惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

WordPress大学
WordPress大学
G
Google Developers Blog
小众软件
小众软件
V
V2EX
月光博客
月光博客
腾讯CDC
aimingoo的专栏
aimingoo的专栏
J
Java Code Geeks
Y
Y Combinator Blog
人人都是产品经理
人人都是产品经理
B
Blog RSS Feed
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 【当耐特】
D
Docker
M
MIT News - Artificial intelligence
Google DeepMind News
Google DeepMind News
N
Netflix TechBlog - Medium
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
I
InfoQ
MongoDB | Blog
MongoDB | Blog
Apple Machine Learning Research
Apple Machine Learning Research
Jina AI
Jina AI

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
AI stock slump raises the question if investors are just ...
https://apnews.com/author/alex-veiga · 2026-06-24 · via Hacker News - Newest: "AI"

Updated [hour]:[minute] [AMPM] [timezone], [monthFull] [day], [year]  

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.

Some data storage companies have seen even more eye-popping gains. Sandisk shares have soared more than 700% year to date and its P/E ratio stands at 68. Whether Sandisk shares are overvalued will depend on whether it meets Wall Street’s lofty expectations for the next 12 months -- earnings per share of $188.05 per share compared with $29.16 per share for the 12 months ended March 31. When the current stock price is compared to the forecast, the price-to-earnings ratio falls to around 11.

The current price-to-earnings ratio for the S&P 500 is around 25.

Sign up for Morning Wire: Our flagship newsletter breaks down the biggest headlines of the day.

On Tuesday, investors unloaded at least some of their holdings in these stocks. Sandisk sank 13.6%, while Marvell lost 9.4%.

The sell-off also took a bite out of exchange-traded funds, or ETFs, that invest heavily in tech stocks. The Invesco QQQ Trust Series ETF was down 3.3%, while iShares Semiconductor ETF slumped 7.9%.

Pocketing some gains

While some investors may have doubts that companies going full throttle on AI infrastructure spending will ultimately be able to generate profits to justify their investment, it’s likely some of the selling this week may be investors pausing to pocket some of their gains after the stock market’s recent string of all-time highs.

“With no clear catalyst driving the move lower, we believe today’s pullback likely reflects profit-taking following a strong rally from the March lows,” said Brock Weimer, an investments strategy analyst at Edward Jones.

Big Tech gains have powered major stock indexes on record-setting runs this year. Within the S&P 500, the tech sector alone is up nearly 27% just over the last three months and roughly 17% for the year. In Asia, South Korea’s Kospi has nearly doubled so far in 2026.

Heavy selling on Tuesday triggered a halt in trading in the Kospi, which set the stage for the wave of tech stock selling when trading opened in U.S. markets, Wedbush analyst Dan Ives wrote in a research note Tuesday.

Overall AI enterprise demand in Asia is “showing no cracks in the armor, which continue to make us very bullish on owning the tech AI winners over the coming year,” he added.

Still, tech companies’ race to invest in the expansion of AI infrastructure could ultimately be sowing the seeds of future oversupply, according to Philip Straehl, chief investment officer at Morningstar Wealth.

“Periods of elevated capital investment have historically not translated into strong outcomes for investors, leaving us cautious on the outlook,” Straehl wrote in a report last week.

He expects that the rapid expansion of AI computing power will weigh on pricing, hurting companies’ returns and eventually result in a pullback in investing. Semiconductor companies are “particularly exposed to this dynamic,” Straehl wrote.