this post was submitted on 23 Jun 2026
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Technology companies are spending big to incorporate artificial intelligence into their businesses and to build huge data centers. Investors who had jumped on the bandwagon appear to be having second thoughts.

Proponents of artificial intelligence see it as the next great revolution for the global economy. The revolution won’t come cheap. Just four companies — Alphabet, Amazon, Meta Platforms and Microsoft — plan to spend up to $720 billion this year, primarily on AI data centers.

This week, investors are looking at the huge sums being spent and questioning whether AI can produce the profits and productivity necessary to make all the investment worth it. Critics have been talking about the possibility of a bubble in AI investment. On Monday, Amazon and Alphabet fell about 5%.

On Tuesday, several companies that make the chips needed for the data center buildup — Nvidia, Micron Technology, Broadcom and Lam Research — led the market lower.

At first, Microsoft, Alphabet and other so-called hyperscalers turned to cash on hand to fund the AI expansion. But they’re increasingly relying on the markets to raise cash.

AI buildout needs cash

Alphabet, the parent company of Google, said earlier this month that it’s raising $80 billion in cash to help pay for its investments by selling shares of its stock. Overall, Alphabet is planning to spend as much as $190 billion this year — more than all the stock of The Walt Disney Co. is worth, and Alphabet is forecasting its spending on investments next year will “significantly increase.”

In March, Amazon sold $54 billion of bonds in the U.S. and Europe as it plans to spend around $200 billion this year on AI investments.

Elon Musk’s rocket maker SpaceX was on a three-day skid heading into Tuesday. It regained some lost ground, but ended trading slightly below the closing price on its first day of trading on June 12. Musk acknowledges that SpaceX will have to spend heavily to fulfill its plans of sending AI data centers into space, and the company has announced that part of an upcoming bond offering will fund its AI buildout.

High-priced chip companies

Chip companies have benefitted as the demand for memory chips and processing power for AI data centers and other projects has led to a supply shortage and a surge in prices. Investors have bid up the share prices of these companies now in anticipation of big profits down the road. By one measure, which compares a company’s stock price to its earnings per share, these companies might look expensive.

Marvell Technologies lost money for five straight years before turning a profit of $2.7 billion in the fiscal year ended in January, thanks to gains in its data center business. The stock has more than tripled so far this year and its price-to-earnings ratio has gone from about 30 at the start of 2026 to near 100.

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[–] violentfart@lemmy.world 51 points 2 weeks ago (1 children)
[–] Peppycito@sh.itjust.works 5 points 2 weeks ago (2 children)

Looks like Gerry Garcia and George Clinton had a child.

[–] dogslayeggs@lemmy.world 3 points 2 weeks ago

We have just created a child with funk levels that off the charts!

[–] bigbangdangler@reddthat.com 2 points 1 week ago

Nothin but the dead in me, baby

[–] homesweethomeMrL@lemmy.world 33 points 2 weeks ago (2 children)
[–] cmbabul@slrpnk.net 6 points 2 weeks ago

Shit they’ve got a solid bag already and the winds seem to be shifting. Hoping into solar seems a much better bet at the moment if not late

[–] deacon@lemmy.world 3 points 2 weeks ago

Certainly and one could exacerbate the other.

Or not, i have no clue what I’m talking about.

[–] rockSlayer@lemmy.blahaj.zone 20 points 2 weeks ago

Investors shit their pants to a swift breeze, so it doesn't mean much if they get spooked. As long as these corporations see the potential of finally crushing the weak but resurging labor movement, businesses and the ruling class are going to keep pumping as much cash as they can into it until they start feeling consequences.

[–] jaykrown@lemmy.world 15 points 2 weeks ago
[–] lemmy_outta_here@lemmy.world 11 points 2 weeks ago

This article makes it sound like we have a traditional stock market where people buy shares in companies they expect to make a profit. In fact, this is a speculation market, where people buy shares in companies they expect to become more valuable on the speculation market. Everyone is just trying to outguess the herd - they tell themselves, "if I time MY sale right, I can get out before the crash." The whole thing is a game of chicken. Nobody expects these companies to turn a profit proportional to their spending.

[–] riskable@programming.dev 10 points 2 weeks ago (1 children)

Big AI investors should be worried! I use AI every day at work (mostly for code-related things) and the open weights/free models are nearly as good as their ridiculously expensive services. Which are only getting more expensive over time!

Not only that, but the free stuff is improving at a faster rate than the models Big AI is putting out. The only thing keeping Big AI alive right now is coasting. Businesses haven't figured out that they can self-host the free models with their own (or rented) hardware for a fraction of the cost.

As soon as these businesses figure out that you can configure Copilot in Visual Studio Code to use FREE models that are 90% as good as Big AI, it's over for Big AI.

There's also dozens of great tools to run ChatGPT-like interfaces using local models and they let you switch which models you want to use on-the-fly. Also, we've got ZeroClaw now which works better with free/tiny models for most of the stuff you'd want to use it for.

Aside: Big AI also has a Big Problem with security that goes away if you use local AI models: You never have to worry about leaking credentials or proprietary/confidential information to the cloud/Big AI.

[–] oakey66@lemmy.world 3 points 2 weeks ago (1 children)

out of curiosity, which free models are you using? I’ve used meta’s 8B coder and instruct models and they’ve been ok. but after using Claude opus it’s been a bit of a struggle. they’re not close at all. granted I’ve been hosting locally on my pc.

[–] riskable@programming.dev 4 points 2 weeks ago

Qwen3.6 27B for running locally (16GB 4060 Ti) and I do often cheat and use Ollama Cloud to run gpt-oss:120B which is still surprisingly good but I've been trying to use GLM 5.2 lately just to try it out.

The trick is to pit these models against themselves as adversaries to spot hallucinations. That really improves the output.

Over time, though I've found that I've gotten better at using these models. Once you've got some solid .md files for context and you get used to the types of prompts that work best (with these models) I seem to be having less and less trouble over time. As in, I have to make fewer fixes or re-runs.

Note: You have to fix stuff constantly with the big models too. So it's not like any of them are perfect. You have to get used to using them effectively over time or you'll just end up with problems down the line.

[–] pelespirit@sh.itjust.works 5 points 2 weeks ago

Don't they have a shit ton of cash on hand? Serious ?

At first, Microsoft, Alphabet and other so-called hyperscalers turned to cash on hand to fund the AI expansion.