maz1b

Didn't they just recently invest in them? Curious about their strategy, considering NVIDIA already does Nemotron and i think diffusion models as well.

Wow, the rate of improvements in the AI era is staggering.

GDPval-AA v2.1 as of now: 1620

GDPval-AA v2.1 for Haiku 4.5: 735

The 100k tokens pricing makes sense, looks to be a hedge against OpenAI's decisions API and Jev or its open source alternatives that are springing up.

Nice release, congrats to Anthropic.

I'm glad they're keeping at it!

Either way, the fact that xAI or SpaceXAI or whatever the name is, I can commend the team behind it on their rapid ascent and progress by being close and or on the frontier in several respects.

OpenAI really going after ex Apple people who start new companies or startups, eh? First Ive and now the duo behind Portrait mode.

Will be interesting to see how the legal battle plays out as well.

Working on MedAngle, the world's first Super App for current and future doctors.

100k+ users, 150m+ questions solved, 60b seconds of smarter studying, MedGPT, MedAgent, and everything medical/dental students need in one place along with young doctors who have recently graduated

I could be mistaken, but wasn't Mistral openly championing themselves as a company and EU option that wouldn't do this/didn't do this?

Just wanted to say that the rhabdo part mentioned on your site was really impressive! Speaking as a medical doctor and full stack engineer myself.

How does this compare to 4?

Wow. Makes me see OpenAI in an entirely different light.

Wow, that's a pretty massive decrease in latency, which should unlock some use cases, but the linked web page doesn't exactly make it straightforward to understand the differences between the models.

However, based off my personal experiences with general images models, Google in my opinion is the best for my workflows. Granted, I haven't tried far-east providers yet.

What does everyone else think?

Pretty huge move. Google and their TPUs are looking infinitely more prescient as I think they are on their 7th generation, along with the offshoots it inspired like the LPU and even others, perhaps like Cerebras and their Wafer Scale Engine.

However, based off first impressions, it seems like this is meant for inference side, and not training, which is also an interesting choice.

This made me spit my coffee out! Thanks for helping me start my day with a laugh. No comment otherwise :-P

I had to check the date after seeing the headline, and again after opening the page. Thought it was April Fools.

Regardless, as a doctor and full stack engineer, I'm looking forward to learning more about their methodologies, their approaches, but I don't think this is going to be displacing MRIs or remotely close, based off the cursory initial glance. If their vision is to be able to provide end users with more actionable data with some kind of "low fidelity" medical imaging data that is somewhere above zero and or standard imaging and high fidelity modalities like CT/MRI, then this could be somewhat interesting.

Not a radiologist and not medical advice. Just my two cents.