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
Ball or the tennis player made the serve, those are interesting for the purposes of how to understand and synthesize visual inputs.
And so now that you've kind of given this open text box for media, there's going to be a flood of the types of things users are going to want to try to do, some of which Sam is already going to be really well adapted to do, some of which not.
And I think that that's going to be it's going to reveal itself of the types of things that are that are obvious.
One of the things that we want
Wanted to discuss was like where to use SAM and discover how to build with SAM.
So in addition to the meta team building a tremendous playground for being able to interact with images and video and kind of apply effects with like a video emphasis, I think one of the things that we're pretty excited about with SAM3 is how much it positively impacts each part of building a system for visual understanding.
So for example,
The very first step of historically aggregating and collecting a data set, because you think that there's not a model that understands the slice of the world that you want to understand is where automating away lots of labeling can exist.
Basically, if you collected a bunch of data of something that's is already in the SAM 3's knowledge, then you can prompt for SAM3 to automatically label all that data for you.
And so we've actually made a
bet on SAM3 being a core part of autolabel at Roboflow, giving users a first pass of saying, hey, if you have a new image or you have a new video, start providing just a text prompt and allow SAM3 to find and automatically label those regions of interest for you.
Downstream, I think there's areas for fine-tuning, like you know, within a week of releasing SAM3, Med SAM3 came out for adapting SAM.
Into medical contexts.
And I think that's a harbinger of what's to come.
Like there will be lots of domain-specific adaptations of SAM in places where maybe there's a specific ontology that someone wants to understand, or maybe there's a place where just the model doesn't have great awareness yet.
And I think we're already beginning to see that with hundreds of fine-tunes that users are creating for various domains.
And then the last area is like, okay, I've got my model, now I want to use it.
And so one of the things that we're really proud of is to be ready on launch day to showcase the infrastructure we've built to burst and scale like infinitely large as folks have uh models that they want to deploy and make it readily available.
Having an endpoint that serves either a fine-tuned model or a model as is, or even a model that might be able to run on edge hardware as smaller models come out or maybe distillation comes to rise is I think also
awesome place of where we're seeing SAM3 being impactful uh each part of like the computer vision lifecycle and pipeline.
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