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Annual Report 2018
This year, The Essentials Report, has curated & analyzed the content published by 174 influencers like Mariya and Jeremy Howard, discussing hashtags such as #ML , #machinelearning and #DeepLearning.
Read our yearly report or learn more about Essentials.
What matters to our readers VS what matters to the rest of the world in 2018
Popular with our readers
Top Hashtags & Sources
Hashtags our readers care about
Top Mentioned Sources
Best articles in 2018
No time to read AI research? We summarized top 2018 papers for you
Trying to keep up with AI research papers can feel like an exercise in futility given how quickly the industry moves. If you’re buried in papers to read that you haven’t quite gotten around ...
Top 2018 Machine Learning Trends (And Our 2019 Preview!)
As 2018 comes to a close, we thought we’d share our thoughts on the most impactful developments in machine learning over the past year and…
A Review of the Recent History of Natural Language Processing
This is the first blog post in a two-part series. The series expands on the Frontiers of Natural Language Processing session organized by Herman Kamper and me at the Deep …
terryum/awesome-deep-learning-papers
The most cited deep learning papers. Contribute to terryum/awesome-deep-learning-papers development by creating an account on GitHub.
Is deep learning overhyped?
Many critics of deep learning claim it is overhyped. But as AI researcher and data scientist explains, perhaps deep learning is just not understood well.
WTF Is Artificial Intelligence?!
AI is like teenage sex: everyone talks about it, nobody knows how to do it, everyone thinks everyone else is doing it & so they claim to do it too.
How to deliver on Machine Learning projects
A guide to the ML Engineering Loop
Google ponders the shortcomings of machine learning
Scientists of AI at Google's Google Brain and DeepMind units acknowledge machine learning is falling short of human cognition and propose that using models of networks might be a way to ...
How Lyrebird Uses AI to Find Its (Artificial) Voice
We can clone veggies, livestock and pets—so why not our voices?
Troubling Trends in Machine Learning Scholarship
By Zachary C. Lipton* & Jacob Steinhardt* *equal authorship 1 Introduction Collectively, machine learning (ML) researchers are engaged in the creation and dissemination of knowledge about ...
The Pros And Cons Of Hiring A Chief AI Officer
Artificial intelligence is one of the most significant technological developments. Should organizations hire a Chief AI Officer to power their AI strategy?
PocketFlow
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications. - Tencent/PocketFlow
A Developmental Approach to Machine Learning?
Visual learning depends on both the algorithms and the training material. This essay considers the natural statistics of infant- and toddler-egocentric vision. These natural training sets ...
The PyTorch-Kaldi Speech Recognition Toolkit
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and ...
Concrete next steps for transitioning from CS or software engineering into ML engineering for AI safety and alignment
Note that this guide was written in November 2018 to complement an in-depth conversation on the 80,000 Hours Podcast with Catherine Olsson and Daniel Ziegler on how to transition from ...
