Tarrosion

Joined 14 years ago

Karma
1,101
Submissions
207
Member since
Aug 22
I'm enthusiastic about sourdough pizza, cities, biosecurity, space exploration, energy, global development, bikes, and desserts.

By day I'm an engineering manager and research scientist at SecureBio. Drop me a line: evan@<company>.org

Previously I was the VP of data science and engineering at Zoba, a startup building optimization software and analytics for micromobility and on-demand delivery.

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Recent submissions

Comment · 1 month ago
Comment · 4 months ago
Comment · 5 months ago
Comment · 6 months ago
I'm curious to see how Claude can interact with Blender, and how people use it. I use Claude every day for both work and personal research, overall think it's a great product, but I've found it (thus far, never bet against generation n+1) remarkably terrible at spatial reasoning. That seems pretty key for Blender!
Comment · 8 months ago
This author is really prolific in the Julia visualization ecosystem. One of my favorite projects from them is actually quite useful outside Julia: a super minimal but slick Unicode character lookup, glyphy.info.
Comment · 8 months ago
[citation needed] that some combination of "New Urbanism, traditional neighbourhood design, streetcar suburbs, one-way streets, bike paths, walking paths, mixed-zone walkable villages (light commercial with residential), smaller single-family houses and duplexes, triplexes, houses behind houses." is not in fact optimal! (For certain objective functions)
Comment · 9 months ago
Comment · 10 months ago
> Is multi-agent collaboration actually useful or am I just solving my own niche problem?

I often write with Claude, and at work we have Gemini code reviews on GitHub; definitely these two catch different things. I'd be excited to have them working together in parallel in a nice interface.

If our ops team gives this a thumbs-up security wise I'll be excited to try it out when back at work.

Comment · 1 year ago
Comment · 1 year ago
I can confirm this has been true since at least v0.4!
Comment · 1 year ago
I'm sorry for your loss, and I hope that helping others through this project helps you find some solace. IMHO, it's a mark of character that your response to having a problem is "I want to help other people so they suffer this problem less than I did."
Comment · 1 year ago
Comment · 1 year ago
This makes sense in the context of trying to maximize log wealth (or I think any concave function of wealth, though the arithmetic is different). But in one of OP's other articles [1], he says the Kelly criterion doesn't require trying to maximize log-wealth, that this is just a common misconception -- all that's required is maximizing something growing geometrically over time.

This I don't understand, maybe someone help me out? Say the real growth rate of capital (or interest rate available to me, whatever) is 2%/year and I have a 10 year time horizon. So $1.00 today is ~$1.22 in 10 years. More generally, if I have wealth X today I will have 1.22X in 10 years. And if X is not a constant but a random variable and I want to maximize future expected wealth (not log wealth), that's just max(E[1.22X]) and by linearity of expectation I should just maximize wealth today to maximize in 10 years time.

So Kelly being appropriate must have some other conditions, right? Wanting to maximize log wealth is surely sufficient (and individually probably ~rational). What else?

[1]

Comment · 1 year ago
OP, you have a comment there about mouse support in the Keyboardio. I've been using a Keyboardio since 2019 and haven't much tried the mouse support -- any advice? How did you set it up?
Comment · 2 years ago
I'm curious what kind of slow IO is a pain point for you -- I was surprised to read this comment because I normally think of Julia IO being pretty fast. I don't doubt there are cases where the Julia experience is slower than in other languages, I'm just curious what you're encountering since my experience is the opposite.

Tiny example (which blends Julia-the-language and Julia-the-ecosystem, for better and worse): I just timed reading the most recent CSV I generated in real life, a relatively small 14k rows x 19 columns. 10ms in Julia+CSV+DataFrames, 37ms in Python+Pandas...ie much faster in Julia but also not a pain point either way.

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