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GPT-4.5

openai.com

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Re: GPT-4.5

#371

Earlier quoted context omitted.

> We look forward to learning more about its strengths, capabilities, and potential applications in real-world settings. If GPT‑4.5 delivers unique value for your use case, your feedback (opens in a new window) will play an important role in guiding our decision. "We don't really know what this is good for, but spent a lot of money and time making it and are under intense pressure to announce new things right now. If…

> We don't really know what this is good for Oh come on. Think how long of a gap there was between the first microcomputer and VisiCalc. Or between the start of the internet and social networking. First of all, it's going to take us 10 years to figure out how to use LLM's to their full productive potential. And second of all, it's going to take us collectively a long time to also figure out how much accuracy is neces…

I generally agree with the idea of building things, iterating, and experimenting before knowing their full potential, but I do see why there's negative sentiment around this:

1. The first microcomputer predates VisiCalc, yes, but it doesn't predate the realization of what it could be useful for. The Micral was released in 1973. Douglas Engelbart gave "The Mother of All Demos" in 1968 [2]. It included things that wouldn't be commonplace for decades, like a collaborative real-time editor or video-conferencing.

I wasn't yet born back then, but reading about the timeline of things, it sounds like the industry had a much more concrete and concise idea of what this technology would bring to everyone.

"We look forward to learning more about its strengths, capabilities, and potential applications in real-world settings." doesn't inspire that sentiment for something that's already being marketed as "the beginning of a new era" and valued so exorbitantly.

2. I think as AI becomes more generally available, and "good enough" people (understandably) will be more skeptical of closed-source improvements that stem from spending big. Commoditizing AI is more clearly "useful", in the same way commoditizing computing was more clearly useful than just pushing numbers up.

Again, I wasn't yet born back then, but I can imagine the announcement of Apple Macintosh with its 6MHz CPU and 128KB RAM was more exciting and had a bigger impact than the announcement of the Cray-2 with its 1.9GHz and +1GB memory.

[1] https://en.wikipedia.org/wiki/Micral

[2] https://en.wikipedia.org/wiki/The_Mother_of_All_Demos

Re: GPT-4.5

#372

Earlier quoted context omitted.

> * OpenAI seems to be betting that you'll need an ensemble of models with different capabilities, working as a single system, to jump beyond what the reasoning models today can do. Seems inaccurate as their most recent claim I've seen is that they expect this to be their last non-reasoning model, and are aiming to provide all capacities together in the future model releases (unifying the GPT-x and o-x lines) See thi…

From Sam's twitter: > After that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks. > In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model. Yo…

I worry eliminating consumer choice will drive up prices for only a nominal gain in utility for most users.

Re: GPT-4.5

#373
post #167

First impression of GPT-4.5: 1. It is very very slow, for some applications where you want real time interactions is just not viable, the text attached below took 7s to generate with 4o, but 46s with GPT4.5 2. The style it writes is way better: it keeps the tone you ask and makes better improvements on the flow. One of my biggest complaints with 4o is that you want for your content to be more casual and accessible bu…

How do the two versions match so closely? They have the same content in each paragraph, just worded slightly differently. I wouldn't expect them to write paragraphs that match in size and position like that.

Re: GPT-4.5

#374

Earlier quoted context omitted.

The Internet had plenty of very productive use cases before social networking, even from its most nascent origins. Spending billions building something on the assumption that someone else will figure out what it's good for, is not good business.

And LLM's already have tons of productive uses. The biggest ones are probably still waiting, though. But this is about one particular price/performance ratio. You need to build things before you can see how the market responds. You say it's "not good business" but that's entirely wrong. It's excellent business. It's the only way to go about it, in fact. Finding product-market fit is a process. Companies aren't omnisc…

You go into this process with a perspective, you do not build a solution and then start looking for the problem. Otherwise, you cannot estimate your TAM with any reasonable degree of accuracy, and thus cannot know how much to reasonably expect as return to expect on your investment. In the case of AI, which has had the benefit of a lot of hype until now, these expectations have been very much overblown, and this is being used to justify massive investments in infrastructure that the market is not actually demanding at such scale.

Of course, this benefits the likes of Sam Altman, Satya Nadella et al, but has not produced the value promised, and does not appear poised to.

And here you have one of the supposed bleeding edge companies in this space, who very recently was shown up by a much smaller and less capitalized rival, asking their own customers to tell them what their product is good for.

Not a great look for them!

Re: GPT-4.5

#375

Earlier quoted context omitted.

> "Early testing shows that interacting with GPT‑4.5 feels more natural. Its broader knowledge base, improved ability to follow user intent, and greater “EQ” make it useful for tasks like improving writing, programming, and solving practical problems. We also expect it to hallucinate less." "Early testing doesn't show that it hallucinates less, but we expect that putting that sentence nearby will lead you to draw a c…

The usage of "greater" is also interesting. It's like they are trying to say better, but greater is a geographic term and doesn't mean "better" instead it's closer to "wider" or "covers more area."

> but greater is a geographic term and doesn't mean "better" instead it's closer to "wider" or "covers more area."

You are confusing a specific geographical sense of “greater” (e.g. “greater New York”) with the generic sense of “greater” which just means “more great”. In “7 is greater than 6”, “greater” isn’t geographic

The difference between “greater” and “better”, is “greater” just means “more than”, without implying any value judgement-“better” implies the “more than” is a good thing: “The Holocaust had a greater death toll than the Armenian genocide” is an obvious fact, but only a horrendously evil person would use “better” in that sentence (excluding of course someone who accidentally misspoke, or a non-native speaker mixing up words)

Re: GPT-4.5

#376

Earlier quoted context omitted.

I suppose this was their final hurrah after two failed attempts at training GPT-5 with the traditional pre-training paradigm. Just confirms reasoning models are the only way forward.

What it confirms, I think, is, that we are going to need a lot more chips.

Eh, no. More chips won't save this right now, or probably in the near future (IE barring someone sitting on a breakthrough right now).

It just means either

A. Lots and lots of hard work that get you a few percent at a time, but add up to a lot over time.

or

B. Completely different approaches that people actually think about for a while rather than trying to incrementally get something done in the next 1-2 months.

Most fields go through this stage. Sometimes more than once as they mature and loop back around :)

Right now, AI seems bad at doing either - at least, from the outside of most of these companies, and watching open source/etc.

While lots of little improvements seem to be released in lots of parts, it's rare to see anywhere that is collecting and aggregating them en masse and putting them in practice. It feels like for every 100 research papers, maybe 1 makes it into something in a way that anyone ends up using it by default.

This could be because they aren't really even a few percent (which would be yet a different problem, and in some ways worse), or it could be because nobody has cared to, or ...

I'm sure very large companies are doing a fairly reasonable job on this, because they historically do, but everyone else - even frameworks - it's still in the "here's a million knobs and things that may or may not help".

It's like if compilers had no "O0/O1/O2/O3' at all and were just like "here's 16,283 compiler passes - you can put them in any order and amount you want". Thanks! I hate it!

It's worse even because it's like this at every layer of the stack, whereas in this compiler example, it's just one layer.

At the rate of claimed improvements by papers in all parts of the stack, either lots and lots and lots is being lost because this is happening, in which case, eventually that percent adds up to enough for someone to be able to use to kill you, or nothing is being lost, in which case, people appear to be wasting untold amounts of time and energy, then trying to bullshit everyone else, and the field as a whole appears to be doing nothing about it. That seems, in a lot of ways, even worse. FWIW - I already know which one the cynics of HN believe, you don't have to tell me :P. This is obviously also presented as black and white, but the in-betweens don't seem much better.

Additionally, everyone seems to rush half-baked things to try to get the next incremental improvement released and out the door because they think it will help them stay "sticky" or whatever. History does not suggest this is a good plan and even if it was a good plan in theory, it's pretty hard to lock people in with what exists right now. There isn't enough anyone cares about and rushing out half-baked crap is not helping that. mindshare doesn't really matter if no one cares about using your product.

Does anyone using these things truly feel locked into anyone's ecosystem at this point? Do they feel like they will be soon?

I haven't met anyone who feels that way, even in corps spending tons and tons of money with these providers.

The public companies - i can at least understand given the fickleness of public markets. That was supposed to be one of the serious benefit of staying private. So watching private companies do the same thing - it's just sort of mind-boggling.

Hopefully they'll grow up soon, or someone who takes their time and does it right during one of the lulls will come and eat all of their lunches.

Re: GPT-4.5

#377
I imagine it will be used as a base for GPT-5 when it will be trained into a reasoning model, right now it probably doesn't make too much sense to use.

Re: GPT-4.5

#378

Earlier quoted context omitted.

> I want it more correct and capable. How is it supposed to be more correct and capable if these human eval tests are a waste of time? Once you ask it to do more than add two numbers together, it gets a lot more difficult and subjective to determine whether it's correct and how correct.

I agree it's a hard problem. I think there are a number of tests out there however that are able to objectively test capability and truthfulness. I've read reports that some of the changes that are preferred by human evaluators actually hurt the performance on the more objective tests.

Please tell me how we objectively determine how correct something is when you ask an LLM: "Was Russia the aggressor in the current Ukraine / Russia conflict?"

One LLM says: "Yes."

The other says: "Well, it's hard to say because what even is war? And there's been conflict forever, and you have to understand that many people in Russia think there is no such thing as Ukraine and it's always actually just been Russia. How can there be an aggressor if it's not even a war, just a special operation in a civil conflict? And, anyway, Russia is such a good country. Why would it be the aggressor? To it's own people even!? Vladimir Putin is the president of Russia, and he's known to be a kind and just genius who rarely (if ever) makes mistakes. Some people even think he's the second coming of Christ. President Zelenskyy, on the other hand, is considered by many in Russia and even the current White House to be a dictator. He's even been accused by Elon Musk of unspeakable sex crimes. So this is a hard question to answer and there is no consensus among everyone who was the aggressor or what started the conflict. But more people say Russia started it."

Re: GPT-4.5

#379
post #26

GPT 4.5 pricing is insane: Price Input: $75.00 / 1M tokens Cached input: $37.50 / 1M tokens Output: $150.00 / 1M tokens GPT 4o pricing for comparison: Price Input: $2.50 / 1M tokens Cached input: $1.25 / 1M tokens Output: $10.00 / 1M tokens It sounds like it's so expensive and the difference in usefulness is so lacking(?) they're not even gonna keep serving it in the API for long: > GPT‑4.5 is a very large and comput…

> It sounds like it's so expensive and the difference in usefulness is so lacking(?)

The claimed hallucination rate is dropping from 61% to 37%. That's a "correct" rate increasing from 29% to 63%.

Double the correct rate costs 15x the price? That seems absurd, unless you think about how mistakes compound. Even just 2 steps in and you're comparing a 8.4% correct rate vs 40%. 3 automated steps and it's 2.4% vs 25%.

Re: GPT-4.5

#380
@sama, LLMs aren't going to create AGI. I realize you need to generate cash flow, this isn't the play.

Sincerely, Me

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