The entire product I built over the last year can be reduced to basic statistics (e.g. ratios, probabilities) but because of the hype train we build "models" and "predict" certain outcomes over a data set. One of the products the company I work for sells more or less attempts to find duplicate entries in a large, unclean data set with "machine learning." The value added isn't in the use of ML techniques itself, it's…
It's interesting to me that with all the ML hype, it's still not clear what constitutes ML. A basic k-means or naive Bayes approach will show up in ML textbooks, but those aren't clearly different from "use some statistics to make a prediction". There's an interesting group of marginal approaches that have existed as-is for years, but have increasingly focused their branding on machine learning as its profile has ris…
Ask HN: Where is AI/ML actually adding value at your company?
171–180 of 200 posts
Re: Ask HN: Where is AI/ML actually adding value at your company?
#172Here at Matterport, our research team is using deep learning to understand the 3D spaces scanned by our customers. Deep learning is great for a company like ours, where so much of our data is visual in nature and extracting that information in a high-throughput way would have been impossible before the advent of deep learning. One way we're applying this is automatic creation of panoramic tours. Real estate is a big…
Interesting. What is your training objective in deciding which view of the room would be the most appealing?
Also, are you looking into generative models for creating new views from different angles based on existing views?
Re: Ask HN: Where is AI/ML actually adding value at your company?
#173At our data science company, we're building a marketing automation platform that uses deep reinforcement learning to optimize email marketing campaigns. Marketers create their messages and define their goals (e.g., purchasing a product, using an app) and it learns what and when to message customers to drive them towards those goals. Basically, it turns marketing drip campaigns into a game and learns how to win it :)…
That's very interesting case. In my company, we would also like to optimize email marketing campaign using RL. However, based on my little experience using RL, (please correct me if I'm wrong) wouldn't it take long to iterate and update the V and policy function (or Q function if we use Q-learning), so I'm a bit skeptical if it can be used for real world case where we need to wait days to get the email response as feedback from the environment.
Re: Ask HN: Where is AI/ML actually adding value at your company?
#174Amazon 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…
Frankly, Amazon recommendations suck, they suck really hard.
Re: Ask HN: Where is AI/ML actually adding value at your company?
#175My company builds software to analyze customer feedback. We use "real" ML for sentiment classification, as well as some of our natural language processing and opinion mining tools. However, most of the value comes from simple statistical analysis/probabilities/ratios, as other commenters mentioned. The ML is really important for determining that a certain customer was angry in a feedback comment, but less important i…
What do you mean by "real"?
Re: Ask HN: Where is AI/ML actually adding value at your company?
#176[deleted]
Re: Ask HN: Where is AI/ML actually adding value at your company?
#177Earlier quoted context omitted.
I hope you get a decent chunk of those cost savings as a reward for your effort, great job.
D'Angelo Barksdale: Nigga, please. The man who invented them things? Just some sad-ass down at the basement at McDonald's, thinkin' up some shit to make some money for the real players. Malik 'Poot' Carr: Naw, man, that ain't right. D'Angelo Barksdale: Fuck "right." It ain't about right, it's about money. Now you think Ronald McDonald gonna go down in that basement and say, "Hey, Mista Nugget, you the bomb. We sellin…
Can't believe I'm seeing the Wire referenced on HN
Re: Ask HN: Where is AI/ML actually adding value at your company?
#178Earlier quoted context omitted.
It's a hard problem to determine the repeat purchase cadence of a product. At one end of the bell curve you have items re-purchased frequently, e.g. diapers or grocery, and on the other end you have items that are rarely repurchased. I haven't looked at coffee tables specifically, but I know when I've looked at home products in the past I've been surprised at how frequently people will buy two large items, e.g. TVs o…
"It's a hard problem to determine the repeat purchase cadence of a product." I don't think it is.
Do you work at Amazon, or do you have experience in this area? Care to elaborate?
Re: Ask HN: Where is AI/ML actually adding value at your company?
#179I 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…
Nice! You might like these links too. "Machine Learning Meets Economics", uses manufacturing quality as an example.
http://blog.mldb.ai/blog/posts/2016/01/ml-meets-economics/ http://blog.mldb.ai/blog/posts/2016/04/ml-meets-economics2/
Re: Ask HN: Where is AI/ML actually adding value at your company?
#180Earlier quoted context omitted.
It sounds like the OP is scanning for internal defects in bonds via impurities being trapped in there. These occur relatively randomly and there's some balancing point where it's just not worth trying to make the production line cleaner vs binning parts that fail some QA criteria. I do similar things with castings, where you simply just get certain voids and porosity in the steel when cast and either you can spend a…
This is pretty spot on. We know why the defects happen and why they cause downstream test failures, but we lack the ability to prevent (all of) them. To clarify on that 95% value because it is admittedly really vague: That's actually a 95% correct prediction rate. So far we get ~2.5% false-positives and ~2.5% false-negatives. 2.5% of the parts evaluated will be incorrectly allowed to continue and will subsequently fa…
> 2.5% of parts evaluated will be wrongly identified as scrap by the model and tossed
2.5% of what, though? if only 1 in a million parts are actually bad, you're still tossing many more good parts than bad parts.