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CEO of $20 billion AI firm Perplexity says the secret to success is ‘sleeping with that fear’ that your competitor will steal your idea

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Social Security's 2032 deadline puts a 22% cut on the table — but Washington has way less room to negotiate than 1983

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Boomers actually do hold most of the wealth and power. So why do they call it 'whiny' to point that out?

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CEO of $20 billion AI firm Perplexity says the secret to success is ‘sleeping with that fear’ that your competitor will steal your idea

2

Social Security's 2032 deadline puts a 22% cut on the table — but Washington has way less room to negotiate than 1983

3

Boomers actually do hold most of the wealth and power. So why do they call it 'whiny' to point that out?
Tech

How WeWork and Slack Are Scaling Up

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Beth Kowitt
Beth Kowitt
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By
Beth Kowitt
Beth Kowitt
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July 16, 2018, 5:52 PM ET
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If WeWork represents the physical aspect of how we work today, then Slack signifies the digital side.

At the Fortune Brainstorm Tech conference on Monday, the chief product officers of both companies explained how they’re scaling and handling their rapid growth as customers have flocked to their services and platforms.

Slack’s April Underwood said that just two years ago, the company could not support a team of more than a couple of thousand using its service. Now she said Slack has customers who have more than 100,000 employees.

“Increasingly customers who want to use Slack look less and less like us,” she said, noting that the company is now serving customers the size of IBM and those with operations in other countries.

Underwood said that people who use Slack are actively connected 10 hours a day and are actively using the product for two hours and 40 minutes daily. But when asked broadly why workforce productivity hasn’t increased, she said it was a “head-scratcher” since workers now have “the best tools they’ve ever had.” For Slack, she said, that means potential opportunity.

At WeWork, the company is using technology to deploy buildings at scale, said chief product officer Shiva Rajaraman. Once you start to open 50 buildings a month, he said you have to start thinking about patterns. That means taking data that’s been disparate, collect it, and use machine learning to analyze what’s most effective.

If you think of about buildings as you might phones, said Rajaraman, the question is now “what is that operating system and how do we put analytics on everything so we know how it’s being used.”

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