This page will give the readers some idea about the various technologies that I think that are involved in making this a possibility.
A good starting point is Tom Mitchell’s classic text book Machine Learning. If you are just starting or if scalability is not a big issue in the machine learning tasks that you are interested in then Weka, which is written in Java, is a great software. For folks who use R, R-Bloggers has compiled a list of tutorials for machine learning for R programmers. Also checkout Scikit Learn for Python.
A background in computer science and programming is of course quite helpful. The go to resource for beginners for Deep Learning is the Deep Learning book by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Even if you are not a beginner, it is still a good resource to have. My choice for large scale machine learning tasks as well as for deep learning is TensorFlow. If you are new to the Machine learning area and also interested in using TensorFlow then the ideal place to start is this tutorial from the folks at TensorFlow.
Natural Language Processing (NLP)
From Siri to Echo natural language processing has become part and parcel of our everyday life. If you are looking for an online resource that guides you step by step in learning about NLP then one of the best places to start is the Natural Language Processing for Python book, known as the NLTK book, by Steven Bird, Ewan Klein, and Edward Loper. Hidden Markov Models (HMM) are extensively used in NLP. A good place to start is An Introduction to HMM-Based Speech Synthesis by Junichi Yamagishi. It may also be the case that at least for certain speech processing tasks Deep Learning may be as effective as, if not more, techniques based on HMM.
Human Computer Interaction
Since this is not really my area of expertise the resource that I mainly use to keep up with what’s going on is the Tech Reports from the HCI Institute at CMU. Especially for my purpose HCI for Kids by my Amy Bruckman, Alisa Bandlow, and Andrea Forte is quite relevant.
The Turing Test was formulated by Alan Turing in a seminal paper Computing Machinery and Intelligence 1950, it addresses the question how can one ascribe intelligence to a machine. The answer that it gives is that if a machine can fool people that it is a person then the machine is intelligent. There is a plethora of literature on the Turing Test with a number of objections and counter-objections to it, the most famous being the Chinese Room Experiment.
For the long term feasibility and relevance of this project virtual reality would be the ultimate venue to use. This is a relatively new area. Oculus Rift, HTC Vine and Microsoft are the big players in this area. Science Fiction has a long history of discussing the feasabilty, limitations and implications of virtual reality technologies going all the way back to Stanley G. Weinbaum‘s Pygmalion’s Spectacles in the 1930s.
Technology and Bereavement
There are already hundreds of thousands of people who are dead in the real world but whose online presence still lingers on. Facebook has already put in policies for handling a dead person’s account. There are already startups and companies that offer a variety of services for digital bereavement.
Last Updated: October 28, 2016