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Illustration: Lazaro Gamio/Axios
Every carmaker on the planet, large and small, in addition to Wall Street, Silicon Valley and governments, seem united in the conviction that we are all going to abandon the wheel and be driven around by robots.
The trouble is that, apart from a few daredevils abusing (and sometimes crashing) Teslas, there has been little indication to date that a significant number of the world's drivers want such cars.
What's happening: According to a new Axios/SurveyMonkey poll, a lot of Americans are fearful of autonomous cars, but 33% of them are at least somewhat likely to buy one once they are available. That was the case in all age categories through 54.
Why it matters: To the degree the survey is accurate and reflects a broad global trend, everything from the world's sprawling car industry to roads and cities themselves could be on the cusp of a fundamental transformation.
While a solid minority said they might buy one, the majority said they are scared of autonomous cars.
Go deeper: Stanford University professor Jerry Kaplan writes in the WSJ that the problem is not that people reject risk — they know driving is dangerous. It's that they reject risks that seem bizarre: They do not accept machines making mistakes that a human wouldn't; after all, the machines are supposed to be better. That's ostensibly why we are turning to autonomous cars.
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Marsha Miller/UT Austin
The world's most accomplished battery inventor says he has a new cell aimed at electric cars that delivers double the energy density of existing lithium-ion, and, in a first, actually achieves an increase in capacity when it's charged and discharged.
Quick take: The claims, among the most ambitious by any major researcher in recent memory, come in a paper co-authored by John Goodenough, a celebrated 95-year-old professor at the University of Texas who invented the battery used by almost every cell phone on the planet. It was published in the prestigious Journal of the American Chemical Society with co-authors Maria Helena Braga and two other researchers.
In addition to its assertions on energy density and capacity, the paper's main claims include:
Goodenough, a perennial candidate for a Nobel prize in chemistry, commands enormous respect in the field, having had himself invented or had a hand in creating almost every major lithium-ion battery currently sold.
But, like research published a little over a year ago by Braga and Goodenough, the paper has raised questions in the battery community. In interviews with Axios, researchers raised the following technical questions:
Short of seeing added data, all said the findings do not add up. "The way to think about it is that you have a car that can travel 200 miles, and after five years it can go 800 miles," said Venkat Viswanathan, an assistant professor at Carnegie-Mellon University.
I asked Goodenough and Braga about the doubts. Braga responded: "There are a lot of interests. But time will be on our side." In a followup email, she said:
"Data is data and we have similar data from many different cells, in four different instruments, different labs, glove box. And at the end of the day, the LEDs are lit for days with a very small amount of active material after having cycled for more than 23,000 times."
Braga did not respond to another followup email yesterday about whether the battery holds a charge when unplugged.
Illustration: Rebecca Zisser/Axios
Artificial intelligence researchers, notching little recent progress toward the creation of a machine that thinks like a human, have largely halted such work in favor of applying what's been discovered so far, says a leading AI expert.
What's going on: Andrew Moore, dean of computer science at elite Carnegie-Mellon University, tells Axios that while current AI displays impressive capability in visualization, speech, and difficult games, it "still contains no magic."
Why it matters: Moore's remarks align with a growing chorus of doubt in the AI community that current methods can attain what the field calls "artificial general intelligence." In September, for instance, Geoff Hinton, one of the field's most-respected pioneers, said researchers needed to start over.
Go deeper: In January, Gary Marcus, a New York University professor, ignited a firestorm in the field with a paper that catalogued doubts about machine learning, the most broadly practiced method of AI. Among the leading lights to deride him was Facebook's Yann LeCun.
Some leading AI researchers continue the hunt for super-human intelligence. Among them is Judea Pearl, winner of the Turing Award, the highest prize in computer science, and author of The Book of Why, in which he proposes a new map to intelligent machines.
The problem with machine learning, Pearl said, is that it rests on correlation and association, which have made remarkable achievements but are still elementary in terms of true thinking — they can take the field only so far.
Meanwhile, causal reason differs by reasoning out a situation without specific training, said Pearl, and borrows from methods already in use by social and health science researchers.
Go deeper: In this Bloomberg video, Facebook's Yann Lecun discusses how to advance AI.
Illustration: Sarah Grillo/Axios
When Amazon goes from partner to rival (Jay Greene and Laura Stevens - WSJ)
China's tech giants make America's look tame (Raymond Zhong - NYT)
Baidu unveils energy-efficient blockchain (William Suberg - Cointelegraph)
How the robot revolution is changing our lives (Mike Allen - Axios)
Las Vegas bartenders, servers may strike over robots (Dan Hernandez - Guardian)
1977: With Apple co-founder Steve Wozniak at the first West Coast Computer Faire, where they launched the Apple II desktop, their first product. Photo: Tom Munnecke/Getty
Jim Clifton, CEO of the polling firm Gallup, laments the resources the U.S. devotes to identifying and training elite football and basketball players, while failing to scout the next Steve Jobs.
Why it matters: Society apportions much effort to identifying geniuses of almost every type — athletes, intellects, musicians. An exception is "super builders," Clifton says, by which he means the few responsible for our biggest practical companies.
"There may be 400,000 Steve Jobses, but we don't have ay idea who they are. But imagine if they were point guards. We would be all over them."— Clifton
What's happening: Clifton, author of a new book called "Born to Build," tells Axios that Gallup has developed a test to do precisely that — one that "identifies alpha males and females." He calls it a "Builders Assessment."
The difference between innovators and builders, according to Clifton: Silicon Valley and similar innovation hubs around the world are ecosystems for invention, and push out the occasional exceptional company. But, "innovation is what they do at DARPA," the Pentagon's radical invention lab, says Clifton. "Builders are the Bill Gateses and IBMs that built everything up."