May 23, 2019

Axios Future

By Bryan Walsh
Bryan Walsh

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Any stories we should be chasing? Hit reply to this email or message me at steve@axios.com. Kaveh Waddell is at kaveh@axios.com and Erica Pandey at erica@axios.com.

(Smart Brevity count: 1,079 words/<5 min. read)

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1 big thing: Privacy-preserving AI

Illustration: Sarah Grillo/Axios

Data is AI's jet fuel — amassing as much as possible allows tech companies to precisely target ads, or medical AI to differentiate between a benign tumor and a malignant one, Kaveh reports.

No problem for Facebook and its gobs of data — but hard for a small clinic with few patients to learn from. Now, new AI methods are allowing companies to benefit from the collective wisdom of peers and competitors, without giving up sensitive data or trade secrets.

Why it matters: This could help improve health care, among the country’s most stubborn problems, by clearing a key hurdle for medical AI — gathering a big and diverse enough dataset to help doctors diagnose difficult problems or choose better treatments.

  • Confined to each individual company's own data, AI systems don't have access to the staggering range of examples they need to outperform humans.
  • The main recourse has been to send information, assiduously scrubbed of private details, to some central hub to be pooled for study — a slow, laborious process.

What's happening: Privacy-preserving AI techniques like federated learning are powering new systems that can benefit from multiple companies' data — without even having to know what the data is.

  • Google showed off in 2017 how federated learning helped its Android keyboards learn new words, based on lessons gleaned from its enormous user base.
  • More recently, companies have applied the techniques to new industries, allowing sectors with privacy responsibilities to exploit the strength in numbers that other, less regulated industries can marshal.

Perhaps the most obvious application for federated learning is in health care, where strict rules prevent sharing patient data — but the benefit of gathering lots is potentially very high.

  • Owkin, a French startup, has connected more than 30 hospitals and research centers to a system that learns from all of them, in the process rewarding the hospitals that contribute the best data.
  • Each institution's data stays on its own computers, rather than being sent elsewhere for processing.
  • "We can have different hospitals collaborate while being competitive on their research," Anna Huyghues-Despointes, Owkin's director of strategy, tells Axios.

VIA, a Boston-area AI startup, uses federated learning to pool data about the condition of power transformers, such that a utility in Europe can learn from one in Thailand or New Zealand.

  • For power companies, predicting the next catastrophic equipment failure could require data on 1,000 previous problems — but any one company only sees one or two a year, says Colin Gounden, VIA's co-founder.
  • Get a few dozen utilities to team up and those 1,000 examples are within reach. Security concerns prevent them from just doling out information about their transformers, but several have already joined VIA's pilot federated learning system.

What's next: Intel is working on methods that will allow companies to apply an AI model to data without even decrypting it, which would open new doors to cooperation even among the most privacy-conscious companies and industries.

The bottom line: Sharing is just one way to solve one of the biggest problems still ahead of AI — figuring out how to slake computers' unending thirst for data. Researchers are also experimenting with bolstering small datasets with synthetic training data, or creating algorithms that can learn from far fewer examples.

2. Higher prices at the store

Illustration: Rebecca Zisser/Axios

When the Trump administration slapped tariffs on washing machines imported from China last year, American consumers started paying 12% more for them, Erica writes.

  • Now, those price hikes could be coming for all consumer products, including coffee and clothing.
  • Cowen & Co. forecasts that prices of goods from China could rise 10%–15%, per WP.

The big picture: For the past few quarters, retailers have warned analysts that the U.S.-China trade war could push prices up and turn shoppers away. But those effects have been invisible so far because the first two rounds of tariffed products largely excluded consumer goods.

Now things are changing: Tariffs are being imposed on the third and fourth "lists" of goods set out by the Trump administration.

  • Steep 25% tariffs on the third list, which went into effect this month, will affect things like instant coffee and bathrobes.
  • The fourth list includes all imports from China and will touch common consumer products like clothes and shoes.
  • Worth noting: Several types of apparel are heavily tariffed even without the additional duties, says Hun Quach of the Retail Industry Leaders Association. For example, swimsuits already face a 25% tariff and dresses, 16%.

Where it stands: In recent earnings calls, big retailers like Kohl's, Nordstrom and JCPenney have reported disappointing sales numbers and said that the impact of tariffs could make things worse.

The latest: As many as 12,000 stores could close this year if tariffs become a tipping point for smaller or struggling retailers, writes UBS analyst Jay Sole.

  • Dressbarn plans to close all 650 of its stores, and Payless ShoeSource will close its 2,600 stores by July.
  • Hundreds of footwear sellers, including Nike and Adidas, sent an open letter to President Trump saying the effects of tariffs would be "catastrophic" for them.
  • Even the retailers reporting strong growth, such as Macy's and Walmart, said tariffs will likely drive prices up.
3. Today's statistic: New graduate pay is flat

Photo: Dan Kitwood/Getty

Month by month, the tight U.S. jobs market is pushing up wages beyond the rate of inflation. But not if you are a fresh college graduate.

If you graduate this year, your annual pay on average will be $51,347. That's just 1.9% higher than last year's starting salary of $50,390 — and just keeping up with inflation, according to recruiting firm Korn Ferry, per the WSJ's Kelsey Gee.

Economists have struggled to explain why, despite the historically tight market, wage hikes are so sluggish.

Go deeper: Salaries for selected cities and occupations

4. Worthy of your time

Illustration: Aïda Amer/Axios

The story of Big Lithium (Henry Sanderson — FT)

First out: Self-driving mail trucks (Joann Muller — Axios)

These students sent a rocket into space (Daniel Oberhaus — Wired)

Amazon’s German AI ambitions (Janosch DelckerPolitico)

The case for spacing out (Meghan Daum — Medium)

5. 1 hungry thing: A new traffic distraction

Photo: Katherine Frey/Washington Post via Getty

Things people do while stuck in traffic: Listen to music, text (super dangerous), gab on the phone. But in Mexico City, you can also order a burger — right to your car.

  • For a month's trial, Burger King is offering the "Traffic Jam Whopper," reports the WP's Peter Holley. And drivers are gobbling them up — deliveries have been up 63%.

How it works: If you are no more than 1.8 miles from a Burger King, and a restaurant app determines that you will be stuck in traffic for at least 30 minutes, you can use a voice command to place an order. A motorcycle will weave its way through the traffic to your car window with your burger.

What's next: Burger King says it is considering expanding the offering to other super-trafficky cities like Los Angeles, São Paulo and Shanghai.

Watch the promotional video

Bryan Walsh