RT @awjuliani: If you are a recent PhD graduate and want to work on DeepRL @unity3d -> https://t.co/LWgAieGYiOOpen
We are looking for an exceptional researcher to join Unity’s ML-Agents team within [email protected] The ML-Agents team is an applied research team focused on: 1.
RT @rgblong: At @AIImpacts, I'm compiling a list of published arguments that current methods in AI will not lead to human-level intelligence. Featuring @GaryMarcus, @rodneyabrooks, @yudapearl, and others. Who else should be in there? https://t.co/o2CVSCVH5oOpen
This is a list of published arguments that we know of that current methods in artificial intelligence will not lead to human-level AI. Details Clarifications We take 'current methods' to ...
RT @iamtrask: This is one of the most astounding demos of Deep Learning I've ever seen! Huge opportunity for new open-source Web Development tools based on merely 200 lines of Keras code. Really opens up the imagination for what can be done with #DeepLearning https://t.co/5hrIyWlIlqOpen
FloydHub - Deep Learning Platform - Cloud GPU
RT @sleepinyourhat: Excited for this term's NLP speaker lineup at @NYUDataScience. If you're based at NYU or a nearby university/lab, take a look: https://t.co/y2CCEJNVEZ https://t.co/S0BpYWpJgOOpen
The NYU NLP and Text-as-Data Speaker Series takes place on Thursdays from 4 – 5:30 pm at the Center for Data Science, 60 Fifth Avenue (7th floor common area). Expanding from its original ...
In collaboration w/ @ox_ultracold & @FelixHill84, we developed machine learning techniques to optimise the production of a Bose-Einstein condensate, a quantum-mechanical state of matter that can be used to test predictions of theories of many-body physics https://t.co/wXFI46TJT9Open
We apply three machine learning strategies to optimize the atomic cooling processes utilized in the production of a Bose-Einstein condensate (BEC). For the first time, we optimize both ...
Also interesting from Hot Chips: Gaudi from Habana: https://t.co/YGYncwxnbc white paper: https://t.co/8cgHxk3dtp and a news article: https://t.co/cWcjIfZh91 "pure AI" GPU-like chip, most interestingly using open-standard Ethernet for scaling & RoCE. Look fwd to more benchmarks https://t.co/o1GuFqJbDfOpen
Gaudi™ Training Platform White Paper June 2019 Ver 1.0 2019 Habana Labs Ltd. | www.habana.ai | Ver 1.0 | June 2019 2019 Habana Labs Ltd. | www.habana.ai | Ver 1.0 | June 2019 1 Gaudi™ ...
RT @DeepMindAI: We're open sourcing Spriteworld, a flexible, procedural reinforcement learning environment: https://t.co/MkuXLYlhMq Spriteworld is a 2-dimensional arena with movable objects, and is particularly well-suited for small-scale experiments with limited computational resources. https://t.co/Nw6Zfgg4htOpen
Spriteworld: a flexible, configurable python-based reinforcement learning environment - deepmind/spriteworld
[N] Google files patent “Deep Reinforcement Learning for Robotic Manipulation” https://t.co/rKjy1frcMfOpen
92 votes and 20 comments so far on Reddit
RT @kjgeras: Artie Shen (@ArtieShen) just got his first first author paper "Globally-Aware Multiple Instance Classifier for Breast Cancer Screening" (https://t.co/P5CfrLuL4x) accepted at MLMI (https://t.co/QU3vatm31X). Congratulations Artie! https://t.co/K8PrKh579ROpen
Overview Machine learning plays an essential role in the medical imaging field, including computer-aided diagnosis, image segmentation, image registration, image fusion, image-guided ...
The First TextWorld Problems competition enables researchers to have some fun with text-based games while making important strides in reinforcement learning and natural language processing. Find out who won and how their agent tackled the challenge: https://t.co/YlVCSELkWXOpen
First TextWorld Problems, the competition: Using text-based games to advance capabilities of AI agents
The First TextWorld Problems competition enables researchers to have some fun with text-based games while making important strides in reinforcement learning and natural language processing. ...
RT @le_roux_nicolas: Here is the call for papers: https://t.co/o5O1UZxoc9 . Don't wait, deadline is soon! https://t.co/bwRRFQq7FROpen
[“Workshop at NeurIPS, Dec 13-14th. 2019, Vancouver, Canada”]
Listen to the latest podcast of @twimlai, in which @OlivierBachem from Google Research, Zürich talks about the Google Research Football environment (https://t.co/rdvsOINA9e) and the learning of disentangled representations (https://t.co/lrC7eN4EUx). https://t.co/3yi0ixqvs1Open
Today we are joined by Olivier Bachem, a research scientist at Google AI on the Brain team, to discuss Google Research Football Project.
RT @bsaeta: One of the advantages of #CloudTPU's are hardware support for BFloat16, a numerical format invented by @JeffDean and others at #GoogleBrain over half a decade ago. Although source has long been available in @TensorFlow, we're now finally talking about it: https://t.co/HYkPgJOMkbOpen
How the high performance of Google Cloud TPUs is driven by Brain Floating Point Format, or bfloat16
RT @Even_Oldridge: A further improvement upon the RAdam optimizer, combining it with LookAHead (https://t.co/xPhImDNjuk) gives even better performance than SGD while converging faster. Another great article from Less Wright with a @fastdotai implementation. https://t.co/DvaVrXBSdaOpen
New Deep Learning Optimizer, Ranger: Synergistic combination of RAdam + LookAhead for the best of both.
A new paper in part by the famed deep learning researcher Geoffrey Hinton introduces the LookAhead optimizer(“LookAhead optimizer: k steps…
5 votes and 13 comments so far on Reddit
RT @mza: Amazon Forecast – Now Generally Available | AWS News Blog https://t.co/uQg8dpHKRB https://t.co/oNo1AzruYyOpen
Getting accurate time series forecasts from historical data is not an easy task. Last year at re:Invent we introduced , a fully managed service that requires no experience in machine ...
RT @hardmaru: Evolving Networks: A nice review article about NEAT and extensions, with a minimal python implementation. Interesting to read about Neuroevolution from people like @wellecks who mainly work on Deep Learning and NLP. https://t.co/kBv0KGKyzj https://t.co/0J5UDikb91Open
Finding neural network topologies is a problem with a rich history in evolutionary computing, or neuroevolution. This post will revisit some of the key ideas and outgoing research paths. ...