> Euler's formula

So much EE-related math becomes trivial (or at least not-hard) once you've internalized this formula.

What I am trying to decide is 1) Did I zone out in class when Euler's formula was introduced or 2) Did my secondary school mathematics classes just kind of gloss over it?

I lean towards 2 but unfortunately none of my college classes reintroduced the formula and I ended up making a lot of problems harder than they should have been (I have an EE undergrad).

I'm not sure any of my secondary-school classes taught it, but I dropped out of secondary school to go to the university, so maybe they would have in the following year. In secondary school I was in the "smart kids" math track, though, and they also had an "average kids" track and a "dumb kids" track, and I really doubt those tracks covered it.

No link to the original research note. No real details on the methodology used. A few notes on the well-known lack of an AI business model (similar things were said about search in the late 90's).

I just don't see how the broader market is exposed to an AI crash in the way it was exposed to subprime loans. If OpenAI goes belly up is it really taking anyone else down with it?

A shocking statistic is that YTD, 1/6th of the 2% rise in US GDP this year is attributable to AI Datacenters alone.

Source: https://www.economist.com/finance-and-economics/2025/08/18/h...

So I think if there was an AI crash, US economy goes with it in the short term

During the dot-com era, internet or IT in general accounted for a much smaller percentage of the GDP. So, I'm not sure how the percentage of GDP can help us gauge the scale of the bubble, if any.

Doesn’t that prove the post’s hypothesis that this could be larger?

When you're talking the size of investment that AI-centric companies have received, on the order of hundreds of billions of dollars, there's no way it's not exposed to the wider market.

But I agree with you, the article is too light on details for how inflammatory it is.

There's good reason to believe that OpenAI's success (or failure) and the success of many other firms are correlated. If OpenAI's bubble bursts, then that is likely to spread to other close firms and – depending on severity – any other firms that are merely associated.

NVDA, MSFT, AAPL, META, and GOOG are all heavily investing in AI right now, and together make up 28% of the money tied up in S&P 500 indices. Simply investing in the S&P 500, which many people do, exposes you to meaningful downside risk of an AI bubble pop.

Yes.

Don't get me wrong; I'm no fan of the billionaires. Eat the rich, etc. But I don't want the billionaires to lose everything suddenly, because I'm 100% sure my 401k will go down with them, and 50% sure my job will.

> I wonder if an LLM would be up to the job of writing the assembly code from this

Why ask a cluster of GPU's to do something any single CPU from the last 30 years can accomplish?

I ask this question every day, and I think the answer is the same as the answer to the question "why are you doing this with blockchain?"

Do they also believe that the GenAI bubble is propping up the value of the S&P 500? If so, they are behaving irrationally. If not, then it is perfectly reasonable to maintain an S&P 500 investment while asserting the AI bubble will burst.

I feel like setting your alarm earlier, thus reducing the amount of sleep you are getting, may be the wrong thing to do.

Yup, getting up earlier only works if you go to sleep earlier, too. But that's not for everyone, some people are just night owls.

Perhaps by "An annual checkup is not enough", they do not mean you need screenings multiple times a year. Rather, one needs to regularly examine their own skin in addition to yearly checks by a professional.

An aside for my fellow wookies: moles can form under hair!

> skeptical of slathering something all over my body just to go outside

Missing nuance: Outside for how long? And how strong is the sun?

Even with my pasty Northern European complexion, I'm skipping the sunscreen for a 20 minute walk to lunch in November. But for a 10 hour hike above treeline in July? I'll be re-applying every two hours.

> Humans can still enjoy the land without roaring across them in 4x4s.

To clarify: In your view, someone using a vehicle to access a remote area is not "enjoying the land"?

Perhaps you mean that the presence of a motorized vehicle reduces your own enjoyment.

(Personal bias: I am an avid mountain biker, occasional dirt bike rider, and feel the wilderness designation is harsh and used excessively).

Under the Wilderness Act in the US, it breaks federal law to bring a motor into a designated wilderness. The idea is on protecting places where nature can actually be wild. Us humans getting to use them on foot ( or perhaps bike - though it's hard to maintain a bike trail without powered equipment) is a secondary benefit.

I live in a suburban American neighborhood, built in the mid 2010's, which has ample walking paths and wide sidewalks. In fact, I cannot think of any newer neighborhood in this area which lacks walking infrastructure. Good sidewalks are a minimum. Usually there are dedicated walk and bike paths.

What is lacking is places you would actually walk to. There are numerous parks and a pool. But that's it. Don't get me wrong, it's great if you have a dog or enjoy running or walking. But I still have to drive everywhere.

Big O was introduced in my Data Structures and Algorithms (DSA) class which was nominally a second year undergrad class. In practice, most Computer Science (CS) students were far enough advanced to take DSA in their first year.

I took DSA as a third-year Electrical and Computer Engineering student. I recall maybe 15 minutes of exposition on the topic and exam questions of a near-throwaway nature (ergo: write this tree parsing algorithm, 95 points for your code's correctness, 5 points for explaining your algorithm's Big O complexity). It did seem like something that CS professors and teaching assistants considered either trivial or self-explanatory.