A report on the public perception of self-driving vehicles in the United States found that 62% of people surveyed believe autonomous vehicles are the way of the future, and that enthusiasm for those vehicles has risen since the onset of the COVID-19 pandemic. The survey of more than 1,000 Americans and its accompanying Consumer Mobility Report comes from Motional, a driverless technology company created by Hyundai and Aptive. Motional was created to work on commercial uses of SAE level four vehicles, which are fully autonomous and able to perform all tasks from the beginning to the end of a trip. Along with finding enthusiasm for driverless vehicles rising, Motional also found that there's a knowledge gap around self-driving vehicles that plays directly into an enthusiasm gap. Respondents who rated themselves extremely knowledgeable about autonomous vehicles were far more likely to believe that those on the road to day are safe and reliable (76%), versus those that said they are less knowledgeable, of whom only 10% said current self-driving vehicles are safe.
Amazon is rolling out its robot delivery trial to more cities. The e-commerce giant launched its delivery system, Amazon Scout, in January 2019 using electric, autonomous vehicles that can navigate sidewalks to deliver packages. They were first developed and tested in Snohomish County, north of Seattle, then rolled out in Irvine, California in August of that year. Now, Amazon will extend that trial to select customers in Atlanta, Georgia, and Franklin, Tennessee. In a blog post Tuesday, Sean Scott, vice president of Amazon Scout, said the service was most recently used to help meet customer demand in the trial areas during the pandemic, in conjunction with its existing fleet of delivery vehicles.
In the middle of June, I'd discussed why it is a smart move for investors to get in on artificial intelligence (AI). The development of AI has the potential to dramatically reshape our economy and society for decades to come. Today, I want to discuss why Canadians should seek exposure to this space. Moreover, I want to look at two stocks that are betting big on AI to propel their growth going forward. AI development is occurring in a broad array of sectors.
Few have, but it's looking increasingly like that may change -- at least for city dwellers in dense urban environments. The footprints of companies offering autonomous mobile robots to deliver food and groceries, while still small, continues to expand thanks to pandemic-related restrictions on dining in and shifting attitudes on contactless service, and companies are jockeying to be the as-a-service robot of choice for consumers and local businesses. We've seen expanding pilot programs announced from nearly every delivery robot developer, and today we add REV-1, a lightweight, bike-like delivery robot from startup Refraction AI, which is offering free delivery within Ann Arbor from grocery store Produce Station. Refraction is the creation of two University of Michigan professors, Matthew Johnson-Roberson and Ram Vasudevan, who say they've developed a safer, more cost-effective solution for last mile logistics than anything in the current delivery paradigm. "We have created the Goldilocks of autonomous vehicles in terms of size and shape," CEO and cofounder Matthew Johnson-Roberson told ZDNet last July.
One kind of robot has endured for the last half-century: the hulking one-armed Goliaths that dominate industrial assembly lines. These industrial robots have been task-specific -- built to spot weld, say, or add threads to the end of a pipe. They aren't sexy, but in the latter half of the 20th century they transformed industrial manufacturing and, with it, the low- and medium-skilled labor landscape in much of the US, Asia, and Europe. You've probably been hearing a lot more about robots and robotics over the last couple years. That's because, for the first time since the 1961 debut of GM's Unimate, regarded as the first industrial robot, the field is once again transforming world economies. Only this time the impact is going to be broader. That's particularly true in light of the COVID-19 pandemic, which has helped advance automation adoption across a variety of industries as manufacturers, fulfillment centers, retail, and restaurants seek to create durable, hygienic operations that can withstand evolving disruptions and regulations.
We take a closer look at the robotics giant, Nuro. The company believes that great technology should benefit everyone. The team at Nuro is accelerating a future where robots make life easier and help us connect to the people and things we love. Together, they're pushing the boundaries of robotics to improve human life. Dave Ferguson and Jiajun Zhu have devoted their careers to robotics and machine learning, most recently as Principal Engineers at Google's self-driving car project (now Waymo).
The development of 4G's successor began before the fourth-generation wireless network had even rolled out. In 2008, less than a year after Steve Jobs unveiled the first ever iPhone, Nasa started work on 5G in the hope that the futuristic technology would one day facilitate "a new economy in space". It would take another year before 4G became commercially available, which together with the iPhone led the way for a decade of new apps, devices and innovation. But while 4G was an era-defining technology that boosted the speed and utility of already existing products and platforms, the fifth generation feels to some like a solution in search of a problem. While Nasa's research foreshadowed the development of a space-based internet built on 5G networks, there have yet to be any revolutionary applications that people can actually use.
Narrative Science uses a natural language generation (NLG) engine to help businesses make sense of complex enterprise data and tell clearer stories, especially in uncertain times. That said, Nate Nichols, distinguished principal of product strategy and architecture, sees the increased buy-in across the board as nothing but good news. "Their work is helping to make the idea of computers creating language or stories more mainstream than we've seen before," Nichols said. As advanced data processing techniques become more commonplace, so do the errors associated with them. Such errors include implicit bias as a result of fair prediction, or predicting outcomes for one group well and another group poorly, according to Stats Perform Director of Computer Vision Sujoy Ganguly. It's a side effect that he and Relativity Senior Data Scientist Rebecca BurWei are looking to avoid as trends like learned user trust gain steam. "Building AI that understands and responds to user trust could help us build systems that are more accurate and less biased," BurWei said.
Autonomous vehicles were supposed to make human drivers obsolete. But the coronavirus pandemic is exposing how a technology designed to be human-free still relies on a large workforce of contract laborers at almost every level. The Verge reached out to 10 autonomous vehicle developers to find out what they were doing in response to the coronavirus outbreak. Almost all of them said they would be grounding their fleets for at least several weeks as they monitor the spread of the virus. But the fate of human backup drivers who ride around in the vehicles is less certain.
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.