4 ms·

Jup, MS Colab is one of the many commercial Jupyter/IPython notebooks available. There are also Y-combinator startups like https://deepnote.com/ https://deepnot

by ktpsns 6y ago

Jup, MS Colab is one of the many commercial Jupyter/IPython notebooks available. There are also Y-combinator startups like https://deepnote.com/ https://deepnote.com/ I hope that these closed source commercial platforms give back something to the open source community around Jupyter once they get out of the red numbers.

klelatti 6y ago
Indeed and they all use their own notebook interface which are (in my view) inferior or at least no better than JupyterLab. I get that they feel the need to add their own features (collaboration etc) to distinguish themselves but it would be so much better if they had settled on a single UI.
- Jugurtha 6y ago
  We do use JupyterLab for the notebook experience on https://iko.ai https://iko.ai. I had a chat with one of the core members of the project using real-time-collaboration when they were trying iko.ai. We chatted on the notebook itself. What I explained was that in our experience of many years doing paid machine learning projects for large enterprise, we never thought to ourselves: "Darn, if only Jupyter[Lab] had better stylesheets, this project would go so much faster." It has never happened. When we started building our platform, we were not in the position of front-end devs trying to make a better notebook, we were in the position of a company with deliverables for yesterday, and we naturally started solving for actual problems doing machine learning for real clients, as opposed to finding windmills to fight. In our experience, projects are slow not for lack of better stylesheets or animations. Therefore, we ignored that and focused on removing frustrations we had in the real world: long-running notebook scheduling, automatic experiment tracking for parameters, metrics, models, and code. Model deployment and monitoring. Real-time editing. That's why I don't really follow news about "jupyter-killers". I kept an eye out of curiosity, but every time one pops out, they solved things that don't matter much, or claimed they solved hidden state until you read the article and found they're caching results or something like that.
  - klelatti 6y ago
    Thanks - I've just signed up for an account and it looks really good! I'll say hello on Slack in a moment. We've been working on a JupyterLab based product for the insurance industry - not machine learning but shares a lot of the features - e.g. possibly long running models etc. Trying to land our first (fairly large) customer at the moment! Can you share any more on what your plans are especially from a business perspective?
    - Jugurtha 6y ago
      >We've been working on a JupyterLab based product for the insurance industry - not machine learning but shares a lot of the features - e.g. possibly long running models etc Cool. Do you have a link I could check out? I exchanged with someone a few days ago who is working /has worked in the insurance sector. Could you send me your contact information or add it to your profile? I'll ask them if they're interested in getting in touch with you or take a look at your product. >Trying to land our first (fairly large) customer at the moment! Nice. We're coming at it from the other way: we've had organizations as clients for our consultancy and we built complete custom machine learning solutions for them [as in, sometimes doing 3D printing to serve data acquisition, writing libraries for BLE devices, to the models, and web/mobile apps, as they wanted us to completely handle everything]. After doing that for many years, we clustered problems we consistently ran into, and then decided to build our internal platform to help us deliver better. >Can you share any more on what your plans are especially from a business perspective? First, keep our sanity. It feels really good to see all the tedious work we don't have to do anymore on the consulting side because of what our tool does for us. We continue to do consulting to keep our finger on the pulse, plus the problems we solve are really cool and diverse.
      - klelatti 6y ago
        We're very, very niche so we don't even have a presence on the web yet - route to market will be through corporate advisors so it's not something we'd expect clients to sign up for online etc. Very happy to do demo or share more information though. I'll send contact details on Slack. The application is to do long term financial projections for life insurers. Currently market dominated by applications such as FIS Prophet and Risk Agility - but we believe that we're a) faster and b) better integrated with other data / analysis tools. These jobs can be enormously compute intensive (eg see [1]) so being able to do them faster / with less resources can be very valuable. Glad you're keeping your sanity. Very impressed with the utility of what you're doing. [1] https://integrate.milliman.com/-/media/integrate/pdfs/azure-batch-job.ashx https://integrate.milliman.com/-/media/integrate/pdfs/azure-...

by ktpsns 6y ago

klelatti 6y ago

Indeed and they all use their own notebook interface which are (in my view) inferior or at least no better than JupyterLab. I get that they feel the need to add their own features (collaboration etc) to distinguish themselves but it would be so much better if they had settled on a single UI.

Jugurtha 6y ago
We do use JupyterLab for the notebook experience on https://iko.ai https://iko.ai. I had a chat with one of the core members of the project using real-time-collaboration when they were trying iko.ai. We chatted on the notebook itself. What I explained was that in our experience of many years doing paid machine learning projects for large enterprise, we never thought to ourselves: "Darn, if only Jupyter[Lab] had better stylesheets, this project would go so much faster." It has never happened. When we started building our platform, we were not in the position of front-end devs trying to make a better notebook, we were in the position of a company with deliverables for yesterday, and we naturally started solving for actual problems doing machine learning for real clients, as opposed to finding windmills to fight. In our experience, projects are slow not for lack of better stylesheets or animations. Therefore, we ignored that and focused on removing frustrations we had in the real world: long-running notebook scheduling, automatic experiment tracking for parameters, metrics, models, and code. Model deployment and monitoring. Real-time editing. That's why I don't really follow news about "jupyter-killers". I kept an eye out of curiosity, but every time one pops out, they solved things that don't matter much, or claimed they solved hidden state until you read the article and found they're caching results or something like that.
- klelatti 6y ago
  Thanks - I've just signed up for an account and it looks really good! I'll say hello on Slack in a moment. We've been working on a JupyterLab based product for the insurance industry - not machine learning but shares a lot of the features - e.g. possibly long running models etc. Trying to land our first (fairly large) customer at the moment! Can you share any more on what your plans are especially from a business perspective?
  - Jugurtha 6y ago
    >We've been working on a JupyterLab based product for the insurance industry - not machine learning but shares a lot of the features - e.g. possibly long running models etc Cool. Do you have a link I could check out? I exchanged with someone a few days ago who is working /has worked in the insurance sector. Could you send me your contact information or add it to your profile? I'll ask them if they're interested in getting in touch with you or take a look at your product. >Trying to land our first (fairly large) customer at the moment! Nice. We're coming at it from the other way: we've had organizations as clients for our consultancy and we built complete custom machine learning solutions for them [as in, sometimes doing 3D printing to serve data acquisition, writing libraries for BLE devices, to the models, and web/mobile apps, as they wanted us to completely handle everything]. After doing that for many years, we clustered problems we consistently ran into, and then decided to build our internal platform to help us deliver better. >Can you share any more on what your plans are especially from a business perspective? First, keep our sanity. It feels really good to see all the tedious work we don't have to do anymore on the consulting side because of what our tool does for us. We continue to do consulting to keep our finger on the pulse, plus the problems we solve are really cool and diverse.
    - klelatti 6y ago
      We're very, very niche so we don't even have a presence on the web yet - route to market will be through corporate advisors so it's not something we'd expect clients to sign up for online etc. Very happy to do demo or share more information though. I'll send contact details on Slack. The application is to do long term financial projections for life insurers. Currently market dominated by applications such as FIS Prophet and Risk Agility - but we believe that we're a) faster and b) better integrated with other data / analysis tools. These jobs can be enormously compute intensive (eg see [1]) so being able to do them faster / with less resources can be very valuable. Glad you're keeping your sanity. Very impressed with the utility of what you're doing. [1] https://integrate.milliman.com/-/media/integrate/pdfs/azure-batch-job.ashx https://integrate.milliman.com/-/media/integrate/pdfs/azure-...