Alex Graves (computer Scientist)
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Alex Graves (computer Scientist)
Alex Graves was a research scientist at DeepMind. He did a BSc in Theoretical Physics at Edinburgh and obtained a PhD in AI under Jürgen Schmidhuber at IDSIA. He was also a postdoc under Jürgen Schmidhuber at TU Munich and under Geoffrey Hinton at the University of Toronto. At IDSIA, he trained long short-term memory neural networks by a novel method called connectionist temporal classification (CTC).Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376. This method outperformed traditional speech recognition models in certain applications.Santiago Fernandez, Alex Graves, and Jürgen Schmidhuber (2007). An application of recurrent neural networks to discriminative keyword spotting. Proceedings of ICANN (2), pp. 220–229. In 2009, his CTC-trained LSTM was the first recurrent neural network to win pattern recogn ...
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DeepMind
DeepMind Technologies is a British artificial intelligence subsidiary of Alphabet Inc. and research laboratory founded in 2010. DeepMind was acquired by Google in 2014 and became a wholly owned subsidiary of Alphabet Inc, after Google's restructuring in 2015. The company is based in London, with research centres in Canada, France, and the United States. DeepMind has created a neural network that learns how to play video games in a fashion similar to that of humans, as well as a Neural Turing machine, or a neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain. DeepMind made headlines in 2016 after its AlphaGo program beat a human professional Go player Lee Sedol, a world champion, in a five-game match, which was the subject of a documentary film. A more general program, AlphaZero, beat the most powerful programs playing go, chess and shogi (Japanese c ...
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Handwriting Recognition
Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. The image of the written text may be sensed "off line" from a piece of paper by optical scanning (optical character recognition) or intelligent word recognition. Alternatively, the movements of the pen tip may be sensed "on line", for example by a pen-based computer screen surface, a generally easier task as there are more clues available. A handwriting recognition system handles formatting, performs correct segmentation into characters, and finds the most plausible words. Offline recognition Offline handwriting recognition involves the automatic conversion of text in an image into letter codes that are usable within computer and text-processing applications. The data obtained by this form is regarded as a static representation ...
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Computer Scientists
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to practical disciplines (including the design and implementation of hardware and software). Computer science is generally considered an area of academic research and distinct from computer programming. Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing security vulnerabilities. Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of repositories of data. ...
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Artificial Intelligence Researchers
Artificiality (the state of being artificial or manmade) is the state of being the product of intentional human manufacture, rather than occurring naturally through processes not involving or requiring human activity. Connotations Artificiality often carries with it the implication of being false, counterfeit, or deceptive. The philosopher Aristotle wrote in his '' Rhetoric'': However, artificiality does not necessarily have a negative connotation, as it may also reflect the ability of humans to replicate forms or functions arising in nature, as with an artificial heart or artificial intelligence. Political scientist and artificial intelligence expert Herbert A. Simon observes that "some artificial things are imitations of things in nature, and the imitation may use either the same basic materials as those in the natural object or quite different materials. Herbert A. Simon, ''The Sciences of the Artificial'' (1996), p. 4. Simon distinguishes between the artificial and the sy ...
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Living People
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Differentiable Neural Computer
In artificial intelligence, a differentiable neural computer (DNC) is a memory augmented neural network architecture (MANN), which is typically (but not by definition) recurrent in its implementation. The model was published in 2016 by Alex Graves et al. of DeepMind. Applications DNC indirectly takes inspiration from Von-Neumann architecture, making it likely to outperform conventional architectures in tasks that are fundamentally algorithmic that cannot be learned by finding a decision boundary. So far, DNCs have been demonstrated to handle only relatively simple tasks, which can be solved using conventional programming. But DNCs don't need to be programmed for each problem, but can instead be trained. This attention span allows the user to feed complex data structures such as graphs sequentially, and recall them for later use. Furthermore, they can learn aspects of symbolic reasoning and apply it to working memory. The researchers who published the method see promise that ...
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Neural Turing Machine
A Neural Turing machine (NTM) is a recurrent neural network model of a Turing machine. The approach was published by Alex Graves et al. in 2014. NTMs combine the fuzzy pattern matching capabilities of neural networks with the algorithmic power of programmable computers. An NTM has a neural network controller coupled to external memory resources, which it interacts with through attentional mechanisms. The memory interactions are differentiable end-to-end, making it possible to optimize them using gradient descent. An NTM with a long short-term memory (LSTM) network controller can infer simple algorithms such as copying, sorting, and associative recall from examples alone. The authors of the original NTM paper did not publish their source code. The first stable open-source implementation was published in 2018 at the 27th International Conference on Artificial Neural Networks, receiving a best-paper award. Other open source implementations of NTMs exist but as of 2018 they are n ...
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Smartphone
A smartphone is a portable computer device that combines mobile telephone and computing functions into one unit. They are distinguished from feature phones by their stronger hardware capabilities and extensive mobile operating systems, which facilitate wider software, internet (including web browsing over mobile broadband), and multimedia functionality (including music, video, cameras, and gaming), alongside core phone functions such as voice calls and text messaging. Smartphones typically contain a number of metal–oxide–semiconductor (MOS) integrated circuit (IC) chips, include various sensors that can be leveraged by pre-included and third-party software (such as a magnetometer, proximity sensors, barometer, gyroscope, accelerometer and more), and support wireless communications protocols (such as Bluetooth, Wi-Fi, or satellite navigation). Early smartphones were marketed primarily towards the enterprise market, attempting to bridge the functionality of ...
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Google
Google LLC () is an American Multinational corporation, multinational technology company focusing on Search Engine, search engine technology, online advertising, cloud computing, software, computer software, quantum computing, e-commerce, artificial intelligence, and Computer hardware, consumer electronics. It has been referred to as "the most powerful company in the world" and one of the world's List of most valuable brands, most valuable brands due to its market dominance, data collection, and technological advantages in the area of artificial intelligence. Its parent company Alphabet Inc., Alphabet is considered one of the Big Tech, Big Five American information technology companies, alongside Amazon (company), Amazon, Apple Inc., Apple, Meta Platforms, Meta, and Microsoft. Google was founded on September 4, 1998, by Larry Page and Sergey Brin while they were Doctor of Philosophy, PhD students at Stanford University in California. Together they own about 14% of its publicl ...
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Recurrent Neural Network
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replaced ...
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Jürgen Schmidhuber
Jürgen Schmidhuber (born 17 January 1963) is a German computer scientist most noted for his work in the field of artificial intelligence, deep learning and artificial neural networks. He is a co-director of the Dalle Molle Institute for Artificial Intelligence Research in Lugano, in Ticino in southern Switzerland. Following Google Scholar, from 2016 to 2021 he has received more than 100,000 scientific citations. He has been referred to as "father of modern AI," "father of AI," "dad of mature AI," "Papa" of famous AI products, "Godfather," and "father of deep learning." (Schmidhuber himself, however, has called Alexey Grigorevich Ivakhnenko the "father of deep learning.") Schmidhuber completed his undergraduate (1987) and PhD (1991) studies at the Technical University of Munich in Munich, Germany. His PhD advisors were Wilfried Brauer and Klaus Schulten. He taught there from 2004 until 2009 when he became a professor of artificial intelligence at the Università della Sv ...
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Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognitio ...
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