Modern Marvels S11e02 Car Tech Of The Future

Futuristic cars that don’t just turn fake car clean and green machines running on hydrogen instead of gas safety systems that won’t let you crash and burn and cars that push the envelope of engineering car tech of the future next unwatered model in ten years what will you be driving about 20 years or 50 years into the future 50.

Years in the future could be Star Trek transportation pause that’s what it becomes science fiction has steadily projected actual technological progress we can push the envelope.

As fast as you want but you got to be careful that you’re not running by your public keys into the future of automotive technology and you’ll find as many predictions as there.

Are dreams and dreamers one of the breakthrough technologies that will fuel the future is hydrogen the things that we can do electronically it’s absolutely mind-boggling cars won’t just listen.

To our commands they’ll talk back.

I’ll be in the glove compartment if you need me you see in the future of the use of multiplexed electrical systems where we can coordinate a lot of different functions in the vehicle all at the same time cars will do more than react they’ll predict your every move know what you’re going to do before.

You know it yourself the automobile is going to be in touch with you very intimately it won’t be a passive automobile will be very active letting you know things at the.

Right time when you really need to know them aerodynamic design at ultralight materials will push.

The performance of future cars off the charts way it gets adapted from the racing will eventually make us way into everyday passenger cars hurtling into the.

Future will find technological wonders unimaginable today but it took a rocky road to get there with surprising twists and turns that made for an incredible journey.

For centuries men like Leonardo da Vinci dreamed of inventing a horseless self-propelled carriage but it wasn’t.

Until 1769 that the dream became a reality when French army engineer Nicolas kunio mounted a primitive steam engine on a three-wheeled wagon historians.

Regard then 1769 kunio as a world’s first automobile it was steam powered with a tremendously large boiler sitting in front of the singular front wheel kunos car never.

Panned out from then on inventors continued.

To experiment with steam-powered cars while others were developing electric driven vehicles both have their.

Merits as well as their limitations by 1886 German mechanic’s Karl Benz and Gottlieb Daimler had developed two different cars both powered by a brand new type of engine both fill cars of their own independent of each other each car was considered in its own way the first practical vehicle their propulsion.

System was the gasoline-powered internal combustion engine the internal combustion engine is actually much more efficient takes less space on the in the same car and puts out more power than steam in is it.

These early 1 cylinder engines worked very much the same as today’s a potent mist of vaporized fuel and air is compressed inside a cylinder then the spark plug fires igniting a controlled explosion which drives the piston downward the Pistons turn a shaft which transfers that power to the wheels at the bottom of.

See A Car Crash From The Perspective Of Google’s Self Driving Car

One of Google’s self-driving cars was recently involved in an accident, and the company has released a video showing what the crash looked like from the car’s perspective. It’s clear that Google’s car was not at fault — in fact, this accident demonstrates pretty clearly the danger of letting distracted humans drive.

On July 1, one of Google’s Lexus driverless cars was driving autonomously toward a Mountain View intersection. The light was green, but traffic was backed up on the other side, so three cars — including Google’s — slowed to a stop to avoid getting stuck in the middle of the intersection. After they’d stopped, a car crashed into the back of them at 17 mph — and it was obvious that it hadn’t braked at all.

As you can see, the self-driving car braked normally, and the vehicle behind it had plenty of room to stop, but it never slowed down. Why? The driver’s attention was focused elsewhere — a state human drivers find themselves in far too often.

Self-Driving Cars vs. Humans


In terms of safety, how do driverless cars stack up against their human counterparts?

Well, because it’s not fair to use a single incident to answer that question, let’s take a quick look at the accident history of Google’s self-driving cars.

Since the start of the project in 2009, other drivers have hit Google’s self-driving cars 14 times — and 11 of those incidents were rear-enders. After more than a million miles of autonomous driving over the course of six years, according to Google not once has the self-driving car been the cause of a collision. In each case, it’s the result of human error and inattention.

This is very telling, I’d say, but it’s nothing we didn’t already know. Humans are good at a lot of things, but, statistically, driving isn’t one of them.

Think about it: people do all sorts of dangerous things behind the wheel. We eat, we talk on our phones, we text, we drive after drinking alcohol, we fall asleep, and we generally fail to give the task of driving the attention it demands. (Have you ever looked up after a long stretch of road only to realize you haven’t been paying any attention?) Even without blatant negligence, nobody is perfect. Factors like the blind spot and the brain’s inability to multitask can put you in mortal peril.


Self-driving cars don’t have these human failings. They don’t get distracted, they don’t get tired, and they are more aware of their surroundings than any human being could ever be. At any given moment, Google’s self-driving car knows the speed limit, the current state of approaching traffic lights, and the exact position of every vehicle, pedestrian, biker, and traffic cone on the road. It takes all of this data into account and reacts accordingly, ensuring the safety of its passengers and other drivers at all times.

Google’s Chris Urmson puts it this way:

Our self-driving cars can pay attention to hundreds of objects at once, 360 degrees in all directions, and they never get tired, irritable or distracted. People, on the other hand, “drive as if the world is a television show viewed on TiVo that can be paused in real time — one can duck out for a moment, grab a beer from the fridge, and come back to right where they left off without missing a beat” — to quote Sheila Klauer of the Virginia Tech Transportation Institute in Traffic: Why We Drive the Way We Do. That’s certainly consistent with what we’re seeing.

With that said, autonomous vehicles aren’t perfect yet. While they’ve mastered the art of cruising around sunny Silicon Valley, it’s unclear how Google plans to tackle the issue of severe weather. Rain and snow can scatter the laser beams that the robot uses primarily to see. Google largely hasn’t discussed their plans to get around this challenge.


Google’s self-driving cars rely heavily on light to drive autonomously — meaning a snowstorm could easily render the whole system inoperative. That’s a big problem.

There are potential solutions, though, including wireless communication between vehicles and from vehicles to stoplights and sensing devices installed in roadways. A number of automotive suppliers are heavily invested in research and development to prepare for the forecasted $42 billion driverless car manufacturing market, so it’s only a matter of time until weather becomes a non-issue.

What Do You Think?

What are your thoughts on self-driving cars? Research shows they’re safer than human drivers, but many people are (understandably) freaked out by the whole idea. Can you see yourself being chauffeured around by a robot a decade from now? Let us know in the comments below!

Image Credit: Cracked Glass Texture I via Devianart, Google, Sam Abuelsamid

How Will Ai Impact Your Life In The Next Ten Years?

We live in a world of “smart” objects; Smart phones, watches, cars are increasingly becoming the norm. But while the term “smart” originally referred more to the additional features in these devices than their cognitive abilities, that’s beginning to change.

Before we get started, what is Artificial Intelligence (AI)? In its most broad definition, AI refers to computer programs designed to perform complex tasks that have historically required human intelligence. This could be anything from speech recognition and decision-making to visual perception.  While the grand dream of AI that meets or exceeds human capabilities in every area, companies like Google and Facebook are working to assure the present and future of AI will be very practical.

A Smarter Mobile Experience

Even with status updates and selfies, texting is still the dominant usage for cell phones. And yet, up until now, messaging apps have remained relatively basic. But a new messaging app called Emu seeks to make texting more effective. Essentially, the app comes with a built in assistant that feeds you relevant information based on the conversations you’re having. This is meant to save you from always copying and pasting information, or constantly switching back and forth between other apps to perform basic tasks.

Windows Cortana

By now, most of us are familiar with Apple’s mobile assistant, Siri, built into the most recent models of the iPhone, iPad and iPod Touch. The groundbreaking service allows users to ask questions, search the web and set reminders all by asking Siri to do it for them. Now, Microsoft is looking to challenge Apple with an assistant of its own. Cortana, named after the AI in the popular videogame Halo, was specifically designed to get smarter the more people use it. Microsoft is hoping that speaking with Cortana will be almost like speaking with a real person. Users will be able to have follow-up conversations and if Cortana makes a mistake, it’ll learn and adapt, offering more specific and accurate services later on. And Cortana is hardly the endgame for Microsoft in terms of artificial intelligence, as you’ll see below.

Advanced Photo Recognition

Whether your grandparents like it or not, social media is here to stay. And while new platforms are constantly being rolled out to appeal to niche markets, the older, more established titans are looking for innovative ways to make their services even better.

Facebook isn’t just in the business of “likes” and “shares.” It employs a surprisingly large number of AI researchers, some of whom are working on creating a facial recognition software even more accurate at matching people’s faces than humans are. Facebook’s face-processing software, called DeepFace, performs a process called facial verification. It doesn’t match names to faces, but rather, recognizes when two images show the same face. Soon, you’ll quickly be able to upload a photo, and have Facebook realize who needs to be tagged.

Google Photo Recognition

At the same time (though with a slightly different end goal,) Google is working on a similar project. Instead of face-processing, Google is working on a software that accurately describes in complete sentences the scenes in photos.

For example, if you take a few pictures at the zoo, the software will differentiate between the lions, tigers and bears. The descriptions would read something like “A bear sleeps on its back” and “two lions are playing under a tree.”  This represents a revolutionary fusion of natural language and machine vision capabilities, and is a potent sign of things to come.  Machines that can truly understand the contents of images and video and speak naturally about them are powerful tools to make the world accessible to machine intelligence via our smartphone cameras. It’s an incredible step forward for artificial intelligence, and one that could prove fundamental for future AI efforts.

Machine Learning in Computer Search and Beyond

But artificial intelligence doesn’t end with mobile and social media. There are endless opportunities for AI to make our devices smarter and our lives easier. These include safer robots that provide unbiased security for humans and advanced programs that offer smarter, better network security for businesses. It can even be more basic, like improving search results.

Again we turn to Google, who is looking to advance their search function with AI software. For years, Google has been using machine learning to understand queries and provide better results. Now, Google is looking to incorporate deep learning to usher in the next era of search.

While all of these advancements show tremendous potential, there are still those with concerns. Perhaps the most vocal among them is Elon Musk, whose concern over the future of AI has been well documented. He recently donated $10 million to support research aimed at keeping AI beneficial to humanity, fearing that unchecked advancements artificial intelligence could be likened to summoning the devil.

“I’m increasingly inclined to think there should be some regulatory oversight maybe at the national and international level, just to make sure that we don’t do something very foolish.” -Elon Musk

Despite these risks, Musk and several high profile executives from Google, Microsoft, Facebook have added their names to the list of those still committed to future of AI.  The benefits, in other words, outweigh the long-term risks. These people are passionate about building programs and machines that will further technology and enhance our lives like never before. And though we don’t know exactly when the future of AI will arrive in earnest, humanity is taking steps in that direction each and every day.

Image Credit: iphone 6 Plus Elon Musk Wallpaper by Bill Brooks via Flickr, Brand Recognition by Mike Knell via Flickr, Nokia Lumia 635 Cortana Helping by Bhupinder Nayyar via Flickr