Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Launch HN: Replicate (YC W20) – Version control for machine learning

replicate.ai

Post reply on HN
Print view View original

31–40 of 57 posts

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#31

Post by bfirsh »

gitgud wrote: post #28

Congrats on the launch! What's the business concept behind the tool? Can't find anything on the homepage, or in the post. I didn't know YC funded opensource tools like this, it's kind of refreshing.

Yeah, YC is funding lots of open source projects. PostHog[0] was in our batch. GitLab, Docker, Mattermost, and CoreOS come to mind as other open source YC companies.

There are a number of businesses we could build around the project. A cloud service or enterprise products/support are the obvious ones. Right now, we're focused on community building, because a potential open source business can't be successful with a healthy open source project.

[0] https://news.ycombinator.com/item?id=22376732

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#32

Post by gitgud »

bfirsh wrote: post #31
gitgud wrote: post #28

Congrats on the launch! What's the business concept behind the tool? Can't find anything on the homepage, or in the post. I didn't know YC funded opensource tools like this, it's kind of refreshing.

Yeah, YC is funding lots of open source projects. PostHog[0] was in our batch. GitLab, Docker, Mattermost, and CoreOS come to mind as other open source YC companies. There are a number of businesses we could build around the project. A cloud service or enterprise products/support are the obvious ones. Right now, we're focused on community building, because a potential open source business can't be successful with a h…

> There are a number of businesses we could build around the project.

So you got funding from YCombinator without a concrete plan to make a business? That's pretty interesting, I always thought they wanted profitable businesses, and turned down ideas they didn't think would work.

Great to hear they're betting on open-source more!

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#33

Post by bfirsh »

gitgud wrote: post #32
bfirsh wrote: post #31

Earlier quoted context omitted.

Yeah, YC is funding lots of open source projects. PostHog[0] was in our batch. GitLab, Docker, Mattermost, and CoreOS come to mind as other open source YC companies. There are a number of businesses we could build around the project. A cloud service or enterprise products/support are the obvious ones. Right now, we're focused on community building, because a potential open source business can't be successful with a h…

> There are a number of businesses we could build around the project. So you got funding from YCombinator without a concrete plan to make a business? That's pretty interesting, I always thought they wanted profitable businesses, and turned down ideas they didn't think would work. Great to hear they're betting on open-source more!

Funnily we applied with a different thing. We tried a number of different ideas before we settled on this lower-level thing, as I describe in the main comment.

Even still, I think most people apply to YC without a concrete plan of how to make a business. It's normally so early stage, that the plan is yet to be validated and will probably change. A "plausible" plan is perhaps a better way to put it. ;)

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#34

Post by salty_biscuits »

bfirsh wrote: post #2

Hello HN! We're Ben & Andreas, and we made Replicate. It's a lightweight open-source tool for tracking and analyzing your machine learning experiments: https://replicate.ai/ Andreas used to do machine learning at Spotify. He built a lot of ML infrastructure there (versioning, training, deployment, etc). I used to be product manager for Docker's open source projects, and created Docker Compose. We built https://www.ar…

"...and hear your stories about how you’ve done this before."

Basically Mr Kurtz saying "The horror! The horror!" gives you the right impression.

For small datasets and short training times it isn't so bad, a deterministic training script on git and a dataset with gitlfs. So can easily reproduce the model when needed. Having to do this on very large datasets (that are possibly expensive to keep a copy of for just experiments and not prod) or really slow training times is basically disgusting. I'll be interested to see what you have done.

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#35

Post by bfirsh »

flc-anonym wrote: post #27

Congrats on the launch! This looks interesting, however I feel like this space is quite crowded. You mentioned that your most important feature is the fact that you are open-source, but off the top of my head I can think of several projects: * Kubeflow: https://github.com/kubeflow/kubeflow * MLFlow: https://github.com/mlflow/mlflow * Pachyderm: https://github.com/pachyderm/pachyderm * DVC: https://github.com/iterativ…

Yeah, I agree this space is crowded. But we’ve found so few ML researchers/engineers are actually using these tools. This could either be that people aren’t aware of them yet, or that they’re not good enough.

I think it’s a mix of both, honestly, but we’re betting that there’s more of the latter in the mix. :)

I could do comparisons of each of these tools, and some of them are solving quite different problems, but the overarching difference is we’re just trying to do less. These systems might make sense if you’re setting up a company’s ML pipeline, but we found lots of individuals struggling to keep track of their work and store their models. They balked at the idea of setting up things like Kubeflow or MLflow.

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#36

Post by konda »

mfDjB wrote: post #4

As someone who tried to use git to do this for large sets of data, I'm very glad this exists. Will be trying this out in the future.

I'd checkout dolthub.com! Dolt is built for git workflows (branches and merges) on top of large datasets.

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#37

Post by mlthoughts2018 »

bfirsh wrote: post #35
flc-anonym wrote: post #27

Congrats on the launch! This looks interesting, however I feel like this space is quite crowded. You mentioned that your most important feature is the fact that you are open-source, but off the top of my head I can think of several projects: * Kubeflow: https://github.com/kubeflow/kubeflow * MLFlow: https://github.com/mlflow/mlflow * Pachyderm: https://github.com/pachyderm/pachyderm * DVC: https://github.com/iterativ…

Yeah, I agree this space is crowded. But we’ve found so few ML researchers/engineers are actually using these tools. This could either be that people aren’t aware of them yet, or that they’re not good enough. I think it’s a mix of both, honestly, but we’re betting that there’s more of the latter in the mix. :) I could do comparisons of each of these tools, and some of them are solving quite different problems, but th…

Can you share any of the data or market research on this? I am an ML manager in a large ecommerce firm and we stand up our own feature store, experiment tracking system and model training diagnostic / metric system (a la Tensorboard). It is exceedingly easy to DIY, I’ve been doing that stuff DIY with teams of less than 8 engineers for many years.

What I’ve seen is that most vendor solutions aren’t flexible enough. Many firms have their own on-prem and data privacy restrictions that make hosting model training artifacts on a vendor’s servers impossible, and it’s way easier to sell building in house.

I’m very surprised you are hearing that nobody is using MLflow and Kubeflow (though Kubeflow has a lot of genuine usability and bug problems). I am hearing the exact opposite. Everybody, from tiny 5 person startups to giant ecommerce firms is just spinning up simple stuff for model tracking, mostly around MLflow.

Re: Launch HN: Replicate (YC W20) – Version control for machine learning

#38

Post by timsehn »

konda wrote: post #36
mfDjB wrote: post #4

As someone who tried to use git to do this for large sets of data, I'm very glad this exists. Will be trying this out in the future.

I'd checkout dolthub.com! Dolt is built for git workflows (branches and merges) on top of large datasets.

Thanks for the shout out here. CEO of DoltHub speaking :-)
Post reply on HN