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Top news of the week: 09.12.2021.

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@weballergy shared
On Dec 7, 2021
RT @AlexLavin_C137: "Simulation Intelligence" is the merger of scientific computing, simulation, and AI to broaden the scientific method for the machine age. https://t.co/jkmfmfS06b https://t.co/n2Yd45YzRE
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Simulation Intelligence: Towards a New Generation of Scientific Methods

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and ...

@RichardSocher shared
On Dec 6, 2021
RT @BruceQBurke: Advertising & SEO biases of current search engines result in a lack of control over what people read watch research eat & buy. This makes people an object of artificial intelligence algorithms designed to monetize them rather than utilizing technology … https://t.co/juvvzj1C2z
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Will Google ever lose its throne as king of search? You.com is betting on it

Will Google ever lose its throne as king of search? You.com is betting on it

Dozens of companies have tried to disrupt Google's search dominance, and none have really succeeded -- but You.com thinks it has an approach that could work.

@AlisonBLowndes shared
On Dec 7, 2021
RT @ZetaVector: Read our comments on this selection and more interesting papers on our blog https://t.co/kGNMLneBbg
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NeurIPS 2021 — 10 papers you shouldn't miss

NeurIPS 2021 — 10 papers you shouldn't miss

2334 papers, 60 workshops, 8 keynote speakers, 15k+ attendees. A dense landscape that's hard to navigate without a good guide and map, so here are some of our ideas! The 2021 edition of the ...

@hugo_larochelle shared
On Dec 7, 2021
RT @CIFAR_News: Composer turned ML researcher Cheng-Zhi Anna Huang @huangcza (@Mila_Quebec, @GoogleAI) takes a human-centered approach to ML & creativity, expanding artists' creative reach. Huang also helped create Google’s 1st AI Doodle, the “Bach Doodle”. https://t.co/WpRVZLYL4A
Open
CIFAR and Mila name five new Canada CIFAR AI Chairs

CIFAR and Mila name five new Canada CIFAR AI Chairs

Five talented individuals will receive long-term, dedicated funding to support their research and help them train the next generation of AI leaders.

@mxlearn shared
On Dec 7, 2021
[R] UC Berkeley’s Sergey Levine Says Combining Self-Supervised and Offline RL Could Enable Algorithms That Understand the World Through Actions https://t.co/eRSJKZgFrG
Open
[R] UC Berkeley’s Sergey Levine Says Combining Self-Supervised and Offline RL Could Enable Algorithms That Understand the World Through Actions

[R] UC Berkeley’s Sergey Levine Says Combining Self-Supervised and Offline RL Could Enable Algorithms That Understand the World Through Actions

0 votes and 0 comments so far on Reddit

@NandoDF shared
On Dec 7, 2021
RT @vincesitzmann: Our NeurIPS spotlight on using neural light fields instead of 3D neural fields for scene representation has been covered by MIT news! Neural light fields allow rendering without ray-marching. IMO, light fields are the way to go for learning at scale! https://t.co/0vTd4SeAV6
Open
Technique enables real-time rendering of scenes in 3D

Technique enables real-time rendering of scenes in 3D

Researchers at MIT and elsewhere have demonstrated a novel technique that vastly increases the speed of rendering 3D scenes from images by using a neural network to reconstruct the ...

@demishassabis shared
On Dec 8, 2021
RT @Lifrordi: Introducing Player of Games - general and sound search algorithm that combines game theoretic reasoning and reinforcement learning. PoG learns to play both perfect and imperfect information games while bringing new SOTA result in the game of Scotland Yard https://t.co/rK74uZe2uD
Open
Player of Games

Player of Games

Games have a long history of serving as a benchmark for progress in artificial intelligence. Recently, approaches using search and learning have shown strong performance across a set of ...

@MSFTResearch shared
On Dec 6, 2021
Current benchmarks may yield imprecise readings of AI models’ natural language understanding. Two new NLU benchmarks aim for more accurate evaluations. #NeurIPS2021 https://t.co/H69vYbYrFc
Open
You get what you measure: New NLU benchmarks for few-shot learning and robustness evaluation

You get what you measure: New NLU benchmarks for few-shot learning and robustness evaluation

Recent progress in natural language understanding (NLU) has been driven in part by the availability of large-scale benchmarks that provide an environment for researchers to test and measure ...

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