3 ms·

Hey- Jared here! I am one of the founders of Magniv. Let me know if you have any questions. We are excited to get this in the hands of beta testers in the commu

by jzone3 5y ago

Hey- Jared here! I am one of the founders of Magniv. Let me know if you have any questions. We are excited to get this in the hands of beta testers in the community :)

eatonphil 5y ago
The site says open-source but there's no link to code, only a suggestion to sign up for early access?
- jzone3 5y ago
  Yes we are still very early! The core framework will be released to design partners first then to the community.
  - torbTurret 5y ago
    So it’s not currently open-sourced? How did this make it to the front-page - it’s basically nothing more than an advertisement at this stage? Am I misinterpreting something?
    - jonpon 5y ago
      We are looking for people to join the beta -- we are basically offering them free engineering. I guess there are enough people who find this relevant to vote us onto the front page. Would you be interested in the beta? :)
      - torbTurret 5y ago
        Touché! Not at the moment but best of luck with the product. Rereading my initial comment came off more hostile than I wanted, so thanks for the level-headed response :)
      - pvg 5y ago
        Signups can't be Show HN's, take a look at https://news.ycombinator.com/showhn.html https://news.ycombinator.com/showhn.html Show HN is for things people can try right now.
adolph 5y ago
It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products? It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean? https://github.com/allegroai/clearml https://github.com/allegroai/clearml https://codeocean.com/ https://codeocean.com/
- jonpon 5y ago
  Yeah, so one of our differentiating points is that we can integrate with whatever scheduler you are already using. On top of that a lot of the libraries that exist are focused on ML, focusing on resources/gpu etc. We are more focused on the data science side of this problem. Similar though.

by jzone3 5y ago

Hey- Jared here! I am one of the founders of Magniv. Let me know if you have any questions. We are excited to get this in the hands of beta testers in the community :)

eatonphil 5y ago

The site says open-source but there's no link to code, only a suggestion to sign up for early access?

jzone3 5y ago
Yes we are still very early! The core framework will be released to design partners first then to the community.
- torbTurret 5y ago
  So it’s not currently open-sourced? How did this make it to the front-page - it’s basically nothing more than an advertisement at this stage? Am I misinterpreting something?
  - jonpon 5y ago
    We are looking for people to join the beta -- we are basically offering them free engineering. I guess there are enough people who find this relevant to vote us onto the front page. Would you be interested in the beta? :)
    - torbTurret 5y ago
      Touché! Not at the moment but best of luck with the product. Rereading my initial comment came off more hostile than I wanted, so thanks for the level-headed response :)
    - pvg 5y ago
      Signups can't be Show HN's, take a look at https://news.ycombinator.com/showhn.html https://news.ycombinator.com/showhn.html Show HN is for things people can try right now.

adolph 5y ago

It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products? It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean? https://github.com/allegroai/clearml https://github.com/allegroai/clearml https://codeocean.com/ https://codeocean.com/

jonpon 5y ago
Yeah, so one of our differentiating points is that we can integrate with whatever scheduler you are already using. On top of that a lot of the libraries that exist are focused on ML, focusing on resources/gpu etc. We are more focused on the data science side of this problem. Similar though.