hisham bedri

Technologist working on reality-capture and creative tools.
Tiktok: @ultrafro2

[hisham bedri @ultimate_afro]

Yo check out this volumetric video!

[PTC Reality Lab @PTC_RealityLab]

Here's what we do at the Reality Lab when we can't book the village people

[hisham bedri @ultimate_afro]

@karpathy I use https://t.co/gyTkFz7e6R for this.

[hisham bedri @ultimate_afro]

@trq212 Claude code is so addicting, it feels like you're still making games :)

[Thariq @trq212]

I used to make games in a former life with @ultimate_afro

now he's working on putting agent loops inside of game engines and honestly it works pretty well

[Aura @Aura_Assistant]

Aura is an AI agent that can make logic graphs, write and compile flawless Unreal C++, make assets, and perform any action you can in Engine.

Runs on frontier models like Claude Opus 4.5.

Here's 10 min showing how it works:

Dropping 25 invites with $40 of usage in the reply. Let us know what you think.

[Tom Shafron @ShafronTom]

@jordannoone

[Thariq @trq212]

if the government can own 10% of Intel, I feel like a few grocery stores are fine

[hisham bedri @ultimate_afro]

@cohere i think i'm seeing a long time on embedding generation as of an hour ago

[hisham bedri @ultimate_afro]

please donate to his family here:

[hisham bedri @ultimate_afro]

https://t.co/4Xm1H1LgJf

[hisham bedri @ultimate_afro]

@trq212 congratulations to you and a big congratulations to Anthropic!!

[Thariq @trq212]

I joined Anthropic last week!

It’s obvious to me that we’re bottlenecked not by model capabilities, but by creativity and understanding.

I’ll be building demos and prototypes that highlight new capabilities and share what we learn about building using these models at Anthropic.

Excited to build with the best team and the best models.

[hisham bedri @ultimate_afro]

@BenTelAviv Quite a claim about Zohran. What's your evidence that he hates Jews?

[hisham bedri @ultimate_afro]

@metaplane @datadoghq Congratulations!!!!!!!!!!

[hisham bedri @ultimate_afro]

@trq212 yo that works very fast

[hisham bedri @ultimate_afro]

@paulg those of you calling Paul a hypocrite instead of addressing the logic in his point are not pushing the conversation forward. There are better and more fulfilling causes to put software engineering effort into than enshrining the ruling class.

[hisham bedri @ultimate_afro]

@trq212 @GoodfireAI This is awesome!

[Thariq @trq212]

✨ New AI Interfaces powered by Interpretability

I'm excited to share LatentLit, the result of my applied AI research fellowship with @GoodfireAI

Mechanistic interpretability isn’t just important for AI safety, it also gives us new ways to steer and interact with LLMs.

[hisham bedri @ultimate_afro]

@monkeybrainsnet looks like an outage in the financial district in SF

[MrNeRF @janusch_patas]

Wonderland: Navigating 3D Scenes from a Single Image

Contributions:
• First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis.

• Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control.

• Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

[hisham bedri @ultimate_afro]

now with some head-motion