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Wow, 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
by temporalparts 5y ago
Wow, 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/ https://countthings.com/en/
- dawnerd 5y agoMeanwhile industrial manufacturing have been using vision systems for years to count and inspect items. This solution is waaaaay cheaper than what other alternative packages are. They could probably get away with charging a lot more if they build a lite assembly line style counter that takes in a video feed. (They might already have this, I didn’t look too much into it).
- keeble 5y agoThey can also count items from video https://youtu.be/EoCMUfMO2jw https://youtu.be/EoCMUfMO2jw
- Scea91 5y agoThe difficulty of this depends on the acceptance criteria. I can imagine that the industrial requirements for FP/FN count make this quite an interesting and complicated problem.
- distribot 5y agoI wish I could get a bead on how useful ML is. Hackernews makes me think it’s all hype.
- sneak 5y agoSometimes I feel like the whole ML scene is just stringing me along.
- smichel17 5y agoThe main reason I'm trying to cut down on my HN consumption a bit is the incessant pessimism. While a regular reality check is definitely useful, the "I'm so jaded by everything" vibe makes it hard to get excited about anything. I like being excited by things! It feels good and motivates me. Too much HN is a recipe for lethargy.
- rationalData 5y agoI think the most important reason to reduce consumption is due to everything being carefully curated. Actual issues from a particular fruit company like the butterfly keyboard was cause of getting flagged, you weren't allowed to talk about it. Similar problems happen to this day.
- ethbr0 5y agoMac fans being rabid Mac apologists isn't something leaving HN is going to change.
- rationalData 5y agoThis doesn't come from fanboys, this comes from dictators.
- ethbr0 5y agoUsers flag content on HN for dubious, political reasons all the time. Why would this need to be a conspiracy, rather than simply a vocal minority?
- rationalData 5y agoBecause the dictator will personally respond
- darksaints 5y agoI'm as frustrated as you are, but you shouldn't see this as the result of dictators, but rather the result of lots of cult members having access to the flag button.
- toyg 5y agoAs usual, there are exaggerations on both sides. ML is genuinely useful for moderately complex problems like this one, and pretty rubbish for a bunch of other stuff it's been shoehorned on. There is no silver bullet, as usual.
- bonoboTP 5y agoDepends on your baseline excitement. If you're so hyped up that you think it can classify bad and good prospective employees from a single photo, you should tone it down because that's nonsense. If you think it's all fluff, then you are also wrong. There are many great ML applications for constrained scenarios. But this pearl counting does not require modern ML at all. It can be done with decades old image processing algorithms like Canny edge detection, Hough transform, thresholding, Hu moments etc. How reliably is another question. This kind of stuff is/used to be called "Machine Vision" (related to computer vision, but in hard industry they like to say machine vision).
- JackFr 5y agoThere’s also a technique called “weighing”. It’s a transformation which, by assuming the items are identical, turns quantity from a discrete value to a continuous one with some loss of precision. In many cases measurement times can be reduced my more than 99%.
- matsemann 5y agoCut the snark. And if you check the link, the assumption that items are identical is far off.
- JackFr 5y agoYeah I know. And the use cases of people on a beach, crowded theater, trees in the woods, etc. don't lend themselves to weighing. Honestly didn't intend to come off as snarky, just clever and amusing. Tough to convey tone -- risk I take I guess. Oh well.
- carlmr 5y agoI think you're not wrong. Even if the pearls aren't identical, if you weigh enough of them at once the central limit theorem will be on your side.
- TchoBeer 5y ago
- BiteCode_dev 5y agoI 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.
- freddie_mercury 5y agoI live in Southeast Asia and am in a Facebook group where foreigners often post asking for recommendations. Americans always phrase their questions as, "What's the BEST pizza?" or "What's the BEST sushi?" As if they would die (or could even tell the difference) if they had the fourth or tenth best option in the city instead. And if you recommend a place too expensive or too far away it becomes immediately clear they don't actually want the best. All they actually want is a decent place to eat at a moderate price level. But as Americans they can't say that. They have to pretend they deserve nothing but the BEST.
- WindyLakeReturn 5y agoPerhaps it has to do with different interpretations of what is meant by best? If I told you the best Thai place around where I live, I would tell you a place that is best not just because of its food, but also its price, parking, distance to travel. It is the best in that it is the most optimal given my own value judgment of those factors.
- matheweis 5y agoThis is exactly right. Before I lived in Seattle, I was told (moving from the southwest), that there was no good Mexican food in Seattle. Of course after I moved there I found quite a number of excellent Mexican food restaurants, and for a few years I wondered what strange definition they were using. I eventually figured out that they meant that there was no good Mexican food within walking distance of downtown
- rsynnott 5y agoA reasonable summary would probably be "useful in mostly though not always modest ways in many areas, but _severely_ overhyped". It's not nothing, but it's also probably not going to lead to self-driving cars or even fully-accurate voice recognition anytime soon, say.
- rationalData 5y agoIt's literally statistics applied to data. If your data is good and you can fit it to a model it will work. The problem is that data is often poor and the idealized models don't fit real world conditions so you can have problems like overfitting.
- ethbr0 5y agoML needs data engineering like electrical devices need electrical infrastructure (i.e. generators, transmission lines, transformers, last mile lines). It turns out companies have wildly different maturities and proficiencies with these precursors, in addition to simple company ages. Many from having under-invested in actual (not consulting BS) technology transformation and skilling for decades. Consequently, ML is ridiculous to consider and doomed to failure for company A. While company B can toss a simple model at their well-architected data systems and get immediate ROI. This is underappreciated, because VPs and consultants are not typically in the business of saying "Our systems are out of date and have poor hygiene, and we can't do this new thing because of that."
- alisonkisk 5y agoThere's no ML here. This is a decades old software technology being packaged as a phone app.
- typon 5y agoGoogle, the world's most used search engine, uses BERT to power it's queries.
- omarhaneef 5y agoMachine Learning is not a single thing that can be useful or not. It is more like the scientific method. It depends on the data available, and whether something in the arsenal can create something useful. Most experiments yield absolutely nothing, and some achieve delightfully counter-intuitive useful results. The criticism on HN -- perhaps correct(1) -- is not that it is hype but that it is not new. Is statistics great? of course, but its been around for decades, perhaps centuries, so it seems strange to proclaim how it will solve problems now. (1) ML can be distinguished from statistics if you want to. I am not interested in this particular debate myself.
- legulere 5y agoMachine learning is a tool for solving certain tasks. Usefulness lies in finding new places to use those techniques. The hype is about predictions that machine learning (or AI in hype-speak) will be able to do things that it is currently not able to. Right now machine learning seems like a useful tool for certain tasks but not as revolutionary as e.g. the invention of the car.
- darksaints 5y agoMachine learning is extremely useful, used in hundreds of industries for probably a million different things. Most of these uses are not exciting. The latest trendy forms of machine learning, which are all some form of deep learning neural network, are pushing beyond the boundaries of human capability, but for a fairly narrow set of usecases. Some people get excited cause they can exceed human capabilities for some object recognition type of task, and then end up thinking that SkyNet is around the corner and they rightfully get called out for it. You should know though that it is rarely the experts that are guilty of overhyping. It's usually VCs, or product managers, or marketers, or regular software engineers that took an intro class on Coursera where they were told exactly how to solve a problem but haven't yet been exposed to how hard it is to generalize. With deep neural networks in particular, all of the new innovations have come from novel neural connection topologies. Most of the successful new topologies are the result of attempts to model biological function of some sorts, but that is just the tip of the iceberg. With neuron counts technically unbounded, and the topological search space essentially being the factorial of the neuron count, we will never fully explore the capabilities of neural networks, and only an infinitessimally tiny fraction of those would ever be useful in any circumstance. So deep learning is still extremely exciting because the opportunities are so boundless, yet still extremely disappointing because of how hard it is to find anything useful.
- rubenbe 5y agoValue pricing at it's finest. If the customer saves $1000/month per device, they'll happily pay the $100/month. As it still saves them $900. They don't care how complex/simple the ML implementation is.
- Aperocky 5y agoBut is there any barrier to entry though? By the looks of it, none, the next app will charges $5 per month and it could even be generic ('round objects counter')
- toomuchtodo 5y agoUntil then, profit is profit.
- TheAdamAndChe 5y agoIt may not seem like it to those of us who know how to do it, but there actually is quite a barrier to entry. You or an organization needs to have the skills to utilize machine learning algorithms, test them thoroughly, package it in an easy-to-use application, then market it and compete against competitors. Just ask your every day Joe what you should do with a learning rate if your error rate suddenly spikes or how to monitor for overfitting. Then ask them how to form an LLC or how to create and audit a liability release waiver for clients.
- TchoBeer 5y agoI also think part of the "real skill" in this sort of business is making sure you have someone around when it breaks. If the pearl counting algo goes haywire, the pearl company wants to know that they'll have someone to contact to fix it.
- dv_dt 5y agoThe barrier to entry is that many niche markets that latch on to the original service over time are incredibly random and difficult to associate with a uniform market. You can build and price a cheaper app, but reaching the set of customers would be difficult.
- GistNoesis 5y agoLet's just hope their engineering teams in Romania and Vietman get a respectable share of the profits.
- morsanu 5y agoI'm working on this from Romania. Everything is ok.
- 29athrowaway 5y agoI would not say it's that simple, they do have many trained models with high accuracy. https://countthings.com/en/counting-templates https://countthings.com/en/counting-templates
- deleted 5y ago[deleted]
- alisonkisk 5y agoThere's no ML here. This is a decades old software technology being packaged as a phone app.
- carlmr 5y agoI think you meant to say there's no AI here. Since even a linear regression is ML.
- bserge 5y agoThe much better cameras help a lot, I guess. I remember scanning QR codes with a 2014 and a 2018 (yeah, already old) flagship phone and being amazed at the distance the latter was able to do it from. At least 3x the distance from the QR code vs the old model, and the autofocus was near instant, too.