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Is AI right now useful as a way to provide value for small projects or startups? Any examples of that? It feels like most examples of commercial AI usage are f

by devit 11y ago

Is AI right now useful as a way to provide value for small projects or startups? Any examples of that? It feels like most examples of commercial AI usage are features (image search, automatic face tagging, etc.) that get added to existing products by large companies with access to large datasets and computing power.

deleted 11y ago
[deleted]
losteric 11y ago
I've been working on a side project to pulled news articles and gave me summaries of trends I might be interested in. I'm learning so the results are pretty poor... but so far I've spent less than $50/week running the project on AWS. You could go cheaper with spot instances/etc too. Some big deep learning projects might be beyond small projects/startups, but I think AI is reasonable if you work methodically. edit: $50, not $100.
- hobs 11y ago
  Let me know how it works out if you want any beta testers, I have a slack/mumble integration I wrote that captures all the links we post, and I would love to be able to summarize what the link was about and offer that as well.
  - samcodes 11y ago
    If you want to build a bot that does exactly what you are talking about, I just wrote an article [1] on how to do that! It uses an API with 1000 free calls per month, and is easy to host on your own servers or Heroku. [1] https://medium.com/@samhavens/building-somerset-d518ba284c49#.6ok3azfqz https://medium.com/@samhavens/building-somerset-d518ba284c49...
    - hobs 11y ago
      Wow, super simple. I dont know what has been taking me so long to try this out, thanks a lot! Took a look at the site and I signed up, some words of caution for anyone looking for the paid edition, but it works well for me: * You cannot display this information publicly in the free tier, and you must display their logo for attribution on their page at a specific size they mention in their TOS. * They want your phone number for some reason. * On the other hand, the api (AYLIEN https://developer.aylien.com https://developer.aylien.com ) either changed their limits or you might be just mistaken, it looks like the free tier is 1000 calls a day now, which is awesome!
romaniv 11y ago
There is more to AI than complicated neural networks. There are simple well-studied algorithms that deliver predictable results and work very well if you apply them to the right problem. Look into K-means clustering, linear regression and decision trees to get the taste. Good introduction to the field: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/ http://ocw.mit.edu/courses/electrical-engineering-and-comput...
- pvnick 11y ago
  Agreed. Deep learning receives all the hype these days (look at the machine learning subreddit), but in reality it provides very little practical value for the vast majority of data mining tasks that most folks will see. For that, standard methods like you mentioned (and don't forget SVM of course!) are still the go-to methods in my toolbox.
- colllectorof 11y ago
  On a more practical side, there is a good AI book with a misleading name: Programming Collective Intelligence. Instead of going over some abstract algorithms, it poses a series of practical questions (recommend a movie, calculate optimal price, filter spam) and then shows (with source code!) how to solve them using common AI techniques.
  - toby 11y ago
    Appreciate the recommendation (I wrote that)! Honestly the book is very old at this point, it may still be an approachable way to understand what's behind the algorithms but there are much better ways to write the code now.
    - nswanberg 11y ago
      I wore out my copy. Have you come across any books or course with the same approach but more updated code to recommend?
    - romaniv 11y ago
praccu 11y ago
Yes. Language learning, for example. Speech recognition is being used for a lot of IoT stuff, home automation, and toys and the like. Lots of other really interesting niche applications. We do research consulting in speech & language, and tons of small start-ups come to us with a variety of really interesting problems. cobaltspeech.com
- duaneb 11y ago
  It's hard to see how speech recognition requires custom ML; isn't this offered as a service by various OSes and SaaSes? In addition, it's hard to see how this would be critical to the startup's success. I'd expect trained classification to provide automated curation to be the best way for startups to take advantage in an existing project.
  - albemuth 11y ago
    for example: https://wit.ai/ https://wit.ai/
  - praccu 11y ago
    There are a lot of problems in speech besides transcription. I should have been clearer about what I meant. Even for people that do want transcription, though, often you can handily beat the accuracy of off-the-shelf services by tuning the models to the domain. I'm pasting some copy from our website in part because I can't talk too much about specifics, but here's some examples: " High quality speech to text transcription, including in the very difficult areas of conversational human-to-human speech: phone calls, voicemails, meetings, etc. Classification of speech & language: identifying gender, age, regional accents, level of education, etc. Voice front-ends for various applications and devices, including natural language interfaces: heads-up displays, robots, smartphone apps, etc. Speech synthesis (a.k.a. TTS) to generate high-quality synthesized speech from text. Analysis of audio: detecting different types of noise or speech: dog bark, shouting, gunshot, water running, cars, etc. Customization of speech recognition to processed signals, such as proprietary compression or noise reduction algorithms Fine-grained analysis of speech and language, for giving feedback in language pathology or language learning. Analysis of speech & language to detect various health conditions: stroke, dementia, depression, schizophrenia, etc. Information extraction from text or audio: phone numbers, dates, entities and relationships, etc. " [0] [0] http://cobaltspeech.com/our-products.html http://cobaltspeech.com/our-products.html
RBerenguel 11y ago
There are many not-incredibly-large advertising companies using machine learning to optimise (in many sense of the way it can be done) "what the do with (and how they do what they do) ads". Disclaimer: temporary contractor for one of them.
mindcrime 11y ago
Is AI right now useful as a way to provide value for small projects or startups? Any examples of that? I'm going to make the simplifying assumption of saying that "machine learning" is a subset of AI for our purposes, and that "machine learning" includes "simple" techniques like linear regression, logistic regression, k-means clustering, etc. I don't think any of that is terribly controversial, although I know a few people would quibble over it. Anyway... Given that, I'd say the example is absolutely "yes". AI can help startups and small projects. There's actually a really nice example that Andrew Ng talks about in his Machine Learning course on Coursera. In that example, a t-shirt manufacturer is trying to figure out how to size their shirts. So they go out and take a bunch of height/weight measurements of prospective customers, and then use k-means to segment the data into clusters. Let's say they do 5 clusters, corresponding to extra small, small, medium, large, and extra large. Now they can look at the measurements in each cluster and figure out how to size their shirts. More generally, anywhere that you have data, and you want to extract insights from that data, you likely have an application for some level of machine learning / AI. Of course it won't always (or even often, perhaps) be the case that you need a deep neural network, or anything like the cutting edge in academic research. But, then again, you might. :-) that get added to existing products by large companies with access to large datasets and computing power. Do you have an AWS account? If so, you have access to large datasets and computing power as well. Look at all the data that's "out there" in terms of Open Data, LinkedData, etc... As an exercise, browse around data.gov sometime, and look at things like the datasets the UN makes available, and the world bank data, etc., and see if you can think of a way to combine a few of those datasets and extract some meaningful insight from a combination nobody else has looked at before. If you come up with something, it's not terribly hard/expensive to spin up a cluster using EC2 and run some analysis.

by devit 11y ago

deleted 11y ago

[deleted]

losteric 11y ago

I've been working on a side project to pulled news articles and gave me summaries of trends I might be interested in. I'm learning so the results are pretty poor... but so far I've spent less than $50/week running the project on AWS. You could go cheaper with spot instances/etc too. Some big deep learning projects might be beyond small projects/startups, but I think AI is reasonable if you work methodically. edit: $50, not $100.

hobs 11y ago
Let me know how it works out if you want any beta testers, I have a slack/mumble integration I wrote that captures all the links we post, and I would love to be able to summarize what the link was about and offer that as well.
- samcodes 11y ago
  If you want to build a bot that does exactly what you are talking about, I just wrote an article [1] on how to do that! It uses an API with 1000 free calls per month, and is easy to host on your own servers or Heroku. [1] https://medium.com/@samhavens/building-somerset-d518ba284c49#.6ok3azfqz https://medium.com/@samhavens/building-somerset-d518ba284c49...
  - hobs 11y ago
    Wow, super simple. I dont know what has been taking me so long to try this out, thanks a lot! Took a look at the site and I signed up, some words of caution for anyone looking for the paid edition, but it works well for me: * You cannot display this information publicly in the free tier, and you must display their logo for attribution on their page at a specific size they mention in their TOS. * They want your phone number for some reason. * On the other hand, the api (AYLIEN https://developer.aylien.com https://developer.aylien.com ) either changed their limits or you might be just mistaken, it looks like the free tier is 1000 calls a day now, which is awesome!

romaniv 11y ago

There is more to AI than complicated neural networks. There are simple well-studied algorithms that deliver predictable results and work very well if you apply them to the right problem. Look into K-means clustering, linear regression and decision trees to get the taste. Good introduction to the field: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/ http://ocw.mit.edu/courses/electrical-engineering-and-comput...

pvnick 11y ago
Agreed. Deep learning receives all the hype these days (look at the machine learning subreddit), but in reality it provides very little practical value for the vast majority of data mining tasks that most folks will see. For that, standard methods like you mentioned (and don't forget SVM of course!) are still the go-to methods in my toolbox.
colllectorof 11y ago
On a more practical side, there is a good AI book with a misleading name: Programming Collective Intelligence. Instead of going over some abstract algorithms, it poses a series of practical questions (recommend a movie, calculate optimal price, filter spam) and then shows (with source code!) how to solve them using common AI techniques.
- toby 11y ago
  Appreciate the recommendation (I wrote that)! Honestly the book is very old at this point, it may still be an approachable way to understand what's behind the algorithms but there are much better ways to write the code now.
  - nswanberg 11y ago
    I wore out my copy. Have you come across any books or course with the same approach but more updated code to recommend?
  - romaniv 11y ago

praccu 11y ago

Yes. Language learning, for example. Speech recognition is being used for a lot of IoT stuff, home automation, and toys and the like. Lots of other really interesting niche applications. We do research consulting in speech & language, and tons of small start-ups come to us with a variety of really interesting problems. cobaltspeech.com

duaneb 11y ago
It's hard to see how speech recognition requires custom ML; isn't this offered as a service by various OSes and SaaSes? In addition, it's hard to see how this would be critical to the startup's success. I'd expect trained classification to provide automated curation to be the best way for startups to take advantage in an existing project.
- albemuth 11y ago
  for example: https://wit.ai/ https://wit.ai/
- praccu 11y ago
  There are a lot of problems in speech besides transcription. I should have been clearer about what I meant. Even for people that do want transcription, though, often you can handily beat the accuracy of off-the-shelf services by tuning the models to the domain. I'm pasting some copy from our website in part because I can't talk too much about specifics, but here's some examples: " High quality speech to text transcription, including in the very difficult areas of conversational human-to-human speech: phone calls, voicemails, meetings, etc. Classification of speech & language: identifying gender, age, regional accents, level of education, etc. Voice front-ends for various applications and devices, including natural language interfaces: heads-up displays, robots, smartphone apps, etc. Speech synthesis (a.k.a. TTS) to generate high-quality synthesized speech from text. Analysis of audio: detecting different types of noise or speech: dog bark, shouting, gunshot, water running, cars, etc. Customization of speech recognition to processed signals, such as proprietary compression or noise reduction algorithms Fine-grained analysis of speech and language, for giving feedback in language pathology or language learning. Analysis of speech & language to detect various health conditions: stroke, dementia, depression, schizophrenia, etc. Information extraction from text or audio: phone numbers, dates, entities and relationships, etc. " [0] [0] http://cobaltspeech.com/our-products.html http://cobaltspeech.com/our-products.html

RBerenguel 11y ago

There are many not-incredibly-large advertising companies using machine learning to optimise (in many sense of the way it can be done) "what the do with (and how they do what they do) ads". Disclaimer: temporary contractor for one of them.

mindcrime 11y ago

Is AI right now useful as a way to provide value for small projects or startups? Any examples of that? I'm going to make the simplifying assumption of saying that "machine learning" is a subset of AI for our purposes, and that "machine learning" includes "simple" techniques like linear regression, logistic regression, k-means clustering, etc. I don't think any of that is terribly controversial, although I know a few people would quibble over it. Anyway... Given that, I'd say the example is absolutely "yes". AI can help startups and small projects. There's actually a really nice example that Andrew Ng talks about in his Machine Learning course on Coursera. In that example, a t-shirt manufacturer is trying to figure out how to size their shirts. So they go out and take a bunch of height/weight measurements of prospective customers, and then use k-means to segment the data into clusters. Let's say they do 5 clusters, corresponding to extra small, small, medium, large, and extra large. Now they can look at the measurements in each cluster and figure out how to size their shirts. More generally, anywhere that you have data, and you want to extract insights from that data, you likely have an application for some level of machine learning / AI. Of course it won't always (or even often, perhaps) be the case that you need a deep neural network, or anything like the cutting edge in academic research. But, then again, you might. :-) that get added to existing products by large companies with access to large datasets and computing power. Do you have an AWS account? If so, you have access to large datasets and computing power as well. Look at all the data that's "out there" in terms of Open Data, LinkedData, etc... As an exercise, browse around data.gov sometime, and look at things like the datasets the UN makes available, and the world bank data, etc., and see if you can think of a way to combine a few of those datasets and extract some meaningful insight from a combination nobody else has looked at before. If you come up with something, it's not terribly hard/expensive to spin up a cluster using EC2 and run some analysis.