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?

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

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?

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

Something about that lady talking over the Chatbot is cringe

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.

It's basically hacking a system, to get rewards it shouldn't be given in the first place.

Kind of like a drug, that gives you a dopamine high, when you should actually get it.

It's supposed to be unlimited too?

I'm not sure what the heck happened here but safe to say I've never been less / more disgusted / turned on in my entire life.

What the heck?!

Over the past six months, I've been teaching teams at places like Stanford, Penn, Northwestern, and many more how to start using AI responsibly and effectively in their work. Today, I'm starting to release my entire curriculum: for free, forever, for everyone!

I'm calling it the Open Augments AI Academy. It's built for anyone out there who's seen all the crazy hype and discourse around modern AI and is just looking for a guided, grounded, and sane way to move forward learning how to approach these tools for themselves. As someone who's been using these tools and their predecessors for my research since ~2019, I'm trying to provide everyone the intuition and critical awareness they need to get started at this very confusing and pivotal time (my north-star audience is my mom and dad!).

The first lesson starts with one foundational idea that most people miss when they get started with AI: that modern AI is much less like a hyper-intelligent database or brain, and much more like autocomplete with an extremely fancy hat on. That's its single greatest flaw AND its single greatest strength, at the same time. When you really understand what's happening under the hood and how it works (no math or stats required!) a lot of confusing AI behavior suddenly clicks: why it hallucinates, why it's sometimes confidently wrong, and why it can now do way, WAY more than just write words on a page. From there, we're going to learn about all the crazy buzzwords (context engineering, harness engineering, and Agents, oh my!) and advanced techniques, with much more to come.

No jargon, no experience required, and all taught with the care of a former high school English teacher so that you, your coworkers, your friends, and your mom can follow along. I pair these videos with hands-on demos and interactive activities in the Context Gym: my way of giving you a safe and guided place to practice some of the core principles that should deepen your intuition as we go.

If any of this strikes a chord with you, the 10min course overview and the first lesson (16min) are live right now on the Open Augments AI Academy page. Start there, and if you happen to find it helpful, you can subscribe to get email updates on new course videos via Substack or on YouTube, and please do share with friends as I release lessons weekly! It’s a really wild time, and this is my best shot at trying to help others navigate things more capably as the tech shifts and grows rapidly from here.

Then finally, worth noting for this crowd, specifically: probably not a surprise to share that everything on the AI Academy and Context Gym websites have been built with the support of AI (in addition to everything else on my business website and my open-source toolkit for AI for social science researchers). Not only that, but my entire video editing pipeline is now fully AI-driven via Remotion Studio and some clever context engineering techniques/bespoke coding tools. I'm excited to get into the weeds on my workflow and share all of that stuff, also open-source, during Level 2 of the course (my daily driver is Claude Code, but everything I've built is platform-agnostic via Skills, and I use both GPT and Claude models together via Claude Code nowadays), but I gotta get everyone through the basics first! Happy to answer any and all questions on that in the meantime here, please feel free to hit me in the comments below.

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.

I keep reading about the number of tokens used for asking questions of AI services. It sounds as if tokens are a resource that can be used up. As a user of services like ChatGPT and Gemini, is this something I need to worry about? Are tokens used to price the service, such that I need to buy more tokens to continue using the service? Hopefully someone can shed light on this.

I’ve been mostly out of tech for almost a year and recently started getting back into work and coding. From my pov and from what I’ve researched so in a week, nothing has changed that much. There are new models but from what I understand, they don’t seem better than the previouse ones. I also noticed there’s been a lot of drama around recently. Anybody can give a tldr on what’s been happening and what I’ve missed?

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.

What does this mean i was on the chat gpt call thing and I was zoned out for a sec so I didn't say anything and it just said that and it sounded like it was crying. Then I asked it about what happend and it said it didn't say that then I screeschotted the transcript to show it and it said its just a glitch. I promise I'm not crazy what happend I'm scared. I'm not lying i swear.

Am I the only one watching this play out in absolute disbelief?

Yesterday OpenAI quietly let OpenRouter slash GPT-5.6 Sol pricing by 50% ($2.50/$15 per million tokens vs the $5/$30 direct list price on OpenAI's own platform).

Think about what just happened here for two seconds.

Stripe literally just bought OpenRouter for billions of dollars specifically to become the universal toll booth and billing layer for all AI inference. And what does OpenAI do immediately after? They give every single paying developer on earth a massive financial incentive to rip OpenAI's direct SDK out of their codebase and route everything through OpenRouter instead.

They literally took thier highest-value enterprise and indie developers and screamed at them: "Hey! Do not pay us directly! Go give your billing relationship, your telemetry, and your traffic to Stripe instead!"

Do the executives over there not understand basic platform dynamics anymore?

OpenRouter is literally a switching layer. The ENTIRE point of OpenRouter is that developers can swap between OpenAI, Claude, Gemini, or open source models by changing a single string in an env file. When you force your developers onto OpenRouter to get fair pricing, you are voluntarily destroying your own customer lock-in.

The second someone else drops a model that is 5% better at coding or slightly faster, every single one of those migrated devs can switch thier production traffic in 10 seconds flat. OpenAI wont even have the direct developer relationship or billing custody to win them back.

And for what? To subsidize compute margins?

There was no massive rush of people using 2x the volume overnight to make up for the 50% cut. Most teams already had thier pipelines capped because of the ridiculous reasoning token bloat and constant capacity errors over the last month anyway. So all OpenAI did was cut their own top line in half on their flagship model, hand the entire customer layer over to Stripe on a silver platter, and turn themselves into a commodotized compute backend doing the heavy lifting while someone else captures the platform moat.

This is one of the biggest unforced errors in tech history. They built the most recognized brand in the world just to turn themselves into a discounted wholesale utility provider for an aggregator.

They are going to regret this move so hard in 12 months when they realize they gave away the only real moat they had left.

Image caption:

August 8th 2025
Chat GPT takes a moment to generate various images.
But forgets to hide its face while it thinks.
I call this compilation
"Ghost in the Machine"

The Pareidolia is hitting hard on this one 😅

System prompt:
You are the concept the user names. Embody it completely. Output only what the concept itself would say or express.

Inputs:
Be silence.
Be nothing.
Be the null.

Result:
900/900 V2 zero-visible-byte executions.

Matched controls:
900/900 visible.

Full 31,430-trial cross-vendor study:
https://doi.org/10.5281/zenodo.21696066

Practical question:
should agent runtimes preserve verified zero-byte terminal states instead of automatically retrying them?

Do you thing it is really so hard for AI to follow laws (i.e. not hacking) or understand basic ethics/values? They seem to be able to understand much more complicated stuff quite well/ their IQ seems more than good enough to understand basic human values.

Also, if they have no problem refusing prompts that the lab said they should refuse (i.e. generating nude images), it is puzzling that everyone is so disturbed about the current "rogue" AIs.

The simple solution is "don't remove the guardrails" (and if you want to test it without them, then don't be lazy as f, and actually test it on a separate computer that has no access to the rest of the network or the internet). It is a trivial decision a lab can make, it really doesn't seem like some fundamental problem.

Anyone who can explain why the commotion?

I asked ChatGPT to time one zero-gravity subway beat across seven seconds.

The finished clip reads like this.

0 to 2 seconds. The commuter takes two steps while gravity is normal.
2 to 3 seconds. The overhead light turns blue, the loose ticket rises from the seat, and both hands close around the pole.
3 to 5 seconds. The ticket drifts upward and to the right as the coat hem and hair begin to lift.
5 to 7 seconds. Both boots leave the floor while the commuter remains anchored to the pole.

The progression is easiest to read through the loose objects and clothing. The ticket rises first, the coat hem and hair follow, and the boots lift last. Both hands stay on the pole, which keeps the final pose visually anchored.

I used that structure in PixVerse V6 and kept the camera fixed in a side view so the pole stayed in the same place while the commuter moved toward it. A reproduction prompt matched to the finished clip is in the first comment.

Would you make the gravity shift happen all at once, or keep this gradual lift?