so how would you go about doing this using ml?
is it a classification problem? Count the number of instances. Or do we do deep learning and say here is a picture the result is 10?
A Japanese company cut 80% of the time needed to manually count pearls
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Re: A Japanese company cut 80% of the time needed to manually count pearls
#92so how would you go about doing this using ml? is it a classification problem? Count the number of instances. Or do we do deep learning and say here is a picture the result is 10?
Instance segmentation.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#93Earlier quoted context omitted.
If you think old, unoptimized, high-human labor business processes exist only in Japan, have I got a bridge to sell to you.
Optimizing 100 hours per year to 20 hours isn't much either.. It's 3 days, for that to break even development costs have to very low. Of course, selling it as a generic app for counting things is a great way to do this.
That part of the article confused me too, I think it's later implied they pay that 100 vs 20 hour cost much more often than once a year.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#94Wow, this is such a simple application of ML and it is incredibly valuable. On their website, they charge $100/month per device or $1000/year per device [0] and I bet they're making a killing. [0] https://countthings.com/en/
Let's just hope their engineering teams in Romania and Vietman get a respectable share of the profits.
I'm working on this from Romania. Everything is ok.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#95Hi, there! I'm one of the project managers at CountThings, I'll try to respond to comments here but I guess you can AMA.
Is not it something anyone can do for free using image J with a bit of scripting.
If you have the skills, you should definitely try it.
We have a full team working on this for about 7 years. Constant improvements to our algorithms, new challenges, new technologies. A ton of other functionalities besides counting (e.g. forms, reports, integration). A lot of work on the backend, UX. Also, a lot of sales and marketing involved.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#96> All good apps have already been created. There is no room for innovation. > Hold my beer: > I made an app that counts. Honestly, the simplicity of the idea is amazing.
And right now as we speak, there's 10s of people on this thread already working on cloning this idea. Some probably gonna make good money.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#97Earlier quoted context omitted.
We are working on this product in-house for 7 years now. We are an internal startup from a company that does custom computer vision and ML software. No mturk, no tricks, a lot of work in ML and in UX as it is not a very straightforward task.
> It is not a very straightfoward task. I'd well believe it. I used to write computer vision applications for semiconductor manufacturing equipment and there we were able to strictly control the distance from camera to object, lighting etc. and even still getting necessary reliability was not simple. When a failure could lead to damaging a whole wafer, i.e. hundreds of thousands of dollars, 99% accurate is not good e…
It would be very questionable to use this in production, especially as pearls are very glossy and costly, without the error matrix being provided. It would seem more reliable to use the camera as a blocked / non-blocked sensor with what would amount to a cheap coin sorter.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#98Earlier quoted context omitted.
How accurate is the counting? For examples like the case study, I presume your customers will want very close to 100% accuracy, but many other use cases will only need rough numbers. How do you calibrate / verify your app?
For most of our clients, we get to 100% accuracy. For some more difficult scenarios, a lower accuracy is ok for estimations (e.g. estimating the crop in agriculture). It's also super easy to correct mistakes or to add items that are not visible in the image.
You don't mean 100% accuracy, that means mistakes are impossible. Perhaps your error rate is very rare, but it's a bit concerning you don't attempt to quantify it.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#99Wow, this is such a simple application of ML and it is incredibly valuable. On their website, they charge $100/month per device or $1000/year per device [0] and I bet they're making a killing. [0] https://countthings.com/en/
I wish I could get a bead on how useful ML is. Hackernews makes me think it’s all hype.
I don't know about others, but because a lot of IT news comes to me from American medias, I _always_ consider it hype.
The reason is cultural: american can't seem to do without superlatives. They didn't eat good carrots yesterday, there were AMAZING carrots. They don't introduce me to their friends, but to their VERY BEST friends. They are always EXCITED to do X and SO something about Y.
The result is that none of those words have any value anymore. Louis C.K had a very good bit on that.
And then you add agenda, ads, and geek bias toward the new, and you got a recipe for over hype for pretty much everything (NoSQL all the things, Microservice all the things, PWA all the things, SPA all the things, OOP all the things, FP all the things, rust all the things, typescript all the things, etc).
So yes, my default assumption is that stuff on HN are over hyped (although interesting), until proven otherwise.
Re: A Japanese company cut 80% of the time needed to manually count pearls
#100Hi, there! I'm one of the project managers at CountThings, I'll try to respond to comments here but I guess you can AMA.
Do you need help with Salesforce integration?