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40 Days of AI
Artificial intelligence (AI) used to be thought of as an idealistic technology that can only exist in sci-fi movies. Contrasting to the belief, today the technology has become so mature in a short tenure that all major companies are using it to their advantage. AI has become a major catalyst in driving the next revolution. The rate of progress in the field of artificial intelligence is exponentially increasing and impacting our lives like never before. From self-driving cars to robots replacing our jobs, everything seemed like a distant reality is within our vision.
7 Popular Data Science Presentations On SlideShare
Presentations are a go-to approach to introduce new ideas or explaining new techniques in technology with text and infographics to engage an audience and retain attention. Over the years, presentations have catered to the needs of people who want to learn new things or get an overview of something new. Notably, in data science, explaining approaches with speech becomes difficult. Thus, presentation through slides is an effective way to learn or revise technology. Analytics India Magazine brings to you exciting data science presentation that will give a new perspective as well as introduce you to new developments in the landscape.
Into the Future with Artificial Intelligence: Opportunities and Chall…
All our knowledge is about the past, but all our strategic decisions are about the future Conway 2003 What we don't know we don't know about the future What we know What we know we don't know 22. While 63% of CEOs believe AI will have a larger impact on the world than the internet,…. Boards overestimate their digital savviness 62% of boards report they are digitally savvy Source: MIT CISR 2014 Board Survey, 81 companies. Digital Savvy Boards - Higher performance • Companies with digitally savvy boards • 38% higher revenue growth • 34% higher ROA • 34% higher market growth • 3 digitally savvy directors required to impact performance Source: MIT Research 2018 26. A single tech savvy director in the boardroom risks being lonely and misunderstood.
Deep Learning Glossary. @nvidia #AI #DeepLearning #ArtificialIntelligence
The Deep Learning Glossary from NVIDIA The postulation of a principle of causality, "to every effect there is a cause," has been a continuing central problem for philosophy (Popper, 1972). Its role as a source of contention in modern science (Jauch, 1973) is epitomized by Einstein's remark that, "I can't believe that God plays dice." Many of the arguments about the application of the principle are very relevant to systems science and to problems of system identification and machine learning, on the one hand,and to epistemology and behavioural psychology, on the other. In current system science the theory of causal deterministic systems is most well developed and generally applied, while the theory of modeling with alternative structures, e.g., stochastic automata, indeterminate automata, products of asynchronous automata, etc., has not been developed to the same degree. Brian R. Gaines Hoy traemos a este espacio esta slideshare de NVidia, que nos presentan así: Learn the most important terminology from "A" to "Z" utilized in deep learning linked with resources for more in-depth exploration in our glossary.
Deep Learning - The Past, Present and Future of Artificial Intelligence. Slideshare @lukasmasuch Lukas Masuch
TwitterLinkedInGoogle Published on Dec 5, 2015, y que nos presentan así: In the last couple of years, deep learning techniques have transformed the world of artificial intelligence. One by one, the abilities and techniques that humans once imagined were uniquely our own have begun to fall to the onslaught of ever more powerful machines. Deep neural networks are now better than humans at tasks such as face recognition and object recognition. They've mastered the ancient game of Go and thrashed the best human players. "The pace of progress in artificial general intelligence is incredible fast" (Elon Musk – CEO Tesla & SpaceX) leading to an AI that "would be either the best or the worst thing ever to happen to humanity" (Stephen Hawking – Physicist).
Deep learning Malaysia presentation 12/4/2017
Once ordered alphabetically, each word can be referenced by its index, i.e. a, cat, chased, climbed, dog, saw, the, tree}. For this example, the neural network will have eight input neurons and eight output neurons. Let us assume that we decide to use three neurons in the hidden layer. This means that Winput and Woutput will be 8 3 and 3 8 matrices, respectively. Before training begins, these matrices are initialized to small random values as is usual in neural network training.