And if anything, I believe progress has been accelerating.

A year ago the SOTA was GPT-5/Opus 4.1/Gemini 2.5 Pro, two years ago Sonnet 3.5.

Looking at Opus 5 for SOTA performance and GPT 5.6 Luna for a viable cheap alternative, AI is much more capable now.

Honorable mention: GPT 5.6 Sol on Cerebras, capacity limited to a few customers, is supposedly serving 750 tok/s.

Compared to 90 tok/s for non fast mode 5.6 Sol, 56 tok/s for Opus 5, and 190 tok/s for 5.6 Luna.

I am very curious about the next generation of models, GPT-6/Astra is rumored to launch still in August. Not sure what is the state of Anthropic's next Fable checkpoint.

If these models also deliver significant improvements, I really do not see how one could seriously still argue among the lines of AI being a scam, and the demand not being there to support the size of the investments.

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kergonath 8 hours ago | parent [-]

> I really do not see how one could seriously still argue among the lines of AI being a scam, and the demand not being there to support the size of the investments.

I don’t think most people are saying it is purely a scam (well, some do but I don’t think they are to be taken seriously). What all these talks about circular financing and VC money are saying is that demand cannot sustain the sector long-term, not that there is no demand. People are certainly happy to pay say $20/month for whatever AI chatbot, but would they still pay if it were $200/month, which is closer to the actual costs.

There are several other details that point towards a unsustainable projections:

- measurable benefits from AI-ifying companies are nowhere near what is commonly believed. AI providers are hoping that they can keep the show going until the models are good enough, essentially faking it until they’ve made it, but that is not a given. It is also unstable because it is susceptible to change in public opinion.

- permits for new datacenters are not going to become easier to get as public opinion keeps turning against them. They will have to concentrate in friendly regions, which will add cost (more demand for the same location, plus interconnection for network and electricity, both of which can easily become bottlenecks).

- the electric grids are not ready for all those planned datacenters, so something will have to give. Building more and more on-site diesel generator in times where oil supply is so constrained and random is not very sustainable either.

- eventually the loans will come due and if earnings do not match there will be a, possibly severe, correction.

If we look at the historical example of the dot-com bubble, the crash was not caused by no demand. It was just caused by over-estimated demand and too much money going to a single sector of the economy. We still use the Internet, and it is still hugely important, but the correction was still severe and real people lost real money.

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user43928 7 hours ago | parent [-]

Those are good points, but some arguments are weak:

- Chatbot usage in $20 plans is likely nowhere close to a $200 cost.

Inference cost has come down rapidly, with reports from July claiming OpenAI can now serve all of the logged out ChatGPT traffic on just a few hundred GPUs.

- Measurable benefit: I doubt anything of value is being measured. MS Copilot with GPT 5.5 Instant processing SharePoint files? Developers using AI as a fancy autocomplete under a "I review every line" regime?

I rely on my personal value judgement, based on 30h/week I spend using AI outside of my regular job.

I am developing a mobile app, competing with companies with millions in revenue and entire dev teams. I know it is viable. Others lag in effective adoption, their opinion is likely to change soon with even more capable models.

- data center projects in the US: They look to me to mostly be constructed in the most remote backwater. If even there projects with such moderate environmental impact cannot be realized, that would be an embarrassing policy failure

- the grid: I think that one is true. AFAIK the constraint would be gas turbines, not diesel, and oil supply is not structurally constrained

- the loans: Anthropic is rumored to have become profitable earlier this year because of large growth in enterprise revenue. It does not look so bad to me

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AussieWog93 7 hours ago | parent [-]

>I am developing a mobile app, competing with companies with millions in revenue and entire dev teams. I know it is viable. Others lag in effective adoption, their opinion is likely to change soon with even more capable models.

To add to that, as an ex-software dev that mostly works in a semi-unrelated field now (and can only code as a small part of my job): I think a lot of software devs are underestimating what someone with reasonable technical skills and specialised domain knowledge is able to create with AI.

I honestly wouldn't be surprised if, in 5 years' time, the majority of software used by (e.g.) potato farmers was primarily created by other potato farmers. The code might still be less elegant but I think it will be easier for the potato farmer to iterate with an AI than outsourcing to a dev firm.

	▲	user43928 7 hours ago \| parent [-]
		On a tangent, because you mentioned five years for widely used software being implemented by domain experts rather than software engineers: this seems like a very conservative timeline. I have little doubt that a competent potato farmer could possibly implement and sell such software today using Opus 5, Fable, or 5.6 Sol. Now what I am going to say next may sound a bit crazy, and it is outside of my area of expertise. I hear the recent mathematical breakthroughs made by GPT-6/Astra are field medal worthy discoveries. What if the current trajectory of improvement holds for another year or two? Is it impossible that LLMs gain superhuman ability to reason over a large number of constraints so that they can make novel breakthroughs unimaginable to us today? What I hope to see in five years is not potato farmers writing software, but programmable immune cells that safely kill cancer. Perhaps I am an optimist.