Artificial Intelligence

AI Research News

Discover the latest AI research & find out how AI, Machine Learning and advanced algorithms impact our lives, our jobs and the economy, all thanks to expert articles that include discussion on the potential, limits and consequences of AI.

Monthly report: October 2020

This month, The Essentials Report, has curated & analyzed the content published by 150 influencers like WIRED Science and Shakir Mohamed, discussing hashtags such as #AI , #NeurIPS2020 and #computervision.
Read our monthly report or learn more about Essentials.

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What matters to our readers VS what matters to the rest of the world in October 2020

Global Discussions Across the Web
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Popular with our readers

Best articles in October 2020

@kchonyc shared
On Oct 15, 2020
RT @vnfrombucharest: ⚠I am recruiting for a PhD position in ML for NLP⚠ Apply by Nov 19 here: https://t.co/en8idArRa9 Extra context on my website: https://t.co/eeTF9UYk01. DM or email if you have any questions.
Open

PhD position in Machine Learning for Natural Language Processing

PhD position in Machine Learning for Natural Language Processing

@kchonyc shared
On Oct 15, 2020
RT @vnfrombucharest: ⚠I am recruiting for a PhD position in ML for NLP⚠ Apply by Nov 19 here: https://t.co/en8idArRa9 Extra context on my website: https://t.co/eeTF9UYk01. DM or email if you have any questions.
Open
PhD position in Machine Learning for Natural Language Processing

PhD position in Machine Learning for Natural Language Processing

PhD position in Machine Learning for Natural Language Processing

@DeepMind shared
On Oct 12, 2020
How much can AI researchers learn from the field of animal cognition? Find out in a new @CellPressNews (Trends in Cognitive Sciences) paper: https://t.co/4v84d7v6aV Work by @mpshanahan & @BenBeyret, along with @MaCroPhilosophy of @imperialcollege & @LucyCheke of @Cambridge_Uni.
Open

Artificial Intelligence and the Common Sense of Animals

The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on …

@DeepMind shared
On Oct 12, 2020
How much can AI researchers learn from the field of animal cognition? Find out in a new @CellPressNews (Trends in Cognitive Sciences) paper: https://t.co/4v84d7v6aV Work by @mpshanahan & @BenBeyret, along with @MaCroPhilosophy of @imperialcollege & @LucyCheke of @Cambridge_Uni.
Open
Artificial Intelligence and the Common Sense of Animals

Artificial Intelligence and the Common Sense of Animals

The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on …

@dribnet shared
On Oct 5, 2020
RT @CSProfKGD: Excited to finally hang these awesome #AI @dribnet creations in my home office 😍 Intro to Tom’s #AIart https://t.co/eJYegZRaL2 Thank you to my former MSc @mtesfald for the amazing gift!!! https://t.co/glRRDEncTs
Open

Tom White is a New Zealand based artist investigating how machines see the world.

Collaborating with AI systems, White creates physical abstract prints that are reliably classified by neural networks. Selected AI projects by Tom White: White on using artificial intelligence: “My work focuses on how machines see the world. I have created a drawing system that allows ...

@dribnet shared
On Oct 5, 2020
RT @CSProfKGD: Excited to finally hang these awesome #AI @dribnet creations in my home office 😍 Intro to Tom’s #AIart https://t.co/eJYegZRaL2 Thank you to my former MSc @mtesfald for the amazing gift!!! https://t.co/glRRDEncTs
Open
Tom White is a New Zealand based artist investigating how machines see the world.

Tom White is a New Zealand based artist investigating how machines see the world.

Collaborating with AI systems, White creates physical abstract prints that are reliably classified by neural networks. Selected AI projects by Tom White: White on using artificial ...

@NandoDF shared
On Oct 31, 2020
RT @DeepMind: Excited to share #NeurIPS2020 papers on efficient and tight neural network verification, based on efficient solvers for LP and SDP relaxations. Implementations of these in JAX are also available as part of the new jax_verify library, described here: https://t.co/wh9fgit7w7 https://t.co/PTRpNhP898
Open

Efficient and tight neural network verification in JAX

Neural network verification is a powerful technology, offering the promise of provable guarantees on networks satisfying desirable input-output properties or specifications.

@NandoDF shared
On Oct 31, 2020
RT @DeepMind: Excited to share #NeurIPS2020 papers on efficient and tight neural network verification, based on efficient solvers for LP and SDP relaxations. Implementations of these in JAX are also available as part of the new jax_verify library, described here: https://t.co/wh9fgit7w7 https://t.co/PTRpNhP898
Open
Efficient and tight neural network verification in JAX

Efficient and tight neural network verification in JAX

Neural network verification is a powerful technology, offering the promise of provable guarantees on networks satisfying desirable input-output properties or specifications.

@NandoDF shared
On Oct 13, 2020
The Next Generation Of Artificial Intelligence: on self-supervised learning, federated learning and transformers https://t.co/NwCubzJcn8
Open

The Next Generation Of Artificial Intelligence

Five years from now, the field of AI will look very different than it does today.

@NandoDF shared
On Oct 13, 2020
The Next Generation Of Artificial Intelligence: on self-supervised learning, federated learning and transformers https://t.co/NwCubzJcn8
Open
The Next Generation Of Artificial Intelligence

The Next Generation Of Artificial Intelligence

Five years from now, the field of AI will look very different than it does today.

@peteskomoroch shared
On Oct 17, 2020
RT @xamat: "Less than one-shot learning" https://t.co/w0ci6OrQV7
Open

A radical new technique lets AI learn with practically no data

“Less than one”-shot learning can teach a model to identify more objects than the number of examples it is trained on.

@peteskomoroch shared
On Oct 17, 2020
RT @xamat: "Less than one-shot learning" https://t.co/w0ci6OrQV7
Open
A radical new technique lets AI learn with practically no data

A radical new technique lets AI learn with practically no data

“Less than one”-shot learning can teach a model to identify more objects than the number of examples it is trained on.

@NandoDF shared
On Oct 20, 2020
RT @suchisaria: AI/ML tweeps, here is a must read. It’s a wonderful article questioning whether we are spending our valuable brain cycles on the right research questions. If you disagree, I’d love to hear why. If you agree, what can be done to accelerate this? https://t.co/NO7TSubCex
Open

Too many AI researchers think real-world problems are not relevant

Any researcher who’s focused on applying machine learning to real-world problems has likely received a response like this one: “The authors present a solution for an original and highly motivating problem, but it is an application and the significance seems limited for the ...

@NandoDF shared
On Oct 20, 2020
RT @suchisaria: AI/ML tweeps, here is a must read. It’s a wonderful article questioning whether we are spending our valuable brain cycles on the right research questions. If you disagree, I’d love to hear why. If you agree, what can be done to accelerate this? https://t.co/NO7TSubCex
Open
Too many AI researchers think real-world problems are not relevant

Too many AI researchers think real-world problems are not relevant

Any researcher who’s focused on applying machine learning to real-world problems has likely received a response like this one: “The authors present a solution for an original and highly ...

@glouppe shared
On Oct 12, 2020
RT @WIREDScience: Improving batteries has always been hampered by slow experimentation and discovery processes. Machine learning is speeding it up by orders of magnitude. https://t.co/jNbThov7dE
Open

AI Is Throwing Battery Development Into Overdrive

Improving batteries has always been hampered by slow experimentation and discovery processes. Machine learning is speeding it up by orders of magnitude.

@glouppe shared
On Oct 12, 2020
RT @WIREDScience: Improving batteries has always been hampered by slow experimentation and discovery processes. Machine learning is speeding it up by orders of magnitude. https://t.co/jNbThov7dE
Open
AI Is Throwing Battery Development Into Overdrive

AI Is Throwing Battery Development Into Overdrive

Improving batteries has always been hampered by slow experimentation and discovery processes. Machine learning is speeding it up by orders of magnitude.

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Towards the Intelligent Machinery of Grace. Research Scientist @DeepMind. Strengthening African ML @DeepIndaba. He/Him. South African 🇿🇦🏳️‍🌈🌍

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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: https://t.co/UunulS3i0g

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I research intelligence to understand what we are, and to harness it wisely. I work at DeepMind and with CIFAR. Before, I was a UBC and Oxford professor.

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research scientist at google brain 🧠 香港人 🏴

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Machine Learning Advisor & Investor. Past: Co-Founder & CEO @SkipFlag (acquired 2018) | @Accel EIR | Data Science Leader @LinkedIn | ML @AOL @MIT

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On a quest to accelerate Science with #AI, or maybe the other way around? Professor @UniversiteLiege. Visiting scientist @CERN.

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Associate Professor of CS and DS at @nyuniversity & @CILVRatNYU pro bono office hours: https://t.co/CqzAsZcR82

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Cofounder-CTO @CuraiHQ. Former Quora VP Eng. Led ML algos at Netflix. ML, AI, eHealth, Recsys, Software. Catalan in the Valley. Long distance runner & Ironman.

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Machine learning PhD and AI enthusiast. Research engineer at DeepMind. Opinions are my own. Re-tweets and favorites not to be considered as endorsements.

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CEO, AIlen Institute for AI (AI2). Professor Emeritus, UW; Venture Partner, Madrona. https://t.co/TqO84WeA9I

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Data nerd wannabe.

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artist exploring computer perception / lecturer at @VicUniWgtn school of design. neural networks and creative coding.

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🇦🇺 Distinguished research scientist: @usfca Deep learning R&D & education: https://t.co/ZvDGNlehRt Software: https://t.co/GMYkPDXNW3 Book: https://t.co/1YSqXvWW87 Course: https://t.co/Q2qMl59EfH

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Professor at NYU. Chief AI Scientist at Facebook. Researcher in AI, Machine Learning, etc. ACM Turing Award Laureate.

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CTO of Jetpac, bought by Google. Apple alumnus, O'Reilly author, blogger, on the TensorFlow team at Google doing deep learning. Email: [email protected]

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Artificial Intelligence expert, Deep Learning #ML research, ex-R☆/Guerrilla #AI Developer, co-Founded #CreativeAI. Director @nuclai conference. #⚘

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Sr. Research Scientist @Amazon Robotics AI. SLAM, Deep Learning, and Robotic Mobility. CMU Robotics Ph.D., MIT Alum. Opinions are my own.

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Dad, Husband, Scientist at @FacebookAI Research (FAIR), Lecturer at @AI_UCL. @UCL_DARK and @UCL_NLP. Working on RL in open-world environments. Opinions my own.

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