AI AI Weekly

The Decade of Deep Learning; AI Experts’ Hopes for 2020; AI Beats Doctors at Cancer Diagnosis?

Synced Global AI Weekly January 5th

Subscribe to Synced Global AI Weekly


The Decade of Deep Learning
This post is an overview of some the most influential Deep Learning papers of the last decade. The author hopes to provide a jumping-off point into many disparate areas of Deep Learning by providing succinct and dense summaries that go slightly deeper than a surface level exposition, with many references to the relevant resources.
(Leo Gao)


Hopes for AI in 2020: Yann LeCun, Kai-Fu Lee, Anima Anandkumar, Richard Socher
Deeplearning.ai has invited Anima Anandkumar, Oren Etzioni, Chelsea Finn, Yann LeCun, Kai-Fu Lee, David Patterson, Richard Socher, Dawn Song and Zhi-Hua Zhou to express their hopes for 2020.
(Deeplearning.ai)


Google Just Beat Humans at Spotting Breast Cancer — But It Won’t Replace Them
Google is developing artificial intelligence to help doctors identify breast cancer. The model, which scans X-ray images known as mammograms, reduces the number of false negatives by 9.4 percent—a hopeful leap forward for a test that currently misses 20 percent of breast cancers.
(The Verge) / (Nature) / (Paper)

Technology

Learning by Cheating
Vision-based urban driving is hard. The autonomous system needs to learn to perceive the world and act in it. Researchers show that this challenging learning problem can be simplified by decomposing it into two stages.
(UT Austin & Intel Labs)


A Modern Introduction to Online Learning
In this monograph, the researcher introduces the basic concepts of Online Learning through a modern view of Online Convex Optimization. Here, online learning refers to the framework of regret minimization under worst-case assumptions.
(Boston University)


Deep Sparse Rectifier Neural Networks
This paper shows that rectifying neurons are an even better model of biological neurons and yield equal or better performance than hyperbolic tangent networks in spite of the hard non-linearity and non-differentiability at zero, creating sparse representations with true zeros, which seem remarkably suitable for naturally sparse data.
(Université de Montréal)

You May Also Like

Happy AI New Year! Global Researchers Reflect on 2019, Talk Trends for 2020
To welcome 2020 with some fresh AI perspectives, Synced spoke with global researchers from Google Brain, Sony AI, Alibaba affiliate Ant Financial (formerly known as Alipay) and other 8 organizations.
(Synced)


2019 in Review: 10 AI Papers That Made an Impact
As part of our year-end series, Synced spotlights 10 artificial intelligence papers that garnered extraordinary attention and accolades in 2019.
(Synced)

Global AI Events

January 7–10: CES 2020 in Las Vegas, United States

February 7–12: AAAI 2020 in New York, United States

February 24–27: Mobile World Congress in Barcelona, Spain

March 23–26: GPU Technology Conference (GTC) in San Jose, United States

Global AI Opportunities

Twitter is Hiring Engineering Manager, ML

Alan Turing Institute Safe and Ethical AI Research Fellow/Fellow

OpenAI Scholars Spring 2020

DeepMind Internship Program

NVIDIA Graduate Fellowships

DeepMind Scholarship: Access to Science

LANDING AI is Recruiting

Stanford HAI is Recruiting

OpenAI Seeking Software Engineers and Deep Learning Researchers

DeepMind is Recruiting


Stay tight with AI!
Subscribe to Synced Global AI Weekly

1 comment on “The Decade of Deep Learning; AI Experts’ Hopes for 2020; AI Beats Doctors at Cancer Diagnosis?

  1. Pingback: The Decade of Deep Learning; AI Experts' Hopes for 2020; AI Beats Doctors at Cancer Diagnosis? – NewsChest Technology

Leave a Reply

Your email address will not be published.

%d bloggers like this: