This past June, the U.S. National Highway Traffic Safety Administration announced a probe into Tesla's autopilot software. Data gathered from 16 crashes raised concerns over the possibility that Tesla's AI may be programmed to quit when a crash is imminent. This way, the car's driver, not the manufacturer, would be legally liable at the moment of impact. It echoes the revelation that Uber's self-driving car, which hit and killed a woman, detected her six seconds before impact. But the AI was not programmed to recognize pedestrians outside of designated crosswalks.

A screen shows a demonstration of SenseTime Group's SenseVideo pedestrian and vehicle recognition system at the company's showroom in Beijing. Facial recognition supporters in the US often argue that the surveillance technology is reserved for the greatest risks -- to help deal with violent crimes, terrorist threats and human trafficking. And while it's still often used for petty crimes like shoplifting, stealing $12 worth of goods or selling $50 worth of drugs, its use in the US still looks tame compared with how widely deployed facial recognition has been in China. A database leak in 2019 gave a glimpse of how pervasive China's surveillance tools are -- with more than 6.8 million records from a single day, taken from cameras positioned around hotels, parks, tourism spots and mosques, logging details on people as young as 9 days old. The Chinese government is accused of using facial recognition to commit atrocities against Uyghur Muslims, relying on the technology to carry out "the largest mass incarceration of a minority population in the world today."

A screen shows a demonstration of SenseTime Group's SenseVideo pedestrian and vehicle recognition system at the company's showroom in Beijing. Facial recognition supporters in the US often argue that the surveillance technology is reserved for the greatest risks -- to help deal with violent crimes, terrorist threats and human trafficking. And while it's still often used for petty crimes like shoplifting, stealing $12 worth of goods or selling $50 worth of drugs, its use in the US still looks tame compared with how widely deployed facial recognition has been in China. A database leak in 2019 gave a glimpse of how pervasive China's surveillance tools are -- with more than 6.8 million records from a single day, taken from cameras positioned around hotels, parks, tourism spots and mosques, logging details on people as young as 9 days old. The Chinese government is accused of using facial recognition to commit atrocities against Uyghur Muslims, relying on the technology to carry out "the largest mass incarceration of a minority population in the world today."

Being from California, I remember one of the first times that I visited New York City (NYC) and made the mistake of renting a car to get around the famous metropolis. I had figured that driving a car around the avenues and streets would give me a good sense of how the city that never sleeps was laid out and where the most notable restaurants, bars, and shops could be found. Turns out that I mainly discovered how much New Yorkers seemed to delight in jaywalking. It was as though there weren't any rules against jaywalking. Want to cut across the street and get over to that popular hangout, no need to walk down to a crosswalk, instead just make your way by walking into traffic. In most cases, the jaywalker didn't even run. One might almost think that you would dart rather than meander, but these fearless jaywalkers tended to take their time. I also found out about the techniques involved in making a devoted stare or gaze that appeared to be a local custom. In some cities, the jaywalker purposely does not make eye contact with the car drivers, seemingly acting as though the car drivers don't exist. Or, maybe by making eye contact it would become a duel to see who looked away first, and the loser perhaps has to back-down from the standoff. In any case, my experience was that the jaywalkers in NYC loved to give the car drivers a straight eye. This might be the same kind of thing you'd do when you encounter a wild animal in the woods. Given them a strong stare might say that you are mighty and the animal should not try to take you on. Some of the car drivers that were locals or that were used to the local customs would often give a stern stare back. On a few occasions, it would get really testy and the jaywalker would wave an arm and act as though they might try to slay the dragon of a car coming down the street. I admit that after I turned in the rental car and became more of a traditional pedestrian on my visits to NYC, I adopted the jaywalking habit. This was especially so because during one of my initial forays as a pedestrian there, I was walking with a colleague that was a native New Yorker, and when I attempted to walk down to a crosswalk, rather than taking the shortcut of jaywalking, he almost came out of his skin at my legal abiding approach. Are you nuts, he asked or demanded incredulously?

All-day and all-weather navigation is a critical capability for autonomous driving, which requires proper reaction to varied environmental conditions and complex agent behaviors. Recently, with the rise of deep learning, end-to-end control for autonomous vehicles has been well studied. However, most works are solely based on visual information, which can be degraded by challenging illumination conditions such as dim light or total darkness. In addition, they usually generate and apply deterministic control commands without considering the uncertainties in the future. In this paper, based on imitation learning, we propose a probabilistic driving model with ultiperception capability utilizing the information from the camera, lidar and radar. We further evaluate its driving performance online on our new driving benchmark, which includes various environmental conditions (e.g., urban and rural areas, traffic densities, weather and times of the day) and dynamic obstacles (e.g., vehicles, pedestrians, motorcyclists and bicyclists). The results suggest that our proposed model outperforms baselines and achieves excellent generalization performance in unseen environments with heavy traffic and extreme weather.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Get all the latest news on coronavirus and more delivered daily to your inbox. China has amassed a vast collection of information about its people in recent years as the Chinese Communist Party continues to deploy its surveillance apparatus to exercise control over its 1.4 billion inhabitants at the expense of privacy. In recent years, China has spent billions to purchase the latest technology like facial recognition, artificial intelligence and other digital technologies to add to its network of monitoring systems.

The golden age for artificial intelligence may have just dawned, but the course is not without its challenges. A plethora of technology glitches seems to indicate that it is not quite there yet. Perhaps machines cannot be not perfect either. Although AI is meant to solve problems, as it turns out, it can create new ones as well. These accounts may alarm or amuse consumers but are very embarrassing for the companies involved.

Last December Synced compiled its first "Artificial Intelligence Failures" recap of AI gaffes from the previous year. AI has achieved remarkable progress, and many scientists dream of creating the Master Algorithm proposed by Pedro Domingos -- which can solve all problems envisioned by humans. It's unavoidable however that researchers, fledgling technologies and biased data will also produce blunders not envisioned by humans. That's why a review of AI failures is necessary and meaningful: The aim of the article is not to downplay or mock research and development results, but to take a look at what went wrong with the hope we can do better next time. Traffic police in major Chinese cities are using AI to address jaywalking.

Face recognition has an old history in science fiction.

There are many criticisms you can level at China's growing reliance on facial recognition, including its absolute faith in technology: what happens if there's a false positive? Unfortunately, we just saw an example of that in action. Police in the city of Ningbo have taken corrective action after the facial recognition system at a crosswalk mistakenly accused famous businesswoman Dong Mingzhu of jaywalking because she appeared in an ad on a passing bus. As with any other detected offender in the area, it posted both Dong's name (incorrectly displaying her surname as "Ju") and government ID. The police have since deleted the infraction and claim they've upgraded the facial recognition technology to "reduce the false recognition rate," although it's unclear just what they could have done to address this specific issue.