In my own experience, often non-technical people will attribute things as AI that we wouldn’t, eg any basic automation. Really anything that’s in any way intelligent or seems that way. I had a project where people were excited about a feature that was basically just alerting when one value crossed over or under another... I wonder if your team could provide real value to customers providing some smart “AI” feature that isn’t actually machine learning.
I had a boss not so long ago who kept selling our customers our "Conversational AI Bot". What we gave them was a fairly dumb keyword search of a library of questions the customer would type in along with answers - wrapped in some html widgets displaying cartoon robot heads.
It still astounds me that not only did none of those customers sue us for blatant misrepresentation, but most of them were delighted with what they'd bought.
I had a similar cognitive dissonance when doing "R&D Grant applications" a long time back. I kept on thinking "Research" was the sort of rigorous academic work you do to earn a PhD. In the government/business world, it seems pretty much spending time or money to learn how to do anything not 100% required for your business previously counts. Including things like "selling our widgets, only via the internet" being valid and acceptable thing to get government rebates for "R&D". I still feel dirty everytime I draft one of those grant applications... :shrug:
The line of were AI starts is not well-defined. If you think about it, virtually all software can be considered AI if you put expectations low enough. From the other end, one could argue that once you understand the inner workings of a piece of AI, it just becomes a fancy algorithm to you. In the end, everything is just a piece of software converting input to output.
My experience is that people tend to consider things AI whenever it feels like "magic" to them, at least in non-technical circles.
On the other hand, actual AI is kinda cut-n-paste accessible now too.
I slapped together a POC javascript tinyYolo feature detector demo last weekend (using someone else's code and pre-trained model from their github project), and joked when I showed it around that "And we can tell investors we're running AI, deep learning, and convolutional neural networks in our realtime production workflow!"...
(But as we all know, all the _proper_ magic is done by the regexes buried in that Perl module dependency hidden in a deeply nested source code directory that no-one without a grey beard is ever game to peer into...)
If you have someone doing a task manually, you could technically argue that you’re using an incredibly advanced neural network. Just not an artificial one.
I was recently joking that I was training a neural network with a water spray bottle (teaching the cat not to jump on the kitchen counter). And just while I type this, my little neural network came to walk over the keyboard...
Completely agree. If its artificial (all software) and its in some way intelligent p, or appears that way, (a lot of software, or features thereof), then you could argue its artificial intelligence, based on just those two words (ignoring the definition technical people give AI). That’s why machine learning is usually more useful from a technical discussion viewpoint.
> From the other end
Yeah, using wongarsu’s example of chess: brute forcing chess was once a highlight if AI achievement and now its just a crude search algorithm.
