AI Essentials

Research

Discover how AI, Machine Learning and advanced algorithms impact our lives, our jobs and the economy thanks to expert articles that include discussion on the potential, limits and consequences of AI

Top news of the week: 10.06.2021.

#AI
#DeepLearning
#TrustworthyAI
#AIforGood
#ArtificialIntelligence
#NLP
#machinelearning
#TheSequence

Research

@egrefen shared
On Jun 9, 2021
RT @_rockt: We are extremely excited to announce the launch of the @NeurIPSConf 2021 NetHack Challenge! Based on @NetHack_LE, presented at NeurIPS last year (https://t.co/X0B9M5UDNg), this accessible challenge will be a showdown between neural and symbolic AI. https://t.co/Ea6DizRbH7
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Launching the NetHack Challenge at NeurIPS 2021

Launching the NetHack Challenge at NeurIPS 2021

We are excited to launch the NetHack Challenge (@NetHack_LE) with a #NeurIPS2021 competition! NetHack is one of the hardest games ever made and it runs 50-100x faster than other RL ...

@MSFTResearch shared
On Jun 9, 2021
Get to know Retiarii, which offers ease of programming, reuse of components and up to 8.5x overall exploratory-training efficiency for DNN models. It has also been implemented on the open-source project NNI to improve Neural Architecture Search design: https://t.co/jIQ6q9Ij7W
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@peteskomoroch shared
On Jun 6, 2021
RT @kayleecat: When I first started at Roboflow, I had a hard time wrapping my mind around the full process of building and deploying a computer vision model. So I built one myself. It's a "Rock, Paper Scissors" detection model - you can explore…https://t.co/ZX1JRbxFag https://t.co/9WlWfIzpi5
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How to Build a Computer Vision Model

How to Build a Computer Vision Model

Developing, deploying and optimizing computer vision models used to be a cumbersome, painful process. With Roboflow, we sought to…

@_rockt shared
On Jun 3, 2021
@Love2Code @Abel_TorresM @NetHack_LE @GaryMarcus You will be pleased to hear that for the @NetHack_LE Challenge at @NeurIPSConf 2021 we will allow deep RL as well as non-machine learning submissions. I am super excited to see which track will win! https://t.co/l3m8Rkc6eG
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NeurIPS 2021 - The NetHack Challenge

NeurIPS 2021 - The NetHack Challenge

🕵️ Introduction The NetHack Learning Environment (NLE) is a Reinforcement Learning environment presented at NeurIPS 2020. The Nethack Challenge - NeuRIPS 2021 The Nethack …

@mxlearn shared
On Jun 8, 2021
[D]Should I care about Statistical relational artificial intelligence? https://t.co/tJI2oFmjlb
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@yaringal shared
On Jun 7, 2021
RT @ITU_AIForGood: DISCOVERY | Enhance your knowledge of Bayesian #DeepLearning methods with @yaringal from @OATML_Oxford 🗓️ Thursday, 10 June 2021 @ 15:00 ℹ️ https://t.co/COxYHy64H7 W/ @ITU @FraunhoferHHI @WojciechSamek #AI #AIforGood #TrustworthyAI https://t.co/VkB8gBPOtz
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Trustworthy AI: Bayesian deep learning

Trustworthy AI: Bayesian deep learning

Bayesian models are rooted in Bayesian statistics and easily benefit from the vast literature in the field. In contrast, deep...

@etzioni shared
On Jun 9, 2021
RT @jrdothoughts: I had a fun chat with @etzioni who is the CEO of #ArtificialIntelligence research powerhouse @allen_ai . We discussed some of their work in #NLP, #AI fairness and the gap between research and engineering: https://t.co/Qck2w6pYWt #machinelearning #deeplearning #TheSequence
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🎙Oren Etzioni/CEO of Allen Institute for AI (AI2) on advancing AI research for the common good

🎙Oren Etzioni/CEO of Allen Institute for AI (AI2) on advancing AI research for the common good

It’s so inspiring to learn from practitioners. Getting to know the experience gained by researchers, engineers, and entrepreneurs doing real ML work is a great source of insights and ...

@etzioni shared
On Jun 4, 2021
RT @ISSUESinST: In ISSUES, Amitai Etzioni and @etzioni describe the nuances of regulating lethal autonomous weapons, and suggest that #AI oversight systems could be implemented to keep these weapons under control. (2/2) https://t.co/LdFfOBMRxA
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Should Artificial Intelligence Be Regulated?

Should Artificial Intelligence Be Regulated?

Suggestions to limit some very specific applications of AI merit close examination and action.