A guy that rediscovered Direct Marketing. Congrats.
You probably don't need AI/ML. You can make do with well written SQL scripts
161–170 of 331 posts
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#162A guy just rediscovered Direct Marketing.
Congrats.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#163ML is not going from 0 -> 25% it's going from 25% to 28%, say, and that 3% being much more in profit than the cost of the ML work.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#164Earlier quoted context omitted.
Product Recommendations. Trending Items (Top items being sold this week as opposed to last week, while filtering out items that are generally popular.) Much easier with Elasticsearch than SQL https://www.elastic.co/blog/significant-terms-aggregation
That's not really ML.
If I were ever to make ML bingo, "That's not really ML" would definitely be on it.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#165What the article describes is called an "expert system" and is what AI in the enterprise used to look like. Basically, you try to capture the instinct of a great salesmen by formalizing it into computer logic. Often that's done with rules like in the article. It works good, but has its limits. The finer reasoning of human judgement are often not expressable, people don't know why they made that decision. Making it ha…
Yes, these are two main approaches to AI, with expert systems being the "old" AI and ML being the "modern" AI. In the old approach, you knew exactly what you wanted to achieve, and very often you had a relatively clear idea how to do it; the challenge was to construct the solution manually. In the new approach you are not so much concerned with how to do it as you train on some dataset anyway. The results are less pr…
I think we do have a good-enough understanding of "understanding" to characterize what is required. However this is to be found in the textbooks of neuroscience, not in the machine manufacture manuals of a silicon lithography plant.
There isn't as much mystery as there seems. When a neuroscientist asks "how does a animal perceive the world?" the answer is reasonably methodologically obvious.
When a computer scientist asks, "how does a machine perceive the world?" the mystery arises only because it doesn't.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#166Companies have a large problem of having their data tucked away or inaccessible to the stakeholders. When people talk about AI / ML what they actually need is their data cleaned to the point where they can communicate to their stakeholders. Also, all of the companies who sell AI / ML as consultants are really good already at cleaning data. When companies actually hire data scientists what they typically do is clean d…
Pretty much this. However I think that you can actually get pretty far with cleaning a surprisingly small subset of data and just quickly tossing together a prototype. Talking to people helps a lot. "Ok so you have this and that data...how helpful would it be if you could predict the price of item X that you buy 10% better"...well ok it would be worth roughly Y$/year. Let's build a small prototype and see how well we can actually predict it. At this point you quite often find out that "oh we more or less predict it via one person who makes the buying decisions by experience" and it might take some convincing to actually compare the two.
I'd summarize that the "big three" of ML/DL are all nontechnical
1) Finding the data/cleaning the data
2) Is there actually some reference you can benchmark against
3) It's not really all that hard and you might need less data than you think to show enough business value (broadly speaking a pretrained net + some usecase layers is good enough to get started for most business cases)
#3 is interesting. I tend to be quite honest but I've seen a lot of mumbo-jumbo hand waving "oh it's very tough" which of course makes sense if you want to sell shiny new stuff. Reminds me a lot of ERP sales where I've seen basically SQL+a little webfrontend pitched as rocket science :D
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#167Earlier quoted context omitted.
Curious. OP gave a few examples for Ecommerce where SQL will do fine. Can you give a few where ML will do something otherwise impossible or harder with SQL?
Forecasting and prediction. Specific example: given a high quality dataset, forecasting sales is a good use case for machine learning. Of course, you could do this with SQL as well, but again, given a good dataset and a complex domain like sales, some relatively simple models will be hard to beat with a 10 line SQL query.
Sorry, I disagree with you. Let's take forecasting. This is a _very_ hard topic and being applied correctly using actuarial methods it will beat ML. To give you some example, you cannot take sales data for IPhone X and predict its future sales. Reason is simple - market will change, IPhone 11 will come out cannibalizing IPhone X sales. So, you need to have 2 more variables into play. One is the lifetime of a product (approximated) and second is, you need to "put in one basket" several products. Having this, you can predict your sales for some specific product group, no magic ML needed. However this requires you to define "similar products". This is hard because currently it is done semi-automatically using human labor. In fact ML is actually the best one to automagically categorize products into groups, however I have not seen any implementations. To summarize, ML do has value, however not where everybody is pointing out.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#168While I see the author’s point, I fail to understand what any if this has to do with SQL. The problem ML solves isn’t querying databases, it’s making decisions. If a human came up with the idea “let’s lookup people X and send them email Y” and it works, great. But a human made that decision, and SQL is just a tool for making it happen. If you want to take the human out of the loop, SQL won’t save you.
I don't think you understand author's point.
His point is highlighted in the first tweet, in which the author appears to be specifically annoyed by the potential founders and investors that can't understand that ML isn't a good solution for all of the problems.
He then goes on and gives an example of such problem by explaining a shopping cart that doesn't actually need ML, but just some old-fashioned SQL. He doesn't claim that SQL is a solution to all ML problems, just this one.
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#169My startup was approached by a corporate VC that wanted to make a strategic investment. Based on the attendee list from our meeting, which included very high up folks from the company, I felt good going in. They expressed interest in our technology that makes reading on screen easier [1], but they were surprised to learn that we didn't use machine learning to accomplish this. I indicated that it was actually quite ef…
Seizure/Nausea warning!
Re: You probably don't need AI/ML. You can make do with well written SQL scripts
#170My startup was approached by a corporate VC that wanted to make a strategic investment. Based on the attendee list from our meeting, which included very high up folks from the company, I felt good going in. They expressed interest in our technology that makes reading on screen easier [1], but they were surprised to learn that we didn't use machine learning to accomplish this. I indicated that it was actually quite ef…
That is just how larger corporations work. They probably decided they wanted to be part of that future market about AI and therefore want to invest in AI/ML startups. Someone sold your company internally as being a nice fit for the AI portfolio, but when you answered the question about ML with "No" the door was shut. From someone who makes large trade deals as his daily business, I learned "Never say 'No'" (during a…
You should never mislead a potential investor. Why would you want an investor who is misaligned with your core technology/strategic direction?