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Why Wall Street is ignoring big tech's debt [video]

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Re: Why Wall Street is ignoring big tech's debt [video]

#81
post #48

Earlier quoted context omitted.

A bubble doesn’t mean a technology is useless. It just means it’s overvalued In the last 30 years, we’ve had multiple bubbles in the tech industry. Every one of them was backed by real stuff that we still use today. They were still bubbles and a ton of people were hurt when they popped.

The railway bubble and the optical fiber bubble left the world with lots of railways and optical fibers. Once their original owners went bankrupt, the assets themselves were quite useful and changed the world. The cryptocurrency bubble, however, didn't. Not really. At best you can use it to buy drugs. Some of the GPUs may have been repurposed for AI, but not enough to make a dent in AI, and the AI reesarchers who kic…

Many of those assets were useless - like railways from nowhere to nowhere. Only some ended up being used.

And many innocent people ended up being hurt in the process.

Bubbles are not good. They are harmful. The ability yo recoup some of the losses in the span of next 15 years does not make the bubbles something positive.

Re: Why Wall Street is ignoring big tech's debt [video]

#82
post #72
post #61

Earlier quoted context omitted.

But AI use translates directly to time savings (if it works). You only need 1-2 hours of time savings per employee per week to break even on a $100/seat/month subscription.

In the US. With how much they've invested in AI they need the entire planet to pay, and pay lots. What's the capex expenditure of Magnificent 7 just this year? Close to $1tn?

They need it to be roughly as popular as first world cell phone usage for a 5-7yr ROI.

Re: Why Wall Street is ignoring big tech's debt [video]

#84
post #18

Earlier quoted context omitted.

After using it a bit I’m convinced it’s not, as a whole, a bubble. Bubbles exist around it. Data center construction may end up overbuilding, much like the dark fiber thing during dot.com, since better chips and models will shrink power and space requirements over time. But the core tech is the most powerful new thing I have seen since discovering the Internet, at least. Maybe more.

A bubble doesn’t mean a technology is useless. It just means it’s overvalued In the last 30 years, we’ve had multiple bubbles in the tech industry. Every one of them was backed by real stuff that we still use today. They were still bubbles and a ton of people were hurt when they popped.

I know. I'm saying that overall I don't believe it's that overvalued.

Specific things may be overvalued. I suspect data center real estate is a bubble, for instance.

Re: Why Wall Street is ignoring big tech's debt [video]

#85
post #29

Earlier quoted context omitted.

The real question is not whether there will be a market for AI, it is obvious that there will be one (as it was obvious the Internet was a gigantic thing in the dotcom boom). It is rather whether the value will be in the models (and if so in which?) or the infrastructure or somewhere else. Interesting thoughts from Dwarkesh Patel on the future of models [1]. In summary, no moat if a client can switch to a competitor…

The moat is in sales, the model and its quality is largely irrelevant. Gross margins will be high enough for moats to not matter that much.

Not hosting in China will be a moat. Tech (software) never really experienced it, but the rest of Western industry all have stories of getting burned by China and their policy of ignoring IP rights.

Re: Why Wall Street is ignoring big tech's debt [video]

#86
post #60

Earlier quoted context omitted.

The thing that's a bit different about AI from a CRM is it translates pretty directly into time savings. You only need each employee to save 1-2 hours of work per month to break even with a $80/seat subscription.

It's true that it can easily save 1-2 hours per month, but it only seems worth it if those hours saved are spent doing something else productive/profitable. It appears that a lot of the time saved is spent either 1) doing nothing instead, 2) waiting for the AI to finish, or 3) increasing the hours spent elsewhere down/up the chain for reviewing, fixing, auditing. The obvious benefit of anything offering to save time…

People will pay out of their pockets if an AI can free up a few of their hybrid hours a month. And already it looks like the vast majority of white collar AI spend is from individuals, not companies.

I mean, why would you show your hand by using the company AI? Use your AI and take the credit...

Re: Why Wall Street is ignoring big tech's debt [video]

#87
post #9

I don't know a single white collar worker who isn't using AI for their job. Not like forced, but like "Oh damn, this bot thing can do a lot of tedious leg work for me". To think that people won't pay $60-$80/mo to continue using it is wild to me. In a white collar environment it pays for itself in a few hours of use. If you focus on how much value AI brings to people (mostly in time saved), the bubble hardly looks bu…

Mods, can you explain what happened here?

This story had 49 points and 81 comments in about four hours and was on the front page. Then it seems to have disappeared from the top stories feed completely.

Re: Why Wall Street is ignoring big tech's debt [video]

#88
post #9

I don't know a single white collar worker who isn't using AI for their job. Not like forced, but like "Oh damn, this bot thing can do a lot of tedious leg work for me". To think that people won't pay $60-$80/mo to continue using it is wild to me. In a white collar environment it pays for itself in a few hours of use. If you focus on how much value AI brings to people (mostly in time saved), the bubble hardly looks bu…

    Google funds Anthropic
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          v
 Anthropic promises to rent Google's TPUs
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          v
 Google guarantees the infrastructure
 needed to fulfil Anthropic's promise
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          v
 Wall Street lends against Google's guarantee
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          v
 Borrowed money buys Google-designed TPUs
          |
          v
 The TPU purchases "prove" demand for Google TPUs
          |
          v
 Anthropic's compute capacity and valuation rise
          |
          v
 Google's investment in Anthropic rises in value
          |
          v
 Higher valuations justify still more financing
          |
          +--------------------------------------+
                                                 |
                                                 v
                                           DO IT AGAIN

Re: Why Wall Street is ignoring big tech's debt [video]

#89
post #76
post #52

Earlier quoted context omitted.

Won't the Chinese providers have to raise their prices as well due to the economics of serving inference at scale?

Buy an M5 max for $4k and you have a portable Deepseek 0731 for life.

But it won't last for life. It will probably last about 4 years so that equates to about 100/mo.

Re: Why Wall Street is ignoring big tech's debt [video]

#90
post #69

Earlier quoted context omitted.

These companies have spent billions of investor dollars and they will need to recoup that cost soon. And then show year over year growth on top of that. Unless they can massively scale down training and inference cost or implement AGI I don't know what their plan is. Just provide a subsidized plan for the next 10 or 20 years? Their costs are directly proportional to the amount of tokens the LLM produces. How is a mon…

They dont need to scale down anything. AGI is a red herring. Even Deepseek at its absurd prices is a very healthy business. Regarding their return on capex multiple, their CEO said they make a six-fold profit on their compute capex with 10 month recuperation. Because of this, all of them are spending aggressively on compute. Apart from that, user acquisition and data labelling are the major costs that are preventing…

> their return on capex multiple, their CEO said they make a six-fold profit on their compute capex with 10 month recuperation

I am not familiar with chineese model companies as much as I am with US based ones so I don't have much to say beyond that the CEO is incentivced to pump up those numbers.

> By limiting the number of tokens you use per month? per week, per hour? And by limiting the inference time compute dedicated to each turn in each session.

If this was so simple I don't know why GitHub copilot went to token based billing at my company.

> This does not need to be solved, but rather only quantified. Innovation is needed to be able to reasonably bound this variance for a reasonable subset of tasks

It's much better to make a business case for them after finding this bound right? Currently I can't use copilot for anything serious since I cannot predict how many credits one request is going to consume.

Your point about non frontier tasks using less tokens makes sense. As you said, let's see if it holds up

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