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Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

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Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#111
Anyone else look at the motherboard & think, wow, heck yeah? It was barren. Flat, hugely unpopulated, painted black.

Seeing such a stark & severely empty slab of pcb is something I've been looking forward to. With more and more on chip, we don't need all this extra componentry all over our systems.

PCB might well be cheaper than cables.. but I can perhaps envision MCIO (Mini Cool-Edge IO)/SFF-TA-1002 taking over some day, disaggregating peripheral cards off the motherboard.

Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#112
post #73

Earlier quoted context omitted.

You're technically right that AI is a superset. But, at least in a computational context, "AI" is hardly ever being used to refer to cognitive science and other AI subsets that are not directly related to ML. So ML is usually the more precise terminology. But I've pretty much given up on that one.

Large language models are definitely AI.

The best example I've seen to contest that LLM's are "AI" is to make it print the total number of line's it's response will be, essentially add

"First answer with the total number of lines your total message will be, including the line with this number"

For example, GPT4 said "12" for this prompt: "First answer with the total number of lines your total message will be, including the line with this number

Make a program in Cpp that sums all prime numbers from 1 to 100"

LLM's cannot "think", they can only make sequential predictions based on their previous answers - so they cannot formulate a response and then modify that response on-the-fly

Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#113

The best thing about this whole event is that they didn't mention AI even once, all they're saying is ML. Which is what it is. AI is a hype word.

ML is subset of AI. AI that is inclusive of other concepts and it's not a buzzword. It's valid to call anything ML as AI. Sure there is a lot of AI hype but it's not some made up marketing jargon.

The general public assumes AGI when they hear AI and that’s a problem worth fighting against.

Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#117

The best thing about this whole event is that they didn't mention AI even once, all they're saying is ML. Which is what it is. AI is a hype word.

ML is subset of AI. AI that is inclusive of other concepts and it's not a buzzword. It's valid to call anything ML as AI. Sure there is a lot of AI hype but it's not some made up marketing jargon.

So is AGI AI? Why use such a broad term that puts AGI, a term defined by science fiction, with Transformer, a practical next token predictor based on gradient descent and attention mechanism, in the same basket?

Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#118

In this discussion: people who know little about Apple Silicon architecture ("no discreet GPU, not buying"), who are not the target audience for this ("$77k for a comoputer!?!?!"), who do have no idea what video creatives need (see: discreet GPU), raging. These systems (especially the Pro) are for people who spend all day working on 4k and up video. Also, guys: do you really think that any of you are smarter than App…

$3,000 just for slots certainly sends the message that Apple views their customers as completely captive though.

Re: Apple unveils new Mac Studio and brings Apple Silicon to Mac Pro

#120

Earlier quoted context omitted.

Large language models are definitely AI.

The best example I've seen to contest that LLM's are "AI" is to make it print the total number of line's it's response will be, essentially add "First answer with the total number of lines your total message will be, including the line with this number" For example, GPT4 said "12" for this prompt: "First answer with the total number of lines your total message will be, including the line with this number Make a progr…

That’s more like an inherent limitation of autoregressive prediction than that of LLM. Maybe LLMs can be trained or finetuned in other ways that allows it to think before answering.
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