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I look forward to learned models as a service. Which you can then script to do more intelligent things. This stuff is too low level for me. In fact that's a gre
by devoply 10y ago
I look forward to learned models as a service. Which you can then script to do more intelligent things. This stuff is too low level for me. In fact that's a great idea for a startup. Learned models as a service via an API.
- lowglow 10y agoThis is what we're working on over at Asteria. It's been fun and challenging. It's still early days, but we're running HITL feedback for model building as well.
- wiradikusuma 10y agoYou mean like https://cloud.google.com/ml/ https://cloud.google.com/ml/ ?
- devoply 10y agoMore like this https://cloud.google.com/vision/ https://cloud.google.com/vision/
- ai_maker 10y agoThere are API aggregation sites like Mashape that are already working toward this goal. My startup thing is about using learned models for text processing [1]. Quick tests are also available here [2]. [1] https://market.mashape.com/atrilla/nlptools https://market.mashape.com/atrilla/nlptools [2] http://nlptools.atrilla.net/web/api.php http://nlptools.atrilla.net/web/api.php
- skewart 10y agoI've thought about that too. I could imagine a near future where people build models and sell access to them in a marketplace, either for direct use or transfer learning - sort of like breeding farm animals. Perhaps in five to ten years neural net farming, or learning agent husbandry, will be common ways for people to earn a living.
- visarga 10y agoCurrently, there is a lot of reinventing the wheel. Many models start from scratch instead of transferring already good results from past models. It should be easy to plug vision models, audio processing models, behavior models together, the way we use various libraries in programming.
- formula_ninguna 10y agoif everyone is going to earn a living doing the same thing, it'll become easy accessible and understood by everyone and thus it'll defeat its own purpose.
- visarga 10y ago> I look forward to learned models as a service. My current disappointment with machine learning as a service is pricing. For example, the same job that could be solved by a cheap $5/month instance with open source software, would cost $45/day if it were implemented in Google's Cloud Prediction API. My task was to classify news and I had a volume of about 100K examples to classify per day. Why would cloud API cost hundreds of times more?
- dekhn 10y agoThat $45/day vs. $5/month comparison ignores the set up and maintenance costs of your personal instance. You would also have to train models, keep them up to date, etc. If you are happy trading your dev time that way, fine, but the value proposition of APIs are clear.