71–80 of 97 posts
The messaging is all over the place anyway. Not so long ago OAI was talking about faster iterations and warning people to not expect huge leaps. (A position that makes sense imo). Yet people talk about AGI in a serious manner?
"AGI achieved internally" -- Sam Altman
Earlier quoted context omitted.
Microsoft AI Revenue In 2025: $13 billion, with $10 billion from OpenAI, sold "at a heavily discounted rate that essentially only covers costs for operating the servers." Capital Expenditures in 2025: $80 billion --- Amazon AI Revenue In 2025: $5 billion Capital Expenditures in 2025: $105 billion --- Google AI Revenue: $7.7 Billion (at most) Capital Expenditures in 2025: $75 Billion --- Meta AI Revenue: $2bn to $3bn…
Take the emotional level down a notch. You seemed to miss the point. Hyperscaler spend does not equate to OpenAI P&L.
Earlier quoted context omitted.
> Do we really want to replace humans? AGI doesn't really replace humans, it merely provides a unified model that can be hooked up to carry out any number of tasks. Fundamentally no different than how we already write bespoke firmware for every appliance, except instead of needing specialized code for each case, you can simply use the same program for everything. To that extent, software developers have always been t…
> Which is what AGI enables. I appreciate the well-crafted response, but respectfully disagree with this sentiment, and I think it's a subtle point. Remember the no free lunch theorems: no general program will be the best at all tasks. Competent LLMs provide an excellent prior from which a compelling program for a particular task can be obtained by finetuning. But this is not what OpenAI, Google, and Anthropic (to a…
Perhaps I wasn't entirely clear, but AGI isn't expected to be the best at all tasks. The bar is only as compared to a human, which also isn't the best at all tasks.
But you are right that nobody knows how to make them good at even some tasks. Hence why everyone is so concerned about LLMs writing code. After all, if you had "true" AGI, what would you need code for? It is well understood that AGI isn't going to happen. What many are banking on, however, is that AGI can be simulated if LLMs can pull off being good at one task (coding).
> They want to be the first for bragging rights, hype, VC funding, and control.
That's the motivation for trying to create AGI (at least pretending to), but not AGI itself.
Earlier quoted context omitted.
With those people being business owners, investors, etc, 100% of the time. The other 99% would like automation to make their lives easier. Who wouldn't want the promised tech utopia? Unfortunately, that's not happening so it's understandable that people are more concerned than joyous about AI.
>With those people being business owners, investors, etc, 100% of the time. How can one run a business by replacing humans, if no humans are left with enough income to buy your products? I suspect that the desire to "replace humans" runs far deeper than just shortsighted business wants.
Earlier quoted context omitted.
> ignoring R&D (which is definitely a huge cost) they run at a profit. how can you say such a hand wavy comment with a straight face? you can't just ignore a huge cost for a company and suddenly they are profitable. that's Enron level moronic. without constant R&D, the company gets beat by competitors that continue R&D. the product is not "good enough" to not continue improving. if i ignored my major costs in my fina…
I don’t know why so many take these discussion with such a high emotional level. Has the ability to constructively discuss a topic been lost? I know you usually respond with high emotion and brash but at least try to be constructive. It’s a valid point and that’s the biggest question when it comes to the medium to long term business plan. Those R&D costs are an important part of it. My point is that since runtime is…
There is no point in saying that an AI company can just ignore its R&D. There is no company without the R&D. Because of that, any conversation pretending it doesn't exist is pointless. There is no constructive conversation with that as the premise.
Earlier quoted context omitted.
> Which is what AGI enables. I appreciate the well-crafted response, but respectfully disagree with this sentiment, and I think it's a subtle point. Remember the no free lunch theorems: no general program will be the best at all tasks. Competent LLMs provide an excellent prior from which a compelling program for a particular task can be obtained by finetuning. But this is not what OpenAI, Google, and Anthropic (to a…
> no general program will be the best at all tasks. Perhaps I wasn't entirely clear, but AGI isn't expected to be the best at all tasks. The bar is only as compared to a human, which also isn't the best at all tasks. But you are right that nobody knows how to make them good at even some tasks. Hence why everyone is so concerned about LLMs writing code. After all, if you had "true" AGI, what would you need code for? I…
But I think we do the discipline a disservice by referring to coding assistance as AGI. Also, having them be good enough that they can write their own code autonomously is a nightmare scenario to me, but I know many others don't feel that way.
I asked it to make a drawing of the US with every state numbered from biggest to smallest with 1 being the largest. Maine was #89 (That is not a typo.) and Oregon was #1. OpenAI as a company simply cannot exist without a constant influx of investor money. Burning money on every request is not a viable business model. Companies built on OpenAI/Anthropic are similarly deeply unprofitable businesses. OpenAI needs to con…
PhDs need to catch up!
Earlier quoted context omitted.
I don’t know why so many take these discussion with such a high emotional level. Has the ability to constructively discuss a topic been lost? I know you usually respond with high emotion and brash but at least try to be constructive. It’s a valid point and that’s the biggest question when it comes to the medium to long term business plan. Those R&D costs are an important part of it. My point is that since runtime is…
I like how when your illogical notion is challenged, you respond by saying the challenger is being emotional. There is no point in saying that an AI company can just ignore its R&D. There is no company without the R&D. Because of that, any conversation pretending it doesn't exist is pointless. There is no constructive conversation with that as the premise.
That’s a very different conversation than “pretend R&D doesn’t matter.” No one is suggesting they stop building; the question is whether they can align the burn rate with the revenue base over time. Companies make those tradeoffs constantly when maturing from heavy investment to profitability.
And yes, you are being emotional, not because I disagree with you, but because your language is inflammatory and brutish. It’s hard to have a constructive discussion when every response is dialed to 11. Misframing the premise as “ignoring a huge cost” isn’t debate, it’s a straw man, and it sidesteps the real question of whether the underlying business model works once R&D is right-sized.
Would love to have a real critical discussion on why you disagree but please leave the bad language out of it. It’s boring and I know it’s your typical route in these types of discussions but at least have a valid retort.
Earlier quoted context omitted.
See the sibling comment from AlexandrB. Altman and tons of other hype men in tech do this thing where they make outrageous promises, then retcon as “just jokes” whichever ones don’t come true, so that they can never be disproven. It’s a swindle made all the more irritating by the enablers like you who go “why did you take the joke seriously?” to get cred on the internet while helping the scam continue. Or to put it a…
Again, out of all the quotes to call out the weakest one was picked.
Yes, GPT-5 is more of an iteration than anything else, and to me this says more about OpenAI than the rest of the industry. However, I think the majority of the improvements over the past year have been difficult to quantify using benchmarks. Users often talk about how certain models "feel" smarter on their particular tasks, and we won't know if the same is true for GPT-5 until people use it for a while. The "GPT-5 w…
The idea that models “feel” smarter may be 100% human psychology. If you invest in a new product, admitting that it isn’t better than what you had is hard for humans. So, if users say a model “feels” smarter, we won’t know that it really is smarter.
Also, if users manage to improve quality of responses after using it for a while, who says they couldn’t have reached similar results if they stayed using the old tool, tweaking their prompts to make that model perform better?