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You probably don't need AI/ML. You can make do with well written SQL scripts

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Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#251

Post by Mahn »

leblancfg wrote: post #204
nkozyra wrote: post #30

Earlier quoted context omitted.

100%. What this all boils down to in 2018 is data. Data acquisition, data cleansing, data filing, etc. But what else is there, now? You're going to create a new, novel ANN network? Cool, can't wait to peruse your paper. Maybe someday it's considered groundbreaking. Right now it's not solving immediate problems. Immediate problems were solved with 1970s ideas + 2018's infrastructure.

A word against hasty generalisation - just because you don't interact with it on a daily basis doesn't mean it isn't being worked on elsewhere. There is an increasing number of ML-first companies out there. They are solving problems like object detection, portfolio strategy optimization, medical diagnosis, etc. Things that are 100% not possible to do with just SQL and Bash, and much less expensive than to have humans…

Maybe we could all just agree that AI and ML have their use cases, but they are not necesarily a good fit to any and all computing problems indiscriminately?

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#252

Post by Retra »

sverhagen wrote: post #121
didibus wrote: post #75

What 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…

Newbie question: would you not design ML systems to be able to explain themselves? Alike: hey, query planner, what's your query plan?

Is there any guarantee that every concept which a machine can learn can be represented in present-day human language in a manner compact enough to use?

One worry is that a machine might learn to do something we can't represent efficiently. I mean, people write whole libraries of books on ethics, so how can you expect a machine to punch out one or two lines on its own?

There's no upper limit on how long a proof to a given problem must be in any fixed language. And if you have to invent new language, people won't be able to read it anymore.

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#253

Post by zhte415 »

gnicholas wrote: post #40

My 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…

General comment on colour highlighting -

I read the updated /individual page and found it very... difficult.

The colours led me to speed up and slow down at an uncomfortable rate, to the extent I had to re-read it three times. I typically receive 200-1000 emails per day which all need to be read (yay!) plus at least 30k words per day out of email (business stuff but excluding newspapers, books, etc).

I speed-read about 6-10 words per flick of the eyes (for a short document), which is about 50 words per second. Do slow down to ponder: careful phrasing, a needingly precise written document, some graphics, and this is not for detriment.

I found the colour-coding very difficult, however.

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#254

Post by Piskvorrr »

cup-of-tea wrote: post #188
Piskvorrr wrote: post #187

Earlier quoted context omitted.

Except wan you gat whoa ird trance scriptions, people tagged as gorillas and recommendations "I see you bought $that, do you also want to buy $that?" There's No Silver Bullet, welcome to $any_year.

What language is this?

It's English...run through a transcription. ("Except when you get weird transcriptions")

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#255

Post by Avshalom »

xevb3k wrote: post #64
gnicholas wrote: post #40

My 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…

Can someone explain the dynamic that’s going on here? I somehow can believe that VCs are so stupid to be purely hype driven, so what is pushing them to make this their investment focus? Do they just jump on every bandwagon in the hope that one of them might pan out?

The thing is we're at a stage where companies hoover up every bit and byte of data they can get hold of on every customer and many non-customers because... well it's gotta be valuable some how right?

But it's so much damn data so loosely coupled to a company's actual product that trying to get any actionable intelligence out of it is basically impossible. Enter ML. "Just" chuck your data at a NN use A/B tests to train and hope the company ends up with higher revenues, if they do: claim the 'data scientists' are definitely a profit center; if they don't: claim you need more data.

Until Exxon-Mobile stops storing metrics on how many goldfish I own in a given month, cranking out ML related companies seems like a good bet for VCs because it's not going to get any easier to turn progressively more esoteric data points into money.

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#256

Post by templar_muse »

cup-of-tea wrote: post #188
Piskvorrr wrote: post #187

Earlier quoted context omitted.

Except wan you gat whoa ird trance scriptions, people tagged as gorillas and recommendations "I see you bought $that, do you also want to buy $that?" There's No Silver Bullet, welcome to $any_year.

What language is this?

Irony.

Except wan you gat whoa ird trance scriptions = Except when you get weird transcriptions

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#257

Post by dotmanish »

r3bl wrote: post #168
maltalex wrote: post #107

While 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…

(I'm not the parent commenter who you replied to, but I think I understood what his/her point was).

Taking the shopping cart example: "In a former life, I used to write SQL to extract customer of the week. Basically, select from orders table where basket size is the biggest."

The author decided that 'customer of the week' will be selected by 'biggest basket size'. Not by 'biggest $ amount spent', 'fastest time from add-to-cart to checkout' (and numerous other attributes or combination of them). This decision (the "best attribute") was taken by a human, leaving a field open where a combination of attributes could've resulted in overall better business outcome (how much did 99% of these retained customers shop for, in $ value over lifetime?, etc)

This is possibly what the parent commenter is hinting at - this human decision leaves a lot of optimization scope, where ML could have helped.

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#258

Post by soared »

mygo wrote: post #6
soared wrote: post #5

Earlier quoted context omitted.

Agreed. The advertising agency I previously worked at would take the first month and only work on how data is collected and stored. After that first month they would begin addressing goals, plans, etc. About a year later is when true value would be realized because data that previously never existed could be analyzed. Few things were more enjoyable for me than getting a new client, imagining what analysis I'd like to…

how did you convince them to stick on for a year when most clients want to see some results within 2 months or they give up? according to your schedule they’d ask what I’ve been doing and if I tell them I’ve just been “collecting data” that translates to them as “I haven’t done anything in 2 months”. If I say “keep paying me and you’ll see results in a year” that translates to “I haven’t done anything in 2 months but…

The other answers are good - For my experience specifically it was at a very very small agency, so the client chose us specifically for this purpose and knowingly agreed to it.

The first few months aren't just us working silently. It was always a very intensive process, I'd be on the phone with the client a few times a day to work through issues. They also get valuable tidbits of data early on. Most clients had ideas about how they expected data to look (70% of my revenue comes from product x) but often times the reality is different and they see immediate value.

Clients sign up for a contract that auto-renews every three months and they have to give 30 days notice to terminate. At a small agency you have the luxury of denying clients all the time too that you don't want to work with.

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#259

Post by preordained »

sixdimensional wrote: post #34

Well, we are in the peak of a wave of hype about AI/ML, maybe even just past that peak. Many fundamental technological advancements in the field of AI/ML have sort of coalesced together at the current time to form a strong feature set that can be more broadly applied by a wider audience, not just those hardcore computer scientists who invented the technology. I've been in the thick of this previously, facing a comple…

>I will say, though, that I for one don't want to be caught on the side of the discussion where I don't learn enough about what is possible with AI/ML, and then get left behind.

I understand that feeling. On the other hand, aren't there a lot of trains you can miss? Do you try to guess which trains are the critical ones (and can you, really?) or do you try to keep up with all of them?

AI/machine learning, quantum, block chain...the list goes on. It seems like the best you can do is not be blindingly ignorant of any of the technologies and their potential...I think few people can really "keep up" unless they have the luck (or misfortune?) to have a job like "Quantum Crypto AI Researcher".

Re: You probably don't need AI/ML. You can make do with well written SQL scripts

#260

Post by geebee »

collyw wrote: post #146
firasd wrote: post #15

Earlier 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.

As a classic example, how about music or movie recommendations? You have a giant set of attributes about songs and a binary classification (thumbs up/thumbs down) from millions of listeners. You can use this this to train a random forest or neural net (or other algorithms) to make song recommendations to someone based on that person's pattern of thumbs up/down. I'd guess most recommendation systems do something along these lines, though I don't really know.

I'm not sure how I'd do this with SQL. That certainly doesn't mean you couldn't take a SQL approach to the problem of "how do I make recommendations based on this training set and this particular individual's attributes" and do something creative and useful. But I do think you can, in this situation, get something out of ML that would be difficult (ok, I'll say impossible) to get with a pure SQL approach.

To be clear, I love SQL. I still get a little flash of anger when I remember my arguments with "architects" who announced to a room full of non-technical people that I was pretty much a dinosaur unwilling to move away from an obsolete technology when they advocated no-sql approaches to data that was deeply relational. And I'm sure that there are plenty of people who think "need answer from data, must use ML" and end up somehow trying to train a neural net to perform a WHERE clause. Having seen the hype cycle several times, I am absolutely certain this has occurred in boardrooms/open office cubicle farms all across the you ess aye and beyond.

But keep in mind, even though reports of SQL's death were remarkably exaggerated, "nosql" approaches often do make the most sense. Plenty of good ideas and technologies came from nosql, and many of the people who created them and advocated them continued to use (and argue for) SQL and relational databases depending on the problem. A graph database is a vastly superior approach to some types of network problems than standard SQL, and not helpful for others. When the hype cycle around ML dies down (and some people start writing articles that ML is "dead" or whatever), ML will continue to be used effectively in all kinds of places, as it is now.

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