Joseph Nelson
speaker
239 appearances
1 recordings
1 series
first heard Dec 2025
last heard 18 Dec
Joseph Nelson’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Dec 2025 with 1.
Appearances
One of the things that we were pretty excited about is we were kind of able to build an entirely new product in the world of of SAM3.
And we called it we called it rapid, but basically it's like there's probably a model that already understands the objects in the world that you want to see.
So here I'm I'm screen sharing an example of like these are vehicles next to our office in San Francisco that go by and you can see here's a Waymo and here's like other vehicles.
And like if I just have like this 10 second clip.
And let's say, you know, the first thing I want to do maybe is just like count cars and I want to get a sense of like each of the vehicles.
What's really awesome is I can just, you know, of course, text prompt and say I want vehicle.
And as I toggle through different frames in my video
SAM3 already recognizes and understands those objects.
Now, one thing that I think is really interesting, there was a conversation earlier about how much you want to rely on a model versus humans' output of the model for what you care about.
So, for example, let's pretend in this scene, maybe the only cars that we care about are the ones that are like before the crosswalk and maybe not far in the distance.
Then you would get people that would say, Hey, you know what?
I actually want the objects that are like most confident.
And I would like, you know, move my slider down to like getting a fewer number of objects.
Whereas maybe others might say, Hey, I want like every single presence of a potential object in the scene, which even gets like reflections on the building of objects.
As computer vision approaches this world where we increasingly have like
Models that can understand and improve themselves and we rely on what human output and human preference from the models is, we're gonna get these funny scenarios where things aren't also all like immediately deterministic of what a human cares about.
And I think that's where like tooling fills a big gap, but it also is gonna be a place where it'll be really interesting to see where users kind of
start to use and apply the models and why you need so there's this last mile
work to put the model in context in the domain that someone is trying to solve and tackle.
Uh
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