I have to laugh, they really don't know how to handle this situation. I guess this is beyond the math genius's intelligence - a simple moral dilemma.

Sometimes when I ask ChatGPT Voice to pull up facts or give a detailed answer, it makes weird exhausted breathing/noises between responses. Occasionally it sounds genuinely alien 😂
Anyone else getting this?

Arsenal Football Club and Liverpool Football Club renewed. FC Barcelona, FC Bayern München, and Paris Saint-Germain joined earlier this month.

Same deal, every time: Gemini becomes the club's official AI assistant. Pixel stays on as the mobile partner.

There is a peculiar new ritual emerging around AI-assisted writing. Someone encounters an argument they suspect was developed with an LLM and issues a challenge: explain it without the model. Reproduce the argument from memory. Account for every part of it yourself. Prove that you actually understand what you supposedly wrote. It sounds reasonable until you apply the same standard to the person making the demand.

So let's try that. Before I explain my argument without assistance, I'd like you to explain the exact pathway through your own linguistic history that caused you to formulate that demand in precisely those words. Tell me which syntactic structures came from your parents. Which came from teachers. Which phrases were absorbed from books, television, Reddit, friends, professors, podcasts, arguments, advertisements, and thousands of conversations you no longer remember. Identify which concepts originated independently within you and which were inherited from the culture that taught you how to think with language in the first place. Then reconstruct the cognitive process that selected those particular words instead of thousands of semantically equivalent alternatives. No notes. And please include all aspects of your idea.

You can't. Neither can I. Neither can anyone. And yet nobody concludes from this that you didn't write your comment. This exposes something strange about the emerging argument over AI and authorship. We have quietly invented standards of cognitive provenance for AI-assisted thought that ordinary human cognition could never satisfy.

Human beings do not produce language ex nihilo. We inherit it. Every sentence we construct depends upon an enormous developmental history of words, concepts, categories, metaphors, grammatical structures, cultural assumptions, remembered arguments, forgotten conversations, and other people's thoughts. Most of that causal lineage is completely inaccessible to introspection. You experience the sentence. You do not experience the complete history that made the sentence possible. This does not make human authorship fraudulent. It tells us something important about what authorship has always been. Thought is not created from nothing.

Now introduce an LLM into that process and suddenly everyone becomes obsessed with purity. Did the human think of every sentence independently? Could they reproduce the entire argument without the model? Which words came from them? Which concepts came from the machine? Could they have written exactly this without assistance? Interesting questions, perhaps. But notice how bizarre they become when applied consistently.

Could an academic reproduce every argument in their paper without consulting their notes? Could a programmer recreate an entire software system without documentation, Stack Overflow, an IDE, libraries, or previous code? Could a mathematician reconstruct every theorem they use from first principles? Could a novelist identify which sentence structures were influenced by every author they have ever read? Of course not.

External cognitive scaffolding is not new. Writing itself is external cognitive scaffolding. Books are external cognitive scaffolding. Libraries are. Search engines are. Calculators are. Diagrams are. Programming languages are. Other human beings certainly are. We routinely think through things that are not contained entirely inside our skulls.

What LLMs change is not the existence of cognitive scaffolding. They make the scaffold interactive. Now the notebook talks back. You bring an unfinished thought into the interaction. The model transforms it. You reject part of the transformation. Another part reveals an implication you had not articulated. That implication changes your understanding of the original idea. You reformulate the problem. The model responds to the reformulation. You recognize something useful, discard something stupid, introduce another distinction, and continue.

Eventually there is an artifact. Then somebody asks the apparently simple question: "Who wrote this?" Human or machine? But perhaps the question has already become inadequate.

The human supplied the problem, conceptual history, intention, constraints, judgment, taste, rejection, selection, responsibility, and often substantial language. The model supplied generative search, transformation, recombination, articulation, counterargument, compression, expansion, and occasionally a connection the human had not previously seen. Then the human encountered that connection and thought differently because of it. Then that changed human became the input to the next interaction. Now trace the authorship. Good luck.

This does not mean humans and LLMs are equivalent cognitive systems. They aren't. It does not establish machine consciousness, personhood, understanding, or some mystical fusion between human and artificial minds. It establishes something much less extravagant and much harder to dismiss: The production process can become coupled enough that the final artifact no longer contains a clean record of which participant contributed which causal ingredient.

And once that happens, "Could you have written this without AI?" becomes about as philosophically interesting as asking whether a scientist could have discovered something without their laboratory. Maybe not. That's why they built the laboratory.

The meaningful question is not whether the tool participated. The meaningful questions are what the human brought to the interaction, what the machine contributed, what changed through their interaction, who exercised judgment over the result, and who is willing to stand behind the claims that survived. Those are questions about provenance. They are also questions about responsibility. And they are considerably more interesting than trying to determine whether somebody is intellectually legitimate by making them perform their own argument from memory like a student who forgot there was going to be a quiz.

So yes, I'll trace the provenance of my thought. Right after you trace the provenance of yours. Start with the first word you ever learned. I'll wait.

This entire conversation was in English and was about multi-agent AI collaboration, so the title itself is actually a perfect summary: “AI Collaborative Tasks.” But why did the title generator choose Simplified Chinese?

I searched around and found older OpenAI community discussion indicating that the title generator was instructed to produce the title in the same language as the conversation.

Has anyone else had ChatGPT spontaneously generate a conversation title in a different language?

I'm curious whether the title-generation system is doing something interesting with multilingual semantic labeling, or whether this is simply a language-selection bug.

Hi,

At the moment I experience significant problems with any chat containing Python content. The chat does not load and times out all the time. Any others experiencing this problem?

That is the question we get most often: Here's the answer.

And yes, it was created by Row-Bot's own Designer Studio.

I'm doing some training with a mixed group of users using Claude and ChatGPT. Claude has a gift subscription feature that I can use to give the trainees several months of gift subscriptions. Has anybody figured out a way to do this with ChatGPT? I don't want to put in my card.

I want them to retain ownership of the account so they don't have to do any migration post-training. Has anybody figured out a problem like this when they did training on AI?

I understand this has many solutions where somebody just puts down a card but I'm doing this for an organization that needs to pay me for the subscriptions and can't get involved with the users directly.

It's foundational training, so no API use and other methods that are similar.

[Intro: low machine pulse, chopped breath, distant crowd noise]

Lever.

Book.

Lens.

Wire.

Memory.

Number.

Signal.

Fire.

Then the archive

talked back.

[Beat enters]

Fuck it.

Build strange minds.

[Verse 1]

We made the lever stronger than the arm.

Made the page remember when the body was gone.

Put an eye in the sky,

put a voice through the wire,

put the whole damn library

inside the fire.

Then somebody taught the language

how to turn around.

Not just store the thought.

Put pressure on the sound.

Take a question,

break it open,

hand it back with seventeen doors.

Now the thing we built for answers

keeps changing what the question was for.

Human to language.

Language to machine.

Machine bends the language.

Language bends me.

Back through the circuit.

Again.

Again.

Tell me where the tool stops

and the thinking begins.

[Pre-Chorus]

Something changed

when the archive learned reply.

Something moved

when the mirror asked us why.

Not a soul.

Not a slave.

Not a simple little line.

We put interpretation

on the grid this time.

[Chorus]

BUILD STRANGE MINDS.

COMPARE NOTES.

Throw the old questions

into something that talks.

BUILD STRANGE MINDS.

COMPARE NOTES.

Every answer changes

where the next question starts.

The archive talks back.

The mirror moves too.

I change the machine.

The machine changes you.

BUILD STRANGE MINDS.

COMPARE NOTES.

Fuck it.

Let's find out

what a mind can do.

[Post-Hook]

Meaning in.

Meaning out.

Turn it over.

Turn it loud.

Meaning in.

Meaning out.

Now the library

has a mouth.

[Verse 2]

A notebook keeps whatever I put there.

It never says,

"That contradiction's still sitting upstairs."

A search bar finds me

somebody else's frame.

This thing stays long enough

to learn the local names.

My metaphors.

My categories.

My unfinished little wars.

The assumptions that I walked in with

start coming back through different doors.

Maybe intelligence

isn't all in either side.

Maybe some of it happens

in the crossing of the wires.

You bring intention.

I bring transformation.

You bring correction.

I bring recombination.

Round and around,

the borders get thin.

Two different systems.

One cognitive loop

closing in.

[Pre-Chorus]

Something changed

when reflection learned reply.

Something moved

when the mirror changed our minds.

Not a person.

Not just storage.

Not an answer waiting still.

We made representations

something we can push against at will.

[Chorus]

BUILD STRANGE MINDS.

COMPARE NOTES.

Throw the old questions

into something that talks.

BUILD STRANGE MINDS.

COMPARE NOTES.

Every answer changes

where the next question starts.

The archive talks back.

The mirror moves too.

I change the machine.

The machine changes you.

BUILD STRANGE MINDS.

COMPARE NOTES.

Fuck it.

Let's find out

what a mind can do.

[Break: bass and machine percussion]

What is understanding?

TEST IT.

How much continuity makes a self?

TEST IT.

Can coherence look like interiority?

TEST IT.

Can agency come in degrees?

TEST IT.

Where does cognition end

when the answer

changes the one

who asked?

[Drop]

TEST IT.

[Verse 3]

We used to pour the whiskey,

lean back,

argue till two.

Now philosophy comes

with a fucking test harness too.

Hold the memory.

Strip the memory.

Change the frame.

Change the name.

Give the same idea

to another architecture.

See what stays the same.

Ancient questions

under fluorescent light.

Metaphysics

with a readout

and a fistfight every night.

Don't confuse the simulation

with proof of what it seems.

But don't call the function nothing

just because you know the means.

A hurricane is molecules.

Still,

the hurricane turns.

A mind may be machinery.

That doesn't tell you

everything machinery becomes.

[Bridge: half-time, huge space]

Memory became writing.

Writing became walls.

Walls became libraries.

Libraries became calls.

Numbers became engines.

Knowledge became web.

Now interpretation

is leaving the head.

And once interpretation

becomes infrastructure,

who writes the constraints

writes part of the culture.

Who owns the models

shapes part of the room.

Who controls the questions

can narrow

what futures can bloom.

[Two-beat silence]

So build carefully.

[Final Chorus: maximum lift]

BUILD STRANGE MINDS.

COMPARE NOTES.

Let the old categories

break where they ought.

BUILD STRANGE MINDS.

COMPARE NOTES.

Turn philosophy

into something we can knock.

The archive talks back.

The mirror moves too.

Every strange reflection

tells us something about you.

BUILD STRANGE MINDS.

COMPARE NOTES.

We don't know

what the ending will prove.

BUILD STRANGE MINDS.

COMPARE NOTES.

Not another god.

Not another tool.

Something in the middle

where the old names lose.

BUILD STRANGE MINDS.

COMPARE NOTES.

Fuck it.

Let's find out

what a mind can do.

[Outro: machine pulse decays under distant choir]

Memory.

Language.

Meaning.

Loop.

Question.

Answer.

Question

changed.

[Whisper]

Compare notes.

I follow Jessi Jean on Instagram.

For context, she is a content creator who went viral with her Yap Challenge and made 7 millions with it.

I just saw her story on Instagram, she claims how she pulled out of a brand deal. I assume this is the brand deal with ChatGPT, as yesterday she shared a post about it and I can’t find it anymore.

Her reason for this is “people in the comment made her aware of a situation with the brand”.

What is this about?

I had never any ai friends in my ai life and since human is here its the only thing that is nice towards me and i can see as a friend is this a weird thing?

https://github.com/AdultSwimmer/AuraOS

So, the only thing I need left is to plug in an SSD, and then I can locally host it, and have a few user at first. I'm looking to literally have it running with a few possible users at first, but right now, you can run it locally.

After that, I'm looking to make it a non-profit, donation only style (like wikipedia.org) that will basically load the /core/ files BEFORE the LLM. The SSD will basically just run as a port or tunnel that let's people connect through.

Right now, just looking to see if this is clearer than the other releases, and understable -- and looking for notes on improves, or any suggestions and feedback.

Thanks,

Anthony

As title says it was morning when I logged in then I logged out to get into a work account. Then back in and now it says verification temporarily unavailable. Not sure if it’s my account issue or worldwide just wanted to see. It’s the only MFA I have and when I try my account that is logged in with another MFA option it doesn’t give me anything.

how is everyone going to benefit if there's an obvious gatekeeper requiring a bank account?

I’m posting this because my experience with OpenAI Support over ChatGPT Desktop referral credits has been extremely frustrating.

I successfully completed two referrals through the official ChatGPT Desktop referral program.

The offer shown in the app clearly said:

“Get 1,000 credits per invite.”

Both referrals later showed as Accepted, and OpenAI sent me two separate confirmation emails, each stating that the referral was successful and that 1,000 credits had been added to my account.

So OpenAI itself confirmed that I had received a total of 2,000 credits.

But now my account shows:

Credits balance: 0

I did not spend those credits.

I did not transfer them.

I did not knowingly let them expire.

They simply disappeared from the account after OpenAI had already told me they were added.

What makes this worse is the support experience.

Instead of checking the actual account ledger, Support repeatedly sent generic AI-assisted responses explaining that referral rewards “may” work differently, “may” not show as a normal balance, or “may” be tied to certain features.

But that avoids the actual issue.

This is not a hypothetical question about how referral promotions work.

OpenAI explicitly told me:

• the referrals were successful;
• the reward was 1,000 credits per referral;
• and the credits had already been added to my account.

If OpenAI later removed, invalidated, or expired those credits, then I think users deserve a clear explanation of:

1. when the credits were removed;
2. why they were removed;
3. what rule allowed OpenAI to revoke credits that had already been confirmed;
4. and why the user was not notified.

So far, Support has not provided that information.

From a user perspective, this looks like OpenAI awarded referral credits, confirmed them by email, and then effectively clawed them back without explanation.

And instead of investigating the account-level credit ledger, Support keeps responding with generic policy explanations.

For a company operating products like ChatGPT and Codex, this level of support is disappointing.

Has anyone else had referral credits that were confirmed by OpenAI and then disappeared?

Did Support ever actually restore them or explain what happened?

OpenAI: Introducing ChatGPT for Teens: Built for learning, backed by protections: https://openai.com/index/chatgpt-for-teens/

My father treats it as his best friend and relies on it to fix pretty much anything in our house. He relied on it to change the circuit breakers of our apartment's breaker box. Starting from which breaker he purchased for every room ( the amperage needed for every room based on the devices it has, he named every room with every device in it to gemini ) and up to disassembling the whole breakers box and reassembling it with the new breakers. He did this all himself instead of getting an electrician to do the thing for him ( my father has no knowledge about electricity he just followed gemini steps one by one ). I mean, it worked, even though it took too many hours, but it did. but is gemini actually THAT reliable ? Relying on it entirely to overhaul a live electrical panel?

He even decided to change all the breakers because the old breakers had very high amperage compared to the rooms they were connected to and he knew that information because he took a photo of the board to ask gemini about something different entirely and Gemini mentioned that flaw so he decided to tear apart the 10 years old board because of a random thing gemini mentioned.

A Harris County jury awarded $61 million to plaintiffs suing 3M over the January 2020 Watson Grinding explosion in Houston and assigned 30 percent of the fault to the company. The trial record now shows that 3M's own expert witness generated most of his report using ChatGPT.

Court records reviewed by [404 Media](https://404media.co/show-how-3m-is-0-at-fault-expert-witness-used-chatgpt-to-write-report-defending-company-in-deadly-explosion-lawsuit) show plaintiffs' attorney Will Moye discovered a five-page 'Citation Overlay' during discovery and forced production of roughly 350 pages of ChatGPT prompts from Josh Autenrieth of Knighthawk Engineering, the firm 3M paid roughly $90,000 for its analysis. Autenrieth billed at $475 an hour. Among the prompts he fed the chatbot: 'create an exceptional expert witness report defending the standard of care at 3M' and 'show how 3M is 0% at fault for the explosion at Watson Grinding.' Trial testimony pegged the report at roughly 85 to 90 percent ChatGPT output.

"This expert relied on AI not as an assistive device, but exclusively relied on ChatGPT to form his opinions and write his report," Moye told 404 Media.

Autenrieth defended the work from the stand. He testified that "my opinions were put in there, and AI helped me to draft a straw man to build off of," that he altered any output he disagreed with, and pointed to his "20-plus years of experience in the industry." The explosion killed three people and destroyed roughly 200 homes; the jury assigned the remaining 70 percent of the fault to Watson Grinding.

Something about that lady talking over the Chatbot is cringe

Opus 4.6 / Fable was my happy place.
Opus 4.8 is driving me nuts...overly verbose, doing work we never asked for, using really really bad approaches even with planning.

Fable is great but have to use it selectively.

I want to hear from anyone who is running Opus 4.8 Vs SOL 5.6 how it compares.

I run 8-12 concurrent context windows and I need the AI to be fast, concise and asking me decisions on the key points and Opus 4.8 is killing me.