Top news of the week: 12.03.2020.
Computer vision, Machine learning, Training, Seminar, Human, Acid
Research
RT @Eric_Wallace_: Not everyone can afford to train huge neural models. So, we typically *reduce* model size to train/test faster.
However, you should actually *increase* model size to speed up training and inference for transformers.
Why? [1/6] 👇
https://t.co/GcjytCEmox
https://t.co/HatYO5GfhP https://t.co/ivKyNo1ve0
Open
CS294-158 Deep Unsupervised Learning Spring 2019
About: This course will cover two areas of deep learning in which labeled data is not required: Deep Generative Models and Self-supervised Learning. Instructors: Pieter Abbeel, …
@Sss95620990 UAE's infection rate is considered "unusually low" apparently https://t.co/5p4xdn3G83
OpenThe UAE’s exemplary resilience to COVID-19
The WHO reported that around 300 new coronavirus cases were being reported outside of China each day.
RT @WWRob: New article on how Human-in-the-Loop Machine Learning can avoid bias, create employment, augment rare data, maintain accuracy, incorporate experts, ensure consistency, make work easier, improve efficiency, provide transparency, and increase safety:
https://t.co/i17BvXC0Bg
Open10 Ways that Human-in-the-Loop Machine Learning is Used Today
Ten advantages of using Human-in-the-Loop systems over purely automated systems are: avoiding bias, creating employment, augmenting rare data, maintaining human-level precision, …
Navigating how to include AI in the complex world of human emotional states is a tough challenge. Watch these researchers weigh strengths and weaknesses of AI’s ability to complement human emotions currently and consider ideas for AI design in the future: https://t.co/046LQW07mV
OpenArtificial Emotional Intelligence, Social Systems, and the Future of Collaboration
We’re on a path to a future where artificial intelligence (AI) and humans collaborate; one could argue that time is already here. Issues of trust in teams, building rapport, and group ...
Introducing ProGen, a large language model trained on 280 million protein sequences that can generate viable proteins based on user specifications. A step towards AI & #nlpproc helping cure disease and clean our planet.
Paper: https://t.co/kFmTC6RpYl
Blog: https://t.co/UCBxHqlTPl https://t.co/r0BzfjmeQj
OpenProGen: Using AI to Generate Proteins
In our study, we demonstrate that our artificial intelligence model, ProGen, can learn the language of biology in order to controllably generate proteins.
Saw this interesting project on r/ML that seems to be highly unconventional and non-mainstream. There are many independent researchers who have their own theories of how AI should work, but they have a GitHub repo, papers, and decent RL benchmark results.
https://t.co/gZ1VoMBW2Q https://t.co/itEz7bQBzx https://t.co/kH026lQKZC
OpenFractal AI: A Fragile Theory of Intelligence
Celular automaton-based calculus for the masses. Contribute to Guillemdb/FractalAI development by creating an account on GitHub.
RT @Tim_Dettmers: After talking to many students about their grad school experience I compiled this blog post on "How to pick your grad school". I discuss all the important factors and details from contrasting but complementary perspectives. I hope it will be helpful! https://t.co/eGoMPMpHRn
OpenHow to Pick Your Grad School
How to pick a good advisor? How important is school prestige? How important are peers? I answer these questions and help you find the right grad school.