371–380 of 391 posts
I’ve been working in the “real world business processes that companies are trying to AI-ify” realm for quite a while now. Pharma, cyber security, oil and gas production, etc. This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them. An automated process only has to be wrong once to compel human operators to double o…
Earlier quoted context omitted.
The AI effect: AI gets a bad rap because once something exists and is practical it's no longer called AI. [0]: https://en.wikipedia.org/wiki/AI_effect
Eh, I think we still have the Turing test, and AFAIK it hasn't had a case where it's passed without raising eyebrows for potentially trying to cover up for deficiencies. I think the threshold needs to be high (maybe "beyond a reasonable doubt"?) and reproducible with high probability: I'd say at least X% (I don't know what X should be, but it should be much higher than 50%) of the adults that engage in or read the co…
Earlier quoted context omitted.
The existence of the aether isn't borne out by experiments; rather, we have justification in believing in its non-existence. The algorithms of AI of decades past still work. That's a big difference. E.g. SHRDLU can be built today and you can have a conversation with it about its world of blocks. Algorithms are artifacts of mathematics. To calculate distance between two points, we still use sqrt(dx^2 + dy^2); it doesn…
Fine, plum pudding model of the atom then. It isn't perfect, but we don't throw out the name physics. I don't get this hate for new techniques being classified as AI. Just because they learn distributions instead of using classic prolog?
I knew what a neural network was, and understood it as part of AI, when Wham! was in the Top 40 charts.
The hate isn't for the "new" techniques, I think; just for the posers who claim to be AI experts because they know how to use some Python library or whatnot.
You don't have AI creds if you have no background in the symbolic stuff.
Earlier quoted context omitted.
Do you do any work with uncertainty estimation with neural networks? There are many different ways to estimate uncertainty depending on your application, such as ensemble-training or dropout during testing to produce ranges of predictions that you can then use to get boundable error measurements.
The problem with this is that NN are in general, overconfident in their predictions, even when they are wrong. This is a well known problem in the AI/ML literature. Using ensembles of overconfident predictors is not the same as getting an unbiased estimate of the uncertainty.
Business needs to solve the prediction (i.e., regression) problem, which is a completely different kettle of fish.
P.S. Of course by "AI" I mean the 2020 definition of "multilayered neural network".
AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess because by definition those problems seem easy. Think how much Microsoft Office and competitors have amplified business productivity over the last 20 years (yeah yeah, make your jokes too). Word and Powerpoint and Excel are full of AI whether it's spellcheck or a…
Your definition of AI seems to be particularly broad. There are several general and specific algorithms designed to handle the examples you gave and they have been working well for the last few decades, some even earlier and have been implemented on computers later. E.g. linear programming was designed to solve several classes of programs and was initially done on paper. Lumping all this as "AI" doesn't seem fair to me.
AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess because by definition those problems seem easy. Think how much Microsoft Office and competitors have amplified business productivity over the last 20 years (yeah yeah, make your jokes too). Word and Powerpoint and Excel are full of AI whether it's spellcheck or a…
Is this the point in the curve we redefine anything successful as using 'AI' because it uses a computer program? Literally the only things you mention using AI/ML techniques are "speech-to-text, asking Siri for answers, translating web pages" and search engines, which are external to business process. Internal search is usually a disaster because processes are document based rather than web/publication based. There a…
AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess because by definition those problems seem easy. Think how much Microsoft Office and competitors have amplified business productivity over the last 20 years (yeah yeah, make your jokes too). Word and Powerpoint and Excel are full of AI whether it's spellcheck or a…
Is it? These have largely been done with MILP and related tools for decades, and those approaches have never been called AI. What AI techniques are you thinking of here?
Anyway, AI gets a bad rap because there's so much hype and snake oil out there that the signal is being lost in the noise. I'll be much better disposed towards it once the next AI winter hits. Like for instance, I have great respect for anybody selling an expert system at this point in time.
Earlier quoted context omitted.
"most businesses don't know how to transform unpredictable progress into profit" Unpredictable progress is lethal to businesses. As an example, it does not matter how brilliant Steve Jobs was or Elon Musk is, they both need to show regular results that build confidence from shareholders. About the only time you may not care for steady progress is if you have abundance of resources and clear goal like Bill Gates with…
> Unpredictable progress is lethal to businesses At peace, or in a quasi steady state, yes. But not in all situations. Eg. in war or other adversarial situations you need to both be making progress and be as unpredictable as possible, in the hope that in some indefinite future you can exterminate and/or enslave the other players. As the world is becoming more and more war-like, these types of strategies can become mo…
I did not intended this to apply to anything else.
I may have made an error in my post, though. Making unpredictable progress is not lethal in itself if you can show steady progress. It should have probably been worded "lack of steady progress is lethal to businesses". It is ok to have some unpredictable projects as long as you can build trust with steady progress somewhere else in sufficient quantity.
AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess because by definition those problems seem easy. Think how much Microsoft Office and competitors have amplified business productivity over the last 20 years (yeah yeah, make your jokes too). Word and Powerpoint and Excel are full of AI whether it's spellcheck or a…
Why would we have such a term as AI , if not to distinguish it from algorithmic ? I thought the whole point was to get out of the business of having to write down procedures for everything, to have the computer approach novel problems like a programmer does. Is this only a contemporary perspective? Seems like that's where the goalposts were at least 15 years ago.
That would have been uncomfortable, so the AI prophets have instead responded by changing the meaning of the term.