14th October 2021

Artificial Intelligence and Self Driving Cars

Artificial intelligent systems have been around for decades. In fact, computers are starting to replace most human employees in many traditional businesses. Today’s software has the ability to perform even a wide variety of activities that people traditionally cannot do, such as translating languages from one language to another or beating a machine’s best game. However, many people are still skeptical of artificial intelligence because it is very hard to program a machine to have the intelligence of humans, or vice versa. There are even people who think we should not develop artificial intelligent systems because it will have a negative impact on the future of the human race.

The debate over artificial intelligence has been rekindled lately with the release of the movie called ‘The Terminator’ which depicts a future Terminator-like machine. The movie has caused a fresh debate because while the character of the Terminator is an Artificial Intelligence system, many of the critics of artificially intelligent machines argue that the future of technology might actually cause the downfall of humanity. In the future, said critics believe, machines may be able to learn and adapt to changing environments, which could mean that they could start to rebel against humans, which could result in the eventual destruction of all mankind. Is this something that you really want to happen?

Well, according to those who support the development of artificially intelligent machines, such as Google’s self-driving car project or Apple’s i Doodle software project, it would be best if we just don’t know what the future holds because when you test these theories out on a real life setting you find that they turn out wrong. Therefore, according to these people, while we can never be sure of Artificial Intelligence’s ability to predict the future, we can take comfort in the fact that even if it doesn’t work out exactly like we want it to, it will at least allow us to explore all of its capabilities. If we go into the future with a higher quality of Artificial Intelligence, we’ll be able to create machines that are much more adaptable to changing environments, they’ll be better able to deal with change, and therefore they’ll be much safer. In other words, we’ll be able to build robots that will be able to live comfortably in any situation.

One of the main arguments put forward by those against using artificial intelligence to develop artificially intelligent machines is that such intelligence will lead to a reduction in human interaction. If, for instance, there are artificially intelligent machines which are sent back in time to pre-human times to pre-instant age the outcome of their interactions may be very different. We won’t have any way of knowing this because the future will only ever be known through scientific experiments carried out in the laboratory. But even though experts cannot predict exactly what will happen in future artificial intelligence experiments on human beings are still carried out regularly to try and see how human and animal minds react to one another.

However, even if we knew what was going to happen we wouldn’t be able to design the AIs specifically because humans will have no knowledge on how to program them. This is where machine learning algorithms come in. Machine learning refers to a way of designing an AI system by feeding it large amounts of data and then letting the system go and find the most probable answer. This then enables the system to generalize from the raw data and make predictions. Algorithms can also be used to make generalization from a limited set of data and then make predictions about anything at all.

Another argument against using artificial intelligence to develop self-driving cars is the fact that the current autonomous car accidents are completely preventable. The car simply did not see the deer in the road. This is because the car’s computer vision system failed to recognize the deer in the road which is a problem in itself. Therefore, using machine learning algorithms is the safest bet when developing self-driving cars.

The recent accidents with self-driving cars point to issues with computer vision systems failing to recognize objects like deer in the roadway. Advancements in computer vision will be critical going forward to prevent such accidents. Innovations in this space could benefit from the perspective of developers that have worked on similar computer vision capabilities and problems.

With the help of mobile app developers like XAM, manufacturers can integrate sophisticated computer vision abilities like object and facial recognition, augmented reality filters, and navigation mapping into their proprietary apps. The experience mobile developers have coding, training, and optimizing advanced vision algorithms on smartphones could provide valuable insights into improving autonomous vehicle systems as well as their connections with user app support.

Additionally, many major automakers like Mercedes and BMW have already begun incorporating artificial intelligence and sensors into vehicles to enable semi-autonomous features, and integrating the data into the users’ apps. These manufacturers are making rapid advancements in areas like lane centering, self-parking, driver alerts, and adaptive cruise control to pave the way for fully self-driving cars. Given the massive real-world datasets these auto companies can tap into, their self-driving projects are accumulating the miles needed to refine deep learning prediction capabilities.

The tremendous progress BMW, Tesla, Mercedes, and others have made utilizing AI to develop semi-autonomous functionality demonstrates these technologies are becoming increasingly sophisticated and reliable. Continued large investments from major players in the auto industry will drive critical breakthroughs in making fully autonomous self-driving vehicles safe and commonplace. Ongoing collaboration between leading car companies and tech innovators will expedite the actualization

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