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.
579 karma · joined June 24, 2014
Will be interesting to see how the legal battle plays out as well.
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 myself am the first medical doctor and full stack engineer in the history of my country (250 million), graduated as a doctor at age 25, and we have over 100+ users [all of which are medical/dental students and doctors], 10s of billions of seconds studying smarter, hundreds of millions of questions solved, and more.
Our Super App has subsystems including MedGPT, MedAgent, Spaci (our own take on spaced repetition) and much more.
We're bootstrapped, and continuing to scale. If you are in medical school or know someone who is, please reach out!
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?
However, based off first impressions, it seems like this is meant for inference side, and not training, which is also an interesting choice.
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.
I get why they aren't disclosing all the details, but it seems more hype-train-esque to me for this moment. I don't disagree that this could be big.
MedAngle is literally everything one could need, personalized to their curriculum across 4-6 years of medical school. Quizzes, videos, notes, flashcards, reminders, scheduling, performance, search, and more.
Our Super App is comprised of MedGPT + MedAgent + Spaci (futuristic spaced repetition), which serve as layers over our massive collection of features such as the Smart Suite, Learning Library, Clinical Corner, Tested Tools and more.
100k+ users, 10s of billions of seconds spent studying smarter, invite only. Bootstrapped, growing nicely. I lead a team of top medical students and doctors.
As a customer of Mercury, it's truly one of the critical companies my toolkit, and I just can't help but feel that their choosing of Haskell made their progress, development and overall journey that much better. I realize that you can make this argument with most languages, and it's not to say that a FP lang like Haskell is a recipe for success, but this intentional decision particularly pre "vibe coding" and the LLM era seems particularly prescient, of course combined with their engineering culture that was detailed in the post.
BTW, that last line about hiring/commissioning a cartographer, very rad and cool :~)
Pricing is also quite surprising, compared to comparable competitors. I guess they have tons of capacity or really want to bring over more people.
All in the MedAngle Super App - literally everything a future doctor needs in one place. 100k+ users, 150m+ questions solved, tens of billions of seconds spent studying smarter
The ruby::box thing looks pretty interesting, from a cursory glance you can run two simultaneous versions of something like a feature or rollout much more conveniently.
Also being able to do
if condition1
&& condition2
...
end
Good start to the morning.