Gerardo1

Can I submit a request somewhere to have my data removed?

Can users here submit an issue to have data associated with their account removed?

because the people driving these products are disconnected and deeply unbalanced people

Because the first couple major iterations looked like exponential improvements, and, because VC/private money is stupid, they assumed the trend must continue on the same curve.

And because there's something in the human mind that has a very strong reaction to being talked to, and because LLMs are specifically good at mimicking plausible human speech patterns, chatGPT really, really hooked a lot of people (including said VC/private money people).

If you re--calibrate from any lofty idea of their motives to "get investor money now", this and other moves/announcements make more sense: anything that could look good to an investor.

User count going up? Sure.

New browser that will deeply integrate chatGPT into users lives and give OAI access to their browsing/shopping data? Sure

Several new hardware products that are totally coming in the next several months? Sure

We're totally going to start delivering ads? Sure

We're making commitments to all these compute providers because our growth is totally going to warrant it? Sure

Oh, since we're investing in all of that compute, we're also going to become a compute vendor! Sure

None of it is particularly intentional, strategic, or sound. OAI is a money pit, they can always see the end of the runway, and must secure funding now. That is their perpetual state.

They would say that explicitly, that's the kind of marketing you can't buy.

Did you, the company who built and sold this SaaS product, offer and agree to provide the service your customers paid you for?

Did your product fail to render those services? Or do damage to the customer by operating outside of the boundaries of your agreement?

There is no difference between "Company A did not fulfill the services they agreed to fulfill" and "Company A's product did not fulfill the services they agreed to fulfill", therefore there is no difference between "Company A's product, in the category of AI agents, did not fulfill the services they agreed to fulfill."

Exactly. I have said several times that the largest and most lucrative market for AI and agents in general is liability-laundering.

It's just that you can't advertise that, or you ruin the service.

And it already does work. See the sweet, sweet deal Anthropic got recently (and if you think $1.5B isn't a good deal, look at the range of of compensation they could have been subject to had they gone to court and lost).

Remember the story about Replit's LLM deleting a production database? All the stories were AI goes rogue, AI deletes database, etc.

If an Amazon RDS database was just wiped a production DB out of nowhere, with no reason, the story wouldn't be "Rogue hosted database service deletes DB" it would be "AWS randomly deletes production DB" (and, AWS would take a serious reputational hit because of that).

It's not reasonable to claim inference is profitable when they've also never released those numbers. Also the price they charge for inference is not indicative of the price they're paying to provide inference. Also, at least in openAI's case, they are getting a fantastic deal on compute from Microsoft, so even if the price they charge is reflective of the price they pay, it's still not reflective of a market rate.

Don't even need to get too fancy with it. Open AI has publicly committed to ~$500B in spending over the next several years (nevermind even they don't expect to actually bring that much revenue in)

$500B/$100,000 is 5 million, or 167k 30-year careers.

The math is ludicrous, and the people saying it's fine are incomnprehensible to me.

Another comment on a similar post just said, no hyperbole, irony, or joke intended: "Just you switching away from Google is already justifying 1T infrastructure spend."

...what were you doing before?

That's bread and butter development work.

What is?

On the provider end, yes. Not on the consumer end.

These are business customers buying a consumer-facing product.

That's...not hard. Pregnancy produces a whole slew of relatively predictable behavior changes. The whole point of recommendation systems is to aggregate data points across services.

What makes it seem like progress isn't flat?

1 Trillion US dollars?

1 trillion dollars is justified because people use chatGPT instead of google sometimes?

>No, that’s not what it means.

That's fair but it's what I believe.

...see?

Being consistent with stating your beliefs isn't the same as engaging with and about those beliefs.

Advertising isn't conversation. Evangelism isn't discussion.

> That's fair. But it's what I believe.

That response suggests you aren't interested in discussion or conversation at all.

It suggests that your purpose here is to advertise.

Your privacy policy and security page say you do not use any user data for training, it also says you don't store any user data. How do you square that with this comment?

- https://tryapril.com/security - https://tryapril.com/privacy

"The key difference isn’t the words — it’s how you structure the thinking process. By breaking down the task into numbered steps as we see in option B, you’re leveraging how transformer attention works: structured, sequential instructions create clearer context that guides the model’s reasoning."

Can you support that assertion in a more rigorous way than "when I do that I seem to get better results?"

> I cannot reproduce this in any version of copilot?

Because LLM-based service outputs are fundamentally not-reproduceable. We have no insight into any of the model settings, the context, what model is being run, etc.

> One fascinating aspect of LLMs is they make out-in-the-wild anecdotes instantly reproducible

How? I would argue they do the exact opposite of that.

> because MCP brings _nothing_ to the table that I could not do with a "proper" API using completely standard tooling.

This is what drives me crazy and has stopped my tinkering with MCP in its tracks: what is the point? It's not bringing anything new. It's usually not easier to set-up than what you're describing. Or, if you absolutely must have an LLM in the mix, normal function calling does just as well as MCP.

It's a real, "I feel like I'm taking crazy pills" moment: there's all this hype and bluster and "wow look at this", but there is no "this". Everyone's talking about "it can do" and "it'll be amazing when", but there's nothing actually built and present and ready that is impressive.

> By then comparable or even better models will easily run on edge.

What are you basing that on?

From prices that were already losing services money.

If you aren't making a profit, lowering prices is only about trying to capture market share before you're forced to increase prices to remain solvent.

> What about money?

The hundreds of billions being sunk into AI.

> You can't force me to want (or not want) someone's goods and services.

What are you talking about? What does that have to do with anything in this conversation?

> If you're worried about large scale automation and so forth

I'm not.

> I'm fine with something like UBI.

Well as long as you're fine with UBI I guess we can put this conversation to rest.

Seriously, if you don't want to actually participate in the conversation you can just ignore comments. It's fine.

> I want to live in a world with more options and freedom to choose

And you think that AI will be beneficial to that want?

No you can start with actual money.

I don't love that this is the conversation and when these models bake-in these silly scenarios with training data, everyone goes "see, pelican bike! super human intelligence!"

The point is never the pelican. The point is that if a thing has information about pelicans, and has information about bicycles, then why can't it combine those ideas? Is it because it's not intelligent?

That's a rather crappy product naming scheme.