfinished.
By involution, I mean that Kafka's stories, to a greater extent than just about any other writer, forestall the influence of "outside" forces. His worlds do not rely on historical context, and his characters hardly, if ever, propose a new and narrative-changing idea from whole clothe, although the conclusions they draw are often strange, novel, and sudden. Kafka's land surveyor in The Castle is always circling back to the fact that he is a land surveyor as the basis for his behavior, even though he never actually fulfills or comes close to fulfilling his vocational imperative.
I always recommend Reiner Stach's three volume biography of Kafka to people. The author does a great job of looking into the literature as much as he looks into the life.
I recently watched an interesting conversation between Todd McGowan and Walter Davis on Kafka[1] which you might enjoy.
There's a bit in the aforementioned interview where they mention if one is learning German, a good introductory route is reading Kafka and Heidegger's Being and Time. I've been contemplating whether I should learn German to read my favorite thinkers in their primary written language (and even potentially make a move to Germany, away from the weariness of California), or, rather, become more grounded in the English language.
Thank you for the link, I got 17 minutes into this lazy slop and got to the something about law (judicial law that is) being "alive and sexual" and couldn't take any more.
Little useful is extracted, it's mainly academics grooming each other over their cleverness. I just couldn't bear it any more.
An essay on writing by Raymond Carver [1] (as well as pretty much anything by Raymond Carver and authors he mentions in the essay :)). It's about good fiction writing, but, I think, good to keep in mind for writing in general.
No discussion of Carver is complete without mentioning his relationship with editor Gordon Lish.
>Carver had been up all night reviewing Lish’s severe editorial cuts––two stories had been slashed by nearly seventy per cent, many by almost half; many descriptions and digressions were gone; endings had been truncated or rewritten––and he was unnerved to the point of desperation.
> Vector search, though, isn't as good on handling typos and not good at all when it comes to as you type searching. Vehic won't match on auto, for example.
This is incorrect in general case and it entirely depends on the model that is used to produce word vectors and the text corpus the model is trained with.
For instance, fastText model is trained on words, but also their parts (n-grams), so it should produce word vectors that would be close (in cosine-distance) to vectors of their corresponding typos and partials, even if the text corpus that was used to train the model doesn't contain same typos and partially typed words verbatim.
Could you share details about the machine translation engine that is used (or where to find out more about it)? Are there any plans to open source the extension code (with the WebAssembly optmizations that are mentioned in the article)?
You can find the engine used here [1], the API built around it here [2] and its WASM port here [3] and the WebAssembly matrix multiplication optimizations are here [4]
I can experience something similar with the ventilation system in my apartment. Usually, the sound of it is immersed in the background noise together with other sounds coming from the outside, so most of the time I'm not aware of it at all. However, sometimes when I meditate I hear it and if I focus my attention on it, after a while it becomes clear and loud, rich and versatile, not unlike a music played on a wind instrument.
Related to this and discussed quite a few times on HN ([1],[2]), 'In Praise of Idleness', an essay by Bertrand Russell: https://libcom.org/files/Bertrand%20Russell%20-%20In%20Prais... . I return to it every once in a while, if not to regain a bit of sanity, than just to enjoy clarity of thought and style in his writing.
- the Cul-de-Sac: AI progress flattens as scaling data and compute, RL and algorithmic improvements hit diminishing returns.
- democratization: LLMs decentralize, mirroring the shift from mainframes to personal computers.
- AI creates new jobs and thus new dependencies for the capitalist class
- Any combination of the above.
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