You make some good points, but this part feels like a wild overreach:

    > torpedoing confidence in LLMs with their search AI summaries

That is some real tin foil hat thinking.

Straightforward observations of market impact aren’t tin foil :)

Google didn’t launch LLM products despite being a tech leader, and have gotten piles of bad press for their misleading AI search summaries. They know how and why they suck. Google search is a highly popular and market facing service packaging bad summaries as “AI”. Meanwhile LLM searches threaten to disrupt Googles primary cash cow (advertising around search).

Here on HN, on Reddit, and media writ large, a lot of the “AI” failure stories are not about ChatGPT hallucinations, it’s the shockingly wrong search summaries from Google, undermining consumer confidence and breaching trust.

ChatGPT and other LLM providers rarely show conflicting source material side by side with misleading text gen. The number one search provider who leads in some LLM tech does though, routinely, looking incompetent and generating negative “AI” sentiment through repeated failures at mass scale…

So the theory here is either that the best search org in the world filled with geniuses can’t tell they’re pooping on their own product and profitability and aren’t fixing it because they can’t/won’t… … or <tinfoil mode engaged>… Google already makes money and is happy with substandard product and market performance in the cases where it hurts the necessary hype critical to other businesses but not themselves (while also pre-positioning in case LLM search becomes essential).

Win/win/win strategy with a substandard product, versus Google not being aware of what their biggest product is doing.

Googles AI summaries are doing lotsa work to make AI summaries seem terrible. I ascribe profit motives to their actions. Ascribing incompetence seems naive and irreconcilable with their strategic corporate history.

Hat tip. Great point. To quote J Paul Getty: "If you owe the bank $100, that's your problem. If you owe the bank $100 million, that's the bank's problem." In this case, yes, the investment is large, but not bankrupting for Google if it goes wrong.

I don't know the full the history of this story, but I honestly wonder if type of scandal is still possible in the United States. After Enron and Worldcomm, the US introduced Sarbanes-Oxley reporting regulations. Additionally, after the Global Financial Crisis of 2008/2009, there was a dramatic increase in regulations for banks (of all kinds) and insurance companies.

.. yet today we have Kalshi, Polymarket, et al.

Those are private gambling businesses akin to a casino, not publicly listed businesses subject to the aforementioned regulations.

    > To be honest, I think "vendor financing" is still a very risky premise.

Are you aware that all heavy industry in all highly developed nations make extensive use of vendor financing to sell their products? Siemens is a perfect example of a well-run, stable, industrial giant. They offer vendor financing for large purchases. Same for the "heavies" (Mitsubishi, Kawasaki, IHI, Hyundai, Doosan, Hanjin) in Japan and Korea.

If anyone is interested to learn about the damage that the financialisation of General Electric (USA) brought upon itself, you can ask ChatGPT to tell you the story. It is too long to repeat here.

Here is a sample prompt that I used to remind myself:

    > I am interested in the history of General Electric and the trouble that their financing units brought in the early to mid 2000s. Can you tell me more?

Are we replacing "Let me google that for you" with "Here is a prompt to feed ChatGPT" now?

Edit: I am not asking whether ChatGPT is better than Google Search, I am asking after the standard dodge of citing one's sources.

Fair point/question. For many of my HN responses, I first ask ChatGPT for a bit of information about the topic. For the case of GE Cap's wrecking of parent GE with excessive financialisation, I could only loosely remember the details from the 2000s. It is a long time ago! That prompt that I shared gave a reply that was 100s of words. Too much for copy/pasta, and too hard for me to summarise briefly. Instead, I decided to share the prompt. It is not my intention to dodge sources. Plus, the newest versions of ChatGPT is pretty good about sharing sources. (Of course, the quality of sources can be debatable.) In short, it was not my intention to be snarky by sharing my ChatGPT prompt.

EDIT ---- Also, the OP was so brief about GE Cap, I realised that most readers under 30 (maybe 35) will have almost no knowledge or memory of that economic history. I wanted to offer an "intellectual carrot" (ChatGPT prompt) for anyone wishing to learn more. ----

What bothered me most about the original post was the person was putting all vendor financing in the same "bad" bucket. I disagree. I would characterise GE Cap as an infamous example! They were the worst of the worst in a generation (25 years). Most vendor financing is very boring and is used to buy big heavy things with very long operational lives. If the buyer goes bankrupt, it is (relatively) easy to repossess the big heavy thing and sell it again (probably with vendor financing again!).

Very tangentially related comment, but I remember seeing a post on a local Facebook clone with a prompt to throw at Claude to "make a custom YouTube downloader for MacOS", so the general "Here is a prompt to feed an LLM" is somewhat real for some, apparently

Yes, cause google has been giving crap results long before chatgpt was a thing and it only got worse. Before ai it was "let me google that on reddit for you".

It's a good use case really – it'll tell it differently according to what it knows about your background, if you 'just Google it' you'll get the same maybe-appropriate results as anyone else.

Google search has gone way down hill after they nerfed it and then did nothing to prevent the flood of AI slop seo websites. So unfortunately, instead of sharing links everyone now gets sent to the inefficient text generator that hallucinates nonsense and will color the average summary of a topic by whoever trained it and your most recent chat history instead.

I haven't run a Google search in two years. Your comment just made me realize that. Doing a Google search is like trying to watch cable after being on YouTube for years.

I use different search engines than Google. They have similar issues, but some are better at ignoring the slop.

I just cannot justify the environmental impact and surveillance of using LLMs for everything. I prefer to summarize recent information myself. LLMs are not particularly good at it.

Funny thing about the cable analogy. Ever since all streaming providers have started cranking up prices and still forcing users to see hundreds of ads my family has been buying second hand dvds. So we have regressed from streaming to right after cable. I know one family that went back to cable, they do still watch YouTubes here and there but they got sick of it.

Yes.

> Are you aware that all heavy industry in all highly developed nations make extensive use of vendor financing to sell their products?

The OP did mention GE Capital, the motherload of all heavy industry vendor financing. And of massaging the accounting books in order to increase shareholder value in the short term, also.

    > motherload of all heavy industry vendor financing

I doubt they are bigger than other national "heavy industry" champions from East Asia and Western/Central Europe. Without checking, I would guess that the global leaders are Boeing and Airbus.

Its odd that don't care enough to at least confirm your arguments are right.

I'd suggest learning more about this subject instead of assuming you already know enough.

    > Clojure was not a hiring barrier - it was a hiring filter.

It makes me think about this HN comment: https://news.ycombinator.com/item?id=11933250

    > Jane Street Capital's Yaron Minsky once said that contrary to popular belief hiring for OCaml developers was easier because the signal to noise ratio in the OCaml community is so much better than other, more approachable languages.

I saw a YouTube vidoe years ago that featured Yaron Minsky. He made similar points. In short, some programming languages are like catnip for excellent programmers.

It also helps that Jane Street has like 3k employees, a good chunk of whom never touch code at all, and of those that do, a good chunk who won't be touching OCaml. Hundreds of OCaml programmers though, yes.

That may not scale for larger companies.

Also important to note, they don't require you to know OCaml when you get the job. They will teach you OCaml.

All that said, man it would be cool to work for JS (or anyone really) and write OCaml.

PG wrote about this back in 2004: https://www.paulgraham.com/pypar.html

> Hence what, for lack of a better name, I'll call the Python paradox: if a company chooses to write its software in a comparatively esoteric language, they'll be able to hire better programmers, because they'll attract only those who cared enough to learn it.

>In short, some programming languages are like catnip for excellent programmers.

I think that misses the point.

Things that are hard have a higher percentage of people who don't need it to be easy.

If you're a "good" programmer you don't need the "community support" (i.e. a bunch of stuff to tell you why you should do things one way or the other in your particular language) so you're free to choose niche languages based on other factors and in turn there will be more good programmers programming in those languages.

You see this in all sorts of subjects not just programming.

I would offer a small correction to your point: Instead of "ballistic missile", I would substitute "Shahed-type drones". It is much easier to detect (and shoot down) a ballistic missile than a Shahed-type drone.

I don't think this is true at all? A ballistic missile is way harder and more expensive to shutdown (they are flying at Mach 5-10 while you can outrun that type of drone with a mid tier car on the freeway)

Shahed is very primitive in general and not hard to shot down but because its extremely cheap it can be used to overwhelm any type of air defenses. Wasting $4 million to destroy a $50k drone doesn't scale at all.

The OP wrote:

    > Imagine doing an easy tour in your air conditioned Kuwaiti logistics office and then getting blown to bits by a ballistic missile because no one bothered to tell you about the war that was being initiated which would cause such missiles in retaliation.

The purpose of my response wasn't about cost effectiveness; rather, it was about the lethality of a ballistic missile vs Shahed-type drone.

A ballistic missile is easily detected by a network of outer space satellites owned and operated by the US Space Force. Whether or not you can defend against it is a different question. There is sufficient time from the detected of ballistic missile launch to move to a hardened underground bunker. All US bases in the Middle East will have these. Soldiers will regularly train for incoming ballistic missile attacks and when/how to move to underground bunkers. As a result, it is very unlikely that soldiers in an "air conditioned Kuwaiti logistics office" would be killed by an incoming ballistic missile.

On the other hand, a Shahed-type drone (similar to a cruise missile) is much harder to detect because they fly very low and difficult to catch on rader until close to base. As a result, soldiers on base will have much less time to move to underground bunkers.

This sounds like a good idea for a science experiment and a following paper!

    > why are americans putting up with this bullshit?

The answer is simple: Golden handcuffs. If you pay people enough money, they will do anything. Also, labor laws are so weak in the US that this is surely allowed. It would take a federal law (or many powerful states to all pass laws in parallel) to outlaw this behaviour. Hint: It will not happen.

I gotta say, the opening line is a gem of British humour:

    > Meta, the company built on watching everything its billions of users do online so it can keep them clicking on ragebait and targeted ads

I am laughing so hard right now.

    > This guy seems much younger than Tim was when he ascended.

I just checked. Tim Cook is 65 now, which makes him about 50 when he became CEO. John Ternus is 50 now.

I'd say a bigger difference is that Jobs casts a much larger shadow than Cook. Maybe Ternus will find it easier to move the company forward.