we have a system that um that we developed that you can go to this website and basically it will just very simply translate papers in neuroscience into developmental biology papers. It's very easy. You just swap a few words and and and everything carries over. There are deep deep symmetries between cognition and morphagenesis which um I think Alan Turing for example recognized

less well known is that the same person was really 00:01:02 interested in morphogenesis

Turing & The Halting Problem

Educators are now administering the Turing test in reverse: What are questions that only humans can answer well? What kinds of thinking does writing make possible for us? 

The original question, ‘Can machines think?’ I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.

You are all computer scientists. You know what FINITE AUTOMATA can do. You know what TURING MACHINES can do. For example, Finite Automata can add but not multiply. Turing Machines can compute any computable function. Turing machines are incredibly more powerful than Finite Automata. Yet the only difference between a FA and a TM is that the TM, unlike the FA, has paper and pencil. Think about it. It tells you something about the power of writing. Without writing, you are reduced to a finite automaton. With writing you have the extraordinary power of a Turing machine.

In fact,Descartes argued that the only sure indication that another body possesses ahuman mind, that it is not a mere automaton, is its ability to use language inthe normal way;

Introduction

Here, the card index func-tions as a ‘thinking machine’,67 and becomes the best communication partner for learned men.68

This comparison is not to claim that the index catalog is already a Turing machine. Comparisons, transfers, and analogies are not that simple. If the elements of a universal discrete machine are present, they still lack the computational logic of an operating system, the development of which constitutes Turing ’ s foundational achievement. What is described here is merely the fact that the card catalog is liter-ally a paper machine, similar to a nontrivial Turing machine only in having similar components — no more, no less.

s Alan Turing proved only years later, these machines merely need (1) a (theoretically infi nite) partitioned paper tape, (2) a writing and reading head, and (3) an exact

Turing-teszt

A neural network with a hidden layer has universality: given enough hidden units, it can approximate any function. This is a frequently quoted – and even more frequently, misunderstood and applied – theorem. It’s true, essentially, because the hidden layer can be used as a lookup table.

We show that BigBird is a universal approximator of sequence functions and is Turing complete,

Turing was an exceptional mathematician with a peculiar and fascinating personality and yet he remains largely unknown. In fact, he might be considered the father of the von Neumann architecture computer and the pioneer of Artificial Intelligence. And all thanks to his machines; both those that Church called “Turing machines” and the a-, c-, o-, unorganized- and p-machines, which gave rise to evolutionary computations and genetic programming as well as connectionism and learning. This paper looks at all of these and at why he is such an often overlooked and misunderstood figure.

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mixing the turing complete of javascript with the markup of HTML eliminates the readability of JSX so that it is actually harder to parse than a solution like hyperscript

A program somewhat controlling it's own flow. That's the key feature that makes a programming language Turing complete.

Here is how you could emulate an if-else-block:

A programming language is Turing complete if you can implement any possible algorithm with it.

Because templates are not Turing-complete, and if they were, they would require vDOM.

At the moment, GPT-2 uses a binary search algorithm, which means that its output can be considered a ‘true’ set of rules. If OpenAI is right, it could eventually generate a Turing complete program, a self-improving machine that can learn (and then improve) itself from the data it encounters. And that would make OpenAI a threat to IBM’s own goals of machine learning and AI, as it could essentially make better than even humans the best possible model that the future machines can use to improve their systems. However, there’s a catch: not just any new AI will do, but a specific type; one that uses deep learning to learn the rules, algorithms, and data necessary to run the machine to any given level of AI.

Player A's role is to trick the interrogator into making the wrong decision, while player B attempts to assist the interrogator in making the right one.

Like many other AI practitioners, I’m a philosophical functionalist: I believe that a cognitive state, such as one derived from reading, should not be defined by what it is made of in terms of hardware or biology, but instead by how it functions, in relation to inputs, outputs and other cognitive states. (Opponents of functionalism include behaviourists – who insist that mental states are nothing other than dispositions to behave in certain ways – and mind-brain identity theorists – who argue that mental states are identical with particular neural states, and are tied to specific biological ‘hardware’.)

référants

des contenus déjà présents sur le web

Il en appelait à des « oracles » : With the help of the oracle we could form a new kind of machine (call them o-machines), having as one of its fundamental processes that of solving a given number-theoretic problem. (Turing, 1939 : 161)

Nearly all ap­pli­ca­tions of prob­a­bil­ity to cryp­tog­ra­phy de­pend on the fac­tor prin­ci­ple (or Bayes’ The­o­rem).

Dr. Lamport received a doctorate in mathematics from Brandeis University, with a dissertation on singularities in analytic partial differential equations. This, together with a complete lack of education in computer science, prepared him for a career as a computer scientist at Massachusetts Computer Associates, SRI, Digital, and Compaq. He claims that it is through no fault of his that of those four corporations, only the one that was supposed to be non-profit still exists. He joined Microsoft in 2001, but that company has not yet succumbed. Dr. Lamport's initial research in concurrent algorithms made him well-known as the author of LaTeX, a document formatting system for the ever-diminishing class of people who write formulas instead of drawing pictures. He is also known for writing A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable. which established him as an expert on distributed systems. His interest in Mediterranean history, including research on Byzantine generals and the mythical Greek island of Paxos, led to his receiving five honorary doctorates from European universities, and to the IEEE sending him to Italy to receive its 2004 Piore Award and to Quebec to receive its 2008 von Neumann medal. However, he has always returned to his home in California. This display of patriotism was rewarded with membership in the National Academy of Engineering, the National Academy of Sciences, and the American Academy of Arts and Sciences. More recently, Dr. Lamport has been annoying computer scientists and engineers by urging them to understand an algorithm or system before implementing it, and scaring them by saying they should use mathematics. In an attempt to get him to talk about other things, the ACM gave him the 2013 Turing Award.