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Top Research papers showcased at NIPS 2017 – Part 2
Continuing from where we left our previous post, we are back with a quick roundup of top research papers on Machine Translation, Predictive Modelling,...
AI is Driving Software 2.0… with Minimal Human Intervention from Featured Blog Posts –...
The future of software development will be model-driven, not code-driven.
Now that my 4th book (“The Economics of Data, Analytics and Digital Transformation”) is in...
Lyft releases an autonomous driving dataset “Level 5” and sponsors research competition
This week, the team at Lyft released a subset of their autonomous driving data, the Level 5 Dataset, and will be sponsoring a research...
Arm announces new CPU and GPU chipsets designs, Mali-G77 GPU, Cortex-A77 CPU, and much...
Yesterday, Arm, the company that has its basic chip architecture utilized by most of the smartphones, announced new designs for its premium CPU and...
AndroidHardening Project renamed to GrapheneOS to reflect progress and expansion of the project
The AndroidHardening project team announced yesterday that they’ve changed the Project name to GrapheneOS.
Daniel Micay, a security researcher, shared the details about GrapheneOS on...
The Verge spotlights the hidden cost of being a Facebook content moderator, a role...
Facebook has been in news in recent years for its data leaks and data privacy concerns. This time the company is on the radar...
NeurIPS Invited Talk: Reproducible, Reusable, and Robust Reinforcement Learning
On the second day of NeurIPS conference held in Montreal, Canada last year, Dr. Joelle Pineau presented a talk on reproducibility in reinforcement learning....
CycleGAN learns to cheat by hiding information in generated images
At NeurIPS 2017, a group of Stanford and Google researchers presented a very intriguing study on how a neural network, CycleGAN learns to cheat....
NeurIPS 2018: How machine learning experts can work with policymakers to make good tech...
At the 32nd annual NeurIPS conference held earlier this month, Edward William Felten, a professor of computer science and public affairs at Princeton University...
NeurIPS 2018: Rethinking transparency and accountability in machine learning
Key takeaways from the discussion
To solve problems with machine learning, you must first understand them.
Different people or groups of people are going...