Self-driving car from the inside
Autonomous Vehicles

Cars Idled, AV Makers Keep Rolling

The pandemic has forced self-driving car companies off the road. Now they’re moving forward by refining their mountains of training data. Self-driving cars typically collect real-world training data with two human operators onboard, but Covid-19 makes that unsafe at any speed.
Graphs and data related to Scan2Plan, a model that segments 3D scans of empty indoor spaces into floor plans
Autonomous Vehicles

Finding a Floor Plan

Robot vacuum cleaners are pretty good at navigating rooms, but they still get stuck in tight spaces. New work takes a step toward giving them the smarts they’ll need to escape the bathroom.
Self-driving software working
Autonomous Vehicles

Tracking the Elusive Stop Sign

Recognizing stop signs, with their bold color scheme and distinctive shape, ought to be easy for computer vision — but it turns out to be a tricky problem. Tesla pulled back the curtain on what it takes to train its self-driving software to perform this task and others.
Road sign with the word "trust"
Autonomous Vehicles

Toward AI We Can Count On

A consortium of top AI experts proposed concrete steps to help machine learning engineers secure the public’s trust. Dozens of researchers and technologists recommended actions to counter public skepticism toward artificial intelligence, fueled by issues like data privacy.
Scans representing pedestrians and other objects
Autonomous Vehicles

Data Augmentation in 3D

An unconventional approach to modifying data is cutting the amount of work required to train self-driving cars. Waymo unveiled a machine learning pipeline that varies lidar scans representing pedestrians and other objects.
Some results from CB Insights' annual list of the 100 most promising startups in AI
Autonomous Vehicles

Machine Learning Churning

Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.
Fragment of a video explaining a model that extracts landmarks on the fly from radar scans
Autonomous Vehicles

Locating Landmarks on the Fly

Directions such as “turn left at the big tree, go three blocks, and stop at the big red house on your left” can get you to your destination because they refer to stationary landmarks. New research enables self-driving cars to identify such stable indicators on their own.
Drone following a person riding an ATV
Autonomous Vehicles

Imitation Learning in the Wild

Faster than a speeding skateboard! Able to dodge tall trees while chasing a dirt bike! It’s … an upgrade in the making from an innovative drone maker.
Autonomous vehicle detecting images projected on the street
Autonomous Vehicles

Phantom Menace

Some self-driving cars can’t tell the difference between a person in the roadway and an image projected on the street. A team of researchers used projectors to trick semiautonomous vehicles into detecting people, road signs, and lane markings that didn’t exist.
Lifelike video imagery of virtual people made by NEON
Autonomous Vehicles

AI Steals CES

Artificial intelligence was everywhere at the biggest, buzziest consumer-technology showcase in the U.S. AI ruled the convention floor at the annual Consumer Electronics Show in Las Vegas, as numerous media outlets proclaimed.
Anima Anandkumar
Autonomous Vehicles

Anima Anandkumar: The Power of Simulation

We’ve had great success with supervised deep learning on labeled data. Now it’s time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring what they learn to the real world.
Illustration of a crystal snowball
Autonomous Vehicles

Simulation Substitutes for Data

The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.
Observational dropout
Autonomous Vehicles

Seeing the World Blindfolded

In reinforcement learning, if researchers want an agent to have an internal representation of its environment, they’ll build and train a world model that it can refer to. New research shows that world models can emerge from standard training, rather than needing to be built separately.
Security robot walking on the street
Autonomous Vehicles

What the Watchbot Sees

Knightscope’s security robots look cute. But these cone-headed automatons, which serve U.S. police departments and businesses, are serious surveillance machines.
Volvo car identifying a pedestrian
Autonomous Vehicles

Blind Spot

In March 2018, one of Uber’s self-driving cars became the first autonomous vehicle reported to have killed a pedestrian. A new report by U.S. authorities suggests that the accident occurred because the car’s software was programmed to ignore jaywalkers.

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