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willwhitney

1,119 karma

ML researcher.

Posts22
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willwhitney.com 1y ago

Computing Inside an AI

willwhitney
1pts0
willwhitney.com 2y ago

Learning 3D physics simulators from video

willwhitney
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willwhitney.com 5y ago

Parallelizing neural networks on one GPU with JAX

willwhitney
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www.robrhinehart.com 5y ago

The New York Times

willwhitney
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www.theverge.com 6y ago

There’s no better time for cities to take space away from cars

willwhitney
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arxiv.org 9y ago

Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

willwhitney
202pts55
willwhitney.github.io 10y ago

Understanding Visual Concepts with Continuation Learning

willwhitney
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news.ycombinator.com 10y ago

Ask HN: Blacklist Forbes?

willwhitney
164pts41
www.reddit.com 10y ago

Popcorn time revived

willwhitney
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atom.io 11y ago

Show HN: Hydrogen Brings Light Table to Atom

willwhitney
190pts70
blog.particle.io 11y ago

Spark is now Particle

willwhitney
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www.theverge.com 11y ago

Facebook launches standalone Messenger for web browsers

willwhitney
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blog.audobox.com 12y ago

The Internet Alphabet

willwhitney
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blog.audobox.com 12y ago

Android development fragmentation

willwhitney
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startupbootcamp.mit.edu 12y ago

Startup Bootcamp 2013 at MIT on Saturday

willwhitney
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blog.audobox.com 12y ago

Android is for startups

willwhitney
514pts299
audobox.com 12y ago

Show HN: Mobile feedback your users will love

willwhitney
70pts19
www.audobox.com 13y ago

Show HN: Audobox – Android Voice Recorder

willwhitney
77pts48
news.ycombinator.com 13y ago

Ask HN: Building an app to make real-world conversations searchable. Want it?

willwhitney
45pts36
pompeiana.org 13y ago

Surprisingly modern graffiti from the walls of Pompeii

willwhitney
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www.crashlytics.com 13y ago

What clang taught us about Objective-C properties

willwhitney
10pts0
github.com 14y ago

My script that spams a Google Form with Urban Dictionary terms and definitions

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12pts1

Would it be bad if we made advertising... illegal? In small part because it would reduce the principal-agent disparity between what you want to do and what Google wants you to do, but more importantly because it would remove the incentive to create blogspam and game the results.

Advertising serves a positive purpose by informing people about products that they will like and otherwise would not find. It also serves a negative purpose by attempting to cause people to make decisions which are not in their best interests.

I am genuinely curious what proportion of ads seen serve each of those two purposes.

That dip is more than 4M people, so I think it's still unexplained. Perhaps due to a shift in response rates or another artifact of COVID churn in the survey methodology?

Handling delays (and the uncertainty they entail) is a huge challenge, and I think it'll be a rich area of research. The simplest part of the problem is that delays in action or perception also slow the propagation of reward signals, and credit assignment is still a really hard problem.

Thinking further afield, future models could learn to adapt their expectations to fit the behavior of a particular opponent. This kind of metalearning is pretty much a wide open problem, though a pair of (roughly equivalent) papers in this direction recently came out from DeepMind: https://arxiv.org/abs/1611.05763 and OpenAI: https://arxiv.org/abs/1611.02779 It's going to be really exciting to see how these techniques scale.

The development experience for statically typed languages is often _amazing_ compared to that of dynamically typed ones; we sometimes choose dynamically typed ones anyway because of the flexibility and speed of development they give. I'd be very happy with an environment that provided dynamically typed languages the same analysis, checking, completion, etc that statically typed languages take for granted.

Jupyter provides a spec for a ZeroMQ-based messaging API, which kernels in each language have implemented. Hydrogen acts as a client to those kernels the same way that the Jupyter frontend does, sending execution requests to the kernel and displaying responses.

I'd love to see live test results in Atom too! It would make it so much easier to be confident in your code's correctness.

I like to break my code up into little functions that are easy to test, so that flow works well for me.

Even more powerful, though, is autocomplete from the running environment. It means that (just like in the Chrome Dev Tools) when you start typing something, the autocomplete suggestions include all of the valid names that are defined. It really helps in navigating complex APIs like Torch: https://www.dropbox.com/s/e6hriw5quwct65a/Screenshot%202015-...

Thanks for the support!

I've been thinking a lot about what makes for a good development experience, and how to properly "factorize" an IDE to provide a consistent experience across different languages. The monolithic IDE experience can be great (once you get it set up) if all your work is in a single language. But for people like me, having a confusingly different development environment for each project is a nightmare.

This is a tiny step toward the dream of having a consistent core editor but with powerful tools for each language that allow introspection into the state of the running machine.

From our pseudo-scientific testing, we got ~5x voice feedback over email feedback. We're still early in the process, so we don't have any rock-solid numbers.

One advantage we found from spoken feedback is that on mobile, people tend to be unwilling to type out a very detailed report, whereas that same level of detail is pretty fast to say.

And yeah — you can definitely tell how happy (or unhappy) they are with the product :)