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Cambricon Technology CEO Chen Tianshi holds up his company's AI processors. Photo: Sun Zifa/China News Service/VCG via Getty Images

After decades of dominance by a few key players, the semiconductor race has been blown wide open. The shift is driven partly by a new demand for AI-specific chips, according to a report from Andy Patrizio in Ars Technica.

Why it matters: There's a lot of new money pouring into a lucrative sector, setting up an explosion of new players — and another venue for the AI arms race between the US and China.

The backdrop: Until fairly recently, the desktop and mobile semiconductor markets were unipolar, ruled by Intel and ARM, respectively. Several changes blew the lid off the industry, Ars reports, but the rise of computing-intensive AI has led to the biggest proliferation of new technologies from both established companies and new players.

The old guard:

  • IBM released an AI processor last year that plays nice with hardware from Nvidia, a company whose GPUs have long been popular in machine-learning circles, along with its newer AI-specific processors.
  • Intel has bought up companies to speed its AI chip development, and offers a whole family of AI chips for various uses.
  • Two processors from ARM are specifically designed for image recognition.

The upstarts:

  • Tech companies not known for semiconductors — Google, Microsoft, Amazon, Apple, Facebook, and even Tesla — are building AI-specific processors to use in their own hardware.
  • Dozens of startups are getting into the game, according to NYT.
  • China's big three tech companies — Baidu, Alibaba, and Tencent — have released or are developing similar tech. Baidu announced an AI-specific processor called Kunlun last week, while Alibaba and Tencent are deploying AI processing capabilities in their cloud platforms.
People see a gold rush; there’s no doubt.
— Brad McCredie, VP of IBM Power systems development, to Ars Technica

Why now? Specialized tasks like machine learning benefit from tailored chips that do one thing well — and efficiently — rather than many things more slowly, Patrizio writes. Different types of machine learning benefit from different chip architectures, opening up a whole range of new needs.

What's next: Many of the chips being developed will never see the light of day, either because they're being made for companies' internal use, or because they'll quickly be bulldozed by the considerable competition. But there's a hefty prize in store for the winners.

Go deeper: Nerd out on the gory details at Ars Technica

More from Axios:

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Massive venture rounds into fintech companies have ballooned this year, pushing up total dollars invested — in just the first three quarters of 2021 — to nearly double the amount in all of 2020, per new PitchBook data.

Why it matters: The maturing of fintech startups means a growing number of companies are able to raise huge later-stage funding rounds as investors look to lock-in their bets.

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Catch up fast: New financial carrots and sticks for utilities to deploy zero-carbon power — the Clean Electricity Performance Program (CEPP) — look unlikely to stay in Democrats' big social spending and climate bill.

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CDC: Unvaccinated are over 11 times more likely to die from COVID

Expand chart
Reproduced from CDC; Note: Data represents 30% of Americans across 16 jurisdictions: Alabama, Arizona, Arkansas, Colorado, Connecticut, Florida, Georgia, Idaho, Louisiana, Massachusetts, Michigan, Nebraska, New Mexico, New York City, Seattle/King County, Wash., Utah and Wisconsin; Chart: Danielle Alberti/Axios

The CDC recently published data evaluating Americans' rate of coronavirus cases and deaths by vaccine status, providing more data on which vaccines are working best and how much protection they offer relative to being unvaccinated.

What they found: As of August, unvaccinated people had a more than six times higher risk of testing positive for the coronavirus, and were more than 11 times more likely to die from the virus.