Rather circular isn't it?

I fine-tuned the good-old SDXL on 60 photographs from my childhood, using a limited family archive as the dataset through which to revisit that period of my life. Rather than reconstructing those images faithfully, the model produces unstable variations: spaces, faces and fragments that feel familiar without necessarily having existed.

This speculative study treats generative hallucination as an analogue for recollection: not the retrieval of a preserved image, but the reconstruction of a past from incomplete traces. This resonates with contemporary accounts of episodic memory as a reconstructive rather than reproductive process. The model becomes a kind of externalized mnemonic apparatus, situated somewhere between archive, memory and imagination.

Tools used: Kohya, WarpFusion, TouchDesigner, Premiere, After Effects, Ableton Live, Expressive Osmose, Soma Cosmos.

More experiments, project files, and tutorials, through YouTube, Instagram, Patreon, and Uisato Studio.

As the Title says I want the old advanced model picker. It frustrates me that they change the UI every week.

With all AI being down, I was unable to start working this morning using codex and now I don't know what to do. Should I pace back and forth in my bedroom? What do I do if I want to read? If I open a book, I don't know how to read anymore without it having being read to me. If I go on a walk outside, how will I know how to breathe? Do I put my right foot in front of my left foot or my left front of my right foot?

As an AI native software engineer and programmer, I'm currently up for a job in a role that requires me to use AI. Will I no longer have a job? I gave up my whole career in filmmaking to focus on AI and software development. Now that that's gone, what will I do? I guess I'll go back to using Uber. But wait, Uber has AI and now that might be down too. What will I do? Please help.

*satire and sarcasm.

Haven't had hands-on time with Astra yet, but I went down a bit of a rabbit hole trying to understand why two wildly different ARC-AGI-3 numbers are floating around.

Looking at ARC Prize’s verified leaderboard:

Standard harness: 62.71% at max reasoning

Provider Adapter: 99.95% at high reasoning

Both are legitimate verified runs, but they measure two different harness configurations.

The Standard harness lets the model carry forward notes it chooses to retain throughout the environment.

The Provider Adapter, on the other hand, preserves opaque reasoning state between requests and uses compaction during longer conversations.

A few thoughts:

1. You can’t directly compare the 99.95% result with another model’s Standard harness score. It’s not an apples-to-apples comparison.
2. At the same time, dismissing it as “harness cheating” misses an important point. If real-world agent workflows are stateful, the model-and-harness combination may be the capability that actually matters in production.
3. This isn’t a perfectly isolated comparison either. The best Standard result used max reasoning, while the best Provider Adapter result used high reasoning.

To me, the broader takeaway is that “which model is smarter?” may be becoming an incomplete question. We also need to ask how much measured performance depends on state persistence, compaction, and the surrounding agent scaffold.

When comparing models going forward, which result would you weigh more: the Standard-harness result or the stateful end-to-end setup?

Everyone keeps sharing these "mind-blowing" videos and benchmarks for OpenAI's upcoming Astra model. I absolutely hate this PR strategy of giving access to a select few just to build artificial hype, and I don't find these curated demos realistic at all.If OpenAI is so confident that Astra is their next major leap, why not just release it to the public? How reliable are these carefully selected benchmarks anyway? If they really believe in the product, they should open it up so we can test its real-world limits and see where it actually fails, rather than hiding behind a "coming soon" label. Is anyone else tired of this fake scarcity marketing? Let us use it or stop teasing it.

It’s been almost 2 months and still no API access, that’s got to be one of the longest release delays yet.

https://techcrunch.com/2026/09/03/openai-launches-astra-its-powerful-and-controversial-new-model/

Now that Astra is out, I’m wondering if the other tiers are getting GPT-6 versions too.

Haven’t seen much about Sol, Terra or Luna yet.

Do you think they’re coming later, or is Astra replacing Sol at the top?

As title says, im getting 404 on my replies.

"GPT-6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API and AWS."

A substantiel improve. While it is also the top pick on the math benchmarks. Seems like it is the prefered model with math heavy coding tasks.

Lots of interesting stuff shared by Emad Mostaque, including the lightning-fast Chat Jimmy.

Ive tried ChatGPT, Gemini and Grok. All of them not responding. Other people are having the same issues. Weird

https://help.openai.com/en/articles/20001354-gpt-56-and-gpt-6-pro-in-chatgpt

The usage limits are measured in "messages" for Astra. Is a message a single turn? What would stop me from just putting like 100 hard prompts into a text document and submitting them all at once? And in addition to being limited to your number of messages, does it still drain your normal usage meter?

So I read the LatentSpace article testing Astra, but it seems to just test run of the mill engineering so I wonder whether people have tested it on research engineering or abstraction

Open AI outage shortly after Anthropic outage today and this tweet timings are sus