HI version is available. Content is displayed in original English for accuracy.
Advertisement
Advertisement
⚡ Community Insights
Discussion Sentiment
84% Positive
Analyzed from 3591 words in the discussion.
Trending Topics
#money#more#market#don#still#going#business#here#lot#where
Discussion (102 Comments)Read Original on HackerNews
After reading these articles go by so often, it feels like what I actually can’t keep up with is the bond market. To paraphrase Trotsky, you may not be interested in the bond market, but the bond market is interested in you. I want to be able to read the signals at the bottom of this article, and divine some kind of prediction that can guide me… I don’t know, to choose whether I should buy a house or change the investment strategy in my retirement fund or something. But I’m just seeing all these signals go by, waiting for the story to be written, which only happens when the dust settles.
I guess I’ll go back to not understanding AI, instead of not understanding the bond market.
By the time you have read this article, the professionals and their computers will have digested that material a thousand times over and have priced it in.
To be more precise: buy the lowest cost most diversified index fund you can buy and then hold it. If you want to spend some smarts to get a better return: look at how to minimise taxes and fees.
I think you overestimate traders. What we call smart money is very often really, really dumb from a macro perspective. Professional traders believe hype and follow trends. There is still at least 2 thesis playing out at the moment for the AI trade, and you don’t need to be a professional trader to take part: one is the AI impact on saas (the market has been very bearish on SaaS companies, and still hasn’t corrected meaningfully), and the ai infrastructure (hardware companies + hyperscalers)
That definitely was true.
I am unsure it is still true. Index funds have taken so much of the trade volume the are becoming momentum strategies
So long as you are happy following the market wherever it goes, and if the recent past is a guide then up is the direction, then yes.
But given the nepotism and corruption in the highest reaches of USAnian society (e.g. Trump's crypto currency scams and the blatant inside dealing and rule ignoring of the Space X float) the future looks much less certain than the past
The interesting thing is: you do not need to keep up. It’s actually way easier and cheaper to wait a bit for the chaos to stabilize, then learn to use the tools. You don’t need to have been someone who experienced the whole evolution, non stop at the edge. It’s ok to let the enthusiasts discover how things work and eventually learn from them. Just like any other technology. The whole „you will be left behind“ is nonsense. If AI is the future, then it will here to stay and you can let others map the domain first
"trajectory of humanity to a parabolic move upward" is poorly defined here. Whether we are headed to a machine god ruled scenario or "just" incredibly powerful productivity tools, there will be a lot of economic pain for some (most) and a lot of economic gain for a few.
I've yet to a see an LLM/agent-based business plan in where scaling with an order fewer workers than before LLMs is not a central part of the value proposition.
I'm inclined to think the collapse has already started but nobody wants to see it yet.
In the last few weeks SP500 is down, kospi is down, nikkei is down, US inflation is still high and growth is softer than expected. Hyper inflated stocks (Tesla, Nvidia, SpaceX) are deflating. US bonds are at a 20 year high.
Interesting times ahead.
Unfortunately the hype machine has far outstripped their capabilities so far, and the amount of money spent doesn’t look like being recouped, so somebody is going to lose money, as people lost money on the overpriced spacex ipo (overpriced because of AI).
In what bubble does this pressure exist?
Im very convinced there's a cult-like level of psychosis in silicon valley (except in Apple) where LLM's must begin displacing labour. It simply is not happening. And the longer this continues, the crazier and unhinged they will get.
I have no illusions that I can time a bubble, but I'm hopeful I'm at least partially shielded, and most importantly I feel better about ignoring wall street again.
I was considering writing a tool that simply follows any index you choose with a .toml of simple config options, like which stocks to exclude, potential fixed locks for specific stocks (or maybe upper and lower percentage of portfolio settings), a hard per stock cap (say AAPL at 3%), and drift threshold. Something you just run once a day and it spits out your buy / sell orders. Seems like this is something brokerages are already offering in some variation though, and I'm not sure what, if any, API access looks like, or export / import options.
What do you mean? Selling everything before this bubble pops?
Revolutionary technology + massive adoption ≠ good investment
Investors have poured money into a bottomless pit, attracted by the growth and glamour of the industry. The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
Commodity Product, no switching costs. Infinite competition
True. But it has added enormous benefits to many other parts of the economy.
Airlines do not capture that value.
That is where the AI companies are. Adding value they cannot capture
The industrialisation essentially socializes the cost across a lot more people though, so even though it doesn't make a profit it does mean people can have air travel without it costing millions per flight for the few people who can afford it. Essentially the economies of scale from having lots of flights isn't enough to make it profitable but they are enough to make it affordable.
There's no spare money to extract from the airline industry but it's still very useful. The same could be true for AI in the long term.
Sometimes the goal of an industry is to exist rather than to make a profit, because the benefit to society is more important than profit. People don't like that though so they do a bit of creative accounting or head-in-the-sand denial around it.
Of course it could, let’s start with making the models open weight and entirely open source. Fully publicly owned and not shaped to maximise profits for the shareholders.
Oh wait, Scam Altman entered the chat and turned a non-profit lab into the next biggest IPO vehicle the world has ever seen.
OpenAI launched as a nonprofit research institution. Its announcement explicitly said it wanted to pursue AI “unconstrained by a need to generate financial return,” produce value for everyone rather than shareholders, publish research and share patents broadly.
The number of competitors for SOTA drops by a few every year. The winners make more money, get more revenue, buy more compute, train better model with compute, buy best talent, and the cycle goes.
I think it's easier to fall behind and never catch back up than people think. One disastrous training run can leave a lab months to a year behind. For example, Meta's disastrous LLAMA 4 models. Meta is lucky to have their ads business as a funding source. However, Anthropic's revenue is growing so fast, that ability to use ads as a funding source to stay in the race may not last much longer for Meta.
To me, SOTA LLM training is very much like new chip fab nodes. One disastrous node can put you behind for many years or forever. The cost to build the next chip node doubles every every 4 years (Rock's law). The cost to train the next SOTA model likely has some similar power law which means over time, it's too costly for losers to keep up. The only reason TSMC isn't a defacto monopoly for advanced chip nodes is strictly due to geopolitics.
I can't prove it. It's just my opinion.
They can barely get any efficiency gains beyond the productivity of software engineers. And even that is not really translating into financial performance.
- Gen AI: Too Much Spend, Too Little Benefit?: https://www.goldmansachs.com/insights/top-of-mind/gen-ai-too... (Goldman Sachs)
- AI’s $600 Billion Question: https://sequoiacap.com/article/ais-600b-question/ (Sequoia Capital)
- The Simple Macroeconomics of AI: https://www.nber.org/system/files/working_papers/w32487/w324... (MIT / Daron Acemoglu)
Obviously there is risk, but can't we really extrapolate the AI gains forward and just see how big it's ahead to become?
Where is this disruption? The longer we go, the more people report that the supposed net-gain of easily 100s of percents is not visible.
I do strongly believe "It's just a tool" - A powerful one, but not one like the invention of the steam machine.
You increased the amount of code written by 10x but unless there’s a 10x increase in demand, its worth nothing
The benefit is neither here nor there - it's whether the borrowed money will ever be repaid on the lenders' terms.
That’s the point: making growth sustainable over time.
Writing a lot of code doesn’t mean much when the moat was never “writing a lot of code”
It’s just coding. It’s not every technical profession at all.
The internet and railroads were highly beneficial, still crashed the economy.
I was called quite disruptive in class when I was young. I'm sure my teachers never meant it as a compliment.
Because what many of us are seeing is meaningless “productivity” improvements.
If at the end of the day you don’t have more users paying for your product or the same users and paying more, then what’s the point of being more productive?
Isn't that the point here? That everyone thinks massive disruption is happening and everyone is 100xing their productivity, but it's not actually showing up in the numbers anywhere?
Lenders are doubting their return. People's benefits have nothing to do with it. The benefits would go in a minute, if doing so yielded a better return.
Directly conflicts with
> Alert and Critical signals represent readings that have historically been associated with meaningful financial stress.
These are all pretty standard things to track and are regularly (and publicly!)
Not saying we’re not in a bubble or near/far from it popping, but these metrics aren’t going to precisely tell you _when_, which is pretty much the only thing that matters.
https://youtu.be/LxJW7hl8oqM?is=IjdyHwZchaiMHk4C
Second, not all money is created via borrowing (but the vast majority is!)
And the YouTube video you linked to is very confused even about the money that is created via borrowing.
Government debt is not required to create money. The Bank of Japan bought stock ETFs to get 'freshly printed' money into circulation. ('Freshly printed' in scare quotes, because these days it's just entries in a database.) Another example: Singapore's central bank (MAS) does not use Singapore government debt to create Singapore dollars; I'm not even quite sure they would even be allowed to.
You can say that money itself is a debt of the central bank; and that's sort-of true, but it's not what David Graeber talks about.
A bit of a pedantic last point: silver coins or bitcoin also require no borrowing to create. Silver coins have been used as money, bitcoin could conceivably be used as money. (There are other problems with these options, but that's besides the narrow point.)
If "money" is the some function of all outstanding credit, then yes, it is created (mostly) by bank lending
If you define money as a web of trust then it is mostly created by those that create the rules. The state
Until they didn't.
The R&D expenditure is a critical requirement for the inference profits, to the point where we should probably lump their financials together, at which point is definitely not profitable.
What will it look like when R&D plateaus (and yes it definitely will, but it could take a while), investment falls, and a few main competitors remain in the music chairs?
It's very difficult to predict. The inference profits we are seeing the profits of a company that is temporarily ahead, but the revenue will level-out in a more stable market, depending on how many survived. It's also hard to tell where the costs will be at the end of the game, with constant efficiency optimisation mixed with cost increases for higher intelligence.
I think it will be quite similar to the semiconductor industry, where, yes there are some key monopolies, but they are not the initial big players, and none of it is actually very profitable; while the real profits are reaped by those that make popular consumer products based on the foundational tech. I guess the main difference is that OpenAI and specially Anthropic have been quite effective at directly tapping into the consumer market rather than remaining technology providers.
Amazon also added/pivoted to AWS, which is where a huge part of its value comes from today.
Not sure what your point is.
so everything is going according to plan, and nobody knows the future, and predicting collpses has never been a profitable business.
I didn't have to read past the first few confusing contorted and convoluted paragraps of this article to decide to come over here and explain it, this is all straightforward corporate finance 102 and the article is fluff
Question is: is that worth enough to cover the debt after the market crashed?