Semiconductor News & Analysis Feed
1291 articles
2026-05-08
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2026-05-08
The Motley Fool
Nvidia(NVDA1.38%)has been one of the biggest beneficiaries of the artificial intelligence (AI) chip boom. Its graphics processing units (GPUs) are parallel processors, designed to break down certain types of massively complex calculations into a host of smaller parts, and then perform all of those small calculations simultaneously, rather than taking each task in sequence. And it turns out, the pr
2026-05-08
www.chartmill.com
2026-05-08
ChartMill
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2026-05-08
www.fool.com
2026-05-08
The Motley Fool
Nvidia(NVDA1.38%)isn't just a company that designs GPUs and products that support its hardware ecosystem; it also has an investment wing. While its portfolio of outside holdings is not as big as some companies hold, it is sizable, and taking note of what Nvidia owns is a smart strategy, because it has more information than the average investor about what's going on inside some of these companies.
2026-05-08
www.fool.com
2026-05-08
The Motley Fool
After a rough start to 2026, shares of AI (artificial intelligence) chipmakerNvidia(NVDA1.38%)have come roaring back. The stock has soared about 19% over the last 30 days, and at one point in late April completed more than a 32% rally off a late-March low. With the stock trading close to $212 as of this writing, they're just shy of their April 27 all-time closing high of $216.61.That kind of run m
2026-05-08
www.heygotrade.com
2026-05-08
Gotrade
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2026-05-08
www.fool.com
2026-05-08
The Motley Fool
A few years ago, the primary argument in the AI computing space was whetherNvidia(NVDA1.38%)could maintain its dominance or whether a competitor like AMD could rise to steal market share. For the most part, Nvidia has maintained its dominance and has grown to own a far larger corner of the market than AMD. That argument has faded a bit, and a new one has emerged: custom AI chips.This debate is ver
2026-05-08
www.digitimes.com
2026-05-08
digitimes
Taiwan remained the largest foreign delegation at the US Department of Commerce's SelectUSA Investment Summit for a third straight year, with TSMC indicating it may further expand its US investment footprint amid rising demand for advanced semiconductor...The article requires paid subscription.Subscribe Now
2026-05-08
www.fool.com
2026-05-08
The Motley Fool
Nvidia(NVDA1.38%)andPalantir Technologies(PLTR+0.92%)both were superstars in the early days of the artificial intelligence (AI) boom. This is because they were among the first to benefit from the revenue opportunity -- and as a result, investors rushed to get in on their shares. Nvidia stock has soared more than 500% over the past three years, while Palantir has surged 1,700%.But in recent times,
2026-05-08
www.fool.com
2026-05-08
The Motley Fool
Chips are the building blocks of artificial intelligence (AI), and the growing demand has sent thePHLX SemiconductorSectorup 258% over the past three years. The bull market may not be over, as Statista estimates the industry will increase from $891 billion in 2026 to nearly $1.3 trillion by 2030.Those estimates won't hold up without growth fromTaiwan Semiconductor Manufacturing(TSM2.10%)andBroadco
2026-05-08
www.thestreet.com
2026-05-08
thestreet.com
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2026-05-08
247wallst.com
2026-05-08
24/7 Wall St.
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2026-05-08
www.fool.com
2026-05-08
The Motley Fool
Nvidia’s Next Big Market The Motley Fool
2026-05-07
news.google.com
2026-05-07
The Motley Fool
2026-05-07
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2026-05-07
CNBC
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2026-05-07
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2026-05-07
TradingKey
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2026-05-07
www.fool.com
2026-05-07
The Motley Fool
When looking at the recent earnings increases from some of the most prominent growth stocks, the effect of artificial intelligence (AI) is nothing short of spectacular. Although such numbers do not reflect the entire company,Microsoftreported 40% Azure cloud growth yearly, and 63% for Google's parent company,Alphabet.For now, most of that growth depends on AI and, by extension, the AI accelerators
2026-05-07
www.fool.com
2026-05-07
The Motley Fool
A shift is happening in the artificial intelligence (AI) computing space. Hyperscalers and AI companies are transitioning from training large language models to putting those models to work on real-world data to unlock the productivity gains that this technology promises.A lot ofmoney has been spenton data center infrastructure that's optimized to train models using large datasets. Inference, on t