@thsottiaux Limits seem messed up with the Sign in with ChatGPT feature. Stream keeps returning: “The ChatGPT user has reached their Subscription Sharing usage limit,” even though the app is allowed to use 100% and I’m nowhere near the limit.
I turned my iPhone to grayscale to stop doomscrolling and it’s absurdly effective. It basically killed the joy of looking at my phone. Everything looks the same & nothing is screaming for my attention anymore.
If users surge in Codex, it means time to switch to Claude or vice versa. They have finite compute, and as demand grows, they prolly start serving different quantized versions to keep up with it.
They expected this to turn into a massive campaign that help with IPO down the line or get investors on board to boost T$ valuation. What they got is a damaged reputation where no logical researcher will use their models for drafts or discussion anymore. Local models are the way.
I keep saying for years “intelligence” is a buzzword that OAI and Anthropic keep using. Models are extremely good at connecting the dots when you point them in the right direction, BUT by themselves, it’s highly unlikely they will find a “unique” solution to a given problem. +++
Ever wonder why Blender/Unreal work suddenly became THE benchmark for frontier models?
My timeline keeps yelling “token efficient” while it eats my limits like cookie monster.
It’s marketing. And people happily ride the hype train because FOMO works. 🤷♂️
BREAKING: MiniMax H3 Max sets the new Pareto Frontier for video generation, nearly 50x faster than the base model.
This model is post-trained by @fal on @MiniMax_AI H3, and it's in a league of its own: no other Image to Video model on the arena delivers higher preference at a lower generation time.
Its Image-to-Video generation time is just 6.4 seconds, 18x faster than average, and its Text-to-Video generation time is just 4.7 seconds, 24x faster than the average.
Huge congratulations to the @fal team on this release!
Even Opus 5 (High Effort) getting noticeably dumber is a signal that Anthropic is serving quantized versions of these models to save compute while training the next iteration. My guess is we’re 2–3 weeks max from the next iteration.
EU policymakers are so dumb they’re forcing companies to invent ways to detect LLM gen. text. It’ll surely hurt output quality, and at best, all these detectors can tell you is “maybe”
These people need a mandtry statistics course before talking about things they don’t understnd
@fkadev Instead of running a speed test every few minutes, why not just read the RX/TX byte counters? No extra data usage, and you can sample much more frequently.
I finally watched @obsessionmovie. It’s a masterpiece given the budget. I was hooked from start to finish. Curry Barker is definitely someone I’ll be keeping an eye on from now on. 🙌
GLM-5.2 is a big win for open source. If they manage to get these models running on accessible consumer hardware, the companies that poured billions into compute are cooked.
Soon? I don’t think so. But I’d love to witness that.
First step: retire the current Copilot and rebuild it from scratch. I genuinely don’t know a single person who enjoys working with a tool that feels this dumbed down.
We need more open source LLM models. The biggest hurdle is access to compute. I genuinely hope governments invest more in making that computing power available to non-profits under truly open licenses.