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These 7 robotic delivery companies are racing to bring shopping to your door

#artificialintelligence

By 2020, people thought the autonomous car would whisk you to the office while you read the paper and tackle your emails, then taking you home from the bar on a Friday evening. That remains lodged somewhere in the pipeline for now. But another slice of science fiction is on the way – robots that deliver your food -- and it's already knocking at the door. Robotic food delivery (or, increasingly, the delivery of anything that fits into a robot) is being tackled by a wide range of companies, from garage startups to retail giants. Many use six-wheeled robots designed to drive themselves along the sidewalk and the pathways of business parks and college campuses.


AI's carbon footprint problem

#artificialintelligence

For all the advances enabled by artificial intelligence, from speech recognition to self-driving cars, AI systems consume a lot of power and can generate high volumes of climate-changing carbon emissions. A study last year found that training an off-the-shelf AI language-processing system produced 1,400 pounds of emissions--about the amount produced by flying one person roundtrip between New York and San Francisco. The full suite of experiments needed to build and train that AI language system from scratch can generate even more: up to 78,000 pounds, depending on the source of power. But there are ways to make machine learning cleaner and greener, a movement that has been called "Green AI." Some algorithms are less power-hungry than others, for example, and many training sessions can be moved to remote locations that get most of their power from renewable sources.


Learning local and compositional representations for zero-shot learning - Microsoft Research

#artificialintelligence

In computer vision, one key property we expect of an intelligent artificial model, agent, or algorithm is that it should be able to correctly recognize the type, or class, of objects it encounters. This is critical in numerous important real-world scenarios--from biomedicine, where an intelligent system might be tasked with distinguishing between cancerous cells and healthy ones, to self-driving cars, where being able to discriminate between pedestrians, other vehicles, and road signs is crucial to successfully and safely navigating roads. Deep learning is one of the most significant tools for state-of-the-art systems in computer vision, and its use has resulted in models that have reached or can even exceed human-level performance in important and challenging real-world image classification tasks. Despite their successes, these models still have difficulty generalizing, or adapting to tasks in testing or deployment scenarios that don't closely resemble the tasks they were trained on. For example, a visual system trained under typical weather conditions in Northern California may fail to properly recognize pedestrians in Quebec because of differences in weather, clothes, demographics, and other features.


Amazon Adds Driverless Car Maker Zoox To Portfolio

#artificialintelligence

Amazon will pay more than $1.2 billion to acquire Zoox, the Foster City, Calif., self-driving technology company, the Financial Times (FT) reported. While the purchase could fuel Amazon's delivery fleet, a source familiar with the deal told the newspaper it could signal the eCommerce giant's entry into ride-hailing. The source said Amazon would collaborate with Zoox to create a ride-hailing fleet, taking on Waymo Co, the California-based self-driving industry leader backed by Alphabet, Google's parent company. Still, some analysts say the deal is more about Amazon's mission to fold autonomous technology into its delivery network. Last year, Amazon participated in a $530 million funding round for autonomous technology firm Aurora Innovation. Last month, PYMNTS reported Amazon was in talks to buy Zoox.


An Introduction to Reinforcement Learning - Lex Fridman, MIT

#artificialintelligence

We were delighted to be joined by Lex Fridman at the San Francisco edition of the Deep Learning Summit, taking part in both a'Deep Dive' session, allowing for a great amount of attendee interaction and collaboration, alongside a fireside chat with OpenAI Co-Founder & Chief Scientist, Ilya Sutskever. The MIT Researcher shared his thoughts on recent developments in AI and its current standing, highlighting its growth in recent years. Lex then referenced, Lee Sedol, the South Korean 9th Dan GO player, whom at this time is the only human to ever beat AI at a video game, which has since become somewhat of an impossible task, describing this feat as a seminal moment and one which changed the course of not only deep learning but also reinforcement learning, increasing the social belief in the subsection of AI. Since then, of course, we have seen video games and tactically based games, including Starcraft become imperative in the development of AI. The comparison of Reinforcement Learning to Human Learning is something which we often come across, referenced by Lex as something which needed addressing, with humans seemingly learning through "very few examples" as opposed to the heavy data sets needed in AI, but why is that?


Amazon to pay over $1 billion to secure self-driving startup Zoox: report

ZDNet

Amazon is reportedly on the verge of announcing a deal to acquire self-driving startup Zoox for over $1 billion. According to The Information, unnamed sources close to the matter say the deal could be announced as soon as Friday. If confirmed, the acquisition of the startup would give the e-commerce giant access to a pool of over 1,000 staff and additional talent in the self-driving space. California-based Zoox, which also has offices across the San Francisco Bay Area, was founded in 2014 by Tim Kentley-Klay and Dr. Jesse Levinson. The startup describes itself as a company focused on building "autonomous mobility from the ground up," which includes self-driving software for vehicles to safely navigate city streets. To date, the startup has raised $955 million over four funding rounds.


Tesla may build 12-seat electric VANS that zip passengers at 127 mph through an underground tunnel

Daily Mail - Science & tech

Tesla is developing its own electric van for zipping passengers through its underground'boring' tunnels. According to a report from The Mercury News, San Bernardino County Transportation Authority will work with Tesla - and its sister drilling company Boring Company - to develop a 12-seat electric van for transporting passengers through a nearly 3-mile tunnel. The vans will be used in a recently approved connector line between Rancho Cucamonga and the Ontario International Airport. Tesla may develop an electric van capable of caring passengers between a 3-mile underground tunnel connecting Rancho Cucamonga and the Ontario International Airport. in San Bernardino County. While plans originally called for specially designed cars, the $60 million project will use the vans instead to eventually carry 1,200 passengers per day or about 10 million per year according to The Mercury News.


Tesla Model 3 'on Autopilot mode' crashes into truck in Taiwan

Daily Mail - Science & tech

Security cameras watching a highway in Taiwan captured the moment a white Tesla Model 3 vehicle plowing into truck that was rolled over on its side. Reports say the driver of the Tesla did not see the overturned Truck while cruising with the Autopilot driver assistant feature activated. The footage also shows that the car's emergency automatic braking system was applied at the last second, due to smoke coming from the tires moments before the collision. An image of the aftermath shows the entire front-end of the Tesla pierced through the roof of the truck, but reports note that neither of the drivers were injured. Tesla's Autopilot features allow the vehicle to steer, accelerate and brake automatically within a lane.


Softbank closes $500 million funding round for Didi's autonomous driving unit

ZDNet

China's Didi Chuxing has banked $500 million in investment dollars for its autonomous driving subsidiary following the closure of its first funding round led by Softbank Vision Fund 2. The investment is expected to help the Chinese ride-hailing service develop and eventually deploy its first fleet of autonomous vehicles in specific areas in China and abroad. "Didi aims to launch autonomous fleet operations in select locations as China seeks to build a comprehensive digital infrastructure network based on 5G, AI, and IoT technologies," the company said. "Didi also plans to further deepen cooperation with global upstream and downstream auto industry partners towards mass production of autonomous driving vehicles, with the aim of advancing the transformation of the global automotive and transportation industries." The company has been working on developing and testing autonomous vehicle technology since 2016, and in August last year spun out its autonomous driving unit into an independent company. Didi has also been operating automated test vehicles in Beijing, Shanghai, and Suzhou in China, as well as the state of California in the US.


Waymo's self-driving minivans will return to California streets in June

Mashable

Waymo is ready to get back to the business of being on the streets of California. The Alphabet-owned company shut down a public testing program for its self-driving minivans in early March, as the global pandemic started to reshape society in the United States. Now that fleet will reportedly return to the streets of San Francisco on June 8. That revelation comes from a company email obtained by The Verge, which reported the news on Saturday. The self-driving fleet will apparently be running deliveries for a pair of non-profits: Wendy McNaughton's #DrawTogether, which sets local kids up with art kits; and Lighthouse for the Blind and Visually Impaired.