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There is a difference between consuming models and training them yourself -- I could be wrong but with tensorflow.js I think it is much more geared toward consu

There is a difference between consuming models and training them yourself -- I could be wrong but with tensorflow.js I think it is much more geared toward consuming models in the browser, rather than training novel ones yourself. Seems like you can customize an existing model via transfer learning, which may or may not be good enough for your usecase, but even then I feel like basically the training side of it is second rate. But you could potentially make _predictions_ with a really sophisticated/cutting edge model in JS -- its not the prediction part that takes enormous compute, it is the training part

memexy 6y ago
You can also build and train models in js. This is one of the features I'm looking at. Currently there is a lot of information websites are throwing away or they're using centralized aggregation mechanisms to provide personalization but Tensorflow.js changes that dynamic. I think small AI models that run completely in the browser and provide personalization by learning from how the user interacts with a given website are the future. This empowers the user and puts them in charge of how their data is used. The example I mentioned previously to demonstrate this was about ranking new submissions on HN: https://news.ycombinator.com/item?id=23407549 https://news.ycombinator.com/item?id=23407549. I'll quote the relevant part > TensorFlow.js is a pretty nifty piece of software and it's underutilized. If the model parameters can be stored in IndexedDB then users could train TensorFlow.js based site augmentation to suit their own needs. For example, what if HN had a TensorFlow.js model for ranking new submissions based on the user's preferences? This model could be trained like a spam filter and would eventually learn the types of articles that someone likes to see but they would be in charge of the model's evolution and so would be empowered to use it however they saw fit. Maybe I don't care about politics then my model parameters would eventually converge on downgrading all political posts and the more technical submissions would rise to the top based on how I upvoted new and front page submissions.
- darepublic 6y ago
  Cool idea, but why not have that client side model operate across websites -- if I switch from hacker news to reddit why not carry over that data to figure out what I will like on the separate platform?
  - memexy 6y ago
    Excellent idea. Yes, you could do that as well. Nothing would prevent copying the parameters and models for one site and using at another one since at the end of the day it would all just be data controlled by the user. One can even imagine a decentralized sharing mechanism where users can create ensembles of models by combining models trained by different users. All the building blocks are there. Just requires mindshare and a few killer applications.
- sroussey 6y ago
  This is a cool idea, but requires some hooks. Otherwise, you also need api access and remake the UI. I guess you could intercept API calls with a browser extension, but having a hook for you personalization so would be great!

memexy 6y ago

You can also build and train models in js. This is one of the features I'm looking at. Currently there is a lot of information websites are throwing away or they're using centralized aggregation mechanisms to provide personalization but Tensorflow.js changes that dynamic. I think small AI models that run completely in the browser and provide personalization by learning from how the user interacts with a given website are the future. This empowers the user and puts them in charge of how their data is used. The example I mentioned previously to demonstrate this was about ranking new submissions on HN: https://news.ycombinator.com/item?id=23407549 https://news.ycombinator.com/item?id=23407549. I'll quote the relevant part > TensorFlow.js is a pretty nifty piece of software and it's underutilized. If the model parameters can be stored in IndexedDB then users could train TensorFlow.js based site augmentation to suit their own needs. For example, what if HN had a TensorFlow.js model for ranking new submissions based on the user's preferences? This model could be trained like a spam filter and would eventually learn the types of articles that someone likes to see but they would be in charge of the model's evolution and so would be empowered to use it however they saw fit. Maybe I don't care about politics then my model parameters would eventually converge on downgrading all political posts and the more technical submissions would rise to the top based on how I upvoted new and front page submissions.

darepublic 6y ago
Cool idea, but why not have that client side model operate across websites -- if I switch from hacker news to reddit why not carry over that data to figure out what I will like on the separate platform?
- memexy 6y ago
  Excellent idea. Yes, you could do that as well. Nothing would prevent copying the parameters and models for one site and using at another one since at the end of the day it would all just be data controlled by the user. One can even imagine a decentralized sharing mechanism where users can create ensembles of models by combining models trained by different users. All the building blocks are there. Just requires mindshare and a few killer applications.
sroussey 6y ago
This is a cool idea, but requires some hooks. Otherwise, you also need api access and remake the UI. I guess you could intercept API calls with a browser extension, but having a hook for you personalization so would be great!