Zara  Bryant

Zara Bryant

1605100821

Wayve | Disrupting Autonomous Driving | Tech Exceptions

Join us for an exceptional conversation with Alex Kendall, co-founder, and CEO of Wayve, who raised more than 40M$ to kickstart the biggest vehicle academy.

Alex shares the technology that powers Wayve, how they are building the largest autonomous driving academy in the world, and what the future holds for this ever-growing ecosystem.

To scale their solution, the three-year-old company is leveraging both Microsoft Azure and Microsoft for Startups: Autonomous Driving program, which provides benefits like free Azure credits and access to Microsoft engineers and program managers to support the development of these complex workloads on the cloud.

Kendall: “Just like humans, our system learns most efficiently using many sources, including unsupervised learning, imitation learning and reinforcement learning.”

#cloud #web-development #programming #developer

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Wayve | Disrupting Autonomous Driving | Tech Exceptions
Vikas  Sharma

Vikas Sharma

1623574551

Vikas Driving School Melbourne - Cheap Indian Driving Lessons

Experts say that you can’t become a skilled driver within a week. Driving, like many other skills, requires patience and lots of practice. Even if you’ve been driving for several years, it’s always a good strategy to learn new techniques and keep improving.

In this article, we’ll explain a few tricks that’ll help you become a better driver and avoid unexpected road accidents. These tricks will include everything, starting from taking professional driving lessons in Melbourne to properly using all the features in your car.

So, without any further ado, let’s get started.

1. Learn from Experts

If you’re an absolute beginner, the first step towards becoming a better driver would be to join a dedicated driving school in Melbourne. These schools have professional driving instructors who have years of experience in training novice drivers.

They’ll help you understand the basics of driving and also give you extra tips to stay confident behind the wheel. Another potential benefit of joining a driving school is that it’ll also help you pass the driving license test more easily. Why? Because the instructors will also share different rules and regulations that you must follow during the test.

2. Always Set Your Mirrors Correctly

Another crucial tip that’ll help you become a better driver is to adjust all the mirrors correctly. Many people keep the side mirrors too close that they only see the rear portion of their car and not the actual road.

Keep in mind that if you’re doing this, you won’t be able to know how many cars are behind you and it’ll become challenging to change lanes. So, learn how to adjust the slider mirror and the internal rearview mirror so that you always have a clear view of the back.

3. Maintain a Safe Distance From Other Cars in Traffic

While driving in traffic, make it a habit to maintain a safe distance from the car in front of you. The general thumb rule says that you should keep a distance of at least two full-length cars from the cars in front of you. This way even if the other driver brakes hard, you won’t go colliding into his/her vehicle.

4. Always Use Indicators While Changing Lanes

When it comes to driving in traffic, it’s quite natural to change lanes from time to time. However, switching lanes without using any signals may confuse other drivers and may become the reason for unexpected accidents.

So, while changing lanes, make sure to check the side and rearview mirrors first and then use the correct indicator. If you’re a beginner, your instructor from the driving school in Melbourne will ask you to master this tactic.

#driving school melbourne #driving school near me #driving school south morang #driving lessons melbourne #driving school werribee

Seamus  Quitzon

Seamus Quitzon

1593304560

Autonomous driving market overview

Indeed, just like we turned from horses to cars about a 100 years ago, mobility is slowly turning from mechanical transportation machines to supercomputers on wheels; creating a new land of opportunities for outsiders to come in and for balances of power to shift drastically in a trillion dollar automotive industry.

“Autonomous driving is at the heart of what is considered the second inflection point of mobility.”

Since autonomous driving activities kicked off with the DARPA challenge in 2004, the ecosystem became a lot larger and fiercely competitive with OEMs and tier 1 suppliers now joined by internet companies, TELCOs, electronics manufacturers, and a large crowd of startups. A spurge of innovation and enthusiasm notably took the market by storm from 2013 to 2017 with expectations that autonomous cars would be widely adopted by 2020.

Billions of funding later, where is autonomous driving standing right now?

The promise of a better future

What’s a self-driving car? In simple words, a self-driving car is a car with the ability to perceive the outside environment and to make driving decisions upon it, and thus, drive by itself. It usually takes the form of a car retrofitted with a bunch of sensors (e.g. cameras, lidars, and radars) and powered by an embedded supercomputer trained to be a super driver (sort of substituting for the eyes and the brain of the driver).

What sounded like science fiction 20 years ago has never seemed so real today with autonomous cars quickly becoming the greatest hope to get rid of bad human drivers (e.g. responsible of 90% of accidents on the road), offer mobility to people with health problems and disabilities, reduce congestion in cities (e.g. traffic jams and parking), increase productivity for soon to be ex-drivers, have robots deliver packages to our doors, or even to bring many mobility companies in profitable territory (e.g. taxis and ride hailing companies).

“Humans spend on average thousands of hours in cars (including hundreds of hours stuck in traffic or looking for parking), while also being held responsible for 90% of road accidents.”

These perspectives for innovation drove tech companies to take the market by storm which in turn, thanks to majorbreakthroughs in artificial intelligence and machine learning, led to unprecedent progress and massive amounts of funding. The boom of the industry in the mid-2010s further drew over-optimistic predictions with a wide range of actors such as General Motors, Ford, Google’s Waymo, Toyota, Honda, and Tesla all promising us autonomous cars around 2020.

Yet, 2020 is here and self-driving cars aren’t.

Overcoming the data challenge

Autonomous driving is at the crossroad of many challenges which are likely to unfold as followed: technology, and then, in a lesser extent, regulation and adoption.

First and foremost, autonomous driving companies need to make sure that the tech is solid and that self-driving cars are as close as possible to being 100% safe, making a case at surpassing their human counterparts. In fact, autonomous cars being 99% safe would result in killing 1 every 100 pedestrians crossed and would amount to millions of deaths very quickly. Making self-driving cars work is extremely difficult and involves a set of very complex technologies such as computer vision, artificial intelligence, or machine learning for cars to learn how to drive from data accumulated on the road and that will be further transformed in hard-coded computer rules.

Once the tech is ready, governments and public institutions will need to lay the ground to introduce and regulate autonomous cars in our day to day transportation. That includes granting authorizations to autonomous driving companies to test and to drive in public areas as well as agreeing on a legislation defining rules and responsibilities (e.g. liability in accidents, proper data collection, sharing of the road for self-driving and regular cars).

Lastly, it will be important to provide user friendly commercial applications and to educate people about self-driving cars in order to enhance public adoption. Today, more than 50% of people still don’t feel comfortable about riding autonomous cars. Moreover, even though younger generations are more inclined to shared mobility services and new technologies, cars have long been meaningful possessions advocating for freedom and social status.

Each of these challenges will take some time to be addressed but what has truly been delaying commercial roll plans is the technical complexity of building the technological stack. Over the last 10 years, the industry has laid the ground to capture, store, and process billions of hours of driving data to teach cars how to behave in increasingly complicated scenarios, but self-driving cars now seem to be confronted to the limitations of big data.

Indeed, in order to learn from new scenarios, self-driving cars need to run into infrequent situations, or “edge cases”, which require an ever-larger number of miles to be driven and data to be accumulated. The trick in improving autonomous driving is that the closer we get to the 100% safety mark, the more infrequent the edge cases are, the more data we need to find them, and the exponentially more difficult progress becomes.

In 2017, Intel notably claimed that self-driving cars generated between 1TO and 5TO of data per hour per test vehicle, which for companies running fleets of tests vehicles all day long represents the equivalent of an ocean of data. Working through these massive amounts of data proved to be highly complex, time consuming, expensive, and unsustainable; forcing many companies to reconsider their go-to-market.

“Self-driving cars generate between 1TO and 5TO of data per hour per vehicle.”

Who’s leading the autonomous driving race?

Despite the bumps in the road, many companies are stepping up their efforts and betting that future gains will far outweigh the burdens of bringing the technology to market.

To help us track the race towards fully automated vehicles, the Society of Automotive Engineers (SAE) notably described autonomous driving in 6 levels of automation ranging from no automation to full automation.

At its core, the tech behind autonomous driving relies on capturing, processing, and deploying data that will power a self-driving software. The driving software is the holy grail of the industry and many tech companies leveraged their unfair advantage in software and data management.

“Not surprisingly, the leader in autonomous driving today isn’t a car manufacturer but Waymo: a Google spinoff.”

Autonomous driving performance has been measured in a few (maybe debatable) metrics that became standards in the industry, one of which being the miles driven per disengagement reported at the Department of Motor Vehicles (DMV) in California (level 3 and above).

In 2019, surprisingly and for the first time since 2015, Waymo came second in miles per disengagement behind Baidu rising to the top with over 18 000 miles per disengagement. However, Waymo and GM Cruise largely dominated other metrics with 1.4 million miles driven by 148 test vehicles and 0.8 million miles driven by 228 test vehicles respectively (e.g. Baidu drove 0.1 million miles with 4 test vehicles).

It’s worth noting that if startups seem to be leading the way in autonomous driving performance, large corporations tend to be more secretive about testing while also filing more patents to protect intellectual property.

In terms of commercialization and state of the art, autonomous driving is still very limited with Tesla proposing the most sophisticated self-driving car on the market with level 2/3 automation and a few actors offering level 4 automation in specific use cases (e.g. parcel and goods delivery, residential transportation).

Hence, besides all the excitement about autonomous driving and all the big announcements about commercial plans rolling out anytime soon, we’re still a long way from level 5 and full automation in our day to day transportation.

“It could take up to a few decades before autonomous cars are widely adopted.”

#self-driving-cars #mobility #autonomous-driving #autonomous-cars #cars #mobile app

Zara  Bryant

Zara Bryant

1605100821

Wayve | Disrupting Autonomous Driving | Tech Exceptions

Join us for an exceptional conversation with Alex Kendall, co-founder, and CEO of Wayve, who raised more than 40M$ to kickstart the biggest vehicle academy.

Alex shares the technology that powers Wayve, how they are building the largest autonomous driving academy in the world, and what the future holds for this ever-growing ecosystem.

To scale their solution, the three-year-old company is leveraging both Microsoft Azure and Microsoft for Startups: Autonomous Driving program, which provides benefits like free Azure credits and access to Microsoft engineers and program managers to support the development of these complex workloads on the cloud.

Kendall: “Just like humans, our system learns most efficiently using many sources, including unsupervised learning, imitation learning and reinforcement learning.”

#cloud #web-development #programming #developer

Exceptions and Exception Handling in C#

C## and the .NET CLR use exceptions to show that an error condition has arisen during program execution. C## programs are under constant threat of running into some sort of problem. As a program’s complexity grows, the probability that something odd would happen during its execution also gets higher.

In this blog, we will go through the basics of Exception and Exception handling. We will also look at how we can achieve exception handling using try, catch, and finally blocks and how to create your own custom exceptions.

Exception

The errors which we are getting at the run time of the application is called an exception.

If any exception is coming into our application then the application is abnormally terminated. The Application is not considered as a good application if any exception is coming and it is not handled.

Every time when we are developing an application and it got successfully build without any errors. Then this happens

Exception

For that, it is good practice to use exception handling.

#c# #exception #exception handling #.net #exception handling best practices #c++

Ilene  Jerde

Ilene Jerde

1599079680

Driving Change: 5 Automotive Trends and Innovations

During the Coronavirus pandemic, people’s attitudes towards public transportation and carsharing have changed. They are not safe enough. Precisely because of that, most users are now finding comfort in owning a private vehicle.

Automotive manufacturers see this trend as an opportunity to attract customers and improve car sales. And, to do so, they need to provide users with impeccable, personalized user experiences.

Here is what technologies and trends are dominating the automotive industry in 2020.

#automotive-industry #autonomous-cars #electric-cars #self-driving-cars #automotive-tech #ai-and-automotive-industry #iot #latest-tech-stories