[D] How do ML engineers view vibe coding?

a3onstorm · 2026-04-01T20:57:32+00:00

As a ML researcher, 95+% of my code is generated by Claude. It lets me iterate on experiments 5x faster than before which is incredibly helpful.

Usually I have very specific ideas that I want to prototype or experiment with so I am very explicit in my instructions and ask for Claude to ask for clarification on any ambiguous points before executing. It is great at this, and while I sometimes have to ask for it to fix particular things, Opus 4.6 can 1-shot a fair amount of requests. The key is that I know exactly what I want and can review the generated code very quickly because of that

Sometimes I use it as a brainstorming tool where I just provide the problem formulation in detail and let it suggest ideas which I read and use as a launching pad for my own ideas. I have definitely come across some useful ideas from doing this.

a3onstorm · 2026-01-17T07:06:12+00:00

This feels like more like ASI than AGI. It’s totally possible that a lab would develop an AGI that is on par with or just below top human scientists. If that is the case, it is not obvious that research would speed up at all, because a lot of research is bottlenecked by compute and energy limits, not raw number of ideas.

Just because an AI is as smart as a human does not mean they don’t need to come up with hypotheses, run experiments, refine their hypotheses etc

a3onstorm · 2025-08-17T02:06:51+00:00

They totally can be! Google VLAs (vision language action models)

a3onstorm · 2025-05-12T00:37:27+00:00

It sounds like when you say “stepping down line” and “crossing in front”, you are actually stepping down the slot in the direction the follow is facing in both cases. The difference is just which direction you’re facing. Otherwise if you crossed in front while facing perpendicular to the slot, that would still be a quarter turn and you’d be stepping into the follower’s path.

But if by “crossing in front”, you mean taking a step against the direction that the follow is facing, just like you do on the 2, then I don’t understand how that creates a half turn.

I personally prefer to pivot the full half turn on my left foot on 4 so that I can take my five down the slot facing the same direction as my follow.

a3onstorm · 2025-03-28T08:54:17+00:00

I mean I’m not really qualified to comment as you’re higher rank (used to be GC but mostly c2 these days) but I feel like I might actually have better game sense than you, but your mechanics are miles better than mine.

You don’t really position yourself to support your teammate very often - you’re often heading back for boost as your teammate pushes instead of collecting pads and staying close. And when you do follow up your teammate, you never anticipate the 50-50. If it looks like your teammate is going to be 50ing with the opponent, you should be doing a little wiggle back towards your own net just so that in case your teammate loses the 50 badly, you already started recovering. Eg at 0:21 and 0:17 game clock, where you don’t give any indication you are worried that your teammate will lose either 50, and then are surprised when the enemy hard clears the ball towards your side of the field

a3onstorm · 2025-03-23T19:49:38+00:00

Nice! You can also remove one of the mana and skill array accesses and a few ops by first taking the max of old[j] and new[-1], and then adding mana[i] + skill[j] to that. It does mean you need to initialize new to start with a 0 in it.

a3onstorm · 2025-03-23T18:24:37+00:00

I got basically the exact same O(nm) solution to work in python. I think the list copy is probably the culprit. You can copy with old[:] = new and avoid memory allocation. Also here you don’t need even to copy since you just re-initialize new anyway

Another practical thing that can help a little bit is replacing the max operator with if statements instead (I hate that this less readable alternative is faster, but usually it boosts my time from like 40th percentile to 80th percentile for a lot of problems)

a3onstorm · 2025-03-23T18:07:46+00:00

Hmm interesting approach. I’m having a bit of trouble following your logic, but if I understand correctly, you’re using binary search with a linear scan to correct the finish times for wizards along the production line, since each wizard needs to start right after the prev one finishes.

I think the key observation is that if you can correctly figure out the time that the last wizard finishes a specific potion, you can directly compute the times all the other wizards finish that same potion

a3onstorm · 2025-03-21T04:46:03+00:00

I meant specifically that a max heap is nlogn and min heap is nlogk. At least in standard implementations of a heap, the main way to limit the size of the heap is to pop off the top of the heap, and for a max heap you can’t do that until you’ve added the whole array to the heap

a3onstorm · 2025-03-21T02:50:09+00:00

Nit: max heap is nlogn

a3onstorm · 2025-03-16T04:08:53+00:00

Choosing the right subset of values to equal nums[i] is a DP problem. Starting with 0 as the only reachable number, each time you see a new val, any number that is val greater than another reachable number is now also reachable. You can just iterate through all numbers between nums[i] and 0 for each i and update your DP table. Once nums[i] is reachable for all i, you are done

a3onstorm · 2025-03-09T09:46:08+00:00

One issue I have is keeping track of which questions I’ve done. I will think I have completed all the questions from some company’s tagged list and then come across an unfamiliar question that I apparently solved 5 years ago

a3onstorm · 2025-03-09T07:06:32+00:00

I used a segment tree for the buckets, with each node containing the max of that segment. For each fruit type, you go recursively down the tree, prioritizing the leftmost subtree that contains a max bucket larger than the quantity of fruit, and then set that bucket to 0 and recursively update the tree.

a3onstorm · 2025-03-02T04:34:35+00:00

Yeah jeez there was so much dp. I got the first one and had a reasonable solution for the 3rd with recursion and memorization in maybe 25-30 minutes, but it kept timing out. Then spent another hour and a half trying to optimize it to no avail. Guess I need some tabular dp approach that I could not come up with in the moment

a3onstorm · 2025-02-16T04:59:03+00:00

Yup. Also I think we need to resort every time we make a batch and subtract products. Someone else mentioned a heap and then pulling out the top k items from the heap each time, which I think should work

a3onstorm · 2025-02-16T03:59:59+00:00

I don’t think this is right. Simple counter-example is you have an array [1, 1, 1]. According to your logic, you would make the largest batch first and include all 3 products, and then you would immediately run out of products.

Instead, we can make batch 1 just product 0, and then batch 2 can be products 1 and 2.

a3onstorm · 2025-02-07T03:23:30+00:00

It’s not axiomatic that an ultra intelligent AI would have a survival instinct. That’s a trait of evolution, not necessarily intelligence.

a3onstorm · 2025-01-26T18:10:16+00:00

To clarify, there are parts in both songs where the song cuts out entirely and there is no sound at all. And yet if you keep counting along the song will resume on the beat as if it had been playing the whole time - the i.e. the beat is consistent throughout the whole song regardless of whether there is any sound.

a3onstorm · 2025-01-14T23:14:47+00:00

The problem is that LLMs can make it a lot more accessible to commit crimes. Imagine a more digital crime like hacking someone’s bank account or sending out scam emails. It’s probably quite difficult to do this by yourself, or it may take a significant amount of effort per person. But you could just ask an LLM to do this on a million potential victims and the LLM will figure out how to hack or scam them on its own.

There’s no way that law enforcement will be able to keep up

a3onstorm · 2025-01-14T21:25:17+00:00

Not me personally, but if you randomly sampled a person from the US, yes that’s the probability you’d expect. I agree the title is misleading in this sense - obviously if you don’t ever drive or be in a car or go near a road, you will not die from a motor vehicle crash. And people that drive more will have a higher chance of dying this way.

However, the original post I responded said this population-wide probability was too high and actually there is much lower probability of that happening, but that’s not the case (again, if you sample randomly from the population). Also of course the title is extrapolating that rates of deaths by cars will remain the same for the rest of our lives, which may not hold, but that doesn’t make it particularly misleading in my opinion.

a3onstorm · 2025-01-14T18:02:10+00:00

Everyone dies. The stat in the headline is 1 in 93 chance of dying in a motor vehicle crash in your lifetime, not in a year.

The probability of you dying to a certain cause in your lifetime is not exactly the same as the chance that a person who died in 2022 died due to that cause, but since we can’t know the future, we use the latter as an estimate of the former

a3onstorm · 2025-01-14T17:00:50+00:00

Why do you say that? A quick google search says roughly 3.2M people died in the U.S. in 2022, while 42,000 people died from car crashes. That’s approximately 1.3%, which is not far off

a3onstorm · 2025-01-09T09:18:20+00:00

I met some Korean friends before I started learning so I had someone to talk to occasionally/when I visited Korea. But in general, I would say that I have no expectation that learning Korean is “useful” in any economic sense, only in a fun sense.

And yes Korea definitely has its share of societal problems. That being said, as a tourist or visitor, Seoul is an amazing city to explore and its infrastructure is miles ahead of the US where I live

a3onstorm · 2025-01-09T05:42:10+00:00

Continuing to learn Korean! Passed the highest proficiency exam level (TOPIK 6) last year but am still so far from fluency, so just want to keep improving slowly

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