Deep Learning London

People platform to discuss and share, research, ideas, #deeplearning methods and applications. Open community initiative organized by @persontyle and @nvidia

[Google DeepMind @GoogleDeepMind]

Arnheim - a generative algorithm for producing pictures made with grammatical brushstrokes.

Interested in trying it out? Type in the title of the picture you want and play around with the code to modify how brushstrokes are generated: https://t.co/iz7C86CQbs 1/

[Zoubin Ghahramani @ZoubinGhahrama1]

I completely agree with the arguments in this article and it’s something I’ve said in many of my talks: we need to move the narrative away from AI as imitating humans and focus on Useful Machine Intelligence that complements humans and provides value to society.

[AI at Meta @AIatMeta]

We built & open sourced the first-ever multilingual model to win the prestigious WMT competition, showing this approach is the future of machine translation. One-model-for-many-languages is simpler, more scalable, and can help deliver better translations. https://t.co/USvdJesWHg

[Deep Learning London @deeplearningldn]

Happy 6th birthday #TensorFlow 🎂

Learn how you can get started → https://t.co/vwWzmJBKzl h

[Deep Learning London @deeplearningldn]

Yann LeCun’s Deep Learning Course at CDS
https://t.co/ahv2lVD18f

[AI at Meta @AIatMeta]

What if you could create virtual boxing athletes that could automatically develop a winning strategy? We released a #deeplearning framework at #SIGGRAPH2021 that generates control policies for two-player sports where the players are simulated. Learn more: https://t.co/wxlkdN0BD0

[Kyunghyun Cho @kchonyc]

https://t.co/kmqKgvbxI3

A Lecture on NLP from Big Ideas in Artificial Intelligence (https://t.co/HkQ1i1Q83B): This is the NLP section of the course organized by NYU in Spring 2021. These are preliminary recordings which were edited and polished for the final versions.

[Martin O'Leary @mewo2]

Continuing to mess around with text-to-image GANs, thought about doing a tarot deck, then thought about doing some 70s scifi novel covers, then decided to combine the two.

[Microsoft Research @MSFTResearch]

Learn more about this neural network engine project that captures human decisions and playing style for the game of chess. #MicrosoftAI

[Google AI @GoogleAI]

While cochlear implants improve the listening experience for many people who are hard of hearing, they can be less effective in noisy environments. Learn how an #ML-based preprocessor can be used to suppress noise, leading to enhanced speech understanding. https://t.co/BCZAThTZ2g

[New Scientist @newscientist]

UK-based AI company DeepMind has mapped the structure of 98.5 per cent of the 20,000 or so proteins in the human body, and made the data freely available https://t.co/DVPo6Z73CM

[EMBL @embl]

EMBL and @DeepMind have partnered – a breakthrough for science.

Together, we're providing a treasure trove of protein structure predictions powered by #AlphaFold to herald a new era for #AI-enabled biology.

https://t.co/QSM55eB2Fk

[Balaji Lakshminarayanan @balajiln]

1/n Attending #ICML2021?

Join us for our workshop on "Uncertainty and Robustness in Deep Learning" @icmlconf this Friday (July 23) 9am-5pm ET!

ICML link: https://t.co/bQnfKaE19p

Co-organized w/ @hendrycks @SharonYixuanLi @latentjasper @tdietterich @csilviavr @sebnowozin

[Google DeepMind @GoogleDeepMind]

Today with @emblebi, we're launching the #AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome, doubling humanity’s accumulated knowledge of high-accuracy human protein structures - for free: https://t.co/vtBGmTkKhy 1/

[Andrej Karpathy @karpathy]

Gave a talk at CVPR over the weekend on our recent work at Tesla Autopilot to estimate very accurate depth, velocity, acceleration with neural nets from vision. Necessary ingredients include: 1M car fleet data engine, strong AI team and a Supercomputer https://t.co/osmEEgkgtL

[Deep Learning London @deeplearningldn]

Dive deep into self-supervised learning with Dr. Ishan Misra @imisra_ from FAIR @facebookai

https://t.co/Zlqr1VYayi

[Demis Hassabis @demishassabis]

Brief update on some exciting progress on #AlphaFold! We’ve been heads down working flat out on our full methods paper (currently under review) with accompanying open source code and on providing broad free access to AlphaFold for the scientific community. More very soon!

[AI at Meta @AIatMeta]

Today we are #open-sourcing FLORES-101, a many-to-many evaluation data set covering 101 languages from all over the world. Our goal is helping empower researchers to create more diverse (and locally relevant) translation tools — learn more: https://t.co/oKWly6C1Jh

[François Chollet @fchollet]

If you're currently reading the advance preview of Deep Learning with Python, 2nd edition: I just uploaded the new set of companion notebooks to GitHub. https://t.co/QXQOV2YJ6g