Intro to Bioinformatics November 2023 topics: Intro to AI what is AI Weak and Strong AI Philosophy of mind AI and Logic History of AI ELIZA Expert system CYC Rise of connectionism Perceptron Modern AI Optimization Natural Language Processing Computer Vision Machine Learning Generative AI Philosophy of mind https://en.wikipedia.org/wiki/Philosophy_of_mind from Wikipedia " Philosophy of mind is a branch of philosophy that studies the ontology and nature of the mind and its relationship with the body. The mind–body problem is a paradigmatic issue in philosophy of mind, although a number of other issues are addressed, such as the hard problem of consciousness and the nature of particular mental states. Aspects of the mind that are studied include mental events, mental functions, mental properties, consciousness and its neural correlates, the ontology of the mind, the nature of cognition and of thought, and the relationship of the mind to the body." Can machines think? https://philpapers.org/browse/can-machines-think Turing test Chinese room problem Cheniese room argument https://en.wikipedia.org/wiki/Chinese_room " The Chinese room argument holds that a digital computer executing a program cannot have a "mind", "understanding", or "consciousness",[a] regardless of how intelligently or human-like the program may make the computer behave. The argument was presented by philosopher John Searle in his paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980. Similar arguments were presented by Gottfried Leibniz (1714), Anatoly Dneprov (1961), Lawrence Davis (1974) and Ned Block (1978). Searle's version has been widely discussed in the years since. The centerpiece of Searle's argument is a thought experiment known as the Chinese room. The argument is directed against the philosophical positions of functionalism and computationalism which hold that the mind may be viewed as an information-processing system operating on formal symbols, and that simulation of a given mental state is sufficient for its presence. Specifically, the argument is intended to refute a position Searle calls the strong AI hypothesis: "The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds." " ELIZA https://en.wikipedia.org/wiki/ELIZA Expert System Rule based Find out about C If B, then C (rule 1) if A, then B (rule 2) ------------ conclusion: If A, then C Question: Is A true? (data) MYCIN https://en.wikipedia.org/wiki/Mycin Textbook (one chapter) https://people.dbmi.columbia.edu/~ehs7001/Buchanan-Shortliffe-1984/Chapter-01.pdf from wikipedia " MYCIN was an early backward chaining expert system that used artificial intelligence to identify bacteria causing severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the dosage adjusted for patient's body weight — the name derived from the antibiotics themselves, as many antibiotics have the suffix "-mycin". The Mycin system was also used for the diagnosis of blood clotting diseases. MYCIN was developed over five or six years in the early 1970s at Stanford University. It was written in Lisp as the doctoral dissertation of Edward Shortliffe under the direction of Bruce G. Buchanan, Stanley N. Cohen and others." EMYCIN https://link.springer.com/chapter/10.1007/978-3-642-96868-6_66 Perceptron https://en.wikipedia.org/wiki/Perceptron " In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector. " CYC https://en.wikipedia.org/wiki/Cyc " Cyc is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge that other AI platforms may take for granted. This is contrasted with facts one might find somewhere on the internet or retrieve via a search engine or Wikipedia. Cyc enables semantic reasoners to perform human-like reasoning and be less "brittle" when confronted with novel situations. Douglas Lenat began the project in July 1984 at MCC, where he was Principal Scientist 1984–1994, and then, since January 1995, has been under active development by the Cycorp company, where he was the CEO." Generative AI simple description https://techsauce.co/saucy-thoughts/what-is-generative-ai-and-how-it-changing-possibility https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai Generative adversarial network https://en.wikipedia.org/wiki/Generative_adversarial_network GAN from Wikipedia " A generative adversarial network (GAN) is a class of machine learning framework and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set. For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning, GANs have also proved useful for semi-supervised learning, fully supervised learning, and reinforcement learning. " Generate more data from existing data