Eric Jang

Eric Jangby noreply@blogger.com (Unknown)·20 Sept 2021

In a previous blog post, I also discussed how iterating in simulation solves some tricky problems around new code changes invalidating old data.

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Eric Jangby noreply@blogger.com (Unknown)·19 Jun 2021

Andy Warhol once said, “Art is what you can get away with.” I interpret the quote as a nihilistic take on “beauty is in the eye of the beholder” — a urinal you found in the junkyard can be...

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Eric Jangby noreply@blogger.com (Unknown)·27 May 2021

Money allows goods, services, and everything else under the sun to be assigned a value using the same unit of measurement. Without money, society reverts to bartering, which is highly inefficient.

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Eric Jangby noreply@blogger.com (Unknown)·14 Mar 2021

This is the text version of a talk I gave on March 12, 2021, at the Brown University Robotics Symposium. As always, all views are my own, and do not represent those of my employer.

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Eric Jangby noreply@blogger.com (Unknown)·13 Feb 2021

Biologically Plausible Deep Learning (BPDL) is an active research field at the intersection of Neuroscience and Machine Learning, studying how we can train deep neural networks with a "learning...

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Eric Jangby noreply@blogger.com (Unknown)·26 Jan 2021

The nice thing about reading most ML papers is that you can cut through the jargon by asking just five simple questions. I try to answer these questions as quickly as I can when skimming papers.

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Eric Jangby noreply@blogger.com (Unknown)·27 Sept 2020

Xiaoyi Yin (尹肖贻) has kindly translated this post into Chinese (中文) Accept-or-reject decisions for the NeurIPS 2020 conference are out, with 9454 submissions and 1900 accepted papers (20% acceptance...

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Eric Jangby noreply@blogger.com (Unknown)·20 Jun 2020

This post was prompted by a tweet I saw from my colleague, Colin: I'm currently a researcher at Google with a "non-traditional background", where non-traditional background means "someone who...

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Eric Jangby noreply@blogger.com (Unknown)·2 Apr 2020

Q1: Can we imitate "thinking" from only observing behavior? Suppose you have a large fleet of autonomous vehicles with human operators driving them around diverse road conditions.

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Eric Jangby noreply@blogger.com (Unknown)·26 Dec 2019

In 1984, a panel at the AAAI conference discussed whether the field was approaching an "AI Winter".

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Eric Jangby noreply@blogger.com (Unknown)·29 Nov 2019

This blog post is a tutorial on implementing path tracing, a physically-based rendering algorithm, in JAX.

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Eric Jangby noreply@blogger.com (Unknown)·6 Nov 2019

The Content is for informational purposes only, you should not construe any such information or other material as legal, tax, investment, financial, or other advice.

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Eric Jangby noreply@blogger.com (Unknown)·5 Jul 2019

This is a tutorial on common practices in training generative models that optimize likelihood directly, such as autoregressive models and normalizing flows.

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Eric Jangby noreply@blogger.com (Unknown)·24 May 2019

I've been at Google Brain robotics (now referred to as Robotics @ Google) for nearly 3 years. It's helpful to reflect, from time to time, on the scientific, engineering and personal productivity...

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Eric Jangby noreply@blogger.com (Unknown)·13 May 2019

I was so duly impressed that I signed up for Snapchat and fiddled around with it this morning to try and figure out what's going on under the hood and how I might break it.

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Eric Jangby noreply@blogger.com (Unknown)·10 Mar 2019

I often hear the remark around the proverbial AI watering hole that there are no examples of reinforcement learning (RL) deployed in commercial settings that couldn’t be replaced by simpler...

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Eric Jangby noreply@blogger.com (Unknown)·6 Feb 2019

Disclaimer: I wasn't a reviewer of this paper for ICLR. I think it was worthy of acceptance to the conference, and hope it prompts further investigation by the research community.

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Eric Jangby noreply@blogger.com (Unknown)·28 Dec 2018

Chinese translation by Xiaoyi Yin Notions of uncertainty are tossed around in conversations around AI safety, risk management, portfolio optimization, scientific measurement, and insurance.

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Eric Jangby noreply@blogger.com (Unknown)·8 Aug 2018

Dijkstra's, Bellman-Ford, Johnson's, Floyd-Warshall are good algorithms for solving the shortest paths problem.

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