Fei-Fei Li of Stanford HAI challenges us to use technology to serve humanity at its broadest and most diverse extent. Join her at #SfN19 for “Dialogues Between Neuroscience and Society” to hear of the potential that AI & #MachineLearning pose for society.
@ArtificialIntelligenceArticles
https://www.sfn.org/Meetings/Neuroscience-2019/Sessions-and-Events/Scientific-Program/Lectures
join
@ArtificialIntelligenceArticles

SC-FEGAN: "Face Editing Generative Adversarial Network with User's Sketch and Color":
https://arxiv.org/abs/1902.06838 https://github.com/run-youngjoo/SC-FEGAN

At the Institute for Advanced Studies in Princeton this week for the workshop "Theory of Deep Learning: Where next?"

https://math.ias.edu/wtdl

Faculty positions in AI and Machine Learning at Oregon State

The School of Electrical Engineering and Computer Science at Oregon State University invites applications for full-time, nine-month, tenure-track faculty positions in Artificial Intelligence to begin in Fall 2020. Candidates with a strong research record in any areas of Artificial Intelligence including Natural Language Processing, Computer Vision, Machine Learning, and Automated Planning will be considered.

Appointment is anticipated at the Assistant Professor rank, but candidates with exceptional qualifications may be considered for appointment at the rank of Associate or Full Professor. Applicants must hold a doctorate degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related field by the start of employment. Applicants should demonstrate a strong commitment and capacity to initiate new funded research as well as to expand, complement, and collaborate with existing research programs in the OSU College of Engineering and beyond. As part of the position, applicants have to regularly perform graduate and undergraduate teaching duties, including developing new courses related to their research expertise. Applicants are expected to mentor students and promote equitable outcomes among learners of diverse and underrepresented identity groups.

The university is located in Corvallis, at the heart of Oregon’s Willamette Valley and close to Portland’s Silicon Forest with numerous collaboration opportunities. The College of Engineering (CoE) boasts of strong graduate programs in Robotics and AI and a newly established Collaborative Robotics and Intelligent Systems Institute (CoRIS). Corvallis has been ranked # 1 on a list of “Best Places for Work-Life Balance” and is within easy reach of the Cascade Mountains and the Oregon Coast.

Oregon State University has a strong institutional commitment to diversity and multiculturalism, and provides a welcoming atmosphere with unique professional opportunities for leaders from underrepresented groups. We are an Affirmative Action/Equal Opportunity employer, and particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who share our vision of an inclusive community.

Apply online at https://jobs.oregonstate.edu/postings/79556 with the following documents: A letter of interest; vita; a two-page statement of research interests; a one-page statement of teaching interests; a one-page statement on efforts towards equity and inclusion; and names and contact information for at least three references.

To be assured full consideration, applications must be received by December 1, 2019.

Get started with machine learning on Arduino
Blog by ARDUINO TEAM : https://blog.arduino.cc/2019/10/15/get-started-with-machine-learning-on-arduino/
#Arduino #MachineLearning #Tensorflow

Cognitive AI breakthrough

https://venturebeat.com/2019/10/14/the-cognitive-ai-breakthrough-real-human-like-reasoning-in-business-ai-solutions/amp/

Workshop on Theory of Deep Learning: Where next?

2019-2020

Tuesday, October 15, 2019 - 09:00 to Friday, October 18, 2019 - 06:00

At Institute for Advanced Studies
Princeton University

Speakers:
Anima Anandkumar, Raman Arora, Sanjeev Arora, Mikhail Belkin, Léon Bottou, Joan Bruna, Michael Collins, Simon Du, Gintare Karolina Dziugaite, Surya Ganguli, Rong Ge, Suriya Gunasekar, Stefanie Jegelka, Chi Jin, Sham Kakade, Yann LeCun, Jason Lee, Ke Li, Tengyu Ma, Aleksander Madry, Chris Manning, Behnam Neyshabur, Dan Roy, Nathan Sbrero, Rachel Ward, Bin Yu

#deeplearning

Live Stream:

https://www.ias.edu/livestream

Stabilizing Transformers for Reinforcement Learning
Parisotto et al.: https://arxiv.org/abs/1910.06764
#DeepLearning #Transformers #ReinforcementLearning

#OpenAi've trained an AI system to solve the Rubik's Cube with a human-like robot hand.

This is an unprecedented level of dexterity for a robot, and is hard even for humans to do.

The system trains in an imperfect simulation and quickly adapts to reality: https://openai.com/blog/solving-rubiks-cube/

BoTorch: Programmable Bayesian Optimization in PyTorch
Balandat et al.: https://arxiv.org/abs/1910.06403
Code: https://github.com/pytorch/botorch
#MachineLearning #Bayesian #PyTorch

🎓 Reinforcement Learning Course from OpenAI

Reinforcement Learning becoming significant part of the data scientist toolbox.
OpenAI created and published one of the best courses in #RL. Algorithms implementation written in #Tensorflow.
But if you are more comfortable with #PyTorch, we have found #PyTorch implementation of this algs

OpenAI Course: https://spinningup.openai.com/en/latest/
Tensorflow Code: https://github.com/openai/spinningup
PyTorch Code: https://github.com/kashif/firedup

#MOOC #edu #course #OpenAI

"Quand la machine apprend"
Un livre dont je suis l'auteur qui sort aujourd'hui en librairie.
Edité par Odile Jacob.

Broché: https://livre.fnac.com/a13700561/Yann-Le-Cun-Quand-la-machine-apprend

Broché: https://www.amazon.fr/gp/aw/d/2738149316/ref=ox_sc_act_image_1

En PDF et ePub: https://www.odilejacob.fr/catalogue/sciences/informatique/quand-la-machine-apprend_9782738149312.php

Format Kindle:
https://www.amazon.fr/dp/B07Z5N3LQM/ref=cm_sw_r_tw_awdb_c_x_wIUPDbTFT7Q07

Unsupervised Word Embeddings Capture Latent Knowledge from Materials Science Literature,"
https://go.nature.com/32dCEfi

An algorithm with no training in materials science can scan the text of millions of papers and uncover new scientific knowledge.

3.3 million abstracts of published materials science papers were fed into an algorithm called Word2vec.

By analyzing relationships between words the algorithm was able to predict discoveries of new thermoelectric materials years in advance and suggest as-yet unknown materials as candidates for thermoelectric materials.

https://towardsdatascience.com/using-unsupervised-machine-learning-to-uncover-hidden-scientific-knowledge-6a3689e1c78d

Online evaluation of machine learning models
https://conferences.oreilly.com/artificial-intelligence/ai-eu/public/schedule/detail/78170

U of T, Vector Institute create new deep learning faculty positions in honour of Geoffrey Hinton


https://www.utoronto.ca/news/u-t-vector-institute-create-new-deep-learning-faculty-positions-honour-geoffrey-hinton https://t.iss.one/ArtificialIntelligenceArticles

High energy: Facebook's AI guru LeCun imagines AI's next frontier
https://www.zdnet.com/article/high-energy-facebooks-ai-guru-lecun-imagines-ais-next-frontier/

Emergent properties of the local geometry of neural loss landscapes
Stanislav Fort and Surya Ganguli : https://arxiv.org/abs/1910.05929
#MachineLearning #NeuralNetwork #DeepLearning

Video Architecture Search
Blog by Michael S. Ryoo and AJ Piergiovanni : https://ai.googleblog.com/2019/10/video-architecture-search.html
#ArtificialIntelligence #DeepLearning #NeuralArchitectureSearch

Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping
Video: https://www.youtube.com/watch?v=-5XxXRABXJs&feature=youtu.be
Code: https://github.com/MIT-SPARK/Kimera
Paper: https://arxiv.org/abs/1910.02490