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The AI Revolution Hasn’t Happened Yet
141–150 of 166 posts
Re: The AI Revolution Hasn’t Happened Yet
#142Earlier quoted context omitted.
We don't really have a theory for Boolean electronic circuits either. What separates bridges from computation is bridges are bound by the fixed laws of physics, computation is far more loosely bound by logic.
You really have no idea what you're talking about. Boolean logic - as a theoretical topic in itself and as it forms the basis for the circuitry of modern computing devices - is about as well-studied a topic as you can find.
What's the optimal layout for a hardware MPEG-4 decoder?
We have heuristics not laws.
Re: The AI Revolution Hasn’t Happened Yet
#143Earlier quoted context omitted.
No. But the parent said 'anything' not 'everything' and that seems less ambitious. I would think that ML which could find patterns in what your employees do day to day and make suggestions about how to make improvements (like virtual efficiency audits) would benefit many businesses. Even for individual users, just having their OS be able to pipe up like a latter-day Clippy and say "hey, I notice you copying data from…
ML is not magic. If you can't run controlled experiments then it isn't actually very easy to make confident recommendations about improvements to business processes.
Sure, I was exaggerating for effect. Maybe not proper ML, but something more like the OS automatically generating (and discarding if unused) macros in the background, and using CV / OCR on the windows to try to interpret what the user is doing - I am sure v1.0 would be laughable, but eventually...
Re: The AI Revolution Hasn’t Happened Yet
#144I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.
Humans are proof that machine intelligence can be improved quite a bit. We are just complicated machines, no?
yes but we're not built on silicon nor were we guided by curated data sets nor did we have a deadline nor does another parallel universe rely on our decisions for potentially life and death outcomes.
I do not like the idea of this simple equality and I think it misses the point. We might not get to us with this tech, the model might not be near enough.
Re: The AI Revolution Hasn’t Happened Yet
#145Earlier quoted context omitted.
I work for an actual tech company, which actually told me to look into a couple of ML projects to improve our operating efficiency, which actually produced good results and had an obvious and short path to being put into production... and which were promptly shelved. Business people make no sense.
Can you go into why they were shelved? Were they normal technology and business reasons - or related to ML directly? I ask so that potentially others can learn to either navigate around those in the future.
I wish I could. I have very little insight. I presume it's some sort of "normal business reasons", but the from my point of view the decision process went something like this:
Me: "It's finished, here are the areas of strength and weakness, and here's where we can deploy the system for maximum effectiveness."
Business: "We're thinking about the best way to deploy this."
Me: "This is how you deploy it."
Business: "We'll think about and get back to you. Don't do anything until we tell you."
Me: "..."
Business: "..."
Re: The AI Revolution Hasn’t Happened Yet
#146Earlier quoted context omitted.
Can you go into why they were shelved? Were they normal technology and business reasons - or related to ML directly? I ask so that potentially others can learn to either navigate around those in the future.
I wish I could. I have very little insight. I presume it's some sort of "normal business reasons", but the from my point of view the decision process went something like this: Me: "It's finished, here are the areas of strength and weakness, and here's where we can deploy the system for maximum effectiveness." Business: "We're thinking about the best way to deploy this." Me: "This is how you deploy it." Business: "We'…
Perhaps they needed you to elucidate the risks or possible downsides?
Re: The AI Revolution Hasn’t Happened Yet
#147Earlier quoted context omitted.
I work for an actual tech company, which actually told me to look into a couple of ML projects to improve our operating efficiency, which actually produced good results and had an obvious and short path to being put into production... and which were promptly shelved. Business people make no sense.
I would also be interested in knowing which projects / applications of ML seemed easy wins - I generally get stumped on "use CV and facial recognition" for a business that has no need of facial recognition.
1. Market prediction -- given basic demographic data, and publicly-available or easily acquirable information like when the person's house was purchased, what their credit score is, etc., how likely is this person to want / need your product, and is it worth spending a salesman's time on them?
2. Data entry. We took a picture of this customer's utility bill / bank statement / receipt / whatever. Now do we give it to human to identify relevant fields and manually type them into a spreadsheet, or do we have a computer automatically extract the business-relevant data? Or, heck, maybe that's too complex, but can we at least have a computer help--automatically filter out bad images, do perspective correction, highlight areas of interest, etc.? (This sort of thing is actually used in, e.g., digitizing census records; we don't trust handwriting OCR to be good enough on its own, but we trust it to automatically highlight relevant fields, in order, and provide a first-draft guess at the transcription to assist the human transcribers).
I could probably come up with a few more if I thought about it for a while, but those are the areas I've actually worked on recently.
Re: The AI Revolution Hasn’t Happened Yet
#148Earlier quoted context omitted.
I wish I could. I have very little insight. I presume it's some sort of "normal business reasons", but the from my point of view the decision process went something like this: Me: "It's finished, here are the areas of strength and weakness, and here's where we can deploy the system for maximum effectiveness." Business: "We're thinking about the best way to deploy this." Me: "This is how you deploy it." Business: "We'…
Perhaps they needed you to elucidate the risks or possible downsides?
That's the "weaknesses" part. And I did in fact spend a good bit of time with my manager going over exactly what the model does not mean, and what you should not conclude from it or use it for.
Re: The AI Revolution Hasn’t Happened Yet
#149Earlier quoted context omitted.
Humans are _amazing_ because they are able to correct the deficiencies of their perception with high level cognition augmented with memory of past experience. Machines can’t do cognition, and they can’t effectively use past experience either, to say nothing of doing a combination of those two things. Current “AI” is basically function approximation and nothing else. And humans do everything they do in a 20W power env…
> Machines can’t do cognition Assuming you mean that machines can’t do cognition at present , why do you think we won’t solve this problem in the next 20 years?
Because nobody knows how to even begin researching something like that.
Re: The AI Revolution Hasn’t Happened Yet
#150Earlier quoted context omitted.
You really have no idea what you're talking about. Boolean logic - as a theoretical topic in itself and as it forms the basis for the circuitry of modern computing devices - is about as well-studied a topic as you can find.
What's the optimal layout for a hardware MPEG-4 decoder? We have heuristics not laws.
How about an even simpler question in the realm of Carnot efficiency.
What's the theoretical minimum number of transistors to build a real time hardware MPEG-4 decoder @4k using Intel's 14nm process.