If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
With ambitions to establish a network of autonomous trucking routes across the US, transport startup TuSimple is taking some steady and significant steps forward as it proves its technology through trials and expands into Europe. The latest test run for its self-driving trucks involved hauling a load of fresh produce over hundreds of miles across the US, where it demonstrated that it can complete such tasks in a fast and highly efficient fashion. Previously, we've seen TuSimple's Level 4 autonomous trucks use its variety of cameras and sensors to move goods as part of trials for the US Postal Service and shipping giant UPS. This time around, the startup has partnered with fresh produce provider The Giumarra Companies and Associated Wholesale Grocers to explore autonomous trucking's potential in the fresh food industry. The trial started in Nogales, Arizona, where TuSimple's truck was loaded up with fresh watermelons from Giumarra's facility.
Artificial intelligence (AI) is the most disruptive innovation in a generation. It is quickly becoming an essential component in many industries, including public safety. However, these are still the nascent stages of AI adoption, and with that, come challenges. One is the so-called “black box,” problem, where human operators overseeing a system do not fully understand why the algorithms recommend a particular action. Data goes in one side and results come out the other, but it is not always clear what happens in the interim. . . .
Robotaxis may still be a few years out, but there are other industries that can be transformed by autonomous vehicles as they are today. MIT spin-off ISEE has identified one in the common shipping yard, where containers are sorted and stored -- today by a dwindling supply of human drivers, but tomorrow perhaps by the company's purpose-built robotic yard truck. With new funding and partnerships with major shippers, the company may be about to go big. Shipping yards are the buffer zone of the logistics industry. When a container is unloaded from a ship full of them, it can't exactly just sit there on the wharf where the crane dropped it. Maybe it's time sensitive and has to trucked out right away; maybe it needs to go through customs and inspections and must stay in the facility for a week; maybe it's refrigerated and needs power and air hookups.
The all-electric Ford F-150 Lightning, announced recently by the Ford Motor Co., will feature hands-free driving by virtue of Blue Cruise advanced driving assistance system (ADAS). The hands-free driving features will also be available on the 2021 internal combustion pickup truck and certain Mustang models through a software update later this year, according to an account in TechCrunch. The hands-free capability uses cameras, radar sensors and software to provide a combination of adaptive cruise control, lane centering and speed-sign recognition. It has undergone some 500,000 miles of development testing, Ford emphasized in an announcement in April. The system also has an in-cabin camera that monitors eye gaze and head position to help ensure the driver's eyes remain on the road.
There is tremendous potential for using AI in supply chain and logistics management. Early adopters in logistics and transportation already see increased profit margins by as much as five percent. AI has allowed them to cut down on shipping costs and time dramatically. Meanwhile, those still holding out on AI are in the red, unable to catch up to their more technologically advanced competitors. There are several ways to implement AI into logistics and supply chain management to save on costs and improve efficiency.
Self-driving cars are taking longer to come to market than many expected. In fact, it's looking like they may be outpaced by pilotless planes and driverless trucks. A truck isn't much different than a car, but self-driving technology is already coming in handy on long-haul trucking routes, as a recent cross-country trip showed. Last month TuSimple, a transportation company focused on self-driving technology for heavy-duty trucks, shipped a truckload of watermelons from Arizona to Oklahoma using the truck's autonomous system for over 80 percent of the journey. The starting point was Nogales, at Arizona's southern end right on the border with Mexico.
One of the most challenging parts is Forecasting a Time Series. If you agree or not, it is pretty hard to predict time-based. If you are working on a project and your task to predict delivery time using already customer-delivered dates. The customer delivery date happens delivery through one truck, and then it is a univariate time series. While in the customer delivery date based on multiple mode truck, ship, airplane, so it is multivariate time series.
Fleet tracking, asset tracking, autonomous vehicles, manufacturing automation and warehousing are all areas in which artificial intelligence-embedded chip technologies can offload network data-carrying loads. They can do this while providing frontline, real-time information. Many of these on-the-go processes need lots of data to be activated. At the same time, they need this data in real time, and in transit, to take place. Instead these processes benefit most from edge computing, which brings compute, networking and other resources directly to the devices and data that need them. By activating artificial intelligence (AI0 processing loads at the level of a system-on-a-chip (SOC), IT can expand its options for distributing and offloading data-processing loads to different layers of enterprise architecture (e.g., cloud, a central data center, or the edge itself).
Autonomous vehicle technology developer Aurora Innovation Inc. said it plans to expand testing throughout Texas as it works toward commercializing self-driving trucks. In a May 27 blog post, the company said that it is expanding its relationships with shippers and motor carriers as it works to refine its autonomous Aurora Driver technology to fit their needs and handle highway traffic. To safely deploy a self-driving truck that can handle the complexities of highway driving, Aurora is developing and refining key capabilities such as complicated lane changes and merges, and entering and exiting the freeway. The goal is to create an autonomous freight system that is "safer, faster, more reliable and more efficient," the company said. Take a closer look at how we're preparing the Aurora Driver to move goods for key logistics companies on middle-mile routes in Texas https://t.co/FlvnmBNaCN Aurora said it takes about three days to deliver goods from Dallas to Los Angeles with humans at the wheel.
Plus plans to merge with Hennessy Capital Investment Corp. V in a transaction that would bring the company, which is based in California and China, about $500 million in gross proceeds and a market capitalization of roughly $3.3 billion. The agreement is expected to close in the third quarter, the companies said Monday. The deal would provide "a significant cash infusion for us to expand our commercialization efforts," Plus Chief Executive and co-founder David Liu said, as the company steps up production and aims to fill thousands of contracted orders and vehicle reservations from Chinese and U.S. fleets. The transaction would include a $150 million private placement of shares with BlackRock Inc., D.E. Top news and in-depth analysis on the world of logistics, from supply chain to transport and technology.