A wind of innovation is blowing in the artificial intelligence sector. As artificial intelligence develops, its use cases diversify. Many companies are emerging and exploiting this technology in a relevant and innovative way. Artificial intelligence and machine learning are increasingly popular among companies in all industries. However, AI algorithms tend to overwork processors and GPUs.
From self-driving cars to SIRI, artificial intelligence (AI) is progressing rapidly, but where's it all headed? Well, the thing to note is that there's definitely a divergence rather than a convergence of intelligence between man and machine. Artificial intelligence is a capacity for logic that is demonstrated by machines, in contrast to the heuristic natural intelligence displayed by animals. The question is, can the former ever become equivalent to the latter? I guess to answer this we must first understand what AI really is.
In another step towards autonomous driving, Skoda Auto has partnered with VSB - Technical University of Ostrava, Czech Republic, to develop new technologies for driving assistance systems. The collaboration between the two parties involve a'Follow the Vehicle' project that aims to have autonomous cars follow a manned lead vehicle. The technology, currently being tested on two correspondingly configured Skoda Superb iVs, has potential for car-sharing service providers, car rental companies or fleet operators. The'Follow the Vehicle' project follows the principle of'two cars, one driver' where the lead vehicle is driven by a human, determining route, speed, lane and other parameters. The autonomous car follows the lead vehicle at a distance of up to ten metres.
Governments, corporations, and individuals are increasingly deploying intelligent systems to safety-critical problem areas, such as transportation, energy, health care, and law enforcement, as well as challenging social system domains such as recruiting. Failures of these systems pose serious risks to life and wellbeing, but even well-intentioned intelligent system developers fail to imagine what can go wrong when their systems are deployed in the real world. These failures can lead to dire consequences, some of which we've already witnessed, from a trading algorithm causing a market "flash crash" in 2010 to an autonomous car killing a pedestrian in 2018 and a facial recognition system causing the wrongful arrest of an innocent person in 2019. Worse, the artificial intelligence community has no formal systems or processes whereby practitioners can discover and learn from the mistakes of the past, especially since there is not a widely used centralized place to collect information about what has gone wrong previously. Avoiding repeated AI failures requires making past failures known.
One of the most common potential scenarios involving autonomous cars is using them as driverless taxis; both Uber and Lyft have made self-driving cars a big part of their future strategies. The possibility of hopping into a ride without a driver just got a little closer, at least in California -- as spotted by The Verge, California approved two new autonomous driving programs last week that let companies charge fares for autonomous rides. The two new programs are the "Drivered Autonomous Vehicle Deployment Program" and the "Driverless Autonomous Vehicle Deployment Program," both of which allow approved participants to offer "passenger service, shared rides, and accept monetary compensation for rides in autonomous vehicles." Naturally, interested companies need to get the necessary permits and show the California Public Utilities Commission (CPUC) that they're taking the proper safety measure. They'll need to get a AV Deployment Permit from California's DMV as well as one of two permits issued by CPUC.
It will take some time before we can carelessly read the newspaper in the back seat of our self-driving car. Nevertheless, the automotive industry is working hard to push the limits in the development of vehicles with higher levels of autonomy. One of the major challenges the industry is facing is how to test an automated driving system. They also need to validate that autonomous vehicles are safe enough to be released on the public road. The verification and validation (V&V) process of automated driving systems is a challenging task, requiring a complex setup of tests.
Gatik, a startup developing an autonomous vehicle stack for B2B short-haul logistics, today closed a $22.5 million series A financing round. The company also announced it will bring a fleet of self-driving vans to Canada as part of a deal with Loblaw, the country's largest retailer with over 200,000 employees. Some experts predict the pandemic will hasten the adoption of autonomous vehicles for delivery. Self-driving cars, vans, and trucks promise to minimize the risk of spreading disease because they inherently limit driver contact. This is particularly true with regard to short-haul freight, which is experiencing a spike in volume during the outbreak.
The idea of analyzing data for decision making has been around for many years, but the popularity of data science has exploded along with the FAANG companies' growth in recent years. No matter your job title, experience level, or industry, I am confident that you will encounter solutions or products that are highly'data-driven' or powered by Artificial Intelligenceᵗᵐ. Here are the Top 4 methods used by data scientists to fool others. As a Machine-Learning researcher and practitioner, I have made these'mistakes' myself in the past, sometimes even unknowingly! "Our model achieves an accuracy of 98.9%"
More than a dozen companies have long been approved to test out self-driving cars in California. Now, they can also charge passengers if they launch a robotaxi service. On Thursday, November 19, the California Public Utilities Commission (CPUC) approved both the ability to launch robotaxi services and charge for them after many months of these companies -- such as Cruise, Waymo, Aurora Innovation, Pony.ai, and Zoox -- lobbying for such policies. Of course, the companies still have to jump through various stacks of paperwork in order to be granted such approvals, but all in time. Waymo has been operating such a service in Arizona, Waymo One, for more than a year.
Luminar, the buzzy sensor startup that is on the verge of becoming a publicly traded company, locked in a supplier deal to furnish Intel subsidiary Mobileye with lidar for its fleet of autonomous vehicles. The deal, announced Friday, will see a rising star paired with a company that has long dominated the automotive industry. While the supplier agreement is nowhere near the scale of Mobileye's core computer vision business, it is an important collaboration that extends beyond a few pilot programs. Luminar has had a development agreement with Mobileye for nearly two years now. This new agreement signals the next critical step for both companies.