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OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

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Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#111

Post by chasd00 »

state_less wrote: post #78
eigenspace wrote: post #63

Earlier quoted context omitted.

Yes, but 10 or 15 years ago, I would have thought that there'd be more to it than just a slight modification on the ideas behind a CNN to get this level of AI. There were somewhat good reasons to think it needed more than just this data-driven ML approach.

There's something startling about how (relatively) simple these networks are and yet how powerful they are. The main ingredient the AI darlings are using is vast amounts of compute and data. I don't want to take away anything from what the researchers came up with, but I suspect even they are surprised at how capable some of these models have become.

early on there was a lot of talk about "emergent behaviors" in the models where they were good at things that were unexpected or did not align to the training data. IIRC doing arithmetic is one example from early on. I think this is where the AGI craze took off, the labs were throwing more and more data in the training to see what other behaviors would emerge. The thought was with enough data and enough parameters AGI would surface on its own.

Then i think tool use became a priority or at lest a sibling priority to more data/more params. Along with multiple specialized models communicating with each other which is sort of a special case of tool use. That pretty much brings us to today.

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#113

Post by keketi »

adastra22 wrote: post #95
petcat wrote: post #37

Earlier quoted context omitted.

> long live open source models There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API. [0] https://allenai.org/

This viewpoint doesn't make any sense to me. The weights + inference code are the "source code" for AI. I literally don't know what else you are demanding for the "open source" label.

> I literally don't know what else you are demanding for the "open source" label

Training data and code.

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#114

Post by kgwgk »

inexcf wrote: post #82
mastercheif wrote: post #20

Earlier quoted context omitted.

The naming schema actually tripped me up for a week or so. My brain's initial conception of the concepts was earth-relative, so I mapped it as: Sol = big, it's the sun Luna = medium, in-between sun and earth, space Terra = small, terrestrial

Pretty weird when the moon is as much between earth and sun as the earth is between the moon and the sun.

And when it’s in between we cannot even see it (unless it’s exactly in line).

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#115

Post by CodingJeebus »

ComputerGuru wrote: post #6

It's a 20% discount on input and a 33% discount on output through at least November 21, 2026; the revised pricing schedule is now Model Input Cached input Cache writes Output gpt-5.6-sol $4.00 $0.40 $5.00 $20.00 gpt-5.6-terra $2.00 $0.20 $2.50 $12.00 gpt-5.6-luna $0.20 $0.02 $0.25 $1.20 So Sol is still 20x Luna, but much more appealing when compared to offerings from Anthropic and others.

It feels like a slightly more palatable version of what Anthropic has been doing, with their constant "use your free tokens before they expire next week!" campaigns. But it's feeling more and more ominous now, like they've hit the top of the demand curve and need to pull back prices to continue growing.

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#116

Post by visarga »

td-andrew wrote: post #11
eigenspace wrote: post #9

The fact that AI models can be so easily distilled and replicated is such a stroke of luck. 10 or 15 years ago if one had asked me to envision a future where a private company invents artificial intelligence, I'd have thought for sure they'd have a massive moat, be very difficult to catch, and it would create an almost instant monopoly. Rather, it seems that selling intelligence might end up as a race to the bottom.…

It reminds me of the seo antics out there. The search results page is the engine, much like how distilling is the "intelligence" for your chinese room machine

Funny you mention Chinese Room and LLMs in the same response, I would say LLMs proved Searle wrong, agents now make cutting edge discoveries and meaningful problem solving. They not lookup tables though and you need to pay for inference, so the intuition of syntax doing the work of semantics without understanding was wrong.

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#117

Post by kingstnap »

adastra22 wrote: post #95
petcat wrote: post #37

Earlier quoted context omitted.

> long live open source models There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API. [0] https://allenai.org/

This viewpoint doesn't make any sense to me. The weights + inference code are the "source code" for AI. I literally don't know what else you are demanding for the "open source" label.

If you think of LLMs as programs. The weights and inference code are very much a binary.

While the training code and data are the true source. Since if you want to robustly modify the LLM that's actually what you need.

But since "compilation" (training) is extremely compute intensive this isn't something accessible to anyone without an entire datacenter.

Anyway semantics aside having the binary is still infinitely better than dealing with an api as far as privacy and control go.

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#118

Post by chasd00 »

t0mas88 wrote: post #96
GMoromisato wrote: post #76

Earlier quoted context omitted.

"Who knows" is the right answer, I think. If (a) demand for AI continues to increase, and (b) SpaceX can get to ~$100/kg to orbit, then they will have a ridiculously deep moat. Probably more like 10 years, though. But as you said, who knows.

They will have moat in the satellite launching business, which is not useful in the AI datacenter market. You can put AI chips in datacenters in the desert for far less than $100/kg. With lots of solar power available, the option to easily access your hardware and far less radiation issues. The datacenter in space story really only exists to make it possible for Musk to sell X to SpaceX and make more money from the I…

> You can put AI chips in datacenters in the desert for far less than $100/kg

if you can't put them outside of Amarillo Texas without people throwing a fit then you can't put them anywhere. I mean freaking Pantex is there ffs!

https://en.wikipedia.org/wiki/Pantex

Re: OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)

#119

Post by zarzavat »

dlandis wrote: post #100
eigenspace wrote: post #9

The fact that AI models can be so easily distilled and replicated is such a stroke of luck. 10 or 15 years ago if one had asked me to envision a future where a private company invents artificial intelligence, I'd have thought for sure they'd have a massive moat, be very difficult to catch, and it would create an almost instant monopoly. Rather, it seems that selling intelligence might end up as a race to the bottom.…

Hmm, don't people think that if the frontier labs really put enough engineering effort into preventing distillation that they would be able to do that, or at least diminish it significantly? I'm sure there are variety of additional techniques they could use on top of what they already do, but I suspect it just hasn't been at the top of their priorities yet. Maybe that will change soon. Worst case they could add addit…

Even if it were possible it wouldn't change the outcome. China is capable of training frontier models even without distillation. Distillation is only an accelerant.

The primary resource you need to train LLMs is money and China has plenty of that.

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