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Dec 9 • 4 tweets • 4 min read
Introducing Dramatron, a new tool for writers to co-write theatre and film scripts with a language model. 🎭

Dramatron can interactively co-create new stories complete with title, characters, location descriptions and dialogue.

Try it yourself now: dpmd.ai/dramatron-gith…
✏️ We interviewed 15 industry experts including playwrights, screenwriters and actors who produced work using Dramatron.

Canadian company @TheatreSports edited co-written theatre scripts and performed them on stage in Plays By Bots to positive reviews. dpmd.ai/dramatron-tw
Want to find out more? The team will be presenting this research at #NeurIPS2022:

📅 December 9
⌚ 3pm CST

dpmd.ai/3YbA0nK @ml4cdworkshop
Dramatron is the result of a collaboration from @MirowskiPiotr, @korymath, Jaylen Pittman, @juliettelove29 and Tara Thomas, based on a prototype by Richard Evans.

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More from @DeepMind

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Dec 8
In @ScienceMagazine, we present #AlphaCode - the first AI system to write computer programs at a human level in competitions.

It placed in the top 54% of participants in coding contests by solving new and complex problems.

How does it work? 🧵 dpmd.ai/alphacode-scie…
🔵 Previous AI systems don’t have the problem-solving skills needed to excel at coding competitions.

By combining advances in large-scale transformer models with large-scale sampling and filtering, #AlphaCode made significant progress in this field: dpmd.ai/alphacode-scie…
🔢 AlphaCode is pre-trained on selected public @GitHub code and fine-tuned on our relatively small competitive programming dataset.

At evaluation time, millions of diverse C++ and Python programs are created for each problem, orders of magnitude larger than previous work.
Read 8 tweets
DeepMind Profile picture
Dec 8
Introducing a generalist neural algorithmic learner, capable of carrying out 30 different reasoning tasks, with a 𝘴𝘪𝘯𝘨𝘭𝘦 graph network.

These include:
🔵 Sorting
🔵 Shortest paths
🔵 String matching
🔵 Convex hull finding

And more: dpmd.ai/3FC1FqA
What makes this the first-of-its-kind? 🤔

Similar to Gato, an AI agent capable of many tasks such as language modelling and image captioning, this model covers a diverse set of algorithm domains, matching single-task specialists' power - and remaining robust out-of-distribution.
Our team will present this work at @LogConference as a spotlight talk:
📅 9 December
⌚ 5.40pm GMT

Want to join us? Save your spot now: dpmd.ai/3FxKKFz
Read 4 tweets
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Dec 1
Introducing DeepNash - the first AI to master Stratego, a game of hidden information which is more complex than chess, Go and poker.

Published in @ScienceMagazine, it uses a novel model-free reinforcement learning algorithm.

Here's how it works. 🧵 dpmd.ai/deepnash-tw
🧩 Stratego is a game of imperfect information: players can't directly observe their opponent's pieces.

This makes it hard for other AI-based systems to go beyond amateur level. It also means that a successful technique called “game tree search” is not sufficiently scalable. Image
🟩 However, DeepNash’s technique approximates a Nash equilibrium, which makes it very hard for opponents to exploit its playing style.

As a result, it’s reached an all-time top-three ranking on Gravon, the world’s biggest online Stratego platform. dpmd.ai/deepnash-scien…
Read 6 tweets
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Oct 20
From helping transform the way we can predict wind power output to improving the performance of Document AI and giving wider access to #AlphaFold, we’re proud to partner with @GoogleCloud to bring our AI research into the real world.

Here’s how. 🧵
1️⃣ Industries aiming to use AI to read documents need lots of training data, which can be hard to find.

We helped develop machine learning models that need 50% less data to parse utility bills and purchase orders for @GoogleCloud Document AI users.
2️⃣ Wind farms are crucial to building a carbon-free future - but the weather makes it hard to predict.

With @GoogleCloud, we helped produce a Custom AI tool to better predict how much wind power could be generated - trained on forecasts and a customer’s historical turbine data.
Read 4 tweets
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Jul 14
Working together with @YouTube’s product and engineering teams, we've helped optimise the decision-making processes that increase safety, decrease latency, and enhance the viewer, creator, and advertiser experience for all.

How? A 🧵...

dpmd.ai/dm-youtube 1/
Our team developed a label quality model that helps label videos with greater precision according to @YouTube’s ad friendly guidelines, improving how videos are identified and classified. 2/
We applied #MuZero to improve the VP9 codec, a coding format that helps compress & transmit video over the internet. It was then applied to some of @YouTube’s live traffic - resulting in an avg. 4% bitrate reduction, helping reduce internet traffic, data usage & loading times. 3/
Read 4 tweets
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Apr 21
Recently the DeepMind Jax Ecosystem was joined by four new libraries: Mctx, KFAC-JAX, DM_AUX, and TF2JAX. See the thread 🧵 for more detail.

We hope that this fosters new research and applications in the ML community! 1/
Mctx provides AlphaZero and MuZero Monte Carlo tree search: dpmd.ai/mctx

Work by @fabiointheuk, Ivo Danihelka, @matteohessel, and @laurentsifre, with support from many others. 2/
KFAC-JAX is a library for second-order optimisation of neural networks, and for computing scalable curvature approximations (such as the one used in K-FAC): dpmd.ai/kfac-jax

Work by Aleksandar Botev and James Martens. 3/
Read 5 tweets

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