prodigycorp
prodigycorp on Hacker News
i'm probably going to spend next or next next weekend having an ai agent go thorugh my old accounts in 1password and have them delete 75% of them. Any surface area on the internet is risk nowadays, and cleaning up after the fact is a bigger headache.
Spare me the celebration. Artificial Analysis should not be granting any company the favor of a #1 ranking for a model that isn't released to the public.
Google's model release is pure PR puffery. It's no coincidence that it was released on the day of its earnings call.
the conflict of quantum mechanics vs general relativity is well within the realm of pop science and most assuredly within the grasp of anyone who read a book.
I don't agree with the delivery. They muddy the message for the western audience by going after science in general. The way they contrast their values against AI, you could similarly contrast their values against any other civilization, modern or pre-industrial.
@tomhow can u please transfer tranking juice? an interesting discussion was brewing and now this is no longer on the FP
Transparently so. MiMo's training dashboard showed the DeepSWE hillclimb in real time.
The accent is received pronunciation, like Tom Hiddleston. It sounds like Tom's voice. Perfectly normal British accent.
Very thoughtful, nice work again!
excellent, thanks. Yes, much more interesting.
A simple line chart would be more helpful, informative and humbling than a heat map.
A weak minded action doesnt produce a win for all parties involved. In fact I applaud their bravery.
Agents have dramatically increased the ability to poke at every single surface out there. I would be surprised if the researcher who found this wasn't assisted by a llm.
athropic had an experiment that did exactly this. we need more experimentation in this space.
Wow! This this reminds me of when we tried doing this with gpt 3 and.. it worked!
The tmux thing had me confused for a moment until i realized it was emulating tmux. Super fun. Is the model window width aware?
There's nothing that makes this paper the be and and end all opinion pieces of the paper. The community will review his review, and people who wish to understand more will read more and more of the paper. I see nothing wrong with this process of progressive understanding.
This only applies to its value in regards to training data for LLMs.
Ha, reminds me of how anthropic publishes their math papers with meat proxy math professors who were compensated for their "authorship" of the paper.
Essentially gifts for the annointed.
can you turn this into a decision model
Hard to call it a "unified platform" when a good portion of the developer base is using pages router despite app router being out for a few years now
You could being playing best jai alai player always knowing where the ball goes.
Whoops, people stopped caring about your sport!
> Just about anyone who has played a sport has heard that they have to target where the ball is moving to, not where the ball is right now. In this regard I am consistently disappointed with the commentary that mathematicians have been producing lately.
Reading this it feels like you haven't played a sport.
You could being playing best jai alai player always knowing where the ball goes. Problem is, nobody cares.
More likely is that frontier labs give huge discounts of EDUs if they consent to allowing training.
Impressive vision benchmarking. If the vision model is truly as good as astra, that would make it best in the world.
Also strong on cyber benchmarks (better than all chinese models), so this is a good defender model.
Lots of people shitting of Mistral for no reason imo. These are pretty good numbers across the board. Definitely good enough to use as a daily driver over other llms, if you have moral qualms with the others. For certain use cases, like cyber security, this may be the go to model.
I like to make fun of europe, but there's lots for mistral to be proud about in this release imo.
I’m typing from my phone and im not going to review the semantics of Anthropic’s storied history of performance issues.
It’s not just ant. There are so many small knobs that providers can claim isn’t nerfing but “load management” or “improving user experience”. One example from OpenAI is reducing juice to reduce time to first token.
Man this was last year and some Claude subreddit drama that I can’t furnish offf the top of my head but maybe one of the historians remember it.
Incorrect.
Anthropic has admitted to nerfing in the past. There have also been inference bugs. On top of that, model performance changes as they move compute to schwaggier providers as well.
Your chart is wrong.
This could and probably is me projecting, but the enthusiasm was tepid. The Opus 5.5 mog cast a pall on the room.
The stuff that came off as potentially exciting was the ultrafast stuff available only to Pro 500 users.
The reset button stuff was an embarrassment. Everything that was released today, in respect to the hype that the team projected on twitter, was a failure. The internal OpenAI slack is a hell of an echo chamber.