Darrow

Thanks @sama

@mandylu Mandy may be Lisan Ai Ghaib

we are seeing Dune in real life

@luaan_ng absolutely mad

While some of you are still applying for Summer 2026 internships, Summer 2027 applications are already out.

@gabriel1 rush is happening right now!! get in there

how do i become a frat leader, is there a cheat code or something?

Excited and humbled to announce that I will be spending a semester at Stanford to finally develop fundamentals required to execute well, with a rigor that is hard to find outside academia. Feeling incredible grateful to develop a thoughtful, rigorous approach to problem solving.

@gabriel1 I knew this was a prank because you said semester instead of quarter

@virkvarjun this class is already overfilled

If this came to Waterloo, classes would overfill. Bring this roster to the loo…

@Bencera what is this from?

$6M → $0 run rate in 24 hours. One Founder + AI. Zero Employees.

@jayelmnop I applied for this class but didn't get in :/

instead I suggest learning by doing cs336.stanford.edu cs336 will kick your ass, but I can't think of a better way to get up to speed with the frontier of AI

protip for stanford undergrads: beware the classes with guest speaker lineups that read like AI coachella. you’re basically paying $5k to listen to a live podcast series.

@_ueaj what's your tech stack?

Wow I fucking hate RL research this is genuinely horrible dogshit. Like 99% of my time has been spent figuring out why my lora won't update on my inference server or other technical problems

@mil0theminer can you explain?

This is like conducting internal investigations. it's all just fraud. Don't play into their games

@vchennai2 they probably mean $140k/year

World class recruiter lowball

I've realized what's stressing me out is my X feed

@kyanyang_ rip ur credits

claude been jitterbugging for over 100 minutes in my claude runner harness

super fast video and audio from dreamverse! I prompted "two men boxing in an arena" and got this in less than 10 seconds

Dreamverse is our AI video engine that generates a video faster than you can watch it. 30s of 1080p video in 4.5 seconds. One GPU. Real-time editing. This is vibe-directing. dreamverse.fastvideo.org

building used to be based on skill, now feels a bit pay-to-win

@DerrickEvans4WV aren't these fees totally arbitrary because the federal gov is funding all of these departments that are doing the labor

🚨 JUST IN: Sec. Marco Rubio’s State Department cuts the fee to renounce U.S. citizenship from $2,350 to $450, an 80% reduction.

@anshulkundaje someone asked one of my cs profs this, and he said that academia takes the long view and he feels he isn't bogged down with needing to make money in industry

I'm not sure why these CS profs are even at universities? Why not just join the frontier labs where you can just do your research yourself with unlimited compute and as many agents as you like? Training is a fundamental responsibility of universities. Or am I just stupid & naive?

@matthewnoto73 super cool!

⚡️We built a new real-time inference stack in FastVideo and have the fastest 1080p TI2AV (text + image to audio and video) pipeline ever. Create a 5 s 1080p video with audio in ~4.55 s on a single GPU! High-quality video generation must be fast to be truly interactive. The only limit in creative workflows should be your imagination. If you have the need for speed (and quality), make video generation go blurrr (for free) at 1080p.fastvideo.org and create whatever you can imagine…

@contextkingceo Congratulations Nishkarsh!!

We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️