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@
DeepMind
London, UK
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We research and build safe AI systems that learn how to solve problems and advance scientific discovery for all. Explore our work: deepmind.com
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1.124
Tweetovi
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116
Pratim
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281.111
Osobe koje vas prate
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DeepMind
@DeepMind
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8 h |
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"One of the things I really like about this article is how it integrates work from the fields of artificial intelligence, psychology, neuroscience, and evolutionary theory."
@TrendsCognSci editor @LindseyDrayton, picks Reinforcement Learning, Fast and Slow as her review of 2019 twitter.com/CellPressNews/…
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DeepMind
@DeepMind
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13 h |
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Congratulations to @wsisaac @m_c_elish and Rich Zemel on being named as co-general Chairs for the ACM Conference on Fairness, Accountability and Transparency for 2021 #FAccT2021 twitter.com/m_c_elish/stat…
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Demis Hassabis
@demishassabis
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2. velj |
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Enjoyed this @NewInChess review on how #AlphaZero has influenced the phenomenal World Chess Champion @MagnusCarlsen, by his coach, the brilliant @PHChess
It has loads of illustrative games from his incredible unbeaten run in 2019!
newinchess.com/media/wysiwyg/… pic.twitter.com/eeyJFOLIqd
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Cambridge Computer Science
@Cambridge_CL
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29. sij |
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Our @DeepMind Scholars for 2019/20 reveal their aims for the future and what motivated them to study the Cambridge MPhil in Advanced Computer Science: ow.ly/KUAN50y7Xp3
#AI #ComputerScience pic.twitter.com/IlYRaw4Pui
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DeepMind
@DeepMind
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29. sij |
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‘Mapping the future’: our recent paper, which provides insight into previously unexplained elements of dopamine-based learning in the brain, is on the front cover of @Nature! 🎉
Read the blog: deepmind.com/blog/article/D… twitter.com/nature/status/…
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DeepMind
@DeepMind
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28. sij |
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In “Artificial Intelligence, Values and Alignment” DeepMind’s @IasonGabriel explores approaches to aligning AI with a wide range of human values: deepmind.com/research/publi… pic.twitter.com/Zo81PSpwyF
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DeepMind
@DeepMind
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23. sij |
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Q-learning is difficult to apply when the number of available actions is large. We show that a simple extension based on amortized stochastic search allows Q-learning to scale to high-dimensional discrete, continuous or hybrid action spaces: arxiv.org/abs/2001.08116
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Partnership on AI
@PartnershipAI
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23. sij |
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With the support of @DeepMind, the Partnership on AI is seeking a Diversity and Inclusion Fellow. This Fellow will design and lead a research project that will yield novel knowledge to increase diversity and inclusion in the AI industry: app.trinethire.com/companies/2365…
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DeepMind
@DeepMind
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21. sij |
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We're recording the entire series and will share it online so everyone can watch. The first lecture kicks off on Monday 3 February with an Introduction to Machine Learning and AI by @ThoreG. See you there! 👋
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DeepMind
@DeepMind
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21. sij |
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🚨New lecture series🚨 We've teamed up with @ai_ucl to bring you the #UCLxDeepMind Deep Learning Lecture Series: 12 lectures covering a range of topics in Deep Learning - all led by DeepMind researchers, all free, and all open to everyone. Info & tickets: eventbrite.co.uk/o/ucl-x-deepmi…
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DeepMind
@DeepMind
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20. sij |
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Given the smoothness of videos, can we learn models more efficiently than with #backprop? We present Sideways - a step towards a high-throughput, approximate backprop that considers the one-way direction of time and pipelines forward and backward passes. arxiv.org/pdf/2001.06232… pic.twitter.com/evbwULE0s2
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DeepMind
@DeepMind
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20. sij |
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DeepMind
@DeepMind
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16. sij |
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How can we predict and control the collective behaviour of artificial agents? Classical game theory isn't much help when there are >2 agents. In our @iclr_conf paper, we find markets impose useful structure on interactions between gradient-based learners: arxiv.org/abs/2001.04678 pic.twitter.com/IeLMcb9f2z
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DeepMind
@DeepMind
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16. sij |
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Read our @nature paper "A distributional code for value in dopamine-based reinforcement learning" online here: rdcu.be/b0mtA
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DeepMind
@DeepMind
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16. sij |
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Read our @nature paper 'Improved protein structure prediction using potentials from deep learning' online here: rdcu.be/b0mtx
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DeepMind
@DeepMind
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15. sij |
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We worked with @harvardbrainsci to show that distributional RL, a recent development in AI research, can provide insight into previously unexplained elements of dopamine-based learning in the brain.
Read the blog: deepmind.com/blog/article/D… (2/2)
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DeepMind
@DeepMind
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15. sij |
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More exciting @Nature news today: an example of how AI and neuroscience continue to propel each other forward. (1/2) pic.twitter.com/ba6ZWjF95o
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DeepMind
@DeepMind
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15. sij |
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While we’re excited by these results, there is still much more we need to understand. We’d like to thank the organisers of CASP13 & the experimentalists whose structures enabled the assessment & we look forward to taking this work forward with the protein folding community. 4/4
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DeepMind
@DeepMind
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15. sij |
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Predicting how these chains will fold into the structure of a protein - the “protein folding problem” - is fundamental to understanding its role within the body and could one day enable scientists to target & design new, effective cures for diseases. 3/4
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DeepMind
@DeepMind
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15. sij |
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Proteins are the building blocks of biology. They start off as a string of amino acids that fold into intricate 3D structures. Knowing the 3D structure helps us understand their function, but predicting such structures is an unsolved question in science. 2/4 pic.twitter.com/1meRwkYKFI
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