Ask HN: Where is AI/ML actually adding value at your company? • Hacker News Board

Re: Ask HN: Where is AI/ML actually adding value at your company?

#61

Post by ocdtrekkie » Mon, Dec 12, 2016, 7:24 PM UTC

brianwawok wrote: post #44

ekarulf wrote: post #35

Amazon Personalization. We use ML/Deep Learning for customer to product recommendations and product to product recommendations. For years we used only algorithms based on basic statistics but we've found places where the machine learned models out perform the simpler models. Here is our blog post and related GitHub repo: https://aws.amazon.com/blogs/big-data/generating-recommendat... https://github.com/amznlabs/amazo…

So is this like the Amazon "feature" where I buy a coffee table on Amazon, then I get suggested to buy a coffee table EVERY DAY for 3 months. Literally row after row of coffee table? Because there must be a big pool of people who buy 1 coffee table buying more coffee tables immediately after?

Obviously the goal of ML in this would be that feeding it enough data about users who buy coffee tables would eventually teach it that you probably don't want another coffee table (because who buys two coffee tables in a row?), but might want to buy say... end tables or other living room furniture in a matching style to the coffee table you just bought.

Not saying it works, but that'd be the goal.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#62

Post by clint » Mon, Dec 12, 2016, 7:25 PM UTC

danielsamuels wrote: post #53

brianwawok wrote: post #44

Earlier quoted context omitted.

So is this like the Amazon "feature" where I buy a coffee table on Amazon, then I get suggested to buy a coffee table EVERY DAY for 3 months. Literally row after row of coffee table? Because there must be a big pool of people who buy 1 coffee table buying more coffee tables immediately after?

Your purchase was merely the inaugural move to establish your newfound hobby of coffee table collecting.

I read this same tweet last week too :)

Re: Ask HN: Where is AI/ML actually adding value at your company?

#63

Post by infinite8s » Mon, Dec 12, 2016, 7:26 PM UTC

splike wrote: post #25

Based on past experimental data, we use ML to predict how effective a given CRISPR target site will be. This information is very valuable to our clients.

That sounds interesting, especially given a good enough physical model could compute that de-novo.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#64

Post by lnanek2 » Mon, Dec 12, 2016, 7:27 PM UTC

Providing users the best recommendations so they participate more, get more from the service, and churn less. Detecting fraud and so saving money. Predicting users who are about to leave and allowing us to reach out to them. Dynamic pricing to take optimum advantage of the supply and demand curve. Delayed release of product so it doesn't all get reserved immediately and people don't have to camp the release times.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#65

Post by lost_name » Mon, Dec 12, 2016, 7:34 PM UTC

Nothing in my department yet, but we actually have a guy actively looking for a reason to implement some kind of ML so we can say our product "has it" I guess.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#66

Post by [deleted] » Mon, Dec 12, 2016, 7:35 PM UTC

sidlls wrote: post #21

AndrewKemendo wrote: post #19

Earlier quoted context omitted.

The value added isn't in the use of ML techniques itself, it's in the hype train that fills the Valley these days: our customers see "Data Science product" and don't get that it's really basic predictive analytics under the hood. I'm not sure the product would actually sell as well as it does without that labeling. So you are misleading your customers through omission? This is the kind of thing that makes people ques…

No, we actually use ML. We just don't need to, in my opinion, because the problems our products solve are more or less solvable without these techniques. My point was that using ML, even though we don't need to, "adds value" by virtue of the hype train. We need ML to sell products, not to create them. I do agree that this sort of arrangement lends itself to supporting skepticism around AI and ML. On the other hand I…

[deleted]

Re: Ask HN: Where is AI/ML actually adding value at your company?

#67

Post by shas3 » Mon, Dec 12, 2016, 7:37 PM UTC

whistlerbrk wrote: post #37

altshiftprtscrn wrote: post #31

I work in manufacturing. We have an acoustic microscope that scans parts with the goal of identifying internal defects (typically particulate trapped in epoxy bonds). It's pretty hard to define what size/shape/position/number of particles is worthy of failing the device. Our final product test can tell us what product is "good" and "bad" based on electrical measurements, but that test can't be applied at the stage of…

This is brilliant, would love to read a full write up on it. I hope you get a big raise.

Surely it would be guarded as a trade secret, as it usually happens in large companies.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#68

Post by LolWolf » Mon, Dec 12, 2016, 7:41 PM UTC

infinite8s wrote: post #58

johndavi wrote: post #49

We exclusively rely on ML for our core product at Diffbot: automatic data extraction from web pages (articles, products, images, discussion threads, more in the pipeline), cross-site data normalization, etc. It's interesting and challenging work, but a definite point of pride for us to be a profitable AI-powered entity.

Are you guys familiar with the DeepDive work from Christopher Re's group at Stanford?

Or his company Lattice for that matter.

Re: Ask HN: Where is AI/ML actually adding value at your company?

#69

Post by LolWolf » Mon, Dec 12, 2016, 7:44 PM UTC

Bartweiss wrote: post #43

sidlls wrote: post #39

Earlier quoted context omitted.

I wouldn't. I'd call it "basic computational statistics." But I think I might be in the minority on that.

I've always thought of regressions, even high-order ones, as just a statistical tool. They're present at the start of ML courses, sure, but as a tool used in ML techniques or a good alternative to them. It looks like that's not the standard view, though.

The whole deal seems weird to me.

Neural networks are just functional approximators, so why isn't a linear regressor of k-th order (e.g. Taylor expansion up to k-th order) also considered "ML"? What's the distinction here?

Re: Ask HN: Where is AI/ML actually adding value at your company?

#70

Post by jngiam1 » Mon, Dec 12, 2016, 7:45 PM UTC

From Coursera - we use ML in a few places:

1. Course Recommendations. We use low rank matrix factorization approaches to do recommendations, and are also looking into integrating other information sources (such as your career goals).

2. Search. Results are relevance ranked based on a variety of signals from popularity to learner preferences.

3. Learning. There's a lot of untapped potential here. We have done some research into peer grading de-biasing [1] and worked with folks at Stanford on studying how people learn to code [2].

We recently co-organized a NIPS workshop on ML for Education: http://ml4ed.cc . There's untapped potential in using ML to improve education.

[1] https://arxiv.org/pdf/1307.2579.pdf

[2] http://jonathan-huang.org/research/pubs/moocshop13/codeweb.h...