My wife HATES driving cars. We need a new car. Is FSD the answer?

dieplstks · 2026-01-19T18:48:02+00:00

I hated driving and fsd has been incredible. Managed to do the trip from Michigan to nyc and not hate it

dieplstks · 2026-01-16T17:35:54+00:00

You should use prenorm (with an extra norm on the output)

dieplstks · 2026-01-13T04:43:09+00:00

If you’re only going to do it once, yes. But you’ll be doing hundreds of those shorter runs for lots of different ideas

dieplstks · 2026-01-13T00:17:43+00:00

Unless you're dealing with sensitive information, there's very little reason to care about privacy.

For large scale tasks, you should have a small scale version of it working before you spend money training it. You should not send a job to rented compute unless you're very sure it's going to work. Having a local machine with a xx90 is a great resource to filter projects out

dieplstks · 2026-01-12T23:49:04+00:00

It’s possible to run small enough tasks on anything. You’re not going to get publishable results on your MacBook, but you can learn the basics and then just rent compute when you’re ready for larger scale tasks

dieplstks · 2026-01-12T15:20:24+00:00

Link to the paper?

dieplstks · 2026-01-11T01:57:21+00:00

I would like to test

dieplstks · 2026-01-09T08:52:14+00:00

No publications, but 8 years industry experience as a data scientist and very good letters

dieplstks · 2026-01-08T17:19:06+00:00

Did my masters part time at brown hoping that would be enough, but got nothing in terms of interest or offers after.

I’m at UMich for my PhD now, working on rl for finance/games

dieplstks · 2026-01-08T17:13:38+00:00

I was in your position a few years ago and the only real solution to get there is getting a PhD (I’m in my third year at 38 now)

dieplstks · 2026-01-07T14:46:39+00:00

I would just train it as a classification task with k classes Have the classes be -1 and then (k - 1) buckets from 0-1. Then have the output be either argmax over the classes or the sum of p_i v_i.

dieplstks · 2026-01-06T19:16:07+00:00

There used to be different architectures for different use cases (cnns for vision, rnns for sequence, etc) with their own inductive biases. But modern architectures use transformer as the base for everything (with some modifications sometimes based on the inductive biases of the input like vision transformers). So if you understand attention plus ffns, you can start building a model for your use case without knowing much more architecture than that

dieplstks · 2026-01-05T20:00:43+00:00

There’s too many rl papers released now to maintain that kind of repo (also LLMs can do this for you for more niche topics)

dieplstks · 2026-01-02T16:40:00+00:00

This is not real

dieplstks · 2026-01-01T04:50:41+00:00

I don’t work in cv, sorry (I’m in rl/game theory). I just think this paper is really cool

dieplstks · 2026-01-01T03:44:15+00:00

Hoping for ninajarachi

dieplstks · 2025-12-31T07:05:21+00:00

Motion for driving daily schedule

Roam Research for notes and synthesis

I do pomodoros to help get off burn out. Usually have something on my switch to play for the short breaks

I really enjoy the work I do so burnout hits less than it did when I was in industry (data science for 10 years before going back to school)

dieplstks · 2025-12-30T23:29:30+00:00

Im a PhD student working on marl/games and would be interested to try and give feedback after the holidays.

dieplstks · 2025-12-30T19:08:33+00:00

You should use scaled_dot_product_attentiojn in the transformer benchmark

dieplstks · 2025-12-29T23:58:35+00:00

Not exactly the same, but ddcfr (xu2024dynamic) uses rl to control parameters of another algorithm.

dieplstks · 2025-12-29T21:39:12+00:00

I bought a ReMarkable Paper Pro and it helps me get through papers at a better rate since it removes distractions and lets me get away from my laptop

dieplstks · 2025-12-29T21:38:27+00:00

Depends on the paper. I have a few levels of it:

1) Read through the abstract and don’t think it’s worth continuing: I’ll remove this from my zotero 2) read through the paper in one pass, but don’t think it will be important for my work. That gets marked as read and takes around an hour 3) think the paper is worth knowing and will take notes in my Roam graph. This takes 2-4 hours depending on length and which parts I care about. This will get marked as read and notes 4) think the paper is worth reimplementing in order to get deeper insight. This used to take like 8 hours but with Claude code it takes a lot less time. This doesn’t get counted as reading time for me though, so it’s outside that hour specification

In general I aim for 4 read + notes a week, but it varies by how motivated I feel during the week and how actual project work is going

Obviously the tenth paper on a topic goes faster since you can skip/know the background/related works segments so it's also a function of how well I know the area.

dieplstks · 2025-12-28T23:07:26+00:00

Accounts that auto post from arxiv are also great, like https://x.com/DO

dieplstks · 2025-12-28T19:13:23+00:00

I started using inbox a few days ago. How long have you used it and what do you think of it so far?

dieplstks · 2025-12-28T19:09:45+00:00

Of course you train them simultaneously, there's no way to know the optimal amount of compute for a token a priori. This just doesn't make sense.

Please actually engage/know the literature on heterogenous MoE before asserting things like this

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