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The Emotion Machine REPACK

Minsky argues that emotions are different ways to think that our mind uses to increase our intelligence. He challenges the distinction between emotions and other kinds of thinking. His main argument is that emotions are "ways to think" for different "problem types" that exist in the world, and that the brain has rule-based mechanisms (selectors) that turn on emotions to deal with various problems. The book reviews the accomplishments of AI, why modelling an AI is difficult in terms of replicating the behaviors of humans, if and how AIs think, and in what manner they might experience struggles and pleasures.[2]

The Emotion Machine

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For christmas: create emotional elf, snowman or father christmas robot faces that you can program to change the emotions on. Use our emotional robot cards as a template to have the class draw their own face pictures with the slots in the same places. Then program the face by pulling the eye, mouth and nose strips to different settings. Perhaps even use them in a puppet show where their expressions change at appropriate points as directed by a script.

A wonderful way to use the emotion machine was used by Donna Golightly: asking students to code and name an emotion, reflecting on a moment in time linked to that emotion, dictating it and then sharing it.

Machine Learning for Dummies provides an entry point for anyone looking to get a foothold on Machine Learning. It covers all the basic concepts and theories of machine learning and how they apply to the real world. It introduces a little coding in Python and R to teach machines to perform data analysis and pattern-oriented tasks.

From small tasks and patterns, the readers can extrapolate the usefulness of machine learning through internet ads, web searches, fraud detection, and so on. Authored by two data science experts, this Artificial Intelligence book makes it easy for any layman to understand and implement machine learning seamlessly.

The primary audience for this book is computer science and engineering undergraduate and graduate students. The book uncovers the gap between the challenging environments of artificial intelligence and machine learning. All the concepts are explained with the help of case studies and worked-out examples.

It also encompasses other forms of learning like reinforcement, supervised, unsupervised, statistical learning, artificial intelligence, and machine learning. Each topic includes well-explained algorithms and pseudo-codes, which makes the book very helpful for beginners who aspire to kickstart their careers in AI.

The book on artificial intelligence gives examples of how machine learning is being used in our day-to-day lives and how it has infiltrated our daily existence. It also discusses the future of machine learning and the ethical and legal implications for data privacy and security. Any reader with a non-Computer Science background will find this book interesting and easy to understand.

This AI Book covers all machine learning fundamentals, practical applications, working examples, and case studies. It gives detailed descriptions of important machine learning approaches used in predictive analytics.

The book covers all major approaches to machine learning. They range from classical linear and logistic regression to modern support vector machines, boosting, Deep Learning, and random forests. This book is perfect for those beginners who want to get familiar with the mathematics behind machine learning algorithms.

As per its title, Machine Learning for Beginners is meant for absolute beginners. It traces the history of the early days of machine learning to what it has become today. It describes how big data is important for machine learning and how programmers use it to develop learning algorithms. Concepts such as AI, neural networks, swarm intelligence, etc., are explained in detail.

This Artificial Intelligence book provides simple examples for the reader to understand the complex math and probability statistics underlying machine learning. It also provides real-world scenarios of how machine learning algorithms improve our lives.

One of the few artificial intelligence books that explain the various theoretical and practical aspects of machine learning techniques very simply. It makes use of plain English to prevent beginners from being overwhelmed by technical jargon. It has clear and accessible explanations with visual examples for the various algorithms.

This AI book by Max Tegmark will surely inspire anyone to dive deeper into the field of Artificial Intelligence. It covers the larger issues and aspects of AI, including superintelligence, physical limits of AI, machine consciousness, etc. It also covers the aspect of automation and societal issues arising from AI.

The AI researcher Stuart Russell explains the probable misuse of Artificial Intelligence and its near-term benefits. It is an optimistic and empathetic take on the journey of humanity in this day and age of AI. The author also talks about the need for rebuilding AI on a new foundation where the machine can be built for humanity and its objectives.

Raj gets asked about his love life and he admits that he broke up with his girlfriends because she didn't want to see him anymore. Sheldon insults Raj by comparing him to a virgin Isaac Newton. Then Raj really starts to wonder why women don't really like him. Amy brings up the fact that a group at M.I.T. has developed a detector that correctly reads human emotional levels 85% of the time. Sheldon decides to borrow one to help test it and help him with human interaction though he wants to use it to determine the fears of his enemies so he can destroy them.

The two apartment couples are discussing what to do with Sheldon's old room. Sheldon suggests a train room; an idea which no one else likes. Also, M.I.T. is sending Sheldon a prototype emotion detector to do a beta test. Raj wants to use it to understand why women keep dumping him. Howard suggests that he just send out a survey to them. Raj decides to invite them all over as a focus group which everyone else thinks is a bad idea. Also Penny announces that she invited her brother out to help him find a job at her dad's request without telling Leonard. Leonard is not happy and thinks that he'll just have a new market to sell his drugs in. Sheldon shows up with his emotion detector that reads human reactions and display the results on his phone. It can only detect happy, sad, angry and excited. Raj tells everyone that he is going to have his ex-girlfriend focus group at his apartment to help improve himself. The rest think he is just going to get emotionally hurt. Sheldon uses the detector on Leonard explaining that he is angry about his brother-in-law staying with them which starts a fight with Penny.

At Raj's apartment, he is meeting with deaf Emily, Lucy, Emily and Claire with Howard interpreting for the first Emily. Lucy broke up with him because he forced her into uncomfortable situations like this one. Raj agrees that he can be insensitive about other people's boundaries. Claire broke up with him because she found him extremely needy and vain. Raj then makes a new rule of only one comment per girlfriend. Emily is not comfortable with sharing details about their relationship in front of Howard. It is implied that she had problems with him in bed. Raj told Howard to leave, though he didn't. Amy has made dinner and calls it beef loaf because Sheldon is unhappy with the non-specificity of meat loaf. Sheldon is not happy with the device. He has always had problems recognizing people's emotions, but the device made it so much more real. Sheldon admits that Amy is something of a sad sack, but he loves her just the way she is.

Twenty years after The Society of Mind, where he introduced the concept that "minds are what brains do," Minsky probes deeper into the question of natural intelligence. Don't look for simple explanations: he believes "we need to find more complicated ways to explain our most familiar mental events"; we need to break our thought processes down into the most precise steps possible. In fact, in order to truly understand the human mind, Minsky suggests, we'll probably need to reverse-engineer a machine that can replicate those functions so we can study it. Thus, he rejects the idea of consciousness as a unitary "Self" in favor of "a decentralized cloud" of more than 20 distinct mental processes. In this view, emotional states like love and shame are not the opposite of rational cogitation; both, Minsky says, are ways of thinking. This is not a book to be read casually; Minsky builds his argument with constant reference to earlier and later sections, imagining objections from a variety of philosophical positions and refuting them. A steady stream of diagrams helps clarify matters, but readers will be forced to dig for the "aha!" moments: they're worth the effort. 100 b&w illus. (Nov. 7)

Writers about the human mind generally fall into three camps: philosophers, psychologists and others who weave elaborate theories about the mind without any reference to the brain; neuroscientists who attempt to link mind matters with brain states; and, finally, members of the computer science and artificial intelligence (AI) communities who suggest that it's possible to replicate human thinking in a machine. Marvin Minsky, professor of electrical engineering and computer science at the Massachusetts Institute of Technology and an early pioneer in developing artificial intelligence, is an eminent denizen of the third camp.

Minsky does a marvelous job parsing other complicated mental activities into simpler elements. He discusses such topics as common sense, thinking and the self and -- most important for this book -- emotional states, which are "not especially different from the processes that we call 'thinking.' "

But he is less effective in relating these emotional functions to what's going on in the brain. Minsky says his book "does not discuss most current beliefs about how our brains work" because our knowledge about the brain soon becomes outdated. But then how can one draw meaningful correlations between brains and machines? 041b061a72


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