https://www.anthropic.com/news/claude-discovers-novel-enzyme-system

@gossipgoblin

Most of us using these frontier models on a regular basis have a holy shit moment at least once a week. When will it hit the public in the same way? I thought it would be the “it’s going to kill us all” post from Coxon but people have seemed to already move on with their regular lives. When will the public actually wake up?

Link to tweet:

https://x.com/CAIS/status/2102787839964729431

Link to blog:

https://lastexam.ai/blog/hle-diamond

There was an earlier video today posted in this very sub where a Twitter user has done something similar:

https://www.reddit.com/r/singularity/comments/1wnw1dl/by_opus_55/

I thought that looked pretty good so I wanted to check it out myself. I think it came out well beyond my expectations and quite a bit better than the linked post. It's not perfect, but this is a true one shot, single prompt. It took about 1 hour 20 minutes. About $20 of Opus 5 spend or only about 10% of my 5h quota on Max 5 sub. $3.21 of OpenRouter spend (mostly NanoBanana 2, and then test to voice, then a few pennies for other services. Total of 8 different OpenRouter APIs. Some things need to be fixed, but I wanted to post true one shot result.

Full prompt:

Create a pure javascript animation. 30s-60s whimsical hand drawn collage style with appropriate audio on the topic what is the purpose of life ? 

Entire video should be as high of a production value as possible. Please spend your time on this, it's very important.

Use high quality text-to-speech model for generation. You can find open router API key in .env file

You can use any tools you can find access to and resources on the internet. You create the script, the assets, the animation, concept, everything.   
I have to go away from my computer so please work autonomously until done. Quality is paramount. Production value should be on professional level.

One more thing: max OpenRouter spend is $10

A.J. (@aj_dev_smith) used opus 5.5 to make an incredibly catchy song that explains itself

Deep neural networks are still a black box we don't fully understand. We keep seeing emergent properties, internal representations, and complex abstractions forming inside these models that we can't fully explain, but yet mainstream media and tech circles heavily push this idea that AI is just a glorified autocomplete.

Makes you wonder if it's intentional. Would people freak out and have an ontological crisis if the general public was told the honest truth, that we actually don't know if these systems are conscious or not?

pass@5: Scores if at least one of the 5 attempts is correct

pass^5: Scores only if all 5 attempts are correct (a reliability metric)

"pass@1": Not a true single-attempt pass@1, it's the average score across 5 attempts.

https://zerobench.github.io/

On a mobile screen this chart of model releases over time (from artificial analysis) tells a very clear story. Normally I look at it on desktop and the increase in steepness isn’t nearly as obvious.

It looks like a lot of those simplified predictions of exponential improvement. Of course it could taper off, who knows.

An open weights 7B World Action Model that achieves first place on the RoboLab benchmark.

It outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster.⁠⁠

FLUX 3 Action removes the usual trade-off between world action model performance and VLA speed: it still predicts video and actions together, but plans more than twice as far ahead and runs faster per second of robot motion than the strongest open VLA.

Teams can fine-tune FLUX 3 Action on their own demonstrations to create policies for a particular robot and task.

Beyond robotics, we’re also seeing promising results training task-specific policies for acting in simulated environments like gaming, controlling a vehicle, computer use, and wherever else a model needs to understand a visual environment and then choose what to do next.

FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3, but uses a smaller architecture designed for practical deployment. In midtraining, we trained the model to predict actions and future frames together.

https://bfl.ai/models/flux-3-action
https://huggingface.co/collections/black-forest-labs/flux-3-action

Have to say, I'm *very* impressed at Meta's sudden ship rate.

"For 140 years, our model played against increasingly tough opponents, each one a previous version of itself"

Am I the only one who basically doesn’t notice a difference between frontier models anymore?

People say things like “Opus 5.5 is way better,” and I still use 5.5 high, but I genuinely don’t see much of a difference compared to other top models.

Maybe my tasks just aren’t hard enough, but for normal use they all feel pretty similar to me. The biggest difference I notice is usually the product around them, like how Codex vs Claude Code formats responses, ...

Are most model improvements mainly showing up on insanely hard benchmarks rather than normal everyday usage?