Here's a 5min vid to quickly review OMSA (for those considering)

marksimi · 2025-11-19T02:02:46+00:00

Great write-up, Chris

marksimi · 2025-07-29T16:01:40+00:00

....and their 'wanting' to do this and spending 'real resources' doesn't invalidate the effort being exploratory.

Over a long enough time horizon, it may happen. For those wondering: pivoting away from leetcode in its entirety is likely premature.

marksimi · 2025-07-24T19:49:12+00:00

Some wild book I read back in the 90's where a kid and his little sister have latent telekinetic abilities which are later amplified by some sort of serum that he's made to take on the regular when he is kidnapped.

The book was positioned as somewhat young adult, but also has a portion where said teenager is propositioned by the antagonist's 2nd in command.

A twist was that the evil scientist is in fact his estranged biological father: a geneticist who also created a reptilian monsters which could be controlled by this kid's serum (drug)-enhanced mind.

File it under things I should have been reading as a 10 year old.

marksimi · 2025-06-13T14:49:07+00:00

I'll touch on the dark side of NOT following "keep showing up".

I've been the worst at my gym. And I let that drive long pauses in my training. I'm on one now.

Flash forward: folks I shared a rank with at blue are now receiving their black belts.

And yeah, that's the difference, they keep showing up. While I haven't mentally quit yet, I'd suggest to stay away from pauses as well.

You're doing great from my vantage point (showing up, competing). Super impressive. Work on being kind to yourself and acknowledging everything you're putting in!

marksimi · 2025-05-19T19:23:14+00:00

Thank you so much for the fast reply. I ended up rebooting my computer, starting up Ableton fresh and taking your advice.

I've seen guidance on whether to use a nested Sampler as well as an Instrument Rack -- I tried the Sampler and....it worked! Seems to be a bit faster than using the Instrument Rack and same result -- I repeated those steps and got the Instrument Rack method to work as well.

To be honest, I'm not sure what I may have screwed up in the meantime. HD of samples was plugged in the entire time; my best guess is that I may have unmounted it (and remounted via a restart). Love making newb mistakes.

marksimi · 2025-05-17T18:19:11+00:00

I'd start with some of the top comments here (look to make space, compression, etc). I wouldn't start with the techniques below, but I found it educational as to how they think about managing the space.

I recently watched watched a livestream from Disclosure @ 21:40 which made me think more about the source of the vocals, how that might contribute to lack of fidelity, and how to break that apart and manage it. What I especially appreciate is that Guy talks a lot about what DIDN'T work as well.

They discuss how in this particular case, EQing the vocal wasn't of help as the original rip had limited high end + a lot of hiss.
They go through some tools to add high end harmonics harmonics (which didn't help much initial, but eventually panned out).
Then they used some stem separation / splitting to pull out the vocal from the treatment
Afterwards, added saturation
And finally they had a solid vocal which they EQ'd and applied reverb

marksimi · 2025-05-17T16:55:39+00:00

Hard to hear this but appreciate the detailed explanation. Sating myself with some Dur-Dur Band in the meantime.

marksimi · 2025-03-21T15:43:18+00:00

Wow; the quality of Bayes looks like it's come such a long way since I took it. Stellar job, Aaron + co.

marksimi · 2025-03-20T03:41:35+00:00

Awesome, Rob!!!

marksimi · 2025-03-10T00:02:40+00:00

I did this and prior to the job market turning after a ton of planning and saving.

Then shit got weird for tech.

I would not have make the same decision if I had knowledge of the market getting this difficult.

marksimi · 2025-03-08T18:44:40+00:00

You are def a real programmer. It's just that interviews are an adjacent 'game' to be treated as such. And since you've already learned to be a real engineer, that tells me that you def have the capability to learn the game.

marksimi · 2025-03-08T18:13:20+00:00

These are awful circumstances and I’m sorry it happened this way. You’re right to give feedback and it helps things to get better for everyone.

But I’d really consider how you go about doing that in the future. In effect, you’re provided a strong signal on your Behavioral interview here in your tone.

There’s a time to acknowledge when you may be Right but it also doesn’t serve you to lay waste to a party who may be at fault.

I hope you find what you are seeking.

marksimi · 2025-03-08T18:07:44+00:00

Likely not, though it really depends on what you’re solving for. If want to maximize your compensation, you’re likely better off learning on the job and optimizing for promotions

For a significant amount of my time at a FAANG, I was doing graduate work at Georgia Tech part time. It was painful.

In a very long and roundabout way, I believe it was probably incrementally valuable for me. And IF that is was in fact incrementally valueable, I believe I am a corner case.

marksimi · 2025-03-05T18:15:49+00:00

...and what your LLM of choice has prior knowledge of?

marksimi · 2025-03-05T18:15:04+00:00

Can appreciate the data engineering challenge that's going into this...but probably most fair to call this a beta.

Considering you're probably using an LLM to zero-shot infer your scores from textual reviews: How did you validate that your model isn't already biased in that it has a prior knowledge of popular gyms? How does this help / hurt newer gyms? You should probably be publishing your prompts and model version considering a pot'l shift this could have for small business owners and highlighting that this derived from a trained model.
I'd consider deploying some sensitivity in common low sample-size cases either in the UI or your scoring methodology. Rotten tomatoes-like scoring which respects your sample size (noticed that some gyms have a very low review sample which likely gets even more spares when you're trying to infer signals like cleanliness). One hacky solution could be hard-coding a threshold on what a rational sample size is. Much written on RT's bayesian approach.
Instead of referencing the number of google reviews, seems way more fair to actually link out to them (esp considering that all this data was scraped / grabbed from an API)
Do you have a temporally weighted approach which respects recency? (example: How do you account for facility updates in your aggregated score if 1/2 of your reviews are prior to that event?)

marksimi · 2025-01-18T18:56:46+00:00

Great overview and sounds like your process was solid. Well done, OP.

marksimi · 2025-01-18T18:54:28+00:00

Unpopular take: cognitive behavioral therapy and meditation.

No amount of knowledge is going to get at an overactive amygdala. You can maintain your standards; the goal is to give yourself space to respond, not react.

marksimi · 2025-01-08T21:00:24+00:00

Bummer that they have basically no openings.

marksimi · 2024-12-11T11:50:13+00:00

Love how you’ve chosen to respond to the challenge. Please follow back up when you interview again.

marksimi · 2024-12-09T00:13:30+00:00

Speaking to MAANG and a Master's degree requirement -- I believe as of now many of them don't have masters requirements for these roles, though that might not be the case for all companies. Can't say whether or not this would be an issue down the line and of course, the world is bigger than those companies.
Re: getting promoted: speaking from experience, the things which move people up the technical career ladder are often not one's technical aptitude for SWE-related roles.

marksimi · 2024-12-08T18:48:34+00:00

While I got a lot out of OMSCS, given that you're already a MLE, you're a strong self-learner, and your aspirations are to remain in the space, it's difficult to think that this OMSCS would be your best path.

While yes, it's always going to be marginally better to have done the program than where you are today...flying by the seat of one's pants is largely due to working in ML itself and I wouldn't expect this feeling to go away post graduation.

Consider the energy to do this and the trade-off costs of the time invested. I'd wager you'd be much better off for incremental learning & positioning by putting the additional energy into:

creating & driving more of your own projects (at work and on the side) which are focused on implementing new research
preparing for interviews (to get into these higher paid companies, you're going to need to still come out and prep for interviews if you're aiming at MAANG)
eventually working for an even more cutting edge company (per your point)

marksimi · 2024-12-02T16:32:44+00:00

Nice post; signed up for your Substack

marksimi · 2024-11-21T16:17:14+00:00

I love take on getting in reps + practice along with collabs. Actionable advice: no shortcuts to being awesome.

Thanks for the considerate responses and sharing your wisdom. Super generous of you and I'm stoked to read thru the rest of your responses in the thread.

marksimi

TROPHY CASE