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

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

#181

Post by iwintermute »

ekarulf wrote: post #106
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?

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…

Do you have any obfuscated training sets available to public?

edit:typo

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

#182

Post by brockf »

mitbal wrote: post #173
brockf wrote: post #129

At 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 fe…

Great points. It's definitely more challenging than learning to play a simple arcade game or something, where feedback is invariant and often instantaneous. To address these challenges, we use a combination of (1) heuristics tailoring our RL algorithms to the problem at hand, (2) many converging sources of feedback. Most importantly, as with any machine learning implementation, it works in practice — our AI-driven campaigns beat randomized, control conditions!

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

#184

Post by gtsteve »

the-dude wrote: post #36

PCB autorouting

It strikes me that you could do this with an algorithmic approach - is there some additional factor when building PCBs that's specifically hard?

Is this one of those things like the bin packing problem [1] where on first glances you'd expect it to have a definitive solution but it's actually deceptively very hard?

[1] https://en.wikipedia.org/wiki/Bin_packing_problem

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

#185

Post by Bartweiss »

shmageggy wrote: post #159
rakmial wrote: post #91

Earlier quoted context omitted.

Actually there's a very clear definition of what types of problems ML ought be used for, and that category of problem is what defines it. Those familiar with regression (and stats in general) ought to be familiar with it already - it's an issue of relationship of datatype between independent and dependent variable. In brief, you're going to run up against two types of data - categorical and continuous. (There are fac…

If I'm reading this correctly, it's just wrong. Whatever the distinction between data analysis and ML might be, it is more than just whether your data and predicted quantities are discrete or continuous. > Categorical Independent vs. Categorical Dependent, for example, is fairly restrictive, as makes logical sense. You may cross-tabulate, you may score likelihood based on previous observation, but obviously, because…

Thanks for the sanity check. I read that reply, and got bogged down enough that I was worried my initial reaction of "what, that's not relevant!" was born of ignorance. Discrete/continuous is a distinction worth making, but as a hidden 'definition' for ML I really don't understand it.

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

#186

Post by johndavi »

suanmeiguo wrote: post #156
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.

Oh interesting. I've used diffbot and never thought Diffbot relies on AI. Could you elaborate? I thought it's a simple crawling and parsing task but I might be naive on this.

Here's a slightly more detailed description: https://www.quora.com/What-is-the-algorithm-used-by-Diffbot-...

All identification and extraction in our APIs is based on our ML models, which have been fed hundreds of thousands of data-point examples from annotated web pages. Basically: our back end has reviewed millions of web pages to learn what various components of a page are -- and even what "type" of page a page is -- and uses that to make judgments on ones submitted via API.

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

#188

Post by pacey »

ilikeatari wrote: post #71

We leverage machine learning in the asset replacement modeling space. Basically there is an optimum time to sell your vehicle and purchase a new one based on our model. Our company works with large fleet organizations and provides analytics suite for vehicle replacement, mechanic staffing, benchmarking, telematics and other aspects of fleet management.

Is this useful for individuals also? I would really like to know the optimal time to sell my car. Or is this more like chart analysis which only works as long as the people having access to that information is limited?

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

#189

Post by StreamBright »

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?

It's more like you bought a coffee table and you get coffee beans in the recommendations. Also, you buddy who you are in the same group with gets a coffee table recommendation.

I guess this would make more sense.

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

#190

Post by ksimek »

anantzoid wrote: post #172
ksimek wrote: post #90

Here 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?

Our users have manually done a lot of the tasks we want to eventually do automatically, which effectively becomes data annotations for us to train on.
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