Tope Ibrahim
@real_topeGrad student | Python lover | law-abiding citizen | computer vision expert, blackinAI | tweet and retweet about responsible AI | Ilorin #Dahiri
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(In my opinion) Structured output, mainly JSON, is not the way to move forward for function calling and agents. I've been using Python based function calling for a few months now, and today I've read the DynaSaur paper, which uses a very straightforward approach shown in the…
PyTorch internals essay by @ezyang why only study PyTorch when you can also learn about the internals from the research engineer who works on PyTorch
Announcing new open-source Python package: aisuite! This makes it easy for developers to use large language models from multiple providers. When building applications I found it a hassle to integrate with multiple providers. Aisuite lets you pick a "provider:model" just by…
Our group at Google DeepMind is now accepting intern applications for summer 2025. Attached is the official "call for interns" email; the links and email aliases that got lost in the screenshot are below.
After working at OpenAI for almost 7 years, I decide to leave. I learned so much and now I'm ready for a reset and something new. Here is the note I just shared with the team. 🩵
Writing your Ph.D. thesis? I have one request. Read every single word from beginning to end before giving it to your advisor. Every word. Straight through. You will immediately find things that are out of order, don't hang together, and don't form a coherent story.
Not a surprising result. But good that someone tried this out.
Curious whether video generation models (like #SORA) qualify as world models? We conduct a systematic study to answer this question by investigating whether a video gen model is able to learn physical laws. Three are three key messages to take home: 1⃣The model generalises…
1/ CrashCourse 🟢Subscribers: 15.9 million 🟢Content: Delivers easy-to-understand courses on topics like history, science, and literature, making learning fun and engaging. 🟢Recommendation: 9/10 – A top choice for its engaging approach and quality content across diverse…
I'm shocked people still don't use ChatGPT for job search Copy and paste these 8 ChatGPT prompts to land your dream job:
Offline goal-conditioned RL could provide a fully unsupervised and fully data-driven way to pretrain broadly capable policies from previously collected data, but progress has been bottlenecked by a lack of complex and compelling tasks. OGBench addresses this. 🧵👇
It was a huge week of AI and robotics news. So I summarized everything announced by Anthropic, Ideogram, Figure, Genmo, Runway, Microsoft, Google DeepMind, OpenAI, UCLA, Apple, Clone Robotics, and more. Here's everything you need to know and how to make sense out of it:
x.infer So, a new computer vision model just dropped last night. It's called GPT-54o-mini-vision-pro-max-xxxl. It's a super cool model, open-source, open-weights, open-data, all the good stuff. You're excited. You want to try it out. But it's written in a new framework,…
Novel view synthesis has long been a core challenge in 3D vision. But how much 3D inductive bias is truly needed? —Surprisingly, very little! Introducing "LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias"—a fully transformer-based approach that enables scalable,…
attention heads aren't learning something useful at every layer (1), so we can remove them (2), dynamically skip them (3), replace them with SWA (4), or use SSM modules (5). but maybe improving the attention rank deficiency (6) will make the model learn useful attention heads.🧵
ARKit LabelMaker: A New Scale for Indoor 3D Scene Understanding @GuangdaJi, @weder_silvan, @FrancisEngelman, @mapo1, @hermannsblum tl;dr: ARKitScenes dataset+LabelMaker->LabelMakerV2 arxiv.org/pdf/2410.13924
.@GoogleDeepMind came up with an ϵ-VAE approach to autoencoders. They propose to use a denoising process instead of traditional decoder. It's a shift from a one-step image rebuild to multi-step iterative refinements of its noisy version, guided by the encoder. Key details:
Creating Generalist robotics policies (GRPs) is tricky. In this video (and code) I share how to create a GRP from scratch from some basic transformer code. This is the first step in my plan to create a course on large models and scaling for RL and Robotics.
Sequence models have skyrocketed in popularity for their ability to analyze data & predict what to do next. MIT’s "Diffusion Forcing" method combines the strengths of next-token prediction (like w/ChatGPT) & video diffusion (like w/Sora), training neural networks to handle…
Are there any famous **transformer based** models that are using sub-quadratic attention? I know there’s a lot of literature on it, but I’m curious if anyone’s using them in practice. Any references are appreciated!
Meta Open Materials 2024: Dataset and models for material property prediction.
Introducing Meta’s Open Materials 2024 (OMat24) Dataset and Models! All under permissive open licenses for commercial and non-commercial use! Paper: arxiv.org/abs/2410.12771 Dataset: huggingface.co/datasets/fairc… Models: huggingface.co/fairchem/OMAT24 🧵1/x
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