Wikimedia, Zipcar, Fitbit Are Among IBM Watson’s New Neighbors

Watson goes west looking to make some new friends. It can start in its neighborhood

3 min read
Wikimedia, Zipcar, Fitbit Are Among IBM Watson’s New Neighbors

IBM in September announced a host of new capabilities for its Watson technology: improving language recognition, multilingual speech, and analysis of images and video posted on social media. The company also said it would be setting up a Watson headquarters in San Francisco, intending to “increase collaboration with local startups, developers, venture capital groups, established businesses, and academic experts” to “take cognitive computing to new markets.”

The Watson project already has a headquarters in New York City. The San Francisco operation will employ several hundred people, mostly in R&D. It all started with a project to build a machine that could win at the game show Jeopardy, using a combination of algorithms that analyze natural language, make inferences, learn by crunching automatically through reams of data and interacting with human trainers, and improve over time. Then Watson essentially went to med school (at least, it digested hordes of medical data) and emerged as “Dr.” Watson (now part of Watson Health)—an effort meant to prove that IBM could apply artificial intelligence to medical diagnostics. This year, IBM released a cooking app, Chef Watson, that comes up with creative but sometimes extremely weird recipes from inputs of key ingredients, types of dishes (casserole, say, or dessert), and other factors.

The Watson technology now lives in the cloud, rather than in dedicated on-site computers, as was the case in the Jeopardy challenge. And, since the technology has proved its mettle in a few disparate fields, IBM is looking to let it loose on just about anything; it has already started signing up corporate partners, including a travel planner and a cybersecurity defender.

IBM hasn’t said exactly which Silicon Valley companies it sees as perfect matches for Watson. But it won’t have to look far. Within an easy walk of the company’s offices at 505 Howard St., are Fitbit, Zipcar, Wikimedia, Quantcast, Yelp, Opentable, Kiva, and others. Just a little further, down Market St., is the Burning Man headquarters and Twitter.

What could an artificial intelligence platform that listens, analyzes, and learns bring to those tech companies? Could Watson participate as an editor in Wikimedia, spotting developments in the news and updating entries appropriately? Could it predict when Zipcars will be in high demand (or, uh-oh, let the company implement surge pricing)? Could it help Fitbit gather huge amounts of data? (The wearable device does a pretty good job of telling me what I want to know personally. But the potential of aggregated data has yet to be tapped—despite the promise shown by some early experiments that have used fitness tracker data to look at earthquakes.)

Quantcast, a company that serves advertisers by measuring and analyzing the traffic going to websites to develop audience profiles, is an obvious partner. Yelp, the business reviews site, constantly struggles with fake reviews, both pro and con, and likely could use a little more help spotting and managing those. OpenTable’s search capabilities haven’t, as far as I can tell, changed in a long time. Could Watson allow it to personalize recommendations? Crawl social media for better photos? Or even fine-tune its existing search (“I need a table for eight at an interesting ethnic restaurant that’s fun but not too loud to talk sometime in the first half of December.” I’d love to ask OpenTable to find me a reservation, in just those words.)

And then there’s Burning Man. What exactly would a cloud-based artificial intelligence do in collaboration with Burning Man? That’s a question for Watson.

Of course, the idea of having a single cloud-based computer intelligence that’s aware of your eating, driving, fitness, and other habits, interests, and opinions—even just those being gathered by a few San Francisco companies—could give you the shivers. Or you could just, as superstar Jeopardy contestant Ken Jennings wrote in his Final Jeopardy answer as Watson was soundly defeating him, resign to welcoming “our new computer overlords.”

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How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman
LightGreen

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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