Business, Spoken

Latest Episodes:

HP Wins Huge Fraud Case Against Autonomy’s Mike Lynch Feb 04, 2022

Show notes

The ruling by the UK’s High Court could also lead to Lynch’s extradition to the United States, where he faces further charges.

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It's Not Just the IRS—the US Government Wants Your Selfies Feb 03, 2022

Show notes

A controversial new program that uses facial recognition is part of a national effort to verify identities and reduce fraud.

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Now Physical Jobs Are Going Remote, Too Feb 02, 2022

Show notes

Advances in artificial intelligence and other technology allow machines to be operated from far away. The trend could spell trouble for workers.

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Synthetic Voices Want to Take Over Audiobooks Feb 01, 2022

Show notes

Publishers hope computer-generated voices can help them tap surging demand, but some fans—and Amazon—are resisting the robots.

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Latino Founders Have a Hard Time Raising Money From VCs Jan 31, 2022

Show notes

Despite diversity pledges, funding to Latino-founded startups in the US still lags—accounting for only 2 percent of venture investments last year.

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Everyone Wants to Be an Entrepreneur Jan 28, 2022

Show notes

Applications for new businesses rose 20 percent last year, after languishing for a decade. Many newly minted founders attribute it to the pandemic.

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Meta and Twitter's NFT Landgrab Could Backfire Jan 27, 2022

Show notes

A new plan to lure social media users to the metaverse could legitimize NFTs, but it could also ruin them.

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Guts, Not Guidelines, Will Stop Tech Mergers Jan 26, 2022

Show notes

Plus: Microsoft’s bid for Yahoo, Silicon Valley’s approach to history, and Tonga’s disastrous eruption.

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China’s ‘People’s Courts’ Resolve Online Disputes at Tech Firms Jan 25, 2022

Show notes

No garlic on the oysters? Soup stained a blanket? Panels of users hear the complaints and can order refunds or removal of critical reviews.

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When It Comes to Health Care, AI Has a Long Way to Go Jan 24, 2022

Show notes

Medical information is more complex and less available than the web data that many algorithms were trained on, so results can be misleading.

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