Bing Me An Uber

A headline in today’s Wall Street Journal: Toyota investing $500 million in Uber in driverless-car pact.

Toyota’s investment values Uber at roughly $72 billion, slightly higher than where SoftBank Group Corp. valued the company earlier this year with its funding.

Through the deal, Uber will integrate self-driving technology into Toyota Sienna minivans for use in Uber’s ride hailing network.

And as the Journal story observes:

For ride-sharing concerns like Uber and Lyft Inc., autonomous vehicles could cut their biggest expense: paying human drivers. For auto makers such as Toyota, the potential of self-driving cars to power car-sharing services represents a major challenge to an industry dominated by individual car ownership.

The Journal also reminds us that Uber CEO Dara Khosrowshahi is looking to take the company public next year and has been selling off unprofitable operations while “putting new focus on rentable bikes and scooters.”

Could a Lime or Bird acquisition be in the offing? 

Also on today’s AI frontiers, Search Engine Land is reporting that Bing is introducing a new “Spotlight” news feature which showcases a timeline of how a story has evolved, differing perspectives from news sources, and related social media posts on a topic.

Uh, can we see the full timeline in Spotlight for the Mueller investigation?

Yeah, there’s probably not enough AI on the planet to fully grok that timeline yet.

Lest you worry that the “Spotlight” will render human editors irrelevant, the Search Engine Land story indicates Bing explained that the perspectives and stories “are compiled using a combination of both AI and experienced human editors.”

Bing monitors millions of queries and news articles every day and identifies impactful stories that evolve over a period of weeks or months. We look at various user signals such as queries and browser logs, and document signals from publishers such as how many publishers cover a story, their angles, and how prominently they feature the story on their site.  For controversial topics, in the Perspectives module, we show different viewpoints from high-quality sources. For a source to be considered high quality, it must meet the Bing News PubHub Guidelines, which is a set of criteria that favors originality, readability, newsworthiness, and transparency. Top caliber news providers identify sources and authors, give attribution and demonstrate sound journalistic practices such as accurate labeling of opinion and commentary. Behind the scenes, we leverage our deep learning algorithms and web graphs of hundreds of millions of web sites in the Bing index to identify top sources for national news, per category, query, or article. Our goal is to provide broader context for impactful stories, from politics to business to major disasters, and much more.

All the news that’s fit to algo.

No Laughing Matter

Did you hear the one about the personal voice assistant that, for seemingly no apparent reason whatsoever, started breaking into strange laughing noises at random?

No?

Well, I heard about it firsthand, but apparently I missed the opportunity to hear random guffawing of my own personal Amazon Tap.

According to Bloomberg, Amazon confirmed yesterday that in rare circumstances, the voice assistant can mistakenly hear the phrase “Alexa, laugh,” which under its normal programming would cause it to chuckle. 

Amazon has updated a fix for the problem, and is changing the trigger phrase for laughing to “Alexa, can you laugh?” instead.

A few moments ago, I tried the new command, and all I got from Alexa was a “Tee hee.”  

How very anti-climactic.

This quirk has been referred to in AI circles as a “false positive.”

Let’s just hope the voice commands for the AI algos running the armed drones have their laughs in order.

Facebook AI to Detect Suicidal Posts

TechCrunch is reporting on Facebook’s new “proactive detection” artificial intelligence technology which will scan all posts for patterns of suicidal thoughts, and when necessary send mental health resources to the user at risk or their friends, or even contact local first-responders.

Facebook also will use AI to prioritize particularly risky or urgent user reports so they’re more quickly addressed by moderators, and tools to instantly surface local language resources and first-responder contact info. It’s also dedicating more moderators to suicide prevention, training them to deal with the cases 24/7, and now has 80 local partners like Save.org, National Suicide Prevention Lifeline and Forefront from which to provide resources to at-risk users and their networks.
– via TechCrunch

TechCrunch’s Josh Constine goes on to observe that this evolution could trigger “some dystopian fears about how else the technology could be applied” (scanning for political dissent or petty crimes, for example), but that Facebook had no comment on the possibility of such scans.

So how did they get to this point?

Facebook trained the AI by finding patterns in the words and imagery used in posts that have been manually reported for suicide risk in the past. It also looks for comments like “are you OK?” and “Do you need help?” “We’ve talked to mental health experts, and one of the best ways to help prevent suicide is for people in need to hear from friends or family that care about them,” Rosen says. “This puts Facebook in a really unique position. We can help connect people who are in distress connect to friends and to organizations that can help them.”
– via TechCrunch