John Paul Mueller - Machine Learning For Dummies

When you begin to realize the importance of environment to machine learning, you can also begin to understand the need for the right hardware and in the right balance to obtain a desired result. The current state-of-the-art systems actually rely on Graphical Processing Units (GPUs) to perform machine learning tasks. Relying on GPUs does speed the machine learning process considerably. A full discussion of using GPUs is outside the scope of this book, but you can read more about the topic at https://devblogs.nvidia.com/parallelforall/bidmach-machine-learning-limit-gpus/ and https://towardsdatascience.com/what-is-a-gpu-and-do-you-need-one-in-deep-learning-718b9597aa0d .

As with many other technologies, AI and machine learning both have their fantasy or fad uses. For example, some people are using machine learning to create Picasso-like art from photos using products like NightCafé ( https://creator.nightcafe.studio/ ), which supports people who really enjoy this art form. You can read all about using machine learning to create art at https://www.washingtonpost.com/news/innovations/wp/2015/08/31/this-algorithm-can-create-a-new-van-gogh-or-picasso-in-just-an-hour/ . Of course, the problems with such use are many. For one thing, most people wouldn’t really want a Picasso created in this manner except as a fad item (because no one had done it before). The point of art isn’t in creating an interesting interpretation of a particular real-world representation, but rather in seeing how the artist interpreted it. The end of the article points out that the computer can only copy an existing style at this stage — not create an entirely new style of its own. The following sections discuss AI and machine learning fantasies of various sorts.

AI is entering an era of innovation that you used to read about only in science fiction. It can be hard to determine whether a particular AI use is real or simply the dream child of a determined scientist. For example, The Six Million Dollar Man ( https://en.wikipedia.org/wiki/The_Six_Million_Dollar_Man ) is a television series that looked fanciful at one time. When it was introduced, no one actually thought that we’d have real-world bionics at some point. However, Hugh Herr ( https://www.smithsonianmag.com/innovation/future-robotic-legs-180953040/ ) and others ( https://www.fiercebiotech.com/medtech/using-onboard-ai-to-power-quicker-more-complex-prosthetic-hands ) have other ideas — bionic legs and arms really are possible now. Of course, they aren’t available for everyone yet; the technology is only now becoming useful. Muddying the waters is The Six Billion Dollar Man movie, based partly on The Six Million Dollar Man television series ( https://www.cinemablend.com/new/Mark-Wahlberg-Six-Billion-Dollar-Man-Just-Made-Big-Change-91947.html ), which has suffered delays for various reasons ( https://screenrant.com/mark-wahlberg-six-billion-dollar-man-delays-updates/ ). The fact is that AI and machine learning will both present opportunities to create some amazing technologies and that we’re already at the stage of creating those technologies, but you still need to take what you hear with a huge grain of salt.

One of the more interesting uses of machine learning for entertainment purposes is the movie B ( https://www.cinemablend.com/news/2548939/one-sci-fi-movie-will-be-able-to-film-during-the-pandemic-thanks-to-casting-an-ai-robot-as-its-lead ), which stars an android named Erica. The inventors of Erica, Hiroshi Ishiguro and Kohei Ogawa, have spent a great deal of time trying to make her lifelike by trying to implement the human qualities of intent and desire ( https://www.yoichimatsuyama.com/conversation-with-evolving-robotic-species-interview-with-hiroshi-ishiguro/ ). The result is something that encroaches on the uncanny valley ( https://www.scientificamerican.com/article/why-uncanny-valley-human-look-alikes-put-us-on-edge/ ) in a new way. The plot of this movie will be on the same order as Ex Machina ( https://www.indiewire.com/2020/06/ex-machina-real-robot-erica-science-fiction-movie-1234569484/ ).

To make the future uses of AI and machine learning match the concepts that science fiction has presented over the years, real-world programmers, data scientists, and other stakeholders need to create tools. Nothing happens by magic, even though it may look like magic when you don’t know what’s happening behind the scenes. In order for the fad uses for AI and machine learning to become real-world uses, developers, data scientists, and others need to continue building real-world tools that may be hard to imagine at this point.

You find AI and machine learning used in a great many applications today. The only problem is that the technology works so well that you don’t know that it even exists. In fact, you might be surprised to find that many devices in your home already make use of both technologies. Both technologies definitely appear in your car and most especially in the workplace. In fact, the uses for both AI and machine learning number in the millions — all safely out of sight even when they’re quite dramatic in nature. Here are just a few of the ways in which you might see AI used:

Fraud detection: You get a call from your credit card company asking whether you made a particular purchase. The credit card company isn’t being nosy; it’s simply alerting you to the fact that someone else could be making a purchase using your card. The AI embedded within the credit card company’s code detected an unfamiliar spending pattern and alerted someone to it.

Resource scheduling: Many organizations need to schedule the use of resources efficiently. For example, a hospital may have to determine where to put a patient based on the patient’s needs, availability of skilled experts, and the amount of time the doctor expects the patient to be in the hospital.

Complex analysis: Humans often need help with complex analysis because there are literally too many factors to consider. For example, the same set of symptoms could indicate more than one problem. A doctor or other expert might need help making a diagnosis in a timely manner to save a patient’s life.

Automation: Any form of automation can benefit from the addition of AI to handle unexpected changes or events. A problem with some types of automation today is that an unexpected event, such as an object in the wrong place, can actually cause the automation to stop. Adding AI to the automation can allow the automation to handle unexpected events and continue as if nothing happened.

Customer service: The customer service line you call today may not even have a human behind it. The automation is good enough to follow scripts and use various resources to handle the vast majority of your questions. With good voice inflection (provided by AI as well), you may not even be able to tell that you’re talking with a computer.

Safety systems: Many of the safety systems found in machines of various sorts today rely on AI to take over the vehicle in a time of crisis. For example, many automatic braking systems rely on AI to stop the car based on all the inputs that a vehicle can provide, such as the direction of a skid.