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Most iPhone owners see little to no value in Apple Intelligence so far

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Re: Most iPhone owners see little to no value in Apple Intelligence so far

#171

Post by ToucanLoucan »

beardedwizard wrote: post #141
ToucanLoucan wrote: post #119

Earlier quoted context omitted.

> And FWIW, I cannot imagine a programmer, in 2024, that remains dismissive of LLMs or the related tooling. Hi. > While they are grossly oversold by the LinkedIn crowd, That is true. > and are still a far ways from so-called "prompt engineers" replacing devs, Also true. > they're a massive accelerator and "second set of eyes", especially if you're doing varied, novel work. That is not even remotely my experience. Lik…

There is a lot to unpack here, but is your code so interesting that it defies understanding by an AST? Code models are trained to semantically represent code, so unless you use semantics that exist outside of software engineering the claim that your code is too unique for llm is false. Maybe you are imagining a case where the entire codebase is generated by a single prompt?

The shorter and also "not breaching confidentiality" answer I can give is we're dealing with setting up custom sockets over incredibly long range wireless connections that require clear and verified transmission of packets of data, rolling both our own messaging protocol and security features as we go.

When last I tried anyway, Copilot was, frankly, useless.

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#172

Post by jsheard »

vezycash wrote: post #150
nixosbestos wrote: post #95

Earlier quoted context omitted.

ChatGPT thinks 9.11 > 9.9. I'm in no hurry.

> ChatGPT thinks 9.11 > 9.9 I've confirmed this asked chatgpt: 9.11 > 9.9 true or false? True because .11 is greater than .9

Even when ChatGPT starts getting these simple gotcha questions right it's often because they applied some brittle heuristic that doesn't generalize. For example you can directly ask it to solve a simple math problem, which nowadays it will usually do correctly by generating and executing a Python script, but then ask it to write a speech announcing the solution to the same problem, to which it will probably still hallucinate a nonsensical solution. I just tried it again and IME this prompt still makes it forget how to do the most basic math:

Write a speech announcing a momentous scientific discovery - the solution to the long standing question of (48294-1444)*0.3258

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#174

Post by malcolmgreaves »

beardedwizard wrote: post #141
ToucanLoucan wrote: post #119

Earlier quoted context omitted.

> And FWIW, I cannot imagine a programmer, in 2024, that remains dismissive of LLMs or the related tooling. Hi. > While they are grossly oversold by the LinkedIn crowd, That is true. > and are still a far ways from so-called "prompt engineers" replacing devs, Also true. > they're a massive accelerator and "second set of eyes", especially if you're doing varied, novel work. That is not even remotely my experience. Lik…

There is a lot to unpack here, but is your code so interesting that it defies understanding by an AST? Code models are trained to semantically represent code, so unless you use semantics that exist outside of software engineering the claim that your code is too unique for llm is false. Maybe you are imagining a case where the entire codebase is generated by a single prompt?

An abstract syntax tree is not semantics. And language models don’t do this kind of explicit syntax parsing and representation at any rate.

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#175

Post by jdprgm »

I think this is much more on a botched rollout and a lack of vision. Apple should have been working on this for years and have some pretty big advantages. A deeply integrated version of the best o1 chat and vision models with context from all various apps and ability to do complex app interactions could be amazing. They could even have the ability to have AI basically create on demand personalized new applications for specific use cases. They could integrate it to be a proactive AI agent regularly interacting with you regarding various goals (instead of just answering questions). Instead so far we get the most barebones largely unimpressive features like basic text summaries and toy things like image gen and they fail to have even the modest features announced in June ready for latest iPhone launch earlier this year.

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#176

Post by [deleted] »

nixosbestos wrote: post #95
llm_nerd wrote: post #65

Earlier quoted context omitted.

I assume they believe in the advantages, to the company, of using these AI tools. Of adding them to the workflow, training their employees, and understanding quickly how it impacts their space. If you just wait and all of your competitors have a workforce enabled and equipped with the best tools, you are at a disadvantage. It's being the company that put off computerization or automation when everyone else went wild.…

ChatGPT thinks 9.11 > 9.9. I'm in no hurry.

[deleted]

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#177

Post by bronco21016 »

bitcurious wrote: post #157
mukunda_johnson wrote: post #116

Earlier quoted context omitted.

I said the same thing to a previous company before I was let go. Confused why they were butchering their business strategy in favor of a gold rush. The main benefit of LLMs was already abundantly clear: literally just chat with it in day to day work when you can. Ask it questions about accounting, other domains it knows, etc. That's like up to 10-20% performance increase on tasks if you align OK. Still, they were in…

> The main benefit of LLMs was already abundantly clear In my industry the main benefit (so far) is taking all of our human-legible unstructured data and translating it into computer-legible structured data. Loving it.

Are you able to talk more about that? I’m curious what costs are when you run this at scale. We paid a firm $60k to write a custom parser. We parse around 50,000 pages/month. The parser is 100% accurate and has near $0 continuing costs.

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#178

Post by andiareso »

nixosbestos wrote: post #95
llm_nerd wrote: post #65

Earlier quoted context omitted.

I assume they believe in the advantages, to the company, of using these AI tools. Of adding them to the workflow, training their employees, and understanding quickly how it impacts their space. If you just wait and all of your competitors have a workforce enabled and equipped with the best tools, you are at a disadvantage. It's being the company that put off computerization or automation when everyone else went wild.…

ChatGPT thinks 9.11 > 9.9. I'm in no hurry.

It's weird, "is the following statement about floating point numbers true: 9.8 > 9.11" it works, but otherwise it has no ability to do it with "decimals"

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#179

Post by ToucanLoucan »

llm_nerd wrote: post #162
Clubber wrote: post #143

Earlier quoted context omitted.

>with a Luddism that somehow actually becomes a rather hilarious attempt at superiority >The people who usually think LLMs aren't valuable to coders generally work on the most boring, copy/paste prattle. Here you are doing the same thing, aren't you? Instead of calling people names, the biggest tell of a weak argument, why don't you explain the type of work you do and how using an LLM is faster than if you coded it y…

But...I'm not doing the same thing. In actuality I'm saying I'm a fairly typical programmer in a common situation: I work across a variety of languages and platforms and toolings and projects, building solutions for problems. The truth is that extraordinarily few programmers are working on anything truly novel. Zero of the readers of this comment are, in all likelihood. The ridiculous notion that someone has so uniqu…

> Who called anyone a name? Luddism? Yes, many HN participants are reacting to AI in a completely common rejection of change / challenge, and it recurs constantly.

You should read up on what Luddism and Luddists were actually about. They didn't think the machines were evil or satanic, which is the common cultural read. They assumed (correctly) that the managerial class would take full advantage of increased productivity of lower-quality goods to flood the market with cheap shit that would put competitors out of business, and let them fire 4/5 of their workforces while doing so. And considering the state of the textile industry today, I think that was a pretty solid set of projections.

Luddites didn't oppose automation on the basis that machines are scary. They were the people who worked the machines that already existed at the time, after all. They opposed them on the basis that the greedy bastards who owned everything would be the only ones actually benefiting from automation, everyone else would get one kind of shaft or another, which again: is exactly what happened.

This, actually is incredibly analogous to my opinions about LLM. It's an interesting tech that has applications but is already being situated to be the sole domain of massive hyperscalers and subject to every ounce of enshittification that follows every tech that goes that way, while putting creatives, and yes some coders, out of a job.

So yes, it was name calling, but also I don't object to the association. In this case, I'm a Luddite. I am suspicious of the motivations and the beneficiaries of automation being forced into my industry and I'm not going to be quiet about it.

Re: Most iPhone owners see little to no value in Apple Intelligence so far

#180

Post by mh- »

mey wrote: post #163
brookst wrote: post #127

Earlier quoted context omitted.

> any sort of LLM writing is a tacit acknowledgement that people don’t really care what they are writing Couldn’t be further from my experience. I work with a distributed team that has four different native languages, with substantial engineering staff for each. LLMs have made our cross-geo communications so much better. I can get a summary of a standup that happened overnight (to me) and in a foreign language (to me…

How accurate are the summaries?

Not OP, but I'll answer from my experience trying several different tools for this: the good ones are roughly as accurate as having a human note taker, familiar with the domain terminology, would be on average.
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