RT @lawrennd: New positions in @Cambridge_CL! These Five-Year Fellowships are targeted at the interface of ML & the Sciences. Part of a new initiative I'm leading that's funded by a major philantropic gift. https://t.co/I4QQ72ell1 Multiple positions! Close: 30th June.Open
Departmental Early Career Academic Fellowships (DECAF) in Machine Learning or Data Science. (Fixed Term)
Departmental Early Career Academic Fellowships (DECAF) in Machine Learning or Data Science. (Fixed Term) in the Department of Computer Science and Technology at the University of Cambridge.
RT @kdnuggets: The Best NLP with Deep Learning Course is Free - KDnuggets https://t.co/vE0qhZPHAT https://t.co/v06RqwEL4qOpen
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
RT @alvations: You've used NLP open source tools and bore grievances but found solution after hours of coffee and computer staring. Share that at #NLPOSS and suggest how open source could change for the better (e.g. best practices, documentation, API design) https://t.co/DSTtI800J7 #nlprocOpen
Workshop for NLP Open Source Software (NLP-OSS)
RT @seb_ruder: 10 Tips for Research and a PhD I've been asked in the past to provide advice on doing research. Here are 10 tips that worked well for me and will hopefully also be useful to others. https://t.co/zEl0l27AciOpen
This post outlines 10 things that I did during my PhD and found particularly helpful in the long run.
RT @ducha_aiki: The third block of labs is about CNNs. That is completely done from scratch rather than migrating. Lab1: training ImageNette (kudos to @jeremyphoward ). To implement: the architecture of choice, lr_find @lnsmith613, training loop, one-cycle. 🧶 https://t.co/Iweat79N2h https://t.co/nleLGh6UFgOpen
Deep Convolutional Neural Networks (CNNs) re-entered into the computer vision community recently, especially after the breakthrough paper of Krizhevsky et al. This success initiated an ...
Microsoft researcher Sid Sen likes to start with the impossible and work back from there. That’s why he chooses to work on optimal decision making, universal data structures, and verifiably safe AI. Hear why he thinks of synergy as a solution: https://t.co/f9urv1CWxk #MSRPodcastOpen
Episode 116 | May 27, 2020 - Dr. Siddhartha Sen is a Principal Researcher in MSR’s New York City lab, and his research interests are, if not impossible, at least impossible sounding: ...
RT @VentureBeat: Baidu open-sources Paddle Quantum toolkit for AI quantum computing research https://t.co/rF46VRBFNg by @Kyle_L_WiggersOpen
Tech giant Baidu has released Paddle Quantum, a toolkit for AI quantum computing research that's available in open source on GitHub.
RT @iammanil: Our Workshop Report on Advancing Machine Learning for Earth Science is now available. Thank you to all the participants for providing valuable input, @OurRadiantEarth for hosting us, and @NASAEarthData for sponsoring the workshop. https://t.co/0pcaa9PFBuOpen
The report from the workshop “Advancing Application of Machine Learning Tools for NASA’s Earth Observation Data” is now available.
Models and examples built with TensorFlow. Contribute to tensorflow/models development by creating an account on GitHub.
Want to stay up to date with recent work being done in AI safety? @vkrakovna recommends the Alignment Newsletter, a weekly publication on AI alignment curated by @rohinmshah. Read it here: https://t.co/32FLIAW3yy & let us know if you have your own #AtHomeWithAI suggestions!Open
I edit and publish the Alignment Newsletter, a weekly publication with recent content relevant to AI alignment with over 1100 subscribers. It turns out that people don’t notice things when ...
RT @jennwvaughan: @MSFTResearch There are SO MANY! My colleague @hannawallach and I wrote a whole book chapter on "A Human-Centered Agenda for Intelligible Machine Learning" which outlines open challenges around applying HCAI methods to interpretable/intelligible ML specifically. https://t.co/hgin8Q09IX 1/3Open
Following recommendations put forth by the European Commission’s High-Level Experts Group on Artificial Intelligence, we break transparency into three components (HLEG, 2019): • ...
Scientific fact-checking using AI language models: COVID-19 research and beyond https://t.co/QDh9LNAdNqOpen
Fact or fiction? That's not always an easy question to answer. Incomplete knowledge, context and bias typically come into play. In the nascent domain of scientific fact checking, things are ...
We are proud to announce Paddle Quantum, a #quantum machine learning development toolkit for training quantum neural network models & supporting advanced #QuantumComputing applications. Read more: https://t.co/tg2zwiA63P https://t.co/SpZ6THcLdBOpen
Introducing Paddle Quantum: How Baidu's Deep Learning Platform PaddlePaddle Empowers Quantum Computing
We are proud to announce Paddle Quantum, a quantum machine learning development toolkit that can help scientists and developers quickly build and train quantum neural network models and ...
RT @marcgbellemare: @Zergylord That anyone informed would feel this way surprises me -- the ALE has always been designed to be used in block, evaluating on a large set of "testing games" (https://t.co/8lwiTqRMAN). OTOH, increasing the amount of training data to get there does break the spirit of the benchmark.Open
Abstract In this article we introduce the Arcade Learning Environment (ALE): both a challenge problem and a platform and methodology for evaluating the development of general, ...
Since our founding in 1991, Microsoft researchers have published tens of thousands of peer-reviewed papers and created a wealth of tools & datasets. The resources are available to be used across a wide variety of fields. Explore some of our favorite tools: https://t.co/kJGWsg3DIrOpen
Editor’s Note: In the diverse and multifaceted world of research, individual contributions can add up to significant results over time. In this new series of posts, we’re connecting the ...
The company’s series B funding round was led by inventors at Andreessen Horowitz and includes new investor Casdin Capital.
RT @nxthompson: "I would give it a B-minus at best." A smart essay by @kaifulee about the ways AI has been helpful---and the ways it has fallen short--in the coronavirus crisis. https://t.co/ZxJrpOfucSOpen
Disease diagnosis, drug discovery, robot delivery—artificial intelligence is already powering change in the pandemic’s wake. That’s only the beginning.
@yogthos @zcknln @mckinley_scan Yes, I've seen Janet. It's cool. It has a similar flavor to the Lisp system Léon Bottou and I built as a front-end for our neural net simulator back in 1987. It was eventually open sourced under name Lush and used actively until the early 2010s. https://t.co/owkzjuWDldOpen
Lush: the programming language for researchers