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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python Your complete guide to building intelligent apps using Python 3.x

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781839219535
Length 618 pages
Edition 2nd Edition
Languages
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Authors (2):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
Alberto Artasanchez Alberto Artasanchez
Author Profile Icon Alberto Artasanchez
Alberto Artasanchez
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Table of Contents (26) Chapters Close

Preface 1. Introduction to Artificial Intelligence 2. Fundamental Use Cases for Artificial Intelligence FREE CHAPTER 3. Machine Learning Pipelines 4. Feature Selection and Feature Engineering 5. Classification and Regression Using Supervised Learning 6. Predictive Analytics with Ensemble Learning 7. Detecting Patterns with Unsupervised Learning 8. Building Recommender Systems 9. Logic Programming 10. Heuristic Search Techniques 11. Genetic Algorithms and Genetic Programming 12. Artificial Intelligence on the Cloud 13. Building Games with Artificial Intelligence 14. Building a Speech Recognizer 15. Natural Language Processing 16. Chatbots 17. Sequential Data and Time Series Analysis 18. Image Recognition 19. Neural Networks 20. Deep Learning with Convolutional Neural Networks 21. Recurrent Neural Networks and Other Deep Learning Models 22. Creating Intelligent Agents with Reinforcement Learning 23. Artificial Intelligence and Big Data 24. Other Books You May Enjoy
25. Index

The smart home

Whenever you bring up the topic of AI to the common folk on the street, they are usually skeptical about how soon it is going to replace human workers. They can rightly point to the fact that we still need to do a lot of housework around the house. AI needs to become not only technologically possible, but it also needs to be economically feasible for adoption to become widespread. House help is normally a low-wage profession and, for that reason, automation to replace it needs to be the same price or cheaper. In addition, house work requires a lot of finesse and it comprises tasks that are not necessarily repetitive. Let's list out some of the tasks that this automaton will need to perform in order to be proficient:

  • Wash and dry clothes
  • Fold clothes
  • Cook dinner
  • Make beds
  • Pick up items off the floor
  • Mop, dust and vacuum
  • Wash dishes
  • Monitor the home

As we already know, some of these tasks are easy to perform for machines (even without AI) and some of them are extremely hard. For this reason and because of the economic considerations, the home will probably be one of the last places to become fully automated. Nonetheless, let's look at some of the amazing advances that have been made in this area.

Home Monitoring

Home monitoring is one area where great solutions are generally available already. The Ring video doorbell from Amazon and the Google Nest thermostat are two inexpensive options that are widely available and popular. These are two simple examples of smart home devices that are available for purchase today.

The Ring video doorbell is a smart home device connected to the internet that can notify the homeowner of activity at their home, such as a visitor, via their smartphone. The system does not continuously record but rather it activates when the doorbell is pressed, or when the motion detector is activated. The Ring doorbell can then let the home owner watch the activity or communicate with the visitor using the built-in microphone and speakers. Some models also allow the homeowner to open the door remotely via a smart lock and let the visitor into the house.

The Nest Learning Thermostat is a smart home device initially developed by Nest Labs, a company that was later bought by Google. It was designed by Tony Fadell, Ben Filson, and Fred Bould. It is programmable, Wi-Fi-enabled, and self-learning. It uses artificial intelligence to optimize the temperature of the home while saving energy.

In the first weeks of use you set the thermostat to your preferred settings and this will serve as a baseline. The thermostat will learn your schedule and your preferred temperatures. Using built-in sensors and your phones' locations, the thermostat will shift into energy saving mode when no one is home.

Since 2011, the Nest Thermostat has saved billions of kWh of energy in millions of homes worldwide. Independent studies have shown that it saves people an average of 10% to 12% on their heating bills and 15% on their cooling bills so in about 2 years it may pay for itself.

Vacuuming and mopping

Two tasks that have been popular to hand off to robots are vacuuming and mopping. A robotic vacuum cleaner is an autonomous robotic vacuum cleaner that uses AI to vacuum a surface. Depending on the design, some of these machines use spinning brushes to reach tight corners and some models include several other features in addition to being able to vacuum, such as mopping and UV sterilization. Much of the credit for popularizing this technology goes to the company (not the film), iRobot.

iRobot was started in 1990 by Rodney Brooks, Colin Angle, and Helen Greiner after meeting each other while working in MIT's Artificial Intelligence Lab. iRobot is best known for its vacuuming robot (Roomba), but for a long time they also had a division devoted to the development of military robots. The Roomba started selling in 2002. As of 2012 iRobot had sold more than eight million home robots as well as creating more than 5,000 defense and security robots. The company's PackBot is a bomb-disposal robot used by the US military that has been used extensively in Iraq and Afghanistan. PackBots were also used to gather information under dangerous conditions at the Fukushima Daiichi nuclear disaster site. iRobot's Seaglider was used to detect underwater pools of oil after the Deepwater Horizon oil spill in the Gulf of Mexico.

Another iRobot product is the Braava series of cleaners. The Braava is a small robot that can mop and sweep floors. It is meant for small spaces like bathrooms and kitchens. It sprays water and uses an assortment of different pads to clean effectively and quietly. Some of the Braava models have a built-in navigation system. The Braava doesn't have enough power to remove deep-set stains, so it's not a complete human replacement, but it does have wide acceptance and high ratings. We expect them to continue to gain popularity.

The potential market for intelligent devices in the home is huge and it is all but certain that we will continue to see attempts from well established companies and startups alike to exploit this largely untapped market.

Picking up your mess

As we learned in the shipping use case, picking objects of different weights, dimensions, and shapes is one of the most difficult tasks to automate. Robots can perform efficiently under homogeneous conditions like a factory floor where certain robots specialize in certain tasks. Picking up a pair of shoes after picking up a chair, however, can be immensely challenging and expensive. For this reason, do not expect this home chore to be pervasively performed by machines in a cost-effective fashion any time soon.

Personal chef

Like picking up items off the floor, cooking involves picking up disparate items. Yet there are two reasons why we can expect "automated cooking" to happen sooner:

  • Certain restaurants may charge hundreds of dollars for their food and be paying high prices for skilled chefs. Therefore, they might be open to using technology to replace their high-priced staff if this should work out to be more profitable. An example for this is a five-star sushi restaurant.
  • Some tasks in the kitchen are repetitive and therefore lend themselves to automation. Think of a fast food joint where hamburgers and fries might have to be made by the hundreds. Thus, rather than having one machine handle the entire disparate cooking process, a series of machines could deal with individual repetitive stages of the process.

Smart prosthetics are great examples of artificial intelligence augmenting humans rather than replacing them. There are more than a few chefs that lost their arm in an accident or were born without a limb.

One example is chef Michael Caines who runs a two Michelin star restaurant and lost his arm in a horrific car accident. Chef Caines was head chef of Gidleigh Park in Devon in England until January 2016.[3] He is currently the executive chef of the Lympstone Manor hotel between Exeter and Exmouth. He now cooks with a prosthetic arm, but you'd never know it given the quality of his food.

Another example is Eduardo Garcia who is a sportsman and a chef – both of which are made possible by the most advanced bionic hand in the world.

On October 2011, while bow-hunting elk he was electrocuted in the Montana backcountry. Eduardo was hunting by himself in October 2011. He was in back country when he saw a dead baby black bear. He stopped to check it out, knelt, and used his knife to prod it.

While doing so, 2,400 volts coursed through his body – the baby bear had been killed by a buried, live electrical wire. He survived but lost his arm during the incident.

In September 2013, Garcia was fitted by Advanced Arm Dynamics with a bionic hand designed by Touch Bionics. The bionic hand is controlled by Garcia's forearm muscles and can grip in 25 different ways. With his new hand, Garcia can perform tasks that normally require great dexterity. His new hand still has some limitations. For example, Garcia cannot lift heavy weights. However, there are things that he can perform now that he couldn't before. For example, he can grab things out of a hot oven and not get burnt and it is impossible to cut his fingers.

Conversely, rather than augmenting humans, robots may replace humans in the kitchen entirely. An example of this is Moley, the robotic kitchen. Moley is not currently in production but the most advanced prototype of the Moley Robotic Kitchen consists of two robotic arms with hands equipped with tactile sensors, a stove top, an oven, a dishwasher, and a touchscreen unit. These artificial hands can lift, grab, and interact with most kitchen equipment including knives, whisks, spoons, and blenders.

Using a 3D camera and a glove it can record a human chef preparing a meal and then upload detailed steps and instructions into a repository. The chef's actions are then translated into robotic movements using gesture recognition models. These models were created in collaboration with Stanford University and Carnegie Mellon University. After that Moley can reproduce the same steps and cooks the exact same meal from scratch.

In the current prototype, the user can operate it using a touchscreen or smartphone application with ingredients prepared in advance and placed in preset locations. The company's long-term goal is to allow users to simply select an option from a list of more 2,000 recipes and Moley will have the meal prepared in minutes.

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Artificial Intelligence with Python - Second Edition
Published in: Jan 2020
Publisher: Packt
ISBN-13: 9781839219535
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