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Comment Demand Chain Crash (Score 4, Informative) 18

The whole data center AI investment thing looks like it is going to BUST. The latest open source models that came out this month have show 10x-100x improvements in efficiency over the last 9 months. And innovations like Deepseek Sparse Attention and other training innovations have made it clear that our CURRENT phones and CURRENT graphics cards are MORE than enough to run MAXIMALLY DANGEROUS allowable AIs already. By the end of THIS QUARTER, algorithmic efficiency alone will SHATTER the current AI investment story.

Think about it... the top models are already restricted for safety. We are now getting Qwen 27b models that are punching at 90% of frontier, and even the AMAZING little Ornith 9b model that came out a couple weeks ago that is equivalent to ChatGPT4 from a couple years back.

Why the hell do we need so much CLAUDE when 90% of people will NEVER use the AI more than casually? Even if AI usage grows.... there is NOT enough demand that will pop up this quarter to close the gap.

We are heading for a BLACK SWAN crash in days because the AI investment story is VAPORIZING before our eyes due to algo efficiency, which is wiping out the hardware investment story upon which the current cycle is based. We have a $2T house of cards going on here. And NOBODY knows how to use the 10x-100X ADDITIONAL efficiency we are likely to see from the already-discovered four or five major algo innovations that have be cross-pollinated the last few weeks, each of which has about 50-100% additional runway of efficiency. So the compounding efficiency means our already-owned PHONES will be enough to satisfy our AI needs THIS QUARTER.

Comment coding productivity (Score 2) 142

The AI coding assistants are very powerful but right now in 2024, because code itself is very complex typically with hundreds of files in an app, AI is not quite there with a holistic code base (application level) training and output just yet.

The most productive AI users now are senior developers who can use the AI to both 1. iterate code sections insanely fast 2. actually read the code the guide the AI in the next iterations.

So TODAY you still have to know what you are doing to leverage AI tools for actually-better quality x speed output.

3-6 months you won't have to know as much.

Comment Re: Snake oil (Score 2) 48

Hey, but the Levenshtein distance was close! Too bad you were searching for an exact number, instead of searching for one of the 200 misspellings of Britney Spears. That would have worked great. Recently their struggle is how to juggle the different search use cases while trying to inject AI wizardry into the mix, in a desperate effort to remain relevant, where they are bursting apart at the seams. Nobody knows how it works anymore. Not even them.

Comment Re:Snake oil (Score 2) 48

Reading this: "Removing it might mean, if you have a massive site, that we're better able to crawl other content on the site. But it doesn't mean we go, 'Oh, now the whole site is so much better' "

Translated into English, that means they can't even get their own story straight. Which is that their algorithms are so old and crufty that they can't even give you a straight answer. And that's kind of the point. Because if they could, you could game it. So the entire algo has turned into this messed up Nash equilibrium game where even Google couldn't exactly tell you on a given day what SEO works these days.

Which explains a LOT about why Google searches are getting less relevant these days.

Comment Re: "Simple for computers" (Score 1) 91

That seems intuitively true but it is actually an oversimplification. What you're saying is not general AI characteristic; really it's sort of a superficial derivative observation of LLM behavior. LLMs are themselves advanced statistical models - and those models are actually so complex they are impossible for humans to operate directly, and it is something only a computer is good at.

Comment Re:It's a language model, not a calculator (Score 5, Insightful) 91

This is all nonsense and a misunderstanding of what they did and how ChatGPT works.

The LLM is always bad at math beyond absolutely trivial stuff.

They had the version from a few months ago hooked up to a Wolfram Mathematica back end (unannounced apart from a separate plug-in to Mathematica) and the connection to that is just wonky at the moment.

The LLM does not "do" math out of the box.

Comment Re: 2016 book? (Score 2) 53

Legal issues/narrative points are:
1. guy writes book
2. producers provably were 100% of book and copied key creative conceits (figuring they could do it safely while threatening dude not to make his own movie)
3. guy is now owed 50% of screenplay rights at least; screenplays = 25% of movie rights by industry convention, so guy has claim to 12.5% of movie
4. Apple settles for 12.5% of producers' fee plus 12.5% of producers' bonus plus legal, or Apple faces 12.5% plus triple damages (50% total loss) or injunction (100% total loss)

Apple/producers should settle this and move on. Producers made risky moves in what appears to be possible bad faith and are in a weak position.

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