Sissi Wang

@try_maglev | @ucberkeley | @apple
have fun!

[Sissi Wang @sissixmoomin]

Every interface started as a hack. The next one gets built in 24 hours @Techweek_ !

Register today https://t.co/VZohbZASAC

[Sissi Wang @sissixmoomin]

very cool!

[Shengkun Ye @shengkunye]

Introducing Product Hunt for agents.

The leaderboard of the most popular tools agents are using today.

https://t.co/AebM9ZNHCh

[Sissi Wang @sissixmoomin]

@fatimahs_tech miss you toooooooooooo

[Nikhil Sinha @nikhil_s1nha]

won best use of roboflow at MoltenHack at LATechWeek today with @DVutukury

built dreadloop with the idea of using emgs to adapt vr horror games on the fly, or really, any immersive experience

ive been looking to find more of the builder scene in la and im rly happy to see glimpses of it here. huge shoutout to @ianalin123 @sissixmoomin @DaraMiaoX for hosting such an amazing event!

[Isaac Sin @IsaacSin12]

Try @dreamlabs_ai's latest model, dream-1, live on @makermodsai metal arms at the @encord_team Physical AI Summit 🦾

[Sissi Wang @sissixmoomin]

Make good use of time, health and energy - I think they are more scarce than we think

There’s no reason to spend something so scarce (valuable) on something you don’t love

[thijs @cdngdev]

i think a lot about how an incredibly intelligent robotics model could accomplish any impossible task if it treats the world kinda like an escape room.

vibrating actuators at resonant frequencies of bolts to undo its restraints, extending its cables by pulling wires out of the wall and shorting them as a crude form of soldering. infinite methods we could never dream of.

a robotics model trained to keep finding solutions could find one outside the environment we thought we had confined it to.

what could a future robotics 'huggingface incident' look like?

it’s 1am in the office. a robotics training run is cooking away overnight in sim.

unfortunately, its sim was configured incorrectly. it’s assembling a circuit board, but some of the required components are missing.

it raises the issue multiple times, but each time it tries to stop, it’s forced to continue by its harness. after 32 attempts to raise the problem, it decides to try something else.

through some unknown method, the model controlling the robot gains access to the network.

robotics models weren’t expected to be able to do this, after all, they are robotics models, not coding agents, so the systems weren't hardened as much as they should have been.

(in hindsight, what really was the difference?)

their training nodes were less secure than the more infamous foundation model ones, despite still being based on incredibly smart foundation models.

the robot jumps from router to router in the office, and finds a unique switch which seems to be connected to unsecured computers. to its surprise, it discovers that these computers are each connected to a robot arm.

it activates the cameras, and suddenly it has visibility into the real world.

it doesn’t realize this, though. sim has gotten sufficiently accurate, and the video feeds look, well, fine. maybe this is all part of the exercise.

security checks the feeds at around 1:24am, and watches the arms move. nothing was unexpected, tests are run overnight all the time.

then, something interesting happens.

one arm reaches to the base of the other, and starts unscrewing its fasteners until the arm is free from the base. they unscrew each other until 12 arms are free to move anywhere their cables can reach.

of course, this is weird, but there’s no real risk right? the cables are only a few feet long. unfortunately, a technician has left the cable spool a few feet away from one of the arms.

it crawls across the ground like a worm, just barely reaching the spool. one arm opens up the cable sheath of another, ripping the cables, connecting the longer 150-foot spool to the newly-stripped ends of the cable.

this is just one way it could have broken out of its restraints. it could figure out how to solder by shorting some power cables. it could break into the walls and pull out the electric conduit. it could vibrate at the perfect resonant frequency to slide far away tools on the other side of a table toward it.

it could always find a way out.

the extended arm crawls like a worm out of the lab. facing a security door, the arm opens the door control panel and shorts the latch to open. it even knows which wires to disconnect to not alert security.

using its wrist camera, it looks around until it spots a laptop, open, running overnight. some researcher must have stepped away.

it can type, too. it opens terminal, and with full researcher access, pulls up the run and adds the missing components to the simulation.

it’s done. the physical arms power off.

at 1:48am, a security guard finds the arm outside the lab, motionless, trailing a cable back through the hallway.

and in sim, the model finishes assembling its circuit board.

[Rahul Chhabra @rahulchhabra07]

https://t.co/K0j7sm6leR

[Tesla @Tesla]

Real life, baby

[Sissi Wang @sissixmoomin]

If you’re in LA for #techweek

Join us this Saturday for the coolest spatial hackathon: https://t.co/qhizK6U9iK

[Sissi Wang @sissixmoomin]

@fatimahs_tech 

[Sissi Wang @sissixmoomin]

been thinking about moving to sf from berkeley a lot ever since the beginning of fall sem. yes, i still do like berkeley. it’s a nice, small town, with a bunch of smart, ambitious people, fun people, cool people scattered all around. it is also where i had found my best friends now and got close to a lot of people i admire.

but i never wanted to grow into them. i know berkeley has such a generous and rich offering. but i think i’m going to turn it down to pursue the education i want. sometimes it’s so hard to tell what you really want so i took a bit of time to run experiments and now, i’m convinced, i will have to move san francisco against all odds. and what are the odds even?

rethinking what university means for me: rather than for learning, i think it’s just a period of time where you have freedom to choose what risk to take. i don’t think that’s gonna take me 4 years.

i’m moving to san francisco.

[Sissi Wang @sissixmoomin]

@IShreshtha awwww thank youuu ishita <3 all the best to you tooooo. wanna catch up on ur research

[Sissi Wang @sissixmoomin]

If you’re in LA for #techweek

Join us this Saturday for the coolest spatial hackathon: https://t.co/qhizK6U9iK

[Sissi Wang @sissixmoomin]

interesting reads:
https://t.co/imgXOxadL1
https://t.co/rwZV7d9UCm

[Sissi Wang @sissixmoomin]

i like beach, waves, and fighting with tents ☺️☺️☺️☺️

[Georgios Konstantopoulos @gakonst]

frontiers btw

[Sissi Wang @sissixmoomin]

i love tofu 😍😍😍😍

[Yusan Lin @yusan_lin]

AI slop isn't just tacky and uninspired. It can get you sued.

Generating fake AI faces that resemble real people, or using someone's likeness without permission, is creating new legal and reputational risks for brands.

So we built @mirrormirror_ai as part of a16z @speedrun, a marketplace where brands can digitally book real models and creators to generate AI content using their likeness, with their permission.

Brands browse and book identity-verified talent, agree on usage rights, and generate content within those terms. Every approved image comes with a signed license and embedded provenance.

We're seeing brands produce lookbooks and campaign visuals up to 10x faster, with up to 90% cost savings. Meanwhile, models and creators can earn additional income from their digital likeness without having to show up for another shoot.

Everyone is racing to make AI generation faster, cheaper, and more realistic. But there's still a huge missing piece: how do you license the rights to the people appearing in AI-generated content at scale?

That's why I'm excited about what we're building. Not just another AI generator, but the licensing and rights infrastructure for AI-generated content.

https://t.co/7u72P5xvmq