U.S. chip startups, long shunned in favor of internet bets, stir excitement again Reuters 2 hrs ago
By Jane Lanhee Lee
OAKLAND, Calif. (Reuters) - Silicon Valley venture capitalists, long focused on software and internet companies, are again pouring money into the semiconductor industry, lured by the promise of a new generation of artificial-intelligence chips that could challenge incumbents like Intel Corp and Nvidia Corp.
The new wave of semiconductor innovation will do little to address the shortage of chips based on older technology that is currently plaguing the auto industry and others. The shortage stems from a confluence of factors as carmakers, which shut plants during the COVID-19 pandemic last year, compete against the sprawling consumer electronics industry for chip supplies.
US chip startups, long shunned in favor of internet bets, stir excitement again
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Last Updated: May 05, 2021, 05:22 PM IST
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Synopsis
The enthusiasm for chip startups is mostly a result of the need, by companies using AI software, for special-purpose processors that can efficiently run machine-learning algorithms requiring huge troves of data - the heart of the booming artificial-intelligence business
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Silicon Valley venture capitalists, long focused on software and internet companies, are again pouring money into the semiconductor industry, lured by the promise of a new generation of artificial-intelligence chips that could challenge incumbents like Intel Corp and Nvidia Corp.
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Filip Diarra, a cofounder of NewNew, has hit out at the prevalence of bias in the tech industry.
He said the stereotypical image of a founder will change, but only over generations.
Around 2.1% of startup executives in the US are Black, research from Kauffman Fellows found. The problem is bias, Filip Diarra said of the shortage of Black and minority founders in the tech industry. We all have bias and pieces of bias that are at the core of who we are as people since the dawn of mankind. Every war has existed because of bias, every hate crime has pretty much existed because of bias.