kingcai

9 ms·

1.
by kingcai 2mo ago
https://jcaip.github.io/ I actually recently updated this for the first time in 5 years!
2.
by kingcai 2y ago
This is cool. Kudos to the team too - I feel like this is what engineerings all about.
3.
by kingcai 2y ago
I've recently been in a rut and while I still have a lot further to go I've been feeling better over the last couple of days and here's what helped: - going to therapy - taking PTO - going outside - hanging out with friends -
4.
by kingcai 3y ago
ML training is not as easily parallelizable as the other problems that have been explored. I'm not familiar with SETI but I know this to be true for folding@home. As you mentioned, ML training can be parallelized but this requires eith
5.
by kingcai 4y ago
I graduated in 2020 and was considering doing a PhD in NLP as I had already been doing research at a lab. I ended up joining a series A startup, trying to turn research into products. I don't regret it much, as I was tired of being a b
6.
by kingcai 4y ago
I like this post a lot, even if it's a somewhat contrived example. In particular I like his point about switch statements making it easier to pulled out shared logic vs. polymorphic code. There's so much emphasis on writing "
7.
by kingcai 4y ago
Hi, I wrote this blog post about startup equity a couple of years ago that answers a lot of the questions you asked, I hope you find it helpful. https://jcaip.github.io/Startup-Equity-TLDR/ You negotiate around dilutio
8.
by kingcai 4y ago
In general I would say expert knowledge is more valuable. However, I think of knowledge as a pyramid - how high you can go is determined by how wide/strong your foundation is. In my experience I've found that trying to develop dee
9.
by kingcai 4y ago
RTO = return to office
10.
by kingcai 4y ago
Very uncommon for people to do ML locally nowadays. Almost everyone uses either cloud or has an cluster they ssh into. NVIDIA is still king for ML, very few people use AMD / M1, although hopefully that will change. If you want to buy a
11.
by kingcai 4y ago
I work on FOSS (pytorch) that I used to use a lot during research. It feels like I've come full circle and I'm giving back. Also I'm well compensated and surrounded by smart and kind people.
12.
by kingcai 4y ago
It's somewhat common in the industry for your employer to give you a stipend to buy equipment / tools / learning materials you like. I would get him the gaming console, but otherwise maybe nice headphones?
13.
by kingcai 4y ago
Absolutely brilliant!
14.
by kingcai 4y ago
My total comp is ~300k, 200 of which is in cash.
15.
by kingcai 4y ago
I think it's really hard to think up of curriculum for a "programming" class. It'd be hard to standardize across different professors. Also while I do think that more programming experience would benefit most new grads,
16.
by kingcai 4y ago
Startups are also not profitable yet and are reliant on fundraising in order to continue to operate. The fundraising market is bleak currently, so there's pressure to reduce burn.
17.
by kingcai 4y ago
I found reading more code helped me to become a better programmer. It helps a lot that reading code (at least for me) is much faster than writing code, so you can do more of it.
18.
by kingcai 4y ago
Old techniques are just as good as the new ones :) If you have a specific problem you are trying to solve, I'd recommend just reading papers and looking up things you don't understand. Otherwise, if you're just looking for g
19.
by kingcai 4y ago
It's an unavoidable part of the job, but it's definitely not most of the work. I feel it's kind of like writing tests in SWE - something you do because it's beneficial even if it's not enjoyable.
20.
by kingcai 4y ago
My best advice is to find people who do what you want to do and try to learn as much as possible from them. If you're interested in doing ML/DL research I think the best way to get into the field is to reach out to professors. I s
21.
by kingcai 5y ago
Other users advice about traveling, relaxing, and exercising is spot on, but probably not what you were looking for. Besides these are things you should do for a lifetime, not just a summer. I know you mentioned working at a research lab bu
22.
by kingcai 5y ago
Sure. I don't work in the ecommerce space, but I think the big problem that industry is attempting to solve right now is - "how can we take off the shelf language models and use them to do things that make us money?". This is
23.
by kingcai 5y ago
For academia: I expect that FAANG will continue to produce larger and larger language models as well. Probably new improvements in multi-task learning to keep on increasing model size - this will probably take ideas from relational / c
24.
by kingcai 5y ago
I saw this quote on a tombstone and it really resonated with me. What is success? To laugh often and much; to win the respect of intelligent people and the affection of children; to earn the appreciation of honest critics and endu
25.
by kingcai 5y ago
I've used Snorkel quite a bit at work, usually combined with transformers models. It has worked quite well for us. The snorkel public package is a bit out of date now, as I think they're building a SaaS solution and focusing more
26.
by kingcai 5y ago
I did a little analysis on this back in 2020 (pre-covid) when I was job searching: https://jcaip.github.io/Startup-Equity-TLDR/ Hope it's helpful!
27.
Distributed Gradient Descent for PyTorch
4 points by kingcai 8y ago|0 comments
28.
Predicting Loan Application Submission(blend.com)
5 points by kingcai 9y ago|0 comments