WeWork is running out of money

Welcome back to Axios Business. Time for a situational awareness:

• Three professors who studied ways to alleviate poverty won the Nobel Prize in Economic Science.
• Headline economic indicators have hit their lowest levels since spring 2016 as the global economy sinks into a "synchronised stagnation" period, new research shows.
• Visa, Mastercard, eBay and Stripe have followed PayPal and dropped out of participation in Libra, the digital currency network spearheaded by Facebook. 

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1 big thing: WeWork is running out of money

By: Dan Primack ? Newsletter: Axios Pro Rata

WeWork doesn't have enough money to finish out 2019, and both of its known bailout options are nightmarish.

What we know: Option 1 is to sell control to SoftBank, which enabled former CEO Adam Neumann's worst excesses. Option 2 is to let J.P. Morgan arrange a massive debt package, which could become so onerous that employees may just mail their vested options to Wall Street.

How we got here: The company reported $2.4 billion of cash at the end of June, with a first-half net loss of $904 million. At that pace, it should have been able to survive at least through the middle of 2020. But I'm told that it significantly increased spend in Q3, partially due to the lumpy nature of real estate cap-ex, believing it would be absorbed by $9 billion in proceeds from the IPO and concurrent debt deal.

• One source says that there's probably enough money to get through Thanksgiving, but not to Christmas.

The big picture: The WeWork debacle isn't yet having a tangible impact on most private market prices, despite headlines to the contrary.

Last night I emailed several late-stage VCs, to ask if they're seeing systemic valuation resets. A sampling of replies:

"A lot of talk but no action yet. In my experience, private valuations move slowly so it may be a bit before we see evidence."

"Back in late 2008/early 2009, only months after the financial crisis, pundits predicted valuations would collapse. I recall VC’s telling LP’s it would be a super-buyers market and that LP’s should load up in fill-in-the-blank-VC-fund. Guess what? Valuations, both for great and sort-of-great companies barely budged. Since then, I’ve largely abandoned the conventional thinking that lumps start-ups together into a single group of assets that move up and down together in price/value."

"Not sure there’s been enough time to see if prices are really moving down, but obviously lots of talk about it internally and externally. I’d say on three weeks of data all I’m really seeing is more questions and fewer overnight deals as people dig in a bit more."

"Not systemic. I do think there is more scrutiny for consumer companies (especially ones that are losing money or not real 'tech' companies). SaaS companies are still as strong as ever. Usually the private market lags the public market so maybe it’s coming."

Bonus: Even presidential candidates are chiming in:

Go deeper: 

• The complicated future of SoftBank Vision Fund
• Our full WeWork coverage

Sign up for my daily newsletter Pro Rata for all the latest WeWork news.

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2. Investors signal they hate Trump's "Phase 1" China trade deal

By: Dion Rabouin ? Newsletter: Axios Markets  

Illustration: Sarah Grillo/Axios

Wall Street was bursting at the seams with excitement about a trade deal between the U.S. and China — until details of the deal were revealed.

The big picture: China agreed to more than double its annual purchases of U.S. agriculture, up to $50 billion and made yet-to-be-determined concessions on intellectual property rights while the U.S. agreed not to implement its planned Oct. 15 tariffs of 30% on Chinese imports.

What happened: The S&P 500 was flirting with a 2% rise for the day, and then details of the agreement started leaking out and the market's gains leaked with them.

Between the lines: The S&P closed 1.1% higher, and the reversal looked like a typical bout of "buy the rumor, sell the news," but comments about the deal from top strategists and money managers suggest many view the agreement as too little, too late.

What they're saying: A flood of investment strategists and fund managers added their 2 cents. Goldman Sachs' analysts see a 60% chance more tariffs are put in place by the end of the year and expect the drag on manufacturing to continue.

• "The manufacturing industry has slowed to the point of stagnation," Goldman analysts said in a note. "While it accounts for a modest share of the economy, many investors worry that negative spillovers to the service sector and consumer confidence will drag down the healthy parts of the economy too."
• “There is not yet a viable path to existing tariffs declining, and tariff escalation remains a meaningful risk,” Morgan Stanley analysts said in a note to clients. “Thus, we do not yet expect a meaningful rebound in corporate behavior that would drive global growth expectations higher.”
• “The market has basically been held hostage by the trade negotiations,” Bryn Mawr Trust CIO Jeffrey Mills said on CNBC Friday. “I don’t know that we’re out of the woods yet with China. We still have trade negotiations going on with the EU [and] the ratification of NAFTA 2.0.”
• “Investors had high hopes for some form of mini-deal in the weeks before the meeting, and Friday’s announcement has at least been partially, if not fully, priced in,” JPMorgan equity analysts said in a note, adding that the deal is unlikely to have a material effect on the already slowing U.S. manufacturing and services sectors.
• “Trump’s statement that ‘We are near the end of the trade war’ is not plausible to us,” analysts at Evercore wrote in a note. “We do not expect tariff cuts in 2020 – but are ready to be favorably surprised."
• “I don’t think this gets us to Christmas,” UBS' NYSE floor director Art Cashin told CNBC. “I think it could be a temporary truce that wouldn’t last very long.”

Go deeper: Trump says U.S. and China reach partial trade agreement

Sign up for Dion's daily newsletter for all the news on how the U.S.-China trade war is affecting markets.

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3. Automating humans with AI

By: Kaveh Waddell ? Newsletter: Axios Future

Illustration: Eniola Odetunde/Axios

Most jobs are still out of reach of robots, which lack the dexterity required on an assembly line or the social grace needed on a customer service call. But in some cases, the humans doing this work are themselves being automated as if they were machines.

What's happening: Even the most vigilant supervisor can only watch over a few workers at one time. But now, increasingly cheap AI systems can monitor every employee in a store, at a call center or on a factory floor, flagging their failures in real time and learning from their triumphs to optimize an entire workforce.

• A network of surveillance cameras hooked up to special software can tally the seconds of each worker's bathroom break or time each step of their work.
• It can also keep workers safe, automatically detecting the absence of hard hats and gloves, for example, or people straying into the path of dangerous machines.
• In some call centers, AI listens into every conversation, cataloging every word, who said it and how, and then scoring each agent.

Why it matters: Companies can use this data to juice workers' productivity and efficiency. Eventually, they could gather enough data from humans to train machines to mimic them."

How often is an employee going out to smoke a cigarette? How long a lunch are they taking? How long are they sitting in the lunchroom?" These are the questions clients want answered with AI software, says Kim Hartman, CEO of Surveillance Secure, a D.C.-area company that installs security systems.

• Hartman says his company has put in video analytics for several area retailers and restaurants that wanted to monitor their employees' productivity.

In a handful of factories in the U.S., cameras have been installed over each worker's head in assembly lines as they put together car parts or electronics.

• Software developed by Drishti, a Silicon Valley startup, watches these assemblers work, timing each step and checking for mistakes.
• The videos let supervisors quickly figure out where something went wrong and teach a worker how to avoid repeating an error, says Drishti CEO Prasad Akella. It can also be used for training new hires.
• And since AI is constantly watching the video streams, it can extract valuable data about timing and actions across the entire assembly line, which can inform new ways of assigning work.

"The most programmable machine on the planet today is still the human." — Drishti CEO Prasad Akella

"Employers and companies attempting to extract more value from its labor force by making that labor more efficient is nothing new," says Jess Kutch, co-founder of Coworker.org, a nonprofit that helps workers organize. A century ago, managers used stopwatches to pursue efficiency under the banner of "scientific management," or Taylorism.

But extreme monitoring enabled by new technologies can be inhumane, Kutch says.

• "In low-wage work we're seeing a lot more decisions that were made by a middle manager being outsourced to an algorithm," says Aiha Nguyen of the research organization Data & Society.
• "What workers are seeing, and have a fear of, is arbitrarily speeding up workplaces," Nguyen tells Axios.

The creators of AI monitoring tools argue that their software benefits employers and employees.

• Drishti provides workers and supervisors with valuable feedback, Akella says. Its software can call out high performers, reward efficiency-improving creativity and even keep workers from hurting themselves.
• Akella argues that employees won't be forced to work much faster and harder because turning up the heat would introduce unacceptable errors.
• Call center agents monitored by AI software from CallMiner prefer being graded by an "impartial computer" over a human supervisor, says CTO Jeff Gallino.

What's next: Extensive AI-annotated video or audio data about how people work is a potential gold mine for automation developers.

• Robots are still too klutzy to take over assembly lines built for humans but could learn how to put together products in a machine-only environment.
• Gallino says CallMiner could use information gathered from human agents to automate the "boring" parts of customer service calls.

Go deeper: Where automation will wipe out the most jobs in the U.S.

Sign up for Axios Future for more from Kaveh on how automation and artificial intelligence are shaping the future of our world.

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Thanks for reading. Let me know what you think in the comments.