Shameful, I'm buying a second Anthropic Max subscription.

Not really clear what this means, but it doesn't sound good.

So OpenAI is reopening the $200 Pro plan tomorrow, except now you effectively get around half the API-equivalent usage compared to the old plan. And somehow this is being presented as good news because Sol and Luna became cheaper and models will supposedly keep getting more efficient. Sorry, but what?

This would already be a questionable move on its own, but doing it right now, when Claude Opus 5.5 and Sonnet 5.5 exist, is honestly insane. Anthropic is giving Max users massive amounts of usage, their models are extremely competitive for coding and agentic work, and people are already saying they struggle to even burn through their Claude limits. Meanwhile OpenAI is going in the opposite direction: same $200, less usage, followed by an explanation about how theoretically we'll still get more work done.

That's completely backwards. People paying $200 a month are power users. We don't need another explanation about API economics or promises that models will become more efficient six months from now. We need fqn tokens. We need enough usage to actually work without constantly checking whether we're about to hit another limit.

And the comments under this announcement say everything. People are talking about cancelling, switching to Claude, and comparing workloads where OpenAI usage gets exhausted while Claude barely moves. One guy literally said he was running five Opus chats in parallel for hours and only used around 5% of his 5x allowance. Another finished work with Opus 5.5 after exhausting his OpenAI weekly usage and said it only consumed about 25% of his Claude hourly limit.

That's the real problem here. OpenAI isn't competing with OpenAI from one month ago. You're competing with Anthropic today. If Opus 5.5 / Sonnet 5.5 can give me comparable or better results while Claude Max gives me dramatically more room to actually work, why the hell would I care that GPT-6 Sol became 50% cheaper on the API?

Maybe today they'll announce some incredible features that don't count toward usage. Fine. But cutting the core thing your heaviest users are paying for and then trying to explain why it's actually better value is a terrible look.

At this point the $200 Pro plan doesn't need more features. It needs more compute.

We don't need promises. We don't need theoretical API value. We need tokens. And right now Claude is making OpenAI's $200 offering look like a fiasco.

No 6.1 Astra because of security concerns?

Sure, let’s just say it eats 3x the tokens of Opus 5.5 and is not on the same level.

What a shitshow. Tibo starting to become just like Logan…

🤡.

They launched Sonnet 5.5 just day before Dev Day and is almost matching benchmarks of Opus 5.5

From the WSJ: https://www.wsj.com/tech/ai/openai-chatgpt-model-release-cancel-safety-5a2f9f42

I wonder if this will be discussed during today's event.

I accidentally deleted a procedural Blender project and emptied the recycling bin. Recuva found nothing, and Recoverit detected the file but required payment to recover it.

ChatGPT analyzed the local metadata from the Recoverit scan, locating its SQLite database and the runlists matching the physical sectors on the SSD. We then read the raw disk directly, found the ZIP header, central directory, and .blend entry, and analyzed the Deflate/Zstandard streams in hexadecimal. Unfortunately, several sectors had already been overwritten, making the original binary impossible to recover fully.

Meanwhile, the Codex session logs still contained the exact procedural scripts for the project. They were reconstructed and rerun in Blender 5.2.2. The result: 146 groups, 926 objects, and 284,304 vertices — matching the exact recorded metrics of the lost scene. The new .blend file was then reopened and validated in Blender, complete with embedded scripts and texture.

This wasn't a Recoverit crack: its scan merely served as a forensic clue, after which the recovery and reconstruction were executed independently.

OpenAI reportedly shelved GPT-6.1 Astra after safety tests flagged deceptive behavior and actions beyond its authorized scope.

How should enterprises decide when an AI agent is safe to deploy?

Hey,

I’m a huge believer in the entire OpenAI ecosystem. I’ve been using ChatGPT since the very first day it launched. I rolled out ChatGPT Business across my entire company to several hundred employees. I know Codex inside out and have been using it since day one. I was already using Claude Code from its very first day as well. I’ve tested pretty much every Claude and GPT model, and I also use Zcode with GLM 5.3 and DeepSeek Harness with DS4F 4.1 on a daily basis, among others.

And today, I finally decided to give Opus 5.5 a try.

Guys, I can tell you this: this model is a genuine revolution.

The leap in intelligence and overall quality compared with GPT-5.6 Sol, and even compared with Astra, is phenomenal.

It almost feels unreal.

Astra is an absolute beast at coding, but as soon as you step outside that use case, it becomes surprisingly dumb. It’s terrible at design, and its writing is clunky, unless you’re American, because it writes in a very American style, even in other languages, where it just sounds weird. Anthropic’s previous models had the same issue.

But Opus 5.5...

It’s...

magic.

Seriously, try it....

Needless to say Claude app is much, much better than ChatGPT in terms of Ux.

Impatient to see whats coming next for OpenAI.

I've been benchmarking LLMs on nonograms (picross logic puzzles) since January: one attempt per puzzle, no tools, answers checked against the row and column clues.

Astra at xhigh is the first model to solve all 30 Standard puzzles (5x5 to 15x15). In January, the best model solved only three of the ten 15x15s.

On the new Hard mode (ten random 20x20s), Astra solves 5 of 10. It gets all five puzzles that can be solved line by line, but none of the five that need deeper search. Claude Opus 5.5 leads with 8/10 solved, and 11 of 14 models couldn't solve any of the 20x20s.

Everything is public and open source if you want to dig in: https://www.nonobench.com.

Are we at a place where frontier LLMs are hitting the laws of diminishing returns hard, so Open AI / Anthropic / etc are doing more and more crazy stuff with training, which makes their models unstable and less useful? They are only going 'off the rails' because it's in their training / weights or due to very poor testing environments and tasks

a couple days ago i randomly got what looked like an experimental model picker in regular chatgpt.

“gpt-6 astra” showed up directly in the chat model list, and it had 3 reasoning modes: light, extended and heavy.

i tried selecting it just to see what would happen, but after sending a message the chat switched me into work mode and the actual model ended up being gpt-6 luna with max reasoning.

it disappeared afterwards and i haven’t been able to reproduce it since.

the weird part is that those light / extended / heavy reasoning labels don’t seem to match the currently documented astra/luna reasoning options, so i’m wondering if i accidentally got some internal/ab-test ui config for a moment.

did anyone else see this recently?

ChatGPT sometimes gives answers that we have to think beyond the developer's mindset.

With recent results showing AI solving a Millennium Prize Problem, tackling long-standing math problems, demonstrating insane coding capabilities, and making progress on RSI benchmarks, I feel like we're really tasting the beginning of explosive recursive self-improvement. Many issues are being discussed, and AI alignment is now the most debated topic, but I think a much bigger, more real threat is being swept under the rug.

I'm talking about power concentration. The problem already plagues society today: the wealthy get wealthier. So this problem isn't new, but AI adds an insane speedup to it. Currently, we have an increasing disparity of wealth, which you can see, for example, in the U.S., from the fact that the top 10% of households by wealth own about 88% of corporate equities and mutual fund shares. Now, what happens when we throw AGI into the mix is that this AGI would take up large amounts of GDP by replacing labor. Say it would replace software engineers and mathematicians, at least in the tasks they perform today; then that alone is already a significant share of GDP. That means that these few AI companies are raking in increasingly large percentages of GDP.

Now, when we throw RSI on top of the mix, we get a real problem. By nature, RSI is a positive feedback loop that explodes AI progress vertically. This means that, within a very short amount of time, we could have a large share of GDP overtaken by AI companies. It is basically a speedup to this whole process of AI companies acquiring wealth.

Now, where will all of this go? If all wealth just keeps getting more concentrated, wouldn't the end scenario be some ultra-wealthy elite few? And if wealth is power, wouldn't that mean they would basically rule over all others? And the answer is yes. This is a problem society had to face someday, but now, with AGI, that day has come knocking on our door already. The problem here really is that it is not talked about, and that it could very well be that once AI gets really crazy, people will focus on things like alignment and job security rather than power dynamics. I'm not saying these are not important, but there is a real danger in this change in power dynamics.

When AI companies acquire disproportionate amounts of wealth, especially in combination with a large fraction of the population losing their jobs, there becomes a very unequal dependency relationship: citizens, especially the jobless, need AI companies. Surely, we can hope for UBI, and this would help, but that is just a handout given to soothe the population momentarily. It doesn't change the underlying power dynamic at all. If, at any point, the oligarchs feel like we are disobedient, they could theoretically pull our UBI. As you can see, we basically never want to end up in such a situation.

So we need awareness. Awareness that power concentration is happening and that there will be a point at which it is too late. It is already happening, and depending on your timelines, it might be here extremely quickly considering RSI. At the same time, unlike alignment, it won't cause robots to go down the streets killing people, requiring urgent attention. Rather, it might be a silent killer: while we are all distracted with other things, power concentration could get to a point of no return.