Swedish luxury automobile manufacturer Volvo Cars and leading ICT provider Ericsson have taken an important step towards achieving seamless cross-border 5G connectivity in vehicles. Partners in the EU-backed 5GCroCo project, the two companies successfully tested the handover of connected cars between two national mobile 5G networks. The trial took place at the AstaZero test site in Sweden. The track has testing capabilities for different traffic environments, making it possible to assess advanced safety systems for all kinds of traffic situations. It features a 5.7 km rural road, a city area, a high-speed area and a multi-lane road.
The transaction provided Luminar with the infusion of capital it needed to begin producing lidar sensors that use lasers to measure distances and classify objects for self-driving vehicles at a commercial scale, according to Chief Financial Officer Tom Fennimore. As a public company, however, Luminar must be mindful of how it spends the cash, he added. Luminar has positioned itself in recent years to benefit from the expected rise of autonomous vehicles. It has announced partnerships with car makers including Volvo Cars, which is owned by China's Zhejiang Geely Holding Group, Daimler AG's trucks business and SAIC Motor Corp. Ltd. to incorporate its sensor technology into self-driving vehicle designs. The Morning Ledger provides daily news and insights on corporate finance from the CFO Journal team.
Artificial intelligence is a promising technology, that has made significant changes in the 21st century. Starting from self-driving cars and robotic assistants to automated disease diagnosis and drug discovery, the stronghold of artificial intelligence is no joke. Along with artificial intelligence, data science has also shifted the way we live and work. With the demand for data science and artificial intelligence spiralling, the job market is opening its door to AI and data science jobs. The tech sphere has ensured that artificial intelligence jobs and data science jobs provide limitless opportunities for professionals to explore cutting edge solutions.
Embark Trucks Inc. is merging with a special-purpose acquisition company to go public in a deal that values the self-driving truck startup at about $5.2 billion, the companies said. Founded in 2016, Embark says it is the oldest U.S. self-driving truck software firm and aims to partner with shippers to bring down carrier costs and make roads safer. The company has partnerships with a number of transportation companies and brands, including beer seller Anheuser-Busch InBev SA, technology firm HP Inc. and Knight-Swift Transportation Holdings Inc., the largest truckload carrier in North America. Embark currently has a small developmental fleet running some routes out of Southern California. The company hopes to fully commercialize its technology and to license it so that carriers can operate a large number of their trucks using Embark's software without needing any human drivers in the years ahead.
Artificial intelligence (AI) is used in a wide variety of products and services, including maps embedded on our smart phones and "chat bots" that help answer our questions on websites. Many hope that AI will transform our economy in ways that drive growth, similar to how steam engines did in the late 19th century and electricity did in the early 20th century. But it is hard to imagine that maps on smart phones, chatbots, and other existing AI-enabled services will drive the type of economic growth we saw from stream and electricity. What we need to see are some dramatic new AI-enabled products and services that transform our way of life--in short, we are waiting for an AI "killer app." Autonomous vehicles (AVs)--vehicles that accelerate, brake, and turn on their own, requiring little or no input from a human driver--may be such a killer app that transforms our economy significantly.
Long-term investments in AI usage have sparked interest in various areas, including customer service, medical diagnostics, and self-driving cars. Because of the additional data accessible as a result of the study, better algorithms have been developed, allowing for more complicated AI systems to improve the user's experience using search engines and online translation tools. Cryptography and blockchain have made it simpler to develop these advancements since they can exchange data openly while keeping firm information private. Security is now high, but AI will raise it to a point where security breaches on online gaming websites and applications will be unheard of. Tesla isn't the only company focused on self-driving cars.
Instead of turning a traditional car into an autonomous one, the Amazon-owned self-driving car service Zoox has created its own type of autonomous vehicle without a steering wheel or front seat. Redesigning a car from the ground up also means redesigning car safety features. On Tuesday, the San Francisco-based company released its first (voluntary) safety report since revealing its electric robotaxi in December. The report highlights what the company considers more than 100 safety features not found in regular (human-driven, conventional) vehicles. Dr. Mark Rosekind, Zoox's chief safety innovation officer, broke down the key features into three categories in a recent call: driving control, redundancy (or back up in case of failure), and rider protection.
Getting your driving licence is a milestone moment for many people. You go through rigorous theory and practical tests, sometimes more than once, before you are given the privilege of being on the road. This, of course, is to ensure the safety of the driver, any passengers and other road users, writes Raina Victor of Birketts LLP. You are also aware of the consequences of driving going wrong, including that the liability for any accident falls (for the most part) on the driver. But what about car accidents that are not caused by the driver of the vehicle but the vehicle itself?
As massive amounts of data are stored every second, it allows for the opportunity to create meaningful and revolutionizing models. This data comes in several forms, including text, images and videos, all allowing for advanced models to be created using techniques such as Deep Learning. Further, using the extensive amount of data, applications using technologies such as computer vision are being used in products such as self-driving cars and facial recognition in phones. When creating a Deep Learning application, one of the first decisions to be made is where the model will be trained, either locally on a machine or through a third-party cloud provider. This is an important decision to be made as it could significantly impact the training time of a model.
On February 25, the Shanghai Government announced its Implementation Plan for Accelerating the Development of the New Energy Automobile Industry (2021-2025). It proposes that by 2025, smart cars with conditional self-driving functionalities shall enter large-scale production, significant progress will be made to set up a standard system for testing, demonstrating smart cars. City officials noted that so far, Shanghai has opened 560 kilometers of test roads. A total of 152 vehicles from 22 companies have been issued with road test and demonstration qualifications, which make Shanghai the first amongst other Chinese cities. We know you don't want to miss any news or research breakthroughs. Subscribe to our popular newsletter Synced Global AI Weekly to get weekly AI updates.