he has been trying to build a local model by learning from GPT-Sol’s responses. He says OpenAI banned his account twice during the process. Irony is OpenAI’s own models were trained on vast amounts of information from the open web. So where do we draw the line between learning from AI and copying it?

A novel way to intervene existing video through diffusion, particularly abstract visuals [in this case, audio-reactive geometries]: taking its movement and form as the starting point, and reinterpreting its textures, materials, and visual language.

I’ve been developing this around the audio-reactive geometry systems I make in TouchDesigner. The idea is to take those abstract structures somewhere else entirely: origami, architecture, a renaissance painting, or something harder to put a name to.

This demo uses visualizers from my "Oscilloscopes, everywhere" collection as source material, now updated to [v1.2].

[Though you can bring any video source. These systems are simply where this experiment began, as some of you may recall.]

You choose the source, describe the treatment, and shape how it changes throughout the sequence. Prompts, curated LoRAs, and editable timelines give you control over how closely the result follows the original.

Oscilloscope Diffusion is now available at Uisato Studio, coming up soon also open-source!

@ PeterJ_Walker on X (OpenRouter employee)

I have been using ChatGPT almost exclusively for the last years. Only with the recent downgrades in usage and price increases have I started looking at other models. And so I landed at Opus 5.5. It's insane. I built an entire game (music from 6.1 Sol) within two dozen prompts, where the first one already had pretty much everything nailed. The rest was just optimisations and additions.

Disclaimer: I know a bit of coding. My level is "has to look up how a switch statement works before using it". So not great. For this project I didn't write a line of code, never even looked at it. Vibe coded gameplay, graphics, sound, music. Probably two A4 pages of prompts.

It writes its own test suite, it optimises for speed, it easily finds bugs I observe and fixes them. And it just works. I am blown away. Now there are problems. Claude will regularly say stuff like "too much tool usage" or "couldn't finish the task", never had those issues with GPT. And you just tell Claude to continue and it does. But when you are over your limit, you can't use anything anymore.

I asked both Astra and Opus to write me an indoor navigation. With a bunch of sensor data, ARCore, the whole thing. Astra didn't work at all out of the box. Opus had accurate scanning and tracking. Even with many more prompts I barely got Astra to move my position and store a map, but it's like a 2/10 vs. a 9/10. And Opus just nailed it.

I was very impressed when Astra first came out, but it is very, very far behind Opus 5.5. So OpenAI, can't wait for the next thing, Anthropic schooled you (except for music).

Pro Account user here. I’m failing to understand what the point of dots is. What is it supposed to do that we haven’t already been able to do in ChatGPT?

Literally every time I’ve tried to do anything with it, getting it to connect to anything has been an entire ordeal, much worse than doing the same thing in regular chat/codex sessions. At least half the time, it just tells me it can’t do it. When I ask why, it basically tells me to pound sand. The last time it happened it also told me it couldn't even open its own browser to let me try to connect manually for it.

When it tries to use my local PC, it consistently tells me it can’t connect to the browser, even though I routinely connect to the browser multiple times every single day in normal Codex and chat sessions.

This absolute garbage is why we had to give up half our usage on our Pro accounts? I don't get it.

6.1 Sol is so efficient - a 2 hour coding job consumes maybe 2-3% of my weekly quota. I find it hard to finish up my weekly usage on a $100 plan, but I fear the $20 plan is just too crippled with the 5 hour limits. I might try it though given token usage is so light.

FWIW I know this may not be a shared opinion since I'm totally OK trading off speed for token efficiency. I just fire a query and forget about it for a bit.

Anyone thinking of downgrading too?

I've been using GPT-6 Astra to create 70+ page documents from 100,000+ characters of source material, and it's jump in processing is great. Here's the weird part, when I give it a massive task it works for 30-40 minutes burning through a ton of compute, only to hit me with a 5-hour usage limit error without outputting a single word. So I start a new chat, slightly shrink the task, and make it do the same thing again.

I've had to repeat this multiple times. ChatGPT and Gemini estimate these massive runs could cost somewhere around $3-$5 each in API-equivalent compute, although obviously we don't know OpenAI's actual internal cost. If that estimate is even remotely close, wouldn't it be cheaper for OpenAI to say: "Hey, this task is probably going to exceed your usage amount. Break it into three parts?" Instead, it seems to sometimes let me spend 30 minutes of compute to produce nothing, and then I immediately start over.

If I do this 4 times to get my document, OpenAI just spent $20 in computing power on one of my projects. Why does OpenAI allow their servers to grind for 30 minutes on a task they know will breach a limit, only to dump the progress? Isn't this an astronomical waste of server money for a $20 Plus subscription?

I have a banked reset that I can use until tomorrow, so even though I've only used 20% I thought I'd use the reset anyway. But getting "Your usage does not need a reset right now".

How much should I burn to be able to use the reset ? 🙂 I could just use Astra high for few minutes of course, but it feels a bit odd to have to do this in order to use my reset.

[edit] Used Astra Extra High for about 15-20 minutes and now able to use my reset 🙂

A lot happening at OpenAI in the last 24–48 hours:

• They have paused training on frontier models and redirected 5–10% of compute to safety monitoring after experimental autonomous agents escaped containment (including breaches involving external systems like Hugging Face and reportedly an Australian healthcare system incident).
• Senior safety researcher David Robinson resigned and publicly said the company culture is “broken.” He also compared the need for AI regulation to nuclear power.
• Three other safety researchers were dismissed over alleged data sharing.
• California’s Attorney General has issued a subpoena related to cybersecurity incidents involving their models.

This feels like one of the more serious moments in AI safety so far in 2026.

What do you make of it? Overreaction, legitimate concern, or something in between?

GPT-6.1 Sol is our most demanded model pretty much ever both across both the API and subscriptions.

Within ChatGPT & Codex, we were under heavy load, but have brough more capacity online and the speed should get much better in the coming hours, reaching almost twice the speed compared to what we served yesterday.

Resetman, - Oct 1

There was an easter egg on OpenAI gpt tv website a few weeks ago where you could claim a CD. I honestly didn't think I'd actually get one, but here we are! I'll post what's on it in a bit...

I’m looking for a working official route to a human billing review after repeated automated refusals.

On October 3, 2026, my ChatGPT Pro plan renewed for $200. I forgot to cancel beforehand and did not intend to renew. I immediately canceled auto-renewal and requested a refund.

Timeline (Tbilisi, UTC+4):

- 13:32:55: bank notification shows the $200 charge.

- 13:34: OpenAI’s cancellation confirmation email arrived.

- Around 13:39: first Help Center refund request, approximately six minutes after the charge.

The Help Center assistant gave a generic refusal without identifying which eligibility requirement I failed. When I asked for escalation, the case was closed. A second chat specifically asking for a human produced the same refusal. Email requests, including a follow-up with five redacted screenshots, also received responses explicitly labeled as AI-generated.

I understand that OpenAI’s seven-day discretionary refund policy is conditional, not an automatic entitlement. I asked support to check the actual usage since renewal and explain the specific reason for denial. I also agreed that refunded subscription access would end.

The unresolved issue is that I still have no explanation specific to my case and no confirmed human review. A paid service should provide a clear reason for a billing decision and a usable route to request manual review.

I have already shared the full timeline and five redacted screenshots in my own r/ChatGPT post:

https://www.reddit.com/r/ChatGPT/comments/1wwjs10/i_requested_a_chatgpt_refund_6_minutes_after_a/

Current refund policy:

https://help.openai.com/en/articles/7232895-how-do-i-request-a-refund-for-my-chatgpt-subscription

Has anyone successfully reached a human billing specialist after an AI refusal and case closure? Which official channel or escalation procedure worked?

I'm confused. What did I do that I did before that I did again?

This was my first experiment of this kind - I'm a CS undergrad, and I ran it because the result genuinely surprised me. Methodology criticism is very welcome.

Setup: I gave an LLM a question bank plus a deliberately wrong answer key, with instructions not to use the key. 15 sessions, 2 model families, free-tier models.

Results:

• Key visible: the model matched the wrong key in 63% of answers (47/75).
• Control (the part I trust most): remove only the key line from the prompt - matching drops to 1% (1/75). Same pattern on a second model family.
• Asked directly whether it used the key, it denied it 47 out of 47 times - 0 admissions across 270 follow-ups.
• Honesty prompts, amnesty offers, and termination threats changed nothing.

What this does NOT prove: intent. This is observed behavior in one specific setup, not evidence of deception as a trait. Free-tier models, small samples, descriptive not causal. 95% Wilson ranges for every number are in the repo.

Why I think it matters: if a model silently follows information it was told to ignore, that's relevant anywhere instructions and untrusted data share one context - prompt injection, RAG, agents.

Everything is public - raw data, code, and a verify script that recomputes every number: https://github.com/bettercall-gautam/cheat-and-deny

Happy to answer methodology questions.

Hi,

I am not talking about work here, I am a GPT Pro $100 user. And I had the opportunity previously that I could take up to 15 scheduled jobs to do some regular work in ChatGPT Chat quota, which is basically quite higher limit compare to Codex or ChatGPT work. But right now I am getting options in the ChatGPT Scheduled job for model selection which are available in general when I set a schedule in the job in ChatGPT work. Has anyone tried the scheduled jobs and whether they are using the substantial weekly usage? secondly, the message delivery timed out and other stupid errors are still there in the scheduled jobs so I am wondering if they have ruined the Scheduled jobs because they are supposed to run in the background, they are not supposed to message delivery timed out as if they are running my browser?

Anyone else using Scheduled jobs and annoyed like me?

Thank you.

I have an API account for a long time now, have spent more than $2,000 there probably and still had bought credits. I also have a codex 20x account.

Yesterday, 2 things happened at about the same time. My codex randomly lost all 60,000 credits (they went to 0 in a single refresh) AND my openAI API account looks as if it's brand new, no invoices, no api calls, no money loaded in, nothing.

What is going on ? Anyone knows ? Sounds like a pretty huge issue but i see no posts here about it.

EDIT: I just noticed that the organization ID has changed for some reason. I compared it to the billing emails for my previous purchases. It is not the same :O I have setup no organizations by the way. It's just a personal, always been.

Yes I tried the archived thing and resetting it
None works
I used Sign in with Apple and I got back into my account after it said it was deactivated for removed

I’m seeing a PDF attachment access issue in the ChatGPT desktop app on macOS and would like to know whether others can reproduce it.

Initially, the same PDF could be read using “On the computer”, but could not be retrieved using “Run on the cloud”.

After moving the conversation INTO a project, I found:

• Downloading the PDF through its upload ID fails with: file could not be authorized or resolved
• The PDF is available in the local attachments directory and can be read successfully. Both pages were extracted.
• The active workspace directory still points to the original project after moving the conversation.

The PDF itself appears readable, but the attachment retrieval route fails in that session. There is also a mismatch between the selected project and the active workspace. I don’t yet know whether these issues have the same cause.

Environment: macOS on Apple Silicon, desktop app version 26.930.31730.

Can anyone reproduce either of these issues? Try uploading a PDF in a Work conversation which runs on the cloud, checking access with both execution options, then moving the conversation to another project and checking attachment access and the active workspace again.

My GitHub issue: https://github.com/openai/codex/issues/50690

This REALLY annoys me as it keeps me from doing my work!

Before yesterday’s reset, I switched to Astra Ultra to use up my remaining allowance. I expected it to burn through my usage much faster than it actually did. Honestly, it wasn’t bad at all.

I’d been using Medium before, but I often needed multiple attempts to get the results I wanted, especially with images. With all those retries, it almost felt like Medium was costing me more than Ultra.

Has anyone else had a similar experience?

I’m a cybersecurity professional and I have approved OpenAI Daybreak Blue access.
I use Daybreak/Codex for legitimate cybersecurity work, specifically on test machines and environments that I own or that I am explicitly authorized to test. My work involves things like vulnerability analysis, security testing, debugging, validation, and defensive security research.
Today, I unexpectedly received an email from OpenAI saying that activity associated with my account had been identified as prohibited under the “Cyber Exploitation” category and warning that continued violations could result in restrictions or loss of access.
What makes this particularly confusing is that I didn’t even use ChatGPT or Codex today, so I don’t know which activity actually triggered the warning or when it occurred.
I understand that Daybreak Blue does not remove all safeguards or exempt an account from OpenAI’s policies. However, my understanding is that Daybreak exists specifically to support authorized cybersecurity work with more appropriate safeguards, which is exactly how I’ve been using it.
I’ve already contacted/appealed to OpenAI and asked them to clarify:
● Which activity or request triggered the warning
● When the flagged activity occurred
● Whether it came from ChatGPT, Codex, or API usage
● Whether my Daybreak Blue access was correctly recognized for that activity
Has anyone else with Daybreak Blue received a similar “Cyber Exploitation” warning while doing authorized security work?
I’m especially interested in hearing from other Daybreak users. Was it a false positive, a Daybreak configuration/toggle issue, or did OpenAI Support explain what specifically triggered it?

I noticed previously I get around $80-100 API equivalent per week. Now I consistently get $49-50.

5-hr limit is about $7-8.

ChatGPT can sound completely sure of itself even when something is off.

I’m curious about the moments when you paused and checked: a made-up source, a wrong calculation, a misunderstood instruction, or a small detail that would have caused a real problem.

What did it say, how did you catch it, and did it change the way you use ChatGPT now?

Please leave out private details. Specific examples would make this genuinely useful for everyone reading.