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I expect this will be an unpopular opinion, but a proliferation of frameworks does not create value for anyone besides the developers employed in making it. Su

I expect this will be an unpopular opinion, but a proliferation of frameworks does not create value for anyone besides the developers employed in making it. Sure different frameworks handle different uses better than others, but it doesn't change the fact that in a given genre (machine learning, web frontend, ORM, etc.) that there is a lot of duplication going on. If you want to look cool and impress people, make a tool that doesn't exist, develop a new algorithm, or contribute a great feature to an existing framework.

xbeta 9y ago
Sure, you sound like anyone can just have a eureka moment and come up with an algorithm. Uber has a legitimate use-case that fits their needs on ML, so they build it for that need. And why not just also talk about it too as a lesson-learned for others. Do you simply have very high expectation of everything in this world?
- jackyinger 9y ago
  There are plenty of meaningful ways to contribute to the body of open source software that don't require strokes of genius. Bug fixes and refactoring come to mind. I just picked this thread as a starting point Uber may have a legit need for a particular framework. My main point is there is no need to make frameworks for frameworking's sake. Purposeful OSS collaboration is just as good, if not a better way to gain influence than a PR splash. Of course that assumes that the goal is to make cool things, which seems loosely connect with wooing investors at best. (Again in general, not picking on Uber.)
  - xbeta 9y ago
    I don't work in Uber's team on ML, so I can't answer this, but I also cannot just simply assume everything is built-for-PR-splash. You can argue why can't they simply talk about the reason of not reusing any existing OSS framework than building yourself, but making an assumption that they did it for the sake of PR is lack of factual support. Are we now living in a world assuming everything Uber did was for PR? Last I heard they had 1500+ engineers and with that size, I am sure they can just talk about things they have done in the last few years.
lwansbrough 9y ago
That's how I feel about most projects I see on here. Toy languages are my personal pet peeve. So much talent being wasted on useless projects. I'm not really one to speak - none of my projects make a substantially positive impact on society, but they have their niches.
- gfodor 9y ago
  Do you really feel this way? It seems like a pretty strange world view to think that someone posting a thing they built on a site called hacker news implores you to judge their talent as being wasted, or their project as being useless. Not only does it seem wrong to judge things people post here that way, anyone out there doing good work knows that the path to doing meaningful work begins with "useless projects."
  - lwansbrough 9y ago
    The reality for the people who post on here is that most of us aren't doing anything truly substantial. I include myself in that group. You can believe your IOT AI messenger bot is going to revolutionize an industry, but the more likely situation is that it doesn't. That being said, such a project is not something I'd consider useless, but it's in the same range as the things I do consider useless. Take toy languages for example: could it revolutionize software development? Maybe. Will it? Almost certainly not. How many languages are commonly used in software engineering, and how much ability have you gained by doing it? It's not for me to say where you apply your time and from what you get your enjoyment from, but I do believe there are objectively more important problems that could be solved. There are plenty of problems out there that need to be solved, and engineers here have the capability to solve them -- I think it's fair to say we're more well equipped than most to solve some of the largest problems humans face. Here's a quick list of problems that are worth solving (in my opinion), vs. things that are figuratively useless: - Rising global temperatures will disrupt agriculture and food supplies, how will we farm when desertification consumes the croplands? - Thousands of people walk by homeless people on the street every day, if a small portion of those people stopped and engaged with the homeless, how many lives could be improved? - Children in third world countries struggle to receive proper education, how can we reach them and improve their education? - Governments around the world are failing to represent the needs and desires of their people, what can be done to help governments succeed? - Growing levels of automation are replacing a staggering number of jobs, and if the growth continues, the great depression will be ahead of us, not behind us. - Global financial markets are controlled by companies which you and I have no say in, yet they hold most of the worlds wealth. In contrast: - I want X programming language that does Y because Z doesn't do Y, in all likelihood, I will be the only one who ever uses this language, but it'll be a personal accomplishment. - I don't want to leave the house or stop working for half an hour to make a meal, how can I improve/speed up the time it takes for me to get a meal from my favourite restaurant? - Making X sucks, I want a robot to do it - Bad AI for X - IOT for X - Framework for X - Uber for X How often do I see the latter vs. the former? Imagine if you saw FOSS projects attempting to solve problems on the first list as often as you saw projects attempting to solve problems on the second list. I truly believe the world would be a better place if that was the case. I said earlier I'm guilty of this myself. I build consumer facing supporting software for entertainment media. I like what I do, but I don't think I'm contributing much to society, and that makes me uneasy.
rockinghigh 9y ago
Have you read the article? Michelangelo is a platform, not a framework. It abstracts the underlying frameworks.
deleted 9y ago
[deleted]
thewhitetulip 9y ago
Yes, but in some cases a platform and framework do help in formalizing things.
deleted 9y ago
[deleted]
bayonetz 9y ago
In this particular genre there are no off-the-shelf platforms or even accepted set of best practices for something as comprehensive as this for generalized ML pipelining infrastructure. It's still very Wild West. I've done a lot of research into what pipelines look like at different companies and cloud providers and I can tell you this is a nice one. Some have a good training story, some have a good deployment story, some have a good experimentation story, and so on but none have all the things. Projects like Tensorflow Serving and PipelineAI are heading there but still quite a lot missing compared with something like what was presented here.
buremba 9y ago
Your comment is indeed not helpful and prevents people to open-source their work unless they think that it is awesome. This tool may not be great but can inspire similar tools or may be helpful for developers who want to learn how to develop a software similar to this one, or attack developers to contribute the project and eventually may become a standard tool as UI for ML pipelines etc.
Maro 9y ago
This is like FB's FBLearner, which I've used a little bit. This is a platform, so this is not at at the SKL/Tensorflow/Caffe level, this is something which says: put your data in our data warehouse in this format, tell me what model you want to run on it, go have a coffee, and by the time you're back I'll magically run your model on a big cluster quickly; if you want I can also try out different hyperparams/models, and I'll give you standard plots/metrics to evaluate the thing. You can also use 1000s of existing feature vectors/metrics that other people have put in the DWH. You can also clone an existing model and tweak that. If you're happy with the model, you can deploy, either on my API by querying and I'll tell you the prediction, or I can publish the model in binary form to a datastore and you can just import it in your iOS code in 3 lines. You can also schedule nightly re-trains, I'll notify you if something big changes in the accuracy metrics, etc. The point is, this sort of ML platform allows engineers at big companies to leverage existing data/metrics/f.vectors, models, infra, etc. and allows them to move 10-100x faster than startups/hobbyists. When I say 10-100x, I actually mean it, I'm also running ML models at home, and the amount of time I waste on this glue stuff is huge (starting from data prep to f---ing around with tensor ranks). I'm sure there are already startups working on platforms like this for everybody, we'll just have to wait for one of those to become good.
- MasterScrat 9y ago
  > I'm sure there are already startups working on platforms like this for everybody Does anyone knows of any such open-source product actually usable today? This would solve a real need. (Also I'd love to work on such a thing)
  - Kpourdeilami 9y ago
    I've been working on something very similar to that. It allows you to connect a SQL database, S3 bucket, etc. then write a query for the data that you want to train the model on. It takes a couple minutes and then it'll expose the trained model over a REST endpoint. It also has feedback loops to fine tune the model on real-time data and has an option to store all the predictions made by model into Redshift or S3 to be visualized on a tool like Tableau. The tool itself is not open-source but it can be installed on the user's AWS, Azure, or GCP account to keep their models and data private. It's still in alpha testing (bunch of pilots) and I'll probably do a "Show HN" post when it is ready for a public beta
gaius 9y ago
It's a bet similar to a startup - your "framework" might not be popular but if it is - for no particular reason other than a cool name and lots of retweets - then you are sorted. How many JS "frameworks" are there now?

xbeta 9y ago

Sure, you sound like anyone can just have a eureka moment and come up with an algorithm. Uber has a legitimate use-case that fits their needs on ML, so they build it for that need. And why not just also talk about it too as a lesson-learned for others. Do you simply have very high expectation of everything in this world?

jackyinger 9y ago
There are plenty of meaningful ways to contribute to the body of open source software that don't require strokes of genius. Bug fixes and refactoring come to mind. I just picked this thread as a starting point Uber may have a legit need for a particular framework. My main point is there is no need to make frameworks for frameworking's sake. Purposeful OSS collaboration is just as good, if not a better way to gain influence than a PR splash. Of course that assumes that the goal is to make cool things, which seems loosely connect with wooing investors at best. (Again in general, not picking on Uber.)
- xbeta 9y ago
  I don't work in Uber's team on ML, so I can't answer this, but I also cannot just simply assume everything is built-for-PR-splash. You can argue why can't they simply talk about the reason of not reusing any existing OSS framework than building yourself, but making an assumption that they did it for the sake of PR is lack of factual support. Are we now living in a world assuming everything Uber did was for PR? Last I heard they had 1500+ engineers and with that size, I am sure they can just talk about things they have done in the last few years.

lwansbrough 9y ago

That's how I feel about most projects I see on here. Toy languages are my personal pet peeve. So much talent being wasted on useless projects. I'm not really one to speak - none of my projects make a substantially positive impact on society, but they have their niches.

gfodor 9y ago
Do you really feel this way? It seems like a pretty strange world view to think that someone posting a thing they built on a site called hacker news implores you to judge their talent as being wasted, or their project as being useless. Not only does it seem wrong to judge things people post here that way, anyone out there doing good work knows that the path to doing meaningful work begins with "useless projects."
- lwansbrough 9y ago
  The reality for the people who post on here is that most of us aren't doing anything truly substantial. I include myself in that group. You can believe your IOT AI messenger bot is going to revolutionize an industry, but the more likely situation is that it doesn't. That being said, such a project is not something I'd consider useless, but it's in the same range as the things I do consider useless. Take toy languages for example: could it revolutionize software development? Maybe. Will it? Almost certainly not. How many languages are commonly used in software engineering, and how much ability have you gained by doing it? It's not for me to say where you apply your time and from what you get your enjoyment from, but I do believe there are objectively more important problems that could be solved. There are plenty of problems out there that need to be solved, and engineers here have the capability to solve them -- I think it's fair to say we're more well equipped than most to solve some of the largest problems humans face. Here's a quick list of problems that are worth solving (in my opinion), vs. things that are figuratively useless: - Rising global temperatures will disrupt agriculture and food supplies, how will we farm when desertification consumes the croplands? - Thousands of people walk by homeless people on the street every day, if a small portion of those people stopped and engaged with the homeless, how many lives could be improved? - Children in third world countries struggle to receive proper education, how can we reach them and improve their education? - Governments around the world are failing to represent the needs and desires of their people, what can be done to help governments succeed? - Growing levels of automation are replacing a staggering number of jobs, and if the growth continues, the great depression will be ahead of us, not behind us. - Global financial markets are controlled by companies which you and I have no say in, yet they hold most of the worlds wealth. In contrast: - I want X programming language that does Y because Z doesn't do Y, in all likelihood, I will be the only one who ever uses this language, but it'll be a personal accomplishment. - I don't want to leave the house or stop working for half an hour to make a meal, how can I improve/speed up the time it takes for me to get a meal from my favourite restaurant? - Making X sucks, I want a robot to do it - Bad AI for X - IOT for X - Framework for X - Uber for X How often do I see the latter vs. the former? Imagine if you saw FOSS projects attempting to solve problems on the first list as often as you saw projects attempting to solve problems on the second list. I truly believe the world would be a better place if that was the case. I said earlier I'm guilty of this myself. I build consumer facing supporting software for entertainment media. I like what I do, but I don't think I'm contributing much to society, and that makes me uneasy.

rockinghigh 9y ago

Have you read the article? Michelangelo is a platform, not a framework. It abstracts the underlying frameworks.

deleted 9y ago

[deleted]

thewhitetulip 9y ago

Yes, but in some cases a platform and framework do help in formalizing things.

deleted 9y ago

[deleted]

bayonetz 9y ago

In this particular genre there are no off-the-shelf platforms or even accepted set of best practices for something as comprehensive as this for generalized ML pipelining infrastructure. It's still very Wild West. I've done a lot of research into what pipelines look like at different companies and cloud providers and I can tell you this is a nice one. Some have a good training story, some have a good deployment story, some have a good experimentation story, and so on but none have all the things. Projects like Tensorflow Serving and PipelineAI are heading there but still quite a lot missing compared with something like what was presented here.

buremba 9y ago

Your comment is indeed not helpful and prevents people to open-source their work unless they think that it is awesome. This tool may not be great but can inspire similar tools or may be helpful for developers who want to learn how to develop a software similar to this one, or attack developers to contribute the project and eventually may become a standard tool as UI for ML pipelines etc.

Maro 9y ago

This is like FB's FBLearner, which I've used a little bit. This is a platform, so this is not at at the SKL/Tensorflow/Caffe level, this is something which says: put your data in our data warehouse in this format, tell me what model you want to run on it, go have a coffee, and by the time you're back I'll magically run your model on a big cluster quickly; if you want I can also try out different hyperparams/models, and I'll give you standard plots/metrics to evaluate the thing. You can also use 1000s of existing feature vectors/metrics that other people have put in the DWH. You can also clone an existing model and tweak that. If you're happy with the model, you can deploy, either on my API by querying and I'll tell you the prediction, or I can publish the model in binary form to a datastore and you can just import it in your iOS code in 3 lines. You can also schedule nightly re-trains, I'll notify you if something big changes in the accuracy metrics, etc. The point is, this sort of ML platform allows engineers at big companies to leverage existing data/metrics/f.vectors, models, infra, etc. and allows them to move 10-100x faster than startups/hobbyists. When I say 10-100x, I actually mean it, I'm also running ML models at home, and the amount of time I waste on this glue stuff is huge (starting from data prep to f---ing around with tensor ranks). I'm sure there are already startups working on platforms like this for everybody, we'll just have to wait for one of those to become good.

MasterScrat 9y ago
> I'm sure there are already startups working on platforms like this for everybody Does anyone knows of any such open-source product actually usable today? This would solve a real need. (Also I'd love to work on such a thing)
- Kpourdeilami 9y ago
  I've been working on something very similar to that. It allows you to connect a SQL database, S3 bucket, etc. then write a query for the data that you want to train the model on. It takes a couple minutes and then it'll expose the trained model over a REST endpoint. It also has feedback loops to fine tune the model on real-time data and has an option to store all the predictions made by model into Redshift or S3 to be visualized on a tool like Tableau. The tool itself is not open-source but it can be installed on the user's AWS, Azure, or GCP account to keep their models and data private. It's still in alpha testing (bunch of pilots) and I'll probably do a "Show HN" post when it is ready for a public beta

gaius 9y ago

It's a bet similar to a startup - your "framework" might not be popular but if it is - for no particular reason other than a cool name and lots of retweets - then you are sorted. How many JS "frameworks" are there now?