Earlier quoted context omitted.
Never heard of terms of service?
Are you regularly getting emails with terms of service? You're, like, doubly proving my point.
Yes, I regularly get emails about terms of service updates.
Beliefs that are true for regular software but false when applied to AI
391–400 of 461 posts
Re: Beliefs that are true for regular software but false when applied to AI
#392Earlier quoted context omitted.
Like most AI products it feels like they started with a solution first and went searching for the problems. Text messages being too long wasn't a real problem to begin with. There are some good parts to Apple Intelligence though. I find the priority notifications feature works pretty well, and the photo cleanup tool works pretty well for small things like removing your finger from the corner of a photo, though it's n…
I mean it happened quite a few times that phishing emails became the priority notification on my phone
Really those should have been filtered out by the spam filter. If it's made it all the way to your inbox it's not surprising it got marked as a priority since phishing emails are written to look urgent, something which if real would be a priority notification.
Re: Beliefs that are true for regular software but false when applied to AI
#393Earlier quoted context omitted.
Claude just analyzed the emotional content of a piece of music for me -- quite accurately -- by just looking at an uploaded PDF of the score. How does that work? "It's a nonlinear system" or "it's a bunch of matrix multiplication" is in no useful way an explanation. That's way down at the bottom of an explanatory abstraction hierarchy that we have only begun to make tools to begin to explore. It's like asking how hum…
Did it show you the reasoning? Did it recognize the notes, the scale, tempo and determine the emotion effect of these or did it use some other reasoning?
I don't know about the reasoning, but it gave "evidence" for its observations in much the same way a human composer might. In terms of "understanding", it seemed in the ballpark of what I get when I ask it to explain some code.
I don't want to paste in the whole giant thing, but if you're curious: [0]
[0] https://drive.google.com/file/d/1D5yICywmkp24YajboKHdYFcBej0...
Re: Beliefs that are true for regular software but false when applied to AI
#394Earlier quoted context omitted.
The regular ChatGPT 5 seems pretty reliable to me? I ~never get crazy output unless I'm pasting a jailbreak prompt I saw on twitter. It might not always meet my standards, but that's true of a lot of things.
Maybe not the same thing, but chatgpt 5 was driving me insane in visual studio co pilot last week. I seemingly could stop it from randomly changing bits of code, to the point where it was apologising then doing the same in next change even when told not to. I've now changed to asking where things are in the code base and how they work then making changes myself.
Deleting comments even when instructed not to do so is another failure mode. They definitely require more fine-tuning in these cases.
Re: Beliefs that are true for regular software but false when applied to AI
#395This made me think about a conversation I had recently with a friend who is a researcher in Natural Language Processing. Obviously what we now call LLMs have taken her field by storm, which now mostly consists of trying to understand how the fuck they work.
I mean, we know they work, and they work unreasonably well, but no one knows how, no one even knows why they work!
Re: Beliefs that are true for regular software but false when applied to AI
#396Earlier quoted context omitted.
I'm happy they ate shit here because I like my mac not getting co-pilot bullshit forced into it, but apparently Apple had two separate teams competing against each other on this topic. Supposedly a lot of politics got in the way of delivering on a good product combined with the general difficulty of building LLM products.
Apparently? From what? Where did this information come from that they had two competing teams?
I heard it from the Verge podcast several months ago but someone has shared another source.
Re: Beliefs that are true for regular software but false when applied to AI
#397Earlier quoted context omitted.
Yes, but we can't inspect, reproduce or explain the emergent property independently. We can't pick out the "math reasoning" part or the "programming" part, or inspect how it's working, or selectively change any of it. You can't turn any dials or twiddle any knobs. You can't replace one part with another, or pick out components. You can't peek inside and say: "hey it's got an irrational preference for naming its varia…
So just because all the parts are collaborating to get the desired outcome, and specific aspects of that outcome cannot be contributed to specific parts of the llm you think we don’t understand LLMs? With mixture of expert systems we’re introducing dedicated subsystems into the llm responsible for specific aspect of the llm, so we’re partially moving in that direction. But overall in my opinion if devs are able to re…
Being able to make it and knowing how it works are just not the same thing. I can make bread of consistent quality, and know how to improve certain aspects of it. To know how it works, I’d need to get a doctorate in biochemistry and then still have a fairly patchy understanding. I know plenty of people who can drive a car very successfully but would never claim they know how it works.
Re: Beliefs that are true for regular software but false when applied to AI
#398Earlier quoted context omitted.
Did it show you the reasoning? Did it recognize the notes, the scale, tempo and determine the emotion effect of these or did it use some other reasoning?
I don't know about the reasoning, but it gave "evidence" for its observations in much the same way a human composer might. In terms of "understanding", it seemed in the ballpark of what I get when I ask it to explain some code. I don't want to paste in the whole giant thing, but if you're curious: [0] [0] https://drive.google.com/file/d/1D5yICywmkp24YajboKHdYFcBej0...
Impressive, it clearly is able to read the score, see patterns, timing, chords, and apply music theory to it. Would be interesting to give it editing and playback capabilities, e.g., by connecting it to something like strudel.
This article describes how Belgian supermarkets are replacing music played in stores by AI music to save costs, but you can easily imagine that the ai could also generate music to play to the emotions of customers to maybe influence their buying behavior: https://www.nu.nl/economie/6372535/veel-belgische-supermarkt...
Re: Beliefs that are true for regular software but false when applied to AI
#399Earlier quoted context omitted.
So just because all the parts are collaborating to get the desired outcome, and specific aspects of that outcome cannot be contributed to specific parts of the llm you think we don’t understand LLMs? With mixture of expert systems we’re introducing dedicated subsystems into the llm responsible for specific aspect of the llm, so we’re partially moving in that direction. But overall in my opinion if devs are able to re…
Being able to make it and knowing how it works are just not the same thing. I can make bread of consistent quality, and know how to improve certain aspects of it. To know how it works , I’d need to get a doctorate in biochemistry and then still have a fairly patchy understanding. I know plenty of people who can drive a car very successfully but would never claim they know how it works.
But with LLMs is there really more to understand? They’re just large functions that take numerical input and transform it into numerical output based on trained weights. There is nothing behind the scenes doing things we don’t understand. The magic is in the weights, and we know how to create these based on training data.
Regarding the car, if you know how to build a car, you understand how a car works. A driver is more like someone using and llm, not a developer able to create an llm.
Re: Beliefs that are true for regular software but false when applied to AI
#400Earlier quoted context omitted.
>> to perform up to Apple's typical standards of polish and control. >i no longer believe they have kept on to the standards in general. One 100% agree with this, if I compare AI's ability to speed up the baseline for me in terms of programming Golang (hard/tricky tasks clearly still require human input - watch out for I/O ops) with Apple's lack of ability to integrate it in even the simplest of ways.. things are jus…
Personally, I’ve never seen an AI flow of any kind that meets what would meet the quality of a typical ‘corporate’ acceptable flow. As in, reliably works, doesn’t go crazy randomly, etc. I’ve seen a lot of things that look like they’re working for a demo, but shortly after starting to use it? Trash. Not every time (and it’s getting a little better), but often enough that personally I’ve found them a net drain on prod…
> Personally, I find apples hesitation here a breath of fresh air
i does not appear to me as hesitation but rather an example of how they were unable to recently deliver on their marketing promises.
calling a suite of incomplete features as "Apple Intelligence" means that they had much higher expectations internally, similar to how they refined as second-movers in other instances. they have a similar situation with XR now.