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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?

#51

Post by psadri »

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.

If not, perhaps you should consider starting a company to develop this tech for others. Drop me a line :-)

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

#52

Post by ep103 »

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…

That's pretty awesome. What are you doing academically to lean this? Went somewhere for a masters?

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

#53

Post by danielsamuels »

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?

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

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

#54

Post by ska »

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…

    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.
This is the right way to approach it. Too many people are looking for "deep" as some sort of silver bullet for an ill defined problem they have. If you can't validate against a simple model trained properly you are already in trouble. Likewise if you don't understand how to evaluate your generalization issues and how/if a simpler model will improve them.

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

#55

Post by overcast »

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…

Also in manufacturing, would be interested in hearing more about this for detecting early on before NCR's are raised down the line.

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

#56

Post by dingbat »

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?

must be the same genius technology that leads Amazon to load up my Prime frontpage with fashion accessories when I've never had any history of searching or buying such, and recommending the same shows "Mozart in the Jungle", "Transparent", "Catastrophe" on Fire TV stick for months even though I've never shown any interest in any of such programming, even after manually "improving recommendations" by clicking "Not Interested".

its amazing that the vaunted Amazon technology is unable to figure out an algorithm that would satisfy a user's deep desire "please stop plastering Jeffrey Tambor's lipstick and mascara covered face on my startup screen, I've gotten tired of looking at it for the past year"

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

#58

Post by infinite8s »

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?

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

#59

Post by BickNowstrom »

Bartweiss wrote: post #46
jorgemf wrote: post #38

Earlier quoted context omitted.

> but those aren't clearly different from "use some statistics to make a prediction" You can reduce 90% of ML to this. Even neural networks are based on statistics. If I have to draw a line between statistics and ML is that ML learns, it means it can predict things, however statistics only gives you information about the data you have. But for sure statistics and ML overlap a lot.

Even that doesn't seem like a clear distinction? If you ask me for the most likely new value for a dataset, I won't know. But if I graph a few things and then write a function to spit back the current mean or median, is that machine learning? I'm not trying to be snarky there, I agree that the bulk of ML tools are fundamentally just statistical tricks with some layer of abstraction. As a result, I have a lot of troub…

I feel like it is foremost a matter of attitude of the practitioner. An applied statistician and a machine learning engineer may deliver exactly the same end product, just the reasoning and assumptions differ. Machine learning uses little to no assumptions, where statisticians do. I also feel that machine learning engineers have a bit less fear of building black boxes.

Caruana showed the cartoon of the difference between a statistician and a machine learning practitioner by showing a cliff. The statistician carefully inches to the edge, stomping her feet to see if the ground is still stable, then 10 meters before the edge she stops and draws her conclusions. The machine learning practitioner dives headfirst from the cliff, with a parachute that reads "cross-validation".

See also:

http://norvig.com/chomsky.html On Chomsky and the Two Cultures of Statistical Learning.

And http://projecteuclid.org/euclid.ss/1009213726 Statistical Modeling: The Two Cultures by Leo Breiman.

and this joke:

> Norvig teamed up with a Stanford statistician to prove that statisticians, data scientists and mathematicians think the same way. They hypothesized that, if they all received the same dataset, worked on it, and came back together, they’d find they all independently used the same techniques. So, they got a very large dataset and shared it between them.

> Norvig used the whole dataset and built a complex predictive model. The statistician took a 1% sample of the dataset, discarded the rest, and showed that the data met certain assumptions.

> The mathematician, believe it or not, didn’t even look at the dataset. Rather, he proved the characteristics of various formulas that could (in theory) be applied to the data.

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

#60

Post by johnny99 »

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?

Predictive analytics tells them you need more coffee tables. Many many more.
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