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Deep learning is a subset of machine learning methods based on neural networks with representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the newer umbrella of Google AI, a research division at Google dedicated to artificial intelligence. Formed in 2011, it combined open-ended machine learning research with information systems and large-scale computing resources. It created tools such as TensorFlow, which allow neural networks to be used by the public, and multiple internal AI research projects, and aimed to create research opportunities in machine learning and natural language processing. It was merged into former Google sister company DeepMind to form Google DeepMind in April 2023.
Google DeepMind Technologies Limited is a British-American artificial intelligence research laboratory which serves as a subsidiary of Google. Founded in the UK in 2010, it was acquired by Google in 2014 and merged with Google AI's Google Brain division to become Google DeepMind in April 2023. The company is based in London, with research centres in Canada, France, Germany, and the United States.
Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images.
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
David Silver is a principal research scientist at Google DeepMind and a professor at University College London. He has led research on reinforcement learning with AlphaGo, AlphaZero and co-lead on AlphaStar.
Ilya Sutskever is a Russian-Israeli computer scientist who specializes in machine learning.
Ian J. Goodfellow is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning. He is a research scientist at Google DeepMind, was previously employed as a research scientist at Google Brain and director of machine learning at Apple, and has made several important contributions to the field of deep learning, including the invention of the generative adversarial network (GAN). Goodfellow co-wrote, as the first author, the textbook Deep Learning (2016) and wrote the chapter on deep learning in the authoritative textbook of the field of artificial intelligence, Artificial Intelligence: A Modern Approach.
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AlphaStar is a computer program by DeepMind that plays the video game StarCraft II. It was unveiled to the public by name in January 2019. In a significant milestone for artificial intelligence, AlphaStar attained Grandmaster status in August 2019.
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Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry. While some of the computational implementations ANNs relate to earlier discoveries in mathematics, the first implementation of ANNs was by psychologist Frank Rosenblatt, who developed the perceptron. Little research was conducted on ANNs in the 1970s and 1980s, with the AAAI calling that period an "AI winter".
A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". Text is converted to numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. At each layer, each token is then contextualized within the scope of the context window with other (unmasked) tokens via a parallel multi-head attention mechanism allowing the signal for key tokens to be amplified and less important tokens to be diminished.
Seq2seq is a family of machine learning approaches used for natural language processing. Applications include language translation, image captioning, conversational models, and text summarization. Seq2seq uses sequence transformation: it turns one sequence into another sequence.
Samy Bengio is a Canadian computer scientist, Senior Director of AI and Machine Learning Research at Apple, and a former long-time scientist at Google known for leading a large group of researchers working in machine learning including adversarial settings. Bengio left Google shortly after the company fired his report, Timnit Gebru, without first notifying him. At the time, Bengio said that he had been "stunned" by what happened to Gebru. He is also among the three authors who developed Torch in 2002, the ancestor of PyTorch, one of today's two largest machine learning frameworks.
Chelsea Finn is an American computer scientist and assistant professor at Stanford University. Her research investigates intelligence through the interactions of robots, with the hope to create robotic systems that can learn how to learn. She is part of the Google Brain group.
Gato is a deep neural network for a range of complex tasks that exhibits multimodality. It can perform tasks such as engaging in a dialogue, playing video games, controlling a robot arm to stack blocks, and more. It was created by researchers at London-based AI firm DeepMind. It is a transformer, like GPT-3. According to MIT Technology Review, the system "learns multiple different tasks at the same time, which means it can switch between them without having to forget one skill before learning another" whereas "[t]he AI systems of today are called “narrow,” meaning they can only do a specific, restricted set of tasks such as generate text", and according to The Independent, it is a "'generalist agent' that can carry out a huge range of complex tasks, from stacking blocks to writing poetry". It uses supervised learning with 1.2B parameters. The technology has been described as "general purpose" artificial intelligence and a "step toward" artificial general intelligence.
Lê Viết Quốc, or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec and seq2seq models in natural language processing. Le also initiated and lead the AutoML initiative at Google Brain, including the proposal of neural architecture search.
Ashish Vaswani is a computer scientist working in deep learning, who is known for his significant contributions to the field of artificial intelligence (AI) and natural language processing (NLP). He is one of the co-authors of the seminal paper "Attention Is All You Need" which introduced the Transformer model, a novel architecture that uses a self-attention mechanism and has since become foundational to many state-of-the-art models in NLP. Transformer architecture is the core of language models that power applications such as ChatGPT. He was a co-founder of Adept AI Labs and a former staff research scientist at Google Brain.
Noam Shazeer is an American computer scientist and entrepreneur known for his contributions to the field of artificial intelligence and deep learning, particularly in the development of transformer models and natural language processing.
References
- ↑ Pascual, Manuel G. (2022-12-03). "Oriol Vinyals: "Nuestra generación verá una inteligencia artificial que iguale o supere a la del ser humano"". El País (in Spanish). Retrieved 2023-04-04.
- ↑ "Oriol Vinyals – Google Research". Google Research. Retrieved 2022-08-01.
- ↑ "9. Oriol Vinyals: Sequence-to-Sequence Machine Learning - The Future of Machine Intelligence [Book]". www.oreilly.com. Retrieved 2022-07-31.
- 1 2 Garro, Juan (17 March 2019). "Oriol Vinyals, el español detrás del último éxito de DeepMind: una IA capaz de arrollar a dos profesionales de Starcraft II". Xataka (in Spanish).
- ↑ Vinyals, Oriol (December 12, 2013). "Tech Reports | EECS at UC Berkeley". eecs.berkeley.edu.
- ↑ Sutskever, Ilya; Vinyals, Oriol; Le, Quoc V (2014). "Sequence to Sequence Learning with Neural Networks". Advances in Neural Information Processing Systems. 27. Curran Associates, Inc. arXiv: 1409.3215 .
- ↑ Vinyals, Oriol; Babuschkin, Igor; Czarnecki, Wojciech M.; Mathieu, Michaël; Dudzik, Andrew; Chung, Junyoung; Choi, David H.; Powell, Richard; Ewalds, Timo; Georgiev, Petko; Oh, Junhyuk (2019-11-14). "Grandmaster level in StarCraft II using multi-agent reinforcement learning". Nature. 575 (7782): 350–354. Bibcode:2019Natur.575..350V. doi:10.1038/s41586-019-1724-z. ISSN 0028-0836. PMID 31666705. S2CID 204972004.
- ↑ Pérez, Rocío (24 August 2016). "El ingeniero español elegido por el MIT entre los innovadores jóvenes del año". elconfidencial (in Spanish).
- ↑ "Oriol Vinyals". MIT Technology Review. Retrieved 2022-07-31.
- ↑ "DeepMind AI rivals average human competitive coder". BBC News. 2022-02-02. Retrieved 2023-04-04.
- ↑ Vincent, James (2022-02-02). "DeepMind says its new AI coding engine is as good as an average human programmer". The Verge. Retrieved 2023-04-04.
- ↑ Staff, Ars (2016-11-25). "Google DeepMind could invent the next generation of AI by playing Starcraft 2". Ars Technica. Retrieved 2023-04-04.
- ↑ "Google brain connects his StarCraft past with AI future". Financial Times. 2017-11-23. Retrieved 2023-04-04.
- ↑ Cai, Kenrick (August 22, 2024). "Google appoints former Character.AI founder as co-lead of its AI models". reuters.
